{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kyle-hale\/#","text":"Kyle Hale - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKyle HaleProduct Specialist at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/praveen-vemulapalli","text":"Praveen Vemulapalli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPraveen VemulapalliDirector- Technology at AT&TBack to speakersPraveen is the Director-Technology for Chief Data Office at AT&T. He oversees and manages AT&T's Network Traffic Data and Artificial Intelligence platforms. Responsible for 5G Analytics\/AI Research & Development (R&D). He also leads the on-premise to cloud transformation of the Core Network Usage platforms. Leading a strong team of Data Engineers, Data Scientists, ML\/AI Ops Engineers and Solution Architects.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/02\/07\/structured-streaming-a-year-in-review.html","text":"An Overview of All the New Structured Streaming Features Developed In 2021 For Databricks & Apache Spark. - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorStructured Streaming: A Year in Reviewby Steven Yu and Ray ZhuFebruary 7, 2022 in Data EngineeringShare this postAs we enter 2022, we want to take a moment to reflect on the great strides made on the streaming front in Databricks and Apache Spark\u2122 ! In 2021, the engineering team and open source contributors made a number of advancements with three goals in mind:Lower latency and improve stateful stream processingImprove observability of Databricks and Spark Structured Streaming workloadsImprove resource allocation and scalabilityUltimately, the motivation behind these goals was to enable more teams to run streaming workloads on Databricks and Spark, make it easier for customers to operate mission critical production streaming applications on Databricks and simultaneously optimizing for cost effectiveness and resource usage.Goal # 1: Lower latency & improved stateful processingThere are two new key features that specifically target lowering latencies with stateful operations, as well as improvements to the stateful APIs. The first is asynchronous checkpointing for large stateful operations, which improves upon a historically synchronous and higher latency design.Asynchronous CheckpointingIn this model, state updates are written to a cloud storage checkpoint location before the next microbatch begins. The advantage is that if a stateful streaming query fails, we can easily restart the query by using the information from the last successfully completed batch. In the asynchronous model, the next microbatch does not have to wait for state updates to be written, improving the end-to-end latency of the overall microbatch execution.You can learn more about this feature in an upcoming deep-dive blog post, and try it in Databricks Runtime 10.3 and above.Arbitrary stateful operator improvementsIn a much earlier post, we introduced Arbitrary Stateful Processing in Structured Streaming with [flat]MapGroupsWithState. These operators provide a lot of flexibility and enable more advanced stateful operations beyond aggregations. We\u2019ve introduced improvements to these operators that:Allow initial state, avoiding the need to reprocess all your streaming data.Enable easier logic testing by exposing a new TestGroupState interface, allowing users to create instances of GroupState and access internal values for what has been set, simplifying unit tests for the state transition functions.Allow Initial StateLet\u2019s start with the following flatMapGroupswithState operator:\ndef flatMapGroupsWithState[S: Encoder, U: Encoder](\n    outputMode: OutputMode,\n    timeoutConf: GroupStateTimeout,\n    initialState: KeyValueGroupedDataset[K, S])(\n    func: (K, Iterator[V], GroupState[S]) => Iterator[U])\nThis custom state function maintains a running count of fruit that have been encountered.\nval fruitCountFunc =(key: String, values: Iterator[String], state: GroupState[RunningCount]) => {\n  val count = state.getOption.map(_.count).getOrElse(0L) + valList.size\n  state.update(new RunningCount(count))\n  Iterator((key, count.toString))\n}\nIn this example, we specify the initial state to the this operator by setting starting values for certain fruit:\nval fruitCountInitialDS: Dataset[(String, RunningCount)] = Seq(\n  (\"apple\", new RunningCount(1)),\n  (\"orange\", new RunningCount(2)),\n  (\"mango\", new RunningCount(5)),\n).toDS()\n\nval fruitCountInitial = initialState.groupByKey(x => x._1).mapValues(_._2)\n\nfruitStream\n  .groupByKey(x => x)\n  .flatMapGroupsWithState(Update, GroupStateTimeout.NoTimeout, fruitCountInitial)(fruitCountFunc)\nEasier Logic TestingYou can also now test state updates using the TestGroupState API.\nimport org.apache.spark.sql.streaming._\nimport org.apache.spark.api.java.Optional\n\ntest(\"flatMapGroupsWithState's state update function\") {\n  var prevState = TestGroupState.create[UserStatus](\n    optionalState = Optional.empty[UserStatus],\n    timeoutConf = GroupStateTimeout.EventTimeTimeout,\n    batchProcessingTimeMs = 1L,\n    eventTimeWatermarkMs = Optional.of(1L),\n    hasTimedOut = false)\n\n  val userId: String = ...\n  val actions: Iterator[UserAction] = ...\n\n  assert(!prevState.hasUpdated)\n\n  updateState(userId, actions, prevState)\n\n  assert(prevState.hasUpdated)\n  \n}\nYou can find these, and more examples in the Databricks documentation.Native support for Session WindowsStructured Streaming introduced the ability to do aggregations over event-time based windows using tumbling or sliding windows, both of which are windows of fixed-length. In Spark 3.2, we introduced the concept of session windows, which allow dynamic window lengths. This historically required custom state operators using flatMapGroupsWithState.An example of using dynamic gaps:\n# Define the session window having dynamic gap duration based on eventType\nsession_window expr = session_window(events.timestamp, \\\n    when(events.eventType == \"type1\", \"5 seconds\") \\\n    .when(events.eventType == \"type2\", \"20 seconds\") \\\n    .otherwise(\"5 minutes\"))\n\n# Group the data by session window and userId, and compute the count of each group\nwindowedCountsDF = events \\\n    .withWatermark(\"timestamp\", \"10 minutes\") \\\n    .groupBy(events.userID, session_window_expr) \\\n    .count()\nGoal #2: Improve observability of streaming workloadsWhile the StreamingQueryListener API allows you to asynchronously monitor queries within a SparkSession and define custom callback functions for query state, progress, and terminated events, understanding back pressure and reasoning about where the bottlenecks are in a microbatch were still challenging. As of Databricks Runtime 8.1, the StreamingQueryProgress object reports data source specific back pressure metrics for Kafka, Kinesis, Delta Lake and Auto Loader streaming sources.An example of the metrics provided for Kafka:\n{\n  \"sources\" : [ {\n    \"description\" : \"KafkaV2[Subscribe[topic]]\",\n    \"metrics\" : {\n      \"avgOffsetsBehindLatest\" : \"4.0\",\n      \"maxOffsetsBehindLatest\" : \"4\",\n      \"minOffsetsBehindLatest\" : \"4\",\n      \"estimatedTotalBytesBehindLatest\" : \"80.0\"\n    },\n  } ]\n}\nDatabricks Runtime 8.3 introduces real-time metrics to help understand the performance of the RocksDB state store and debug the performance of state operations. These can also help identify target workloads for asynchronous checkpointing.An example of the new state store metrics:\n{\n  \"id\" : \"6774075e-8869-454b-ad51-513be86cfd43\",\n  \"runId\" : \"3d08104d-d1d4-4d1a-b21e-0b2e1fb871c5\",\n  \"batchId\" : 7,\n  \"stateOperators\" : [ {\n    \"numRowsTotal\" : 20000000,\n    \"numRowsUpdated\" : 20000000,\n    \"memoryUsedBytes\" : 31005397,\n    \"numRowsDroppedByWatermark\" : 0,\n    \"customMetrics\" : {\n      \"rocksdbBytesCopied\" : 141037747,\n      \"rocksdbCommitCheckpointLatency\" : 2,\n      \"rocksdbCommitCompactLatency\" : 22061,\n      \"rocksdbCommitFileSyncLatencyMs\" : 1710,\n      \"rocksdbCommitFlushLatency\" : 19032,\n      \"rocksdbCommitPauseLatency\" : 0,\n      \"rocksdbCommitWriteBatchLatency\" : 56155,\n      \"rocksdbFilesCopied\" : 2,\n      \"rocksdbFilesReused\" : 0,\n      \"rocksdbGetCount\" : 40000000,\n      \"rocksdbGetLatency\" : 21834,\n      \"rocksdbPutCount\" : 1,\n      \"rocksdbPutLatency\" : 56155599000,\n      \"rocksdbReadBlockCacheHitCount\" : 1988,\n      \"rocksdbReadBlockCacheMissCount\" : 40341617,\n      \"rocksdbSstFileSize\" : 141037747,\n      \"rocksdbTotalBytesReadByCompaction\" : 336853375,\n      \"rocksdbTotalBytesReadByGet\" : 680000000,\n      \"rocksdbTotalBytesReadThroughIterator\" : 0,\n      \"rocksdbTotalBytesWrittenByCompaction\" : 141037747,\n      \"rocksdbTotalBytesWrittenByPut\" : 740000012,\n      \"rocksdbTotalCompactionLatencyMs\" : 21949695000,\n      \"rocksdbWriterStallLatencyMs\" : 0,\n      \"rocksdbZipFileBytesUncompressed\" : 7038\n    }\n  } ],\n  \"sources\" : [ {\n  } ],\n  \"sink\" : {\n  }\n}\nGoal # 3: Improve resource allocation and scalabilityStreaming Autoscaling with Delta Live Tables (DLT)At Data + AI Summit last year, we announced Delta Live Tables, which is a framework that allows you to declaratively build and orchestrate data pipelines, and largely abstracts the need to configure clusters and node types. We\u2019re taking this a step further and introducing an intelligent autoscaling solution for streaming pipelines that improves upon the existing Databricks Optimized Autoscaling. These benefits include:The new algorithm takes advantage of the new back pressure metrics to adjust cluster sizes to better handle scenarios in which there are fluctuations in streaming workloads, which ultimately leads to better cluster utilization.While the existing autoscaling solution retires nodes only if they are idle, the new DLT Autoscaler will proactively shut down selected nodes when utilization is low, while simultaneously guaranteeing that there will be no failed tasks due to the shutdown.Better Cluster Utilization:Proactive Graceful Worker Shutdown:As of writing, this feature is currently in Private Preview. Please reach out to your account team for more information.Trigger.AvailableNowIn Structured Streaming, triggers allow a user to define the timing of a streaming query\u2019s data processing. These trigger types can be micro-batch (default), fixed interval micro-batch (Trigger.ProcessingTime(\u201c\u201d), one-time micro-batch (Trigger.Once), and continuous (Trigger.Continuous). Databricks Runtime 10.1 introduces a new type of trigger; Trigger.AvailableNow that is similar to Trigger.Once but provides better scalability. Like Trigger Once, all available data will be processed before the query is stopped, but in multiple batches instead of one. This is supported for Delta Lake and Auto Loader streaming sources.Example:\nspark.readStream\n  .format(\"delta\")\n  .option(\"maxFilesPerTrigger\", \"1\")\n  .load(inputDir)\n  .writeStream\n  .trigger(Trigger.AvailableNow)\n  .option(\"checkpointLocation\", checkpointDir)\n  .start()\nSummaryAs we head into 2022, we will continue to accelerate innovation in Structured Streaming, further improving performance, decreasing latency and implementing new and exciting features. Stay tuned for more information throughout the year!\u00a0Try Databricks for freeGet StartedRelated postsNative Support of Session Window in Spark Structured StreamingOctober 12, 2021 by Jungtaek Lim, Yuanjian Li and Shixiong Zhu in Engineering Blog\nApache Spark\u2122 Structured Streaming allowed users to do aggregations on windows over event-time. Before Apache Spark 3.2\u2122, Spark supported tumbling windows and sliding win...\nWhat\u2019s New in Apache Spark\u2122 3.1 Release for Structured StreamingApril 27, 2021 by Yuanjian Li, Shixiong Zhu and Bo Zhang in Engineering Blog\nAlong with providing the ability for streaming processing based on Spark Core and SQL API, Structured Streaming is one of the most important...\nInfrastructure Design for Real-time Machine Learning InferenceSeptember 1, 2021 by Yu Chen in Company Blog\nThis is a guest authored post by Yu Chen, Senior Software Engineer, Headspace. 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{"source":"https:\/\/www.databricks.com\/kr\/discover\/demos","text":"Databricks \uc81c\ud488 \ubc0f \ud30c\ud2b8\ub108 \ub370\ubaa8 \ud5c8\ube0c - \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130 \ub370\ubaa8 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, 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\uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks 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\ud504\ub85c\uc81d\ud2b8\uac00 Databricks \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uacfc \uc5b4\ub5a4 \uba74\uc5d0\uc11c \uc801\ud569\ud55c\uc9c0 \ub17c\uc758\ud569\ub2c8\ub2e4.\uc790\uc138\ud788Databricks SQLDatabricks \uc6cc\ud06c\ud50c\ub85cUnity Catalog\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2ddDelta SharingDelta LakeDelta Live \ud14c\uc774\ube14Delta Lake \ub370\uc774\ud130 \ud1b5\ud569 (Auto Loader\uc640 COPY INTO)\ud30c\ud2b8\ub108 \ub370\ubaa8Azure Databricks \ud074\ub77c\uc6b0\ub4dc \ud1b5\ud569Azure Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc640 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uac00\uc7a5 \uc88b\uc740 \uc810\ub9cc \ubaa8\uc544\n\uae30\uc874 Azure \uc11c\ube44\uc2a4\uc640 \uc548\uc804\ud558\uac8c \ud1b5\ud569\ud560 \uc218 \uc788\ub294 \ub2e8\uc21c\ud55c \uc624\ud508 \ud611\uc5c5\ud615 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. \uc774 \ub370\ubaa8\uc5d0\uc11c\ub294 Azure Data Lake Storage(ADLS), Azure Data Factory(ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI \ub4f1 \uac00\uc7a5 \ubcf4\ud3b8\uc801\uc778 Azure Databricks \ud1b5\ud569 \uc0ac\ub840\ub97c \uba87 \uac00\uc9c0 \ub2e4\ub8e8\uace0\uc790 \ud569\ub2c8\ub2e4.\uc790\uc138\ud788AWS \uae30\ubc18 Databricks \ud074\ub77c\uc6b0\ub4dc \ud1b5\ud569Google Cloud\uc5d0 Databricks \ubc30\ud3ecPartner Connect\uc0b0\uc5c5 \uc194\ub8e8\uc1582\uc8fc \uc774\ub0b4\uc5d0 \uad6c\uc0c1\uc5d0\uc11c \uac1c\ub150 \uc99d\uba85 \ub2e8\uacc4\uae4c\uc9c0 \uc644\ub8ccDatabricks \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130\ub294 \ubaa8\ub4e0 \uae30\ub2a5\uc744 \uac16\ucd98 \ub178\ud2b8\ubd81\uacfc \ubaa8\ubc94 \uc0ac\ub840\ub97c \ud3ec\ud568\ud55c \uc804\uc6a9 \uac00\uc774\ub4dc\ub97c \ud1b5\ud574 \ube60\ub978 \uc131\uacfc\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. Databricks \uace0\uac1d\uc740 \ubc1c\uacac, \uc124\uacc4, \uac1c\ubc1c, \ud14c\uc2a4\ud2b8 \uc2dc\uac04\uc744 \ub2e8\ucd95\ud574, \ub300\ubd80\ubd84 2\uc8fc \uc774\ub0b4\uc5d0 \uad6c\uc0c1\uc5d0\uc11c \uac1c\ub150 \uc99d\uba85(PoC) \ub2e8\uacc4\uae4c\uc9c0 \uc644\ub8cc\ud588\uc2b5\ub2c8\ub2e4.\uc561\uc140\ub7ec\ub808\uc774\ud130 \ub458\ub7ec\ubcf4\uae30Databricks \uacc4\uc815 \uc0dd\uc131\ud558\uae301\/2\uc774\ub984\uc131\ud68c\uc0ac \uc774\uba54\uc77c\ud68c\uc0ac\uc9c1\ud568\uc804\ud654\ubc88\ud638(\uc120\ud0dd\uc0ac\ud56d)\ubcf4\uae30 \uc911\uc5d0\uc11c \uc120\ud0dd\ud558\uc138\uc694\uad6d\uac00\uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/explore\/data-science-machine-learning\/intro-mlflow-blog?itm_data=DSproduct-pf-dsml","text":"\n\n\n\n\n\n\n\nMLflow - An open source machine learning platform\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/glossary\/data-lakehouse","text":"What is a Data Lakehouse?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData LakehouseAll>Data LakehouseWhat is a Data Lakehouse?A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data.Data Lakehouse: Simplicity, Flexibility, and Low CostData lakehouses are enabled by a new, open system design: implementing similar data structures and data management features to those in a data warehouse, directly on the kind of low-cost storage used for data lakes. Merging them together into a single system means that data teams can move faster as they are able to use data without needing to access multiple systems. Data lakehouses also ensure that teams have the most complete and up-to-date data available for data science, machine learning, and business analytics projects. Key Technology Enabling the Data LakehouseThere are a few key technology advancements that have enabled the data lakehouse:metadata layers for data lakesnew query engine designs providing high-performance SQL execution on data lakesoptimized access for data science and machine learning tools.Metadata layers, like the open source Delta Lake, sit on top of open file formats (e.g. Parquet files) and track which files are part of different table versions to offer rich management features like ACID-compliant transactions. The metadata layers enable other features common in data lakehouses, like support for streaming I\/O (eliminating the need for message buses like Kafka), time travel to old table versions, schema enforcement and evolution, as well as data validation. Performance is key for data lakehouses to become the predominant data architecture used by businesses today as it's one of the key reasons that data warehouses exist in the two-tier architecture. While data lakes using low-cost object stores have been slow to access in the past, new query engine designs enable high-performance SQL analysis. These optimizations include caching hot data in RAM\/SSDs (possibly transcoded into more efficient formats), data layout optimizations to cluster co-accessed data, auxiliary data structures like statistics and indexes, and vectorized execution on modern CPUs. Combining these technologies together enables data lakehouses to achieve performance on large datasets that rivals popular data warehouses, based on TPC-DS benchmarks. The open data formats used by data lakehouses (like Parquet), make it very easy for data scientists and machine learning engineers to access the data in the lakehouse. They can use tools popular in the DS\/ML ecosystem like pandas, TensorFlow, PyTorch and others that can already access sources like Parquet and ORC. Spark DataFrames even provide declarative interfaces for these open formats which enable further I\/O optimization. The other features of a data lakehouse, like audit history and time travel, also help with improving reproducibility in machine learning. To learn more about the technology advances underpinning the move to the data lakehouse, see the CIDR paper Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics and another academic paper Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores.History of Data ArchitecturesBackground on Data WarehousesData warehouses have a long history in decision support and business intelligence applications, though were not suited or were expensive for handling unstructured data, semi-structured data, and data with high variety, velocity, and volume.Emergence of Data LakesData lakes then emerged to handle raw data in a variety of formats on cheap storage for data science and machine learning, though lacked critical features from the world of data warehouses: they do not support transactions, they do not enforce data quality, and their lack of consistency\/isolation makes it almost impossible to mix appends and reads, and batch and streaming jobs.Common Two-Tier Data ArchitectureData teams consequently stitch these systems together to enable BI and ML across the data in both these systems, resulting in duplicate data, extra infrastructure cost, security challenges, and significant operational costs. In a two-tier data architecture, data is ETLd from the operational databases into a data lake. This lake stores the data from the entire enterprise in low-cost object storage and is stored in a format compatible with common machine learning tools but is often not organized and maintained well. Next, a small segment of the critical business data is ETLd once again to be loaded into the data warehouse for business intelligence and data analytics. Due to multiple ETL steps, this two-tier architecture requires regular maintenance and often results in data staleness, a significant concern of data analysts and data scientists alike according to recent surveys from Kaggle and Fivetran. Learn more about the common issues with the two-tier architecture.Additional ResourcesWhat is a Lakehouse? - BlogLakehouse Architecture: From Vision to RealityIntroduction to Lakehouse and SQL AnalyticsLakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced AnalyticsDelta Lake: The Foundation of Your LakehouseThe Databricks Lakehouse PlatformData Brew Vidcast: Season 1 on Data LakehousesThe Rise of the Lakehouse ParadigmBuilding the Data Lakehouse by Bill InmonThe Data Lakehouse Platform for DummiesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/market-risk","text":"Solution Accelerator - How to build: A modern risk management solution in financial services | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorBuild a Modern Risk Management Solution in Financial ServicesAdopt a more agile approach to risk management by unifying data and AI in the Lakehouse\nThis solution has two parts. First, it shows how Delta Lake and MLflow can be used for value-at-risk calculations \u2014 showing how banks can modernize their risk management practices by back-testing, aggregating and scaling simulations by using a unified approach to data analytics with the Lakehouse. Secondly, the solution uses alternative data to move toward a more holistic, agile and forward-looking approach to risk management and investments.\nRead the full write-up part 1\nRead the full write-up part 2\nDownload notebookBenefits and business valueGain a holistic viewUse a more complete view of risk and investment with real-time and alternative data that can be analyzed on demand\nDetect emerging threatsProactively identify emerging threats to protect capital and optimize exposuresAchieve speed at scaleScan through large volumes of data quickly and thoroughly to respond in time and reduce risk\nReference ArchitectureResourcesWorkshopLearn moreBlogLearn moreeBookLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br","text":"P\u00e1gina inicial da Databricks - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWA melhor solu\u00e7\u00e3o de data warehouse \u00e9 o lakehouseCombine todos os seus dados, an\u00e1lises e IA em uma \u00fanica plataformaComece gratuitamenteSaiba maisReduza custos e acelere a inova\u00e7\u00e3o na Lakehouse PlatformSaiba maisUnificadaUma plataforma para seus dados, consistentemente governada e dispon\u00edvel para todas as suas an\u00e1lises e IAAbertaConstru\u00edda em padr\u00f5es abertos e integrada a todas as nuvens para funcionar perfeitamente em sua pilha de dados modernaEscal\u00e1velEscale de forma eficiente com cada carga de trabalho, de simples pipelines de dados at\u00e9 grandes LLMsOrganiza\u00e7\u00f5es orientadas a dados escolhem o Lakehouse\nVer todos os clientes\nO Lakehouse unifica suas equipes de dadosGerenciamento e engenharia de dadosSimplifique a ingest\u00e3o e o gerenciamento de dadosCom ETL automatizado e confi\u00e1vel, compartilhamento de dados aberto e seguro e desempenho extremamente r\u00e1pido, o Delta Lake transforma seu data lake no destino para todos os seus dados estruturados, semiestruturados e n\u00e3o estruturados.Saiba mais Assista \u00e0 demoData warehousingObtenha novos insights a partir dos dados mais completosCom acesso imediato aos dados mais recentes e abrangentes e o poder do Databricks SQL \u2014 que \u00e9 at\u00e9 12 vezes melhor em rela\u00e7\u00e3o ao pre\u00e7o\/desempenho do que data warehouses em nuvem tradicionais \u2014 analistas e cientistas de dados agora podem obter novos insights rapidamente.Saiba mais Assista \u00e0 demoData science e machine learningAcelerar o ML em todo o ciclo de vidaO lakehouse \u00e9 a base do Databricks Machine Learning \u2014 uma solu\u00e7\u00e3o nativa e colaborativa de dados para todo o ciclo de vida do aprendizado de m\u00e1quina, da prepara\u00e7\u00e3o \u00e0 produ\u00e7\u00e3o. Combinado com pipelines de dados de alta qualidade e desempenho, o lakehouse acelera o machine learning e a produtividade da equipe.Saiba mais Assista \u00e0 demoGovernan\u00e7a e compartilhamento de dadosUnifique a governan\u00e7a e compartilhamento para dados, an\u00e1lises e IACom a Databricks, voc\u00ea tem acesso a um modelo comum de seguran\u00e7a e governan\u00e7a para todos os seus dados, an\u00e1lises e ativos de IA no lakehouse, em qualquer da nuvem. Descubra e compartilhe dados entre plataformas, nuvens ou regi\u00f5es sem replica\u00e7\u00e3o ou v\u00ednculo com um fornecedor. Voc\u00ea pode at\u00e9 distribuir produtos de dados em um mercado aberto.Saiba mais Assista \u00e0 demoO data warehouse \u00e9 hist\u00f3ria. Descubra por que o lakehouse \u00e9 a arquitetura moderna para dados e IA.Descubra o lakehouseCat\u00e1logo de sess\u00f5es j\u00e1 dispon\u00edvelJunte-se a n\u00f3s em S\u00e3o Francisco para explorar o ecossistema do lakehouse e os avan\u00e7os em tecnologias de c\u00f3digo abertoExplorar sess\u00f5esVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivo.Obtenha o relat\u00f3rio600 CIOs. 14 setores. 18 pa\u00edses.Este novo estudo descobriu que a estrat\u00e9gia de dados \u00e9 fundamental para o sucesso da IA. Veja mais perspectivas do CIO.Obtenha o relat\u00f3rioO Livro Completo da Engenharia de DadosFique por dentro das tend\u00eancias mais recentes em engenharia de dados baixando sua c\u00f3pia do Livro Completo da Engenharia de Dados.Obter o e-BookTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-hollander\/#","text":"Jonathan Hollander - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan HollanderVP, Enterprise Data Technology Platforms at TD BankBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-del-balso","text":"Mike Del Balso - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike Del BalsoCo-founder + CEO at TectonBack to speakersMike Del Balso is the co-founder of Tecton, where he is building next-generation data infrastructure for Real-Time ML. Before Tecton, Mike was the PM lead for the Uber's Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power Google\u2019s Search Ads business.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Essayer gratuitement Databricks | DatabricksEssayer gratuitement DatabricksExp\u00e9rimentez pleinement la plateforme Databricks gratuitement pendant 14 jours, sur AWS, Microsoft Azure ou Google Cloud, au choix.Simplification de l'ingestion des donn\u00e9es et automatisation de l\u2019ETLImportez des donn\u00e9es depuis des centaines de sources. Utilisez une approche d\u00e9clarative simple pour cr\u00e9er des pipelines de donn\u00e9es.Collaborez dans votre langage pr\u00e9f\u00e9r\u00e9Codez en Python, R, Scala et SQL. B\u00e9n\u00e9ficiez du RBAC, d\u2019int\u00e9grations avec Git et d\u2019outils comme la r\u00e9daction collaborative et la gestion automatique des versions.Un rapport performance \/ prix jusqu'\u00e0 12 fois sup\u00e9rieur \u00e0 celui des data warehousesD\u00e9couvrez pourquoi plus de 7 000 clients dans le monde s\u2019appuient sur Databricks pour toutes leurs charges de travail de la BI \u00e0 l\u2019IA.Cr\u00e9ez votre compte Databricks1\/2Pr\u00e9nomNomE-mail professionnelEntrepriseIntitul\u00e9 de posteNum\u00e9ro de t\u00e9l\u00e9phone (facultatif)Veuillez s\u00e9lectionnerPaysContinuerAvis de confidentialit\u00e9 (mis \u00e0 jour)Conditions d'utilisationVos choix de confidentialit\u00e9Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ian-galloway","text":"Ian Galloway - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIan GallowaySenior Director, Applications at Collins AerospaceBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rajesh-iyer","text":"Rajesh Iyer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRajesh IyerVice President Financial Services Insights & Data at CapgeminiBack to speakersRajesh is the head of AI COE for Financial Services globally and drives growth in the Machine Learning and Artificial Intelligence Practice, as part of the Insights & Data Global Service Line at Capgemini.\u00a0He\u00a0has 27 years of Financial Services Data Sciences and AI\/ML experience across multiple domains, such as Risk, Distribution, Operations and Marketing, but working mostly with very large financial services institutions across the Banking and Capital Markets and Insurance verticals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/partnerconnect","text":"Partner Connect | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWPartner Connect\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc194\ub8e8\uc158\uc744 \uac04\ud3b8\ud558\uac8c \ud0d0\uc0c9 \ubc0f \ud1b5\ud569\ub370\ubaa8 \ubcf4\uae30Partner Connect\ub97c \uc0ac\uc6a9\ud558\uba74 Databricks \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc9c1\uc811 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \ub3c4\uad6c\ub97c \uc190\uc27d\uac8c \ud0d0\uc0c9\ud558\uace0, \ud604\uc7ac \uc0ac\uc6a9\ud558\uace0 \uc788\ub294 \ub3c4\uad6c\uc5d0 \ube60\ub974\uac8c \ud1b5\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Partner Connect\uc5d0\uc11c\ub294 \ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \ub3c4\uad6c \ud1b5\ud569\uc744 \uac04\uc18c\ud654\ud558\uace0 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ub2a5\uc744 \uc2e0\uc18d\ud788 \ud655\uc7a5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130\uc640 AI \ub3c4\uad6c\ub97c <br \/>\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \uc5f0\uacb0\uc6d0\ud558\ub294 \ub370\uc774\ud130 \ubc0f AI \ub3c4\uad6c\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \uac04\ud3b8\ud558\uac8c \uc5f0\uacb0\ud558\uace0 \ubaa8\ub4e0 \ubd84\uc11d \uc0ac\uc6a9 \uc0ac\ub840 \uc9c0\uc6d0\uc0c8\ub85c\uc6b4 \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c <br \/>\uac80\uc99d\ub41c \ub370\uc774\ud130 \ubc0f AI \uc194\ub8e8\uc158 \ud0d0\uc0c9\uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uc73c\ub85c \uc774\ub8e8\uc5b4\uc9c4 \uc6d0\uc2a4\ud1b1 \ud3ec\ud138\uc744 \ud1b5\ud574 \ub2e4\uc74c \ub370\uc774\ud130 \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uad6c\ucd95 \uae30\uac04 \ub2e8\ucd95\ud074\ub9ad \uba87 \ubc88\uc73c\ub85c <br \/>\uc0ac\uc804 \uad6c\ucd95\ub41c \ud1b5\ud569 \uc124\uc815Partner Connect\ub294 \ud074\ub7ec\uc2a4\ud130, \ud1a0\ud070, \uc5f0\uacb0 \ud30c\uc77c \ub4f1\uc758 \ub9ac\uc18c\uc2a4\ub97c \uc790\ub3d9\uc73c\ub85c \uad6c\uc131\ud558\uc5ec \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uc5d0 \uc5f0\uacb0\ud568\uc73c\ub85c\uc368 \ud1b5\ud569 \uc791\uc5c5 \uac04\uc18c\ud654\ud30c\ud2b8\ub108\ub85c \uc2dc\uc791\ud558\uae30Databricks \ud30c\ud2b8\ub108\ub294 \uace0\uac1d\uc5d0\uac8c \ub354\uc6b1 \ube60\ub978 \ubd84\uc11d \uc778\uc0ac\uc774\ud2b8\ub97c \uc81c\uacf5\ud560 \uc5ed\ub7c9\uc744 \uac16\ucd94\uace0 \uc788\uc2b5\ub2c8\ub2e4. Databricks\uc758 \uac1c\ubc1c \ubc0f \ud30c\ud2b8\ub108 \ub9ac\uc18c\uc2a4\ub97c \ud65c\uc6a9\ud558\uc5ec \ud074\ub77c\uc6b0\ub4dc \uae30\ubc18 \uc624\ud508 \ud50c\ub7ab\ud3fc\uacfc \ud568\uaed8 \uc131\uc7a5\ud558\uc138\uc694.\u0000\u0000\ud30c\ud2b8\ub108 \ub418\uae30\u201c\uc624\ub79c \ud30c\ud2b8\ub108\uc2ed\uc744 \ubc14\ud0d5\uc73c\ub85c \uad6c\ucd95\ub41c Partner Connect\ub294 \uc6b0\ub9ac \ud68c\uc0ac\uc640 \uace0\uac1d \uac04\uc758 \ud1b5\ud569 \ud658\uacbd\uc744 \uc124\uacc4\ud558\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4. Partner Connect\ub97c \ud1b5\ud574 \ud604\uc7ac Fivetran\uc744 \uc0ac\uc6a9\ud558\uac70\ub098 Partner Connect\uc5d0\uc11c \uc6b0\ub9ac \ud68c\uc0ac\ub97c \ubc1c\uacac\ud55c \uc218\ucc9c \uacf3\uc758 Databricks \uace0\uac1d\uc0ac\uc5d0 \ubcf4\ub2e4 \uc27d\uac8c \uac04\uc18c\ud654\ub41c \uacbd\ud5d8\uc744 \uc81c\uacf5\ud558\uace0 \uc788\uc73c\uba70, \uace0\uac1d\uc0ac\uc5d0\uc11c\ub294 \ub370\uc774\ud130\uc758 \uc778\uc0ac\uc774\ud2b8\uc640 \ub354\uc6b1 \ub2e4\uc591\ud55c \ubd84\uc11d \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uac80\uc0c9\ud558\uace0, \uc218\ubc31 \uac1c\uc758 \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uac04\ud3b8\ud558\uac8c \uc5f0\uacb0\ud574 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \ud1b5\ud55c \uac00\uce58 \ucc3d\ucd9c \uae30\uac04\uc744 \ub2e8\ucd95\ud569\ub2c8\ub2e4.\u201d\u2014 George Fraser, Fivetran CEO\ub370\ubaa8FivetranSaaS \uc571(\uc608: Salesforce, Google Analytics)\uc744 \ube44\ub86f\ud55c 180\uac1c \uc774\uc0c1\uc758 \uc571\uc5d0\uc11c \uc5bb\uc740 \ub370\uc774\ud130\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc5f0\uacb0dbtdbt Cloud \ubc0f Databricks\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \ubcc0\ud658 \uad6c\ucd95 \uc2dc\uc791\ud558\uae30Power BIDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uc131\ub2a5\uacfc \uae30\uc220\uc744 \ubaa8\ub4e0 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uc81c\uacf5\ud569\ub2c8\ub2e4.tableauTableau Desktop\uacfc Databricks SQL\uc744 \uc5f0\uacb0\ud558\uc5ec \ubaa8\ub4e0 \uc0ac\uc6a9\uc790\uc5d0\uac8c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \uc81c\uacf5\ud568\uc73c\ub85c\uc368 \ud604\ub300\uc801 \ubd84\uc11d\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.Rivery\ub370\uc774\ud130 \uc218\uc9d1, \ubcc0\ud658 \uadf8\ub9ac\uace0 Delta Lake\ub85c\uc758 \uc804\uc1a1\uae4c\uc9c0 \ub370\uc774\ud130 \uc5ec\uc815 \uac04\uc18c\ud654Labelbox\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c AI \ubc0f \ubd84\uc11d\uc744 \uc704\ud55c \ube44\uad6c\uc870\uc801 \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uc900\ube44\ud569\ub2c8\ub2e4.Prophecy\uc2dc\uac01\uc801 \ub4dc\ub798\uadf8\uc564\ub4dc\ub86d \uc778\ud130\ud398\uc774\uc2a4\ub97c \uc0ac\uc6a9\ud558\uc5ec Spark \ubc0f Delta \ud30c\uc774\ud504\ub77c\uc778 \uad6c\ucd95 \ubc0f \ubc30\ud3ec\uc544\ub974\uc2dc\uc628\ubd84\uc0b0\ub41c CDC \uae30\ubc18 \ubcf5\uc81c \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc5f0\uacb0\ubb34\ub8cc \uc2dc\ud5d8\ud310 \uc0ac\uc6a9\ud574 \ubcf4\uae30\ub9ac\uc18c\uc2a4\ube14\ub85c\uadf82023\ub144 2\uc6d4 \u2013 \ud30c\ud2b8\ub108 \ucee4\ub125\ud2b8\uc758 \uc0c8\ub85c\uc6b4 \ud30c\ud2b8\ub108 \ud1b5\ud569 \ubc1c\ud45c2022\ub144 9\uc6d4 \u2013 \ud30c\ud2b8\ub108 \ucee4\ub125\ud2b8\uc5d0 \uc0c8\ub85c\uc6b4 \ud30c\ud2b8\ub108 \ud1b5\ud569 \ub3c4\uc7852022\ub144 6\uc6d4 \u2013 \ud30c\ud2b8\ub108 \ucee4\ub125\ud2b8\uc758 \uc0c8\ub85c\uc6b4 \ud30c\ud2b8\ub108 \ud1b5\ud569 \ubc1c\ud45cPartner Connect\ub97c \uc0ac\uc6a9\ud558\uc5ec Databricks\uc5d0\uc11c \ube44\uc988\ub2c8\uc2a4 \uad6c\ucd95\uad00\ub828 \ubb38\uc11cDatabricks Partner Connect \uac00\uc774\ub4dc\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcfc \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks\uc758 \uac1c\ubc1c \ubc0f \ud30c\ud2b8\ub108 \ub9ac\uc18c\uc2a4\ub97c \ud65c\uc6a9\ud558\uc5ec \ud074\ub77c\uc6b0\ub4dc \uae30\ubc18 \uc624\ud508 \ud50c\ub7ab\ud3fc\uacfc \ud568\uaed8 \uc131\uc7a5\ud558\uc138\uc694.\ud30c\ud2b8\ub108 \ub418\uae30\ubb38\uc758\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \u0000\uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/overall-equipment-effectiveness","text":"Overall Equipment Effectiveness and KPI Monitoring | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorOverall Equipment EffectivenessPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedAchieve performant and scalable end-to-end equipment monitoringFor operational teams within manufacturing, it\u2019s critical to monitor and measure equipment performance. The advancements in Industry 4.0 and smart manufacturing have allowed manufacturers to collect vast volumes of sensor and equipment data. Making sense of this data to measure productivity provides a crucial competitive advantage.Overall Equipment Effectiveness (OEE) has become the standard for measuring manufacturing equipment productivity.The computation of OEE has traditionally been a manual exercise, and has been difficult to compute at the latency and scale required with legacy systems. In this Solution Accelerator, we demonstrate how the computation of OEE may be achieved in a multi-factory environment and in near real-time on Databricks.Get started with our Solution Accelerator for OEE to realize performant and scalable end-to-end equipment monitoring to:Incrementally ingest and process data from sensor\/IoT devices in a variety of formatsCompute and surface KPIs and metrics to drive valuable insightsOptimize plant operations with data-driven decisionsDownload notebookResourcesBlogLearn moreeBookDownload nowWebinarLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christian-hamilton\/#","text":"Christian Hamilton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristian HamiltonDirector, Data Science Technology at 84.51Back to speakersChristian Hamilton is a Director of Data Science Technology at 84.51\u00b0. He has spent 22 years in Kroger companies, holding diverse titles in Data Science, Retail Operations, and Finance. His work in emerging technology includes developing the first recommender sciences for Kroger\u2019s digital channels & implementing spark streaming. He\u2019s currently focused on democratizing data across the enterprise, establishing single sources of truth, empowering collaboration, and championing observability and governance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nat-friedman","text":"Nat Friedman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNat FriedmanCreator of Copilot; Former CEO at GithubBack to speakersNat Friedman has founded two startups, led GitHub as CEO from 2018 to 2022, and now invests in infrastructure, AI, and developer companies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/category\/data-and-ai\/industry-insights","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Databricks kostenlos testen | DatabricksDatabricks kostenlos testenTesten Sie die komplette Databricks-Plattform 14 Tage lang kostenlos in AWS, Microsoft Azure oder Google Cloud. Die Wahl des Cloud-Anbieters liegt bei Ihnen.Datenaufnahme vereinfachen und ETL automatisierenNehmen Sie Daten aus Hunderten von Quellen auf. Verwenden Sie einen einfachen deklarativen Ansatz zur Erstellung von Datenpipelines.In Ihrer bevorzugten Sprache zusammenarbeitenCode in Python, R, Scala und SQL mit Co-Authoring, automatischer Versionierung, Git-Integrationen und RBAC.12x besseres Preis\/Leistungsverh\u00e4ltnis als Cloud Data WarehousesErfahren Sie, warum mehr als 7.000 Kunden weltweit auf Databricks f\u00fcr all ihre Workloads von BI bis KI vertrauen.Erstellen Sie Ihr Databricks-Konto1\/2VornameNachnameBerufliche E-Mail-AdresseUnternehmenStellenbezeichnungRufnummer (Optional)Bitte ausw\u00e4hlenLandWeiterDatenschutzhinweis (aktualisiert)Terms of UseIhre DatenschutzwahlenIhre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/manbir-paul","text":"Manbir Paul - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingManbir PaulVP of Engineering, Data Insights and MarTech at SephoraBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/hadoop","text":"Apache Hadoop: What is it and how can you use it?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWhat Is Hadoop?All>What Is Hadoop?Try Databricks for freeGet StartedApache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them down into smaller workloads that can be run in parallel. Some key benefits of Hadoop are scalability, resilience and flexibility. The Hadoop Distributed File System (HDFS) provides reliability and resiliency by replicating any node of the cluster to the other nodes of the cluster to protect against hardware or software failures. Hadoop flexibility allows the storage of any data format including structured and unstructured data.Migrating From Hadoop to Data Lakehouse for Dummies\nGet faster insights at a lower cost when you migrate to the lakehouse.Download NowHowever, Hadoop architectures present a list of challenges, especially as time goes on. Hadoop can be overly complex and require significant resources and expertise to set up, maintain and upgrade. It is also time-consuming and inefficient due to the frequent reads and writes used to perform computations. The long-term viability of Hadoop continues to degrade as major Hadoop providers begin to shift away from the platform and because the accelerated need to digitize has encouraged many companies to reevaluate their relationship with Hadoop. The best solution to modernize your data platform is to migrate from Hadoop to the Databricks Lakehouse Platform. Read more about the challenges with Hadoop, and the shift toward modern data platforms, in our blog post.What is Hadoop programming?In the Hadoop framework, code is mostly written in Java but some native code is based in C. Additionally, command-line utilities are typically written as shell scripts. For Hadoop MapReduce, Java is most commonly used but through a module like Hadoop streaming, users can use the programming language of their choice to implement the map and reduce functions.What is a Hadoop database?Hadoop isn\u2019t a solution for data storage or relational databases. Instead, its purpose as an open-source framework is to process large amounts of data simultaneously in real-time.Data is stored in the HDFS, however, this is considered unstructured and does not qualify as a relational database. In fact, with Hadoop, data can be stored in an unstructured, semi-structured, or structured form. This allows for greater flexibility for companies to process big data in ways that meet their business needs and beyond.What type of database is Hadoop?Technically, Hadoop is not in itself a type of database such as SQL or RDBMS. Instead, the Hadoop framework gives users a processing solution to a wide range of database types.Hadoop is a software ecosystem that allows businesses to handle huge amounts of data in short amounts of time. This is accomplished by facilitating the use of parallel computer processing on a massive scale. Various databases such as Apache HBase can be dispersed amongst data node clusters contained on hundreds or thousands of commodity servers.When was Hadoop invented?Apache Hadoop was born out of a need to process ever increasingly large volumes of big data and deliver web results faster as search engines like Yahoo and Google were getting off the ground.Inspired by Google\u2019s MapReduce, a programming model that divides an application into small fractions to run on different nodes, Doug Cutting and Mike Cafarella started Hadoop in 2002 while working on the Apache Nutch project. According to a New York Times article, Doug named Hadoop after his son's toy elephant.A few years later, Hadoop was spun off from Nutch. Nutch focused on the web crawler element, and Hadoop became the distributed computing and processing portion. Two years after Cutting joined Yahoo, Yahoo released Hadoop as an open source project in 2008. The Apache Software Foundation (ASF) made Hadoop available to the public in November 2012 as Apache Hadoop.What\u2019s the impact of Hadoop?Hadoop was a major development in the big data space. In fact, it\u2019s credited with being the foundation for the modern cloud data lake. Hadoop democratized computing power and made it possible for companies to analyze and query big data sets in a scalable manner using free, open source software and inexpensive, off-the-shelf hardware.This was a significant development because it offered a viable alternative to the proprietary data warehouse (DW) solutions and closed data formats that had - until then - ruled the day.With the introduction of Hadoop, organizations quickly had access to the ability to store and process huge amounts of data, increased computing power, fault tolerance, flexibility in data management, lower costs compared to DWs, and greater scalability. Ultimately, Hadoop paved the way for future developments in big data analytics, like the introduction of Apache Spark.What is Hadoop used for?When it comes to Hadoop, the possible use cases are almost endless.RetailLarge organizations have more customer data available on hand than ever before. But often, it\u2019s difficult to make connections between large amounts of seemingly unrelated data. When British retailer M&S deployed the Hadoop-powered Cloudera Enterprise, they were more than impressed with the results.Cloudera uses Hadoop-based support and services for the managing and processing of data. Shortly after implementing the cloud-based platform, M&S found they were able to successfully leverage their data for much improved predictive analytics.This led them to more efficient warehouse use and prevented stock-outs during \u201cunexpected\u201d peaks in demand and gaining a huge advantage over the competition.FinanceHadoop is perhaps more suited to the finance sector than any other. Early on, the software framework was quickly pegged for primary use in handling the advanced algorithms involved with risk modeling. It\u2019s exactly the type of risk management that could help avoid the credit swap disaster that led to the 2008 recession.Banks have also realized this same logic also applies to managing risk for customer portfolios. Today, it\u2019s common for financial institutions to implement Hadoop to better manage the financial security and performance of their client\u2019s assets. JPMorgan Chase is just one of many industry giants that use Hadoop to manage exponentially increasing amounts of customer data from across the globe.HealthcareWhether nationalized or privatized, healthcare providers of any size deal with huge volumes of data and customer information. Hadoop frameworks allow for doctors, nurses and carers to have easy access to the information they need when they need it and it also makes it easy to aggregate data that provides actionable insights. This can apply to matters of public health, better diagnostics, improved treatments and more.Academic and research institutions can also leverage a Hadoop framework to boost their efforts. Take for instance, the field of genetic disease which includes cancer. We have the human genome mapped out and there are nearly three billion base pairs in total. In theory, everything to cure an army of diseases is now right in front of our faces.But to identify complex relationships, systems like Hadoop will be necessary to process such a large amount of information.Security and law enforcementHadoop can help improve the effectiveness of national and local security, too. When it comes to solving related crimes spread across multiple regions, a Hadoop framework can streamline the process for law enforcement by connecting two seemingly isolated events. By cutting down on the time to make case connections, agencies will be able to put out alerts to other agencies and the public as quickly as possible.In 2013, The National Security Agency (NSA) concluded that the open-source Hadoop software was superior to the expensive alternatives they\u2019d been implementing. They now use the framework to aid in the detection of terrorism, cybercrime and other threats.How does Hadoop work?Hadoop is a framework that allows for the distribution of giant data sets across a cluster of commodity hardware. Hadoop processing is performed in parallel on multiple servers simultaneously.Clients submit data and programs to Hadoop. In simple terms, HDFS (a core component of Hadoop) handles the Metadata and distributed file system. Next, Hadoop MapReduce processes and converts the input\/output data. Lastly, YARN divides the tasks across the cluster.With Hadoop, clients can expect much more efficient use of commodity resources with high availability and a built-in point of failure detection. Additionally, clients can expect quick response times when performing queries with connected business systems.In all, Hadoop provides a relatively easy solution for organizations looking to make the most out of big data.What language is Hadoop written in?The Hadoop framework itself is mostly built from Java. Other programming languages include some native code in C and shell scripts for command lines. However, Hadoop programs can be written in many other languages including Python or C++. This allows programmers the flexibility to work with the tools they\u2019re most familiar with.How to use HadoopAs we\u2019ve touched upon, Hadoop creates an easy solution for organizations that need to manage big data. But that doesn\u2019t mean it's always straightforward to use. As we can learn from the use cases above, how you choose to implement the Hadoop framework is pretty flexible.How your business analysts, data scientists, and developers. decide to use Hadoop will all depend on your organization and its goals.Hadoop is not for every company but most organizations should re-evaluate their relationship with Hadoop. If your business handles large amounts of data as part of its core processes, Hadoop provides a flexible, scalable and affordable solution to fit your needs. From there, it\u2019s mostly up to the imagination and technical abilities of you and your team.Hadoop query exampleHere are a few examples of how to query Hadoop:Apache HiveApache Hive was the early go-to solution for how to query SQL with Hadoop. This module emulates the behavior, syntax and interface of MySQL for programming simplicity. It\u2019s a great option if you already heavily use Java applications as it comes with a built-in Java API and JDBC drivers. Hive offers a quick and straightforward solution for developers but it\u2019s also quite limited as the software\u2019s rather slow and suffers from read-only capabilities.IBM BigSQLThis offering from IBM is a high-performance massively parallel processing (MPP) SQL engine for Hadoop. Its query solution catered to enterprises that need ease in a stable and secure environment. In addition to accessing HDFS data, it can also pull from RDBMS, NoSQL databases, WebHDFS and other sources of data.What is the Hadoop ecosystem?The term Hadoop is a general name that may refer to any of the following:The overall Hadoop ecosystem, which encompasses both the core modules and related sub-modules.The core Hadoop modules, including Hadoop Distributed File System (HDFS), Yet Another Resource Negotiator (YARN), MapReduce, and Hadoop Common (discussed below). These are the basic building blocks of a typical Hadoop deployment.Hadoop-related sub-modules, including: Apache Hive, Apache Impala, Apache Pig, and Apache Zookeeper, and Apache Flume among others. These related pieces of software can be used to customize, improve upon, or extend the functionality of core Hadoop.What are the core Hadoop modules?HDFS - Hadoop Distributed File System. HDFS is a Java-based system that allows large data sets to be stored across nodes in a cluster in a fault-tolerant manner.YARN - Yet Another Resource Negotiator. YARN is used for cluster resource management, planning tasks, and scheduling jobs that are running on Hadoop.MapReduce - MapReduce is both a programming model and big data processing engine used for the parallel processing of large data sets. Originally, MapReduce was the only execution engine available in Hadoop. But, later on Hadoop added support for others, including Apache Tez and Apache Spark.Hadoop Common - Hadoop Common provides a set of services across libraries and utilities to support the other Hadoop modules.What are the Hadoop ecosystem components?Several core components make up the Hadoop ecosystem.HDFSThe Hadoop Distributed File System is where all data storage begins and ends. This component manages large data sets across various structured and unstructured data nodes. Simultaneously, it maintains the Metadata in the form of log files. There are two secondary components of HDFS: the NameNode and the DataNode.NameNodeThe master Daemon in Hadoop HDFS is NameNode. This component maintains the filesystem namespace and regulates client access to said files. It\u2019s also known as the Master node and stores Metadata like the number of blocks and their locations. It consists mainly of files and directories and performs file system executions such as naming, closing and opening files.DataNodeThe second component is the slave Daemon and named the DataNode. This HDFS component stores the actual data or blocks as it performs client-requested read and write functions. This means DataNode also is responsible for replica creation, deletion and replication as instructed by the Master NameNode.The DataNode consists of two system files, one for data and one for recording block metadata. When an application is started up, handshaking takes place between the Master and Slave daemons to verify namespace and software version. Any mismatches will automatically take down the DataNode.MapReduceHadoop MapReduce is the core processing component of the Hadoop ecosystem. This software provides an easy framework for application writing when it comes to handling massive amounts of structured and unstructured data. This is mainly achieved by its facilitation of parallel processing of data across various nodes on commodity hardware.MapReduce handles job scheduling from the client. User-requested tasks are divided into independent tasks and processes. Next, these MapReduce jobs are differentiated into subtasks across the clusters and nodes throughout the commodity servers.This is accomplished by two phases; the Map phase and the Reduce phase. During the Map phase, the data set is converted into another set of data broken down into key\/value pairs. Next, the Reduce phase converts the output according to the programmer via the InputFormat class.Programmers specify two main functions in MapReduce. The Map function is the business logic for processing data. The Reduce function produces a summary and aggregate of the intermediate data output of the map function, producing the final output.YARNIn simple terms, Hadoop YARN is a newer and much-improved version of MapReduce. However, that is not a completely accurate picture. This is because YARN is also used for scheduling and processing and the executions of job sequences. But YARN is the resource management layer of Hadoop where each job runs on the data as a separate Java application.Acting as the framework\u2019s operating system, YARN allows things like batch processing and f data handled on a single platform. Much above the capabilities of MapReduce, YARN allows programmers to build interactive and real-time streaming applications.YARN allows for programmers to run as many applications as needed on the same cluster. It provides a secure and stable foundation for the operational management and sharing of system resources for maximum efficiency and flexibility.What are some examples of popular Hadoop-related software?Other popular packages that are not strictly a part of the core Hadoop modules but that are frequently used in conjunction with them include:Apache Hive is data warehouse software that runs on Hadoop and enables users to work with data in HDFS using a SQL-like query language called HiveQL.Apache Impala is the open source, native analytic database for Apache Hadoop.Apache Pig is a tool that is generally used with Hadoop as an abstraction over MapReduce to analyze large sets of data represented as data flows. Pig enables operations like join, filter, sort, and load.Apache Zookeeper is a centralized service for enabling highly reliable distributed processing.Apache Sqoop is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.Apache Oozie is a workflow scheduler system to manage Apache Hadoop jobs. Oozie Workflow jobs are Directed Acyclical Graphs (DAGs) of actions.Interest piqued? Read more about the Hadoop ecosystem.How to use Hadoop for analyticsDepending on data sources and organizational needs, there are three main ways to use the Hadoop framework for analytics.Deploy in your corporate data center(s)This is often a time-effective and financially sound option for those businesses with the necessary existing resources. Otherwise, setting up the technical equipment and IT staff required may overextend monetary and team resources. This option does give businesses greater control over the security and privacy of data.Go with the cloudBusinesses that desire a much more rapid implementation, lower upfront costs and lower maintenance requirements will want to leverage a cloud-based service. With a cloud provider, data and analytics are run on commodity hardware that exists in the cloud. These services streamline the processing of big data at an affordable price but come with certain drawbacks.Firstly, anything that\u2019s on the public internet is fair game for hackers and the like. Secondly, service outages to the internet and network providers can grind your business systems to a halt. For existing framework users, they may involve something like needing to migrate from Hadoop to the Lakehow Architecture.On-premise providersThose opting for better uptime, privacy and security will find all three things with an on-premise Hadoop provider. These vendors offer the best of both worlds. They can streamline the process by providing all equipment, software and service. But since the infrastructure is on-premises, you gain all the benefits that large corporations get from having data centers.What are the benefits of Hadoop?Scalability - Unlike traditional systems that limit data storage, Hadoop is scalable as it operates in a distributed environment. This allowed data architects to build early data lakes on Hadoop. Learn more about the history and evolution of data lakes.Resilience - The Hadoop Distributed File System (HDFS) is fundamentally resilient. Data stored on any node of a Hadoop cluster is also replicated on other nodes of the cluster to prepare for the possibility of hardware or software failures. This intentionally redundant design ensures fault tolerance. If one node goes down, there is always a backup of the data available in the cluster.Flexibility - Differing from relational database management systems, when working with Hadoop, you can store data in any format, including semi-structured or unstructured formats. Hadoop enables businesses to easily access new data sources and tap into different types of data.What are the challenges with Hadoop architectures?Complexity - Hadoop is a low-level, Java-based framework that can be overly complex and difficult for end-users to work with. Hadoop architectures can also require significant expertise and resources to set up, maintain, and upgrade.Performance - Hadoop uses frequent reads and writes to disk to perform computations, which is time-consuming and inefficient compared to frameworks that aim to store and process data in memory as much as possible, like Apache Spark.Long-term viability - In 2019, the world saw a massive unraveling within the Hadoop sphere. Google, whose seminal 2004 paper on MapReduce underpinned the creation of Apache Hadoop, stopped using MapReduce altogether, as tweeted by Google SVP of Technical Infrastructure, Urs H\u00f6lzle. There were also some very high-profile mergers and acquisitions in the world of Hadoop. Furthermore, in 2020, a leading Hadoop provider shifted its product set away from being Hadoop-centric, as Hadoop is now thought of as \u201cmore of a philosophy than a technology.\u201d Lastly, 2021 has been a year of interesting changes. In April 2021, the Apache Software Foundation announced the retirement of ten projects from the Hadoop ecosystem. Then in June 2021, Cloudera agrees to private. The impact of this decision on Hadoop users is still to be seen. This growing collection of concerns paired with the accelerated need to digitize has encouraged many companies to re-evaluate their relationship with Hadoop.Which companies use Hadoop?Hadoop adoption is becoming the standard for successful multinational companies and enterprises. The following is a list of companies that utilize Hadoop today:Adobe - the software and service providers use Apache Hadoop and HBase for data storage and other services.eBay - uses the framework for search engine optimization and research.A9 - a subsidiary of Amazon that is responsible for technologies related to search engines and search-related advertising.LinkedIn - as one of the most popular social and professional networking sites, the company uses many Apache modules including Hadoop, Hive, Kafka, Avro, and DataFu.Spotify - the Swedish music streaming giant used the Hadoop framework for analytics and reporting as well content generation and listening recommendations.Facebook - the social media giant maintains the largest Hadoop cluster in the world, with a dataset that grows a reported half of a PB per day.InMobi - the mobile marketing platform utilizes HDFS and Apache Pig\/MRUnit tasks involving analytics, data science and machine learning.How much does Hadoop cost?The Hadoop framework itself is an open-source Java-based application. This means, unlike other big data alternatives, it\u2019s free of charge. Of course, the cost of the required commodity software depends on what scale.When it comes to services that implement Hadoop frameworks you will have several pricing options:Per Node- most commonPer TBFreemium product with or without subscription-only tech supportAll-in-one package deal including all hardware and softwareCloud-based service with its own broken down pricing options- can essentially pay for what you need or pay as you goRead more about challenges with Hadoop, and the shift toward modern data platforms, in our blog post.Additional ResourcesStep-by-Step Migration: Hadoop to DatabricksMigration hubHidden Value of Hadoop Migration whitepaperIt\u2019s Time to Re-evaluate Your Relationship with Hadoop (Blog)Delta Lake and ETLMaking Apache Spark\u2122 Better with Delta LakeBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/luk-verhelst","text":"Luk Verhelst - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLuk VerhelstData Architect at Volvo Group (consultant)Back to speakersOccupation:\nData architect (consultant)\nClient: Volvo Group\nPersonal:\nBased in Brussels, born in 72, 3 kids (youngest is Linus, an ode to...)\nPrevious:\n- Started software engineering in 90s\n- IT management roles until 2018\n- Since 2018 data architecture roles\n- Graduated Media and Communication studiesLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/blaise-sandwidi","text":"Blaise Sandwidi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBlaise SandwidiLead Data Scientist, As. ESG Officer, PhD at International Finance Corporation (IFC)\u2013World Bank GroupBack to speakersBlaise Sandwidi is a Lead Data Scientist with IFC\u2019s ESG Global Advisory team. Blaise oversees the development of data science to support ESG risk modeling and data science for development. His past work experience includes positions with private sector institutions focused on building machine learning platforms to enable better investment decisions. Blaise holds a Ph.D. and a master\u2019s degree in finance from the University of Paris-Est, France.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/hls-resources\/improving-health-outcomes-data-ai","text":"\n\n\n\n\n\n\n\nImproving Health Outcomes With Data and AI\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/holly-smith","text":"Holly Smith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHolly SmithSenior Resident Solutions Architect at DatabricksBack to speakersHolly Smith is a renowned speaker and multi award winning Data & AI expert who has over a decade of experience working with Data & AI teams in a variety of capacities from individual contributors all the way up to leadership. She has spent the last four years at Databricks working with multi national companies as they embark on their journey to the cutting edge of data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/aws?itm_data=menu-item-awsProduct","text":"Databricks sur la plateforme de donn\u00e9es AWS - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks sur AWSLa plateforme de donn\u00e9es simple et unifi\u00e9e, parfaitement int\u00e9gr\u00e9e \u00e0 AWS\n\u00a0D\u00e9marrerPlanifier une d\u00e9moDatabricks sur AWS vous permet de stocker et de g\u00e9rer toutes vos donn\u00e9es sur une plateforme lakehouse simple et ouverte qui combine le meilleur des data warehouses et des data lakes pour unifier toutes vos charges de travail d'analytique et d'IA.Data engineering fiableSQL Analytics sur toutes vos donn\u00e9es \u2192Data Science collaborativeMachine learning en productionPourquoi Databricks sur AWS\u00a0?Simple\nDatabricks permet une seule architecture de donn\u00e9es unifi\u00e9e sur S3 pour l'analytique SQL, la data science et le machine learning.Rapport performance \/ prix 12 fois sup\u00e9rieur\nB\u00e9n\u00e9ficiez des performances du data warehouse au prix d'un data lake gr\u00e2ce \u00e0 des clusters de calcul optimis\u00e9s par SQL.A fait ses preuves\nDes milliers de clients ont mis en \u0153uvre Databricks sur AWS pour mettre \u00e0 disposition une plateforme d'analytique r\u00e9volutionnaire r\u00e9pondant \u00e0 tous les cas d'usage de l'analytique et de l'IA.Dollar Shave Club\u00a0: personnalisation des exp\u00e9riences clients gr\u00e2ce \u00e0 Databricks\nT\u00e9l\u00e9charger l'ebookHotels.com\u00a0: optimiser l\u2019exp\u00e9rience client avec le machine learning\nT\u00e9l\u00e9charger l'\u00e9tude de casHP\u00a0: de la pr\u00e9paration des donn\u00e9es au deep learning \u2014 comment HP unifie son analytique avec Databricks\nRegarder le webinaire \u00e0 la demandeInt\u00e9grations pharesAWS GravitonAWS GravitonLes clusters Databricks prennent en charge les instances AWS Graviton. Ces instances exploitent les processeurs Graviton con\u00e7us par AWS sur la base du jeu d'instructions Arm64. Selon AWS, ces types d'instance affichent un rapport performance\u00a0\/ prix sup\u00e9rieur \u00e0 tous les autres types sur Amazon\u00a0EC2.En savoir plusS\u00e9curit\u00e9 AWSAmazon RedshiftAWS GlueD\u00e9ploiement en entrepriseCas d\u2019utilisationMoteurs de recommandations personnalis\u00e9es\nTraitez toutes vos donn\u00e9es en temps r\u00e9el pour fournir les recommandations produits et services les plus pertinentes.S\u00e9quen\u00e7age g\u00e9nomique\nModernisez votre pile technologique pour am\u00e9liorer l'exp\u00e9rience des patients et des m\u00e9decins gr\u00e2ce au pipeline DNASeq le plus rapide \u00e0 grande \u00e9chelle.D\u00e9tection et pr\u00e9vention\ndes fraudes\nExploitez des donn\u00e9es historiques compl\u00e8tes avec des flux en temps r\u00e9el pour identifier rapidement les transactions financi\u00e8res anormales et suspectes.RessourcesLIVRES BLANCSExploiter votre data lake pour des insights d'analytiqueRegrouper les Big Data et l'IA dans le secteur des services financiersLa valeur cach\u00e9e de la migration HadoopWebinairesModernisez votre plateforme de donn\u00e9es et d'analytique en toute confiance avec Databricks et AWSPourquoi les start-ups centr\u00e9es sur les donn\u00e9es s'appuient sur le LakehouseUtilisez les avantages de l'analytique en temps r\u00e9el pour une prise de d\u00e9cision rapide au sein de QubyLoyaltyOne simplifie et met \u00e0 l'\u00e9chelle les pipelines d'analytique de donn\u00e9es gr\u00e2ce \u00e0 Delta LakeLib\u00e9rez le potentiel de votre data lakeCr\u00e9ation d\u2019un data lakehouse chez DoorDash et GrammarlyIndustriesExploitation de l'IA et du ML pour extraire des insights concrets \u00e0 partir de donn\u00e9es cliniques \u00e0 l'\u00e9chelle de la population au sein de PrognosComment le machine learning est en train de changer l'analytique des donn\u00e9es au gouvernementPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lindsey-woodland\/#","text":"Lindsey Woodland - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLindsey WoodlandExecutive Vice President, Client Data Science at 605Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tathagata-das\/#","text":"Tathagata Das - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTathagata Das DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/capgemini-migrate-legacy-cards-and-core-banking-portfolios","text":"Migrate Legacy Cards and Core Banking Portfolios by Capgemini and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionMigrate Legacy Cards and Core Banking Portfolios by CapgeminiMigration solution developed by Capgemini and powered by the Databricks Lakehouse Platform\nGet startedReduce migration efforts by up to 50%The ability to migrate monolithic mainframe systems and integrate them into modern tech stacks on cloud is critical for retail banks in today\u2019s competitive market. Organizations require real-time processing, high-quality data, elastic autoscaling, and support for a multiprogramming environment to succeed with complex cards and banking portfolio conversions. This is where Capgemini\u2019s solution for migrating legacy cards and core banking portfolios on the Databricks Lakehouse Platform can offer a distinct advantage \u2014 by enabling rapid conversion from external source systems and providing a fully configurable and industrialized conversion capability. Leveraging public cloud services, this solution provides a cost-efficient conversion platform with predictable time-to-market capabilities, allowing you to:Rapidly complete ingestion and ease development of ETL jobs in order to meet conversion SLAs Reduce time to market for handling different file structures and char encoding by following a low-code\/no-code framework designCompletely reconcile and validate the loads \/ EBCDIC-to-ASCII conversion at record speedGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/product\/aws?itm_data=menu-item-awsProduct","text":"Databricks auf der AWS-Datenplattform \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks auf AWSDie einfache einheitliche Datenplattform, die nahtlos in AWS integriert ist\n\u00a0Erste SchrittePlanen Sie eine DemoMit Databricks auf AWS k\u00f6nnen Sie alle Ihre Daten auf einer einfachen, offenen Lakehouse-Plattform speichern und verwalten, die das Beste aus Data Warehouses und Data Lakes kombiniert, um alle Ihre Analytics- und KI-Workloads zusammenzuf\u00fchren.Zuverl\u00e4ssiges Data EngineeringSQL Analytics\nf\u00fcr alle Ihre DatenKollaborative Data ScienceMachine Learning in der ProduktionWarum Databricks auf AWS?Einfach\nDatabricks erm\u00f6glicht eine einheitliche Datenarchitektur auf S3 f\u00fcr SQL-Analytics, Data Science und Machine Learning.12x besseres Preis\/Leistungsverh\u00e4ltnis\nErzielen Sie durch SQL-optimierte Compute-Cluster eine Data-Warehouse-Leistung, die der Wirtschaftlichkeit des Data Lake entspricht.Bew\u00e4hrt\nTausende Kunden haben Databricks in AWS implementiert, um eine bahnbrechende Analytics-Plattform bereitzustellen, die alle Analytics- und KI-Anwendungsf\u00e4lle abdeckt.Dollar Shave Club: Personalisierung von Kundenerlebnissen mit Databricks\nE-Book herunterladenHotels.com: Optimierung des Kundenerlebnisses durch Machine Learning\nFallstudie herunterladenHP: Von der Datenaufbereitung bis zum Deep Learning \u2013 wie HP Analytics mit Databricks vereinheitlicht\nOn-Demand-Webinar ansehenAusgew\u00e4hlte IntegrationenAWS GravitonAWS GravitonDatabricks-Cluster unterst\u00fctzen\u00a0AWS Graviton-Instances. Diese Instances verwenden von AWS entwickelte Graviton-Prozessoren, die auf die Arm64-Befehlssatzarchitektur aufsetzen. Nach Angaben von AWS weisen Instance-Typen mit diesen Prozessoren das beste Preis-Leistungs-Verh\u00e4ltnis aller Instance-Typen bei Amazon EC2 auf.\u00a0Mehr erfahrenAWS-SicherheitAmazon RedshiftAWS GlueEinf\u00fchrung auf UnternehmensebeneAnwendungsf\u00e4lleEngines f\u00fcr personalisierte Empfehlungen\nVerarbeiten Sie alle Ihre Daten in Echtzeit, um die relevantesten Produkt- und Serviceempfehlungen zu geben.Genomische Sequenzierung\nModernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis f\u00fcr Patienten und \u00c4rzte mit der schnellsten DNASeq-Pipeline in gro\u00dfem Umfang.Betrugserkennung und\n-pr\u00e4vention\nNutzen Sie vollst\u00e4ndige historische Daten zusammen mit Echtzeit-Datenstr\u00f6men, um schnell anomale und verd\u00e4chtige Finanztransaktionen zu identifizieren.RessourcenWhitepaperWie Sie aus Ihrem Data Lake durch Analyse Erkenntnisse gewinnenZusammenf\u00fchren von Big Data und KI in der FinanzdienstleistungsbrancheDer verborgene Mehrwert der Hadoop-MigrationWebinareDaten- und Analytics-Plattformen mit Databricks und AWS souver\u00e4n modernisierenWarum datenorientierte Startups im Lakehouse entwickelnNutzung der Vorteile von Echtzeit-Analytics f\u00fcr eine schnelle Entscheidungsfindung bei QubyLoyaltyOne vereinfacht und skaliert Data Analytics-Pipelines mit Delta LakeDas Potenzial in Ihrem Data Lake erschlie\u00dfenAufbau eines Data Lakehouse bei DoorDash und GrammarlyBranchenNutzung von KI\/ML zur Gewinnung von Erkenntnissen aus der Praxis aus klinischen Labordaten auf Populationsbasis bei PrognosWie Machine Learning die Data Analytics bei den Beh\u00f6rden ver\u00e4ndertM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/jp\/product\/data-science","text":"\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u3092\u5171\u6709\u3057\u3001HTML \u3084 IPython \u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306a\u3069\u306e\u8907\u6570\u306e\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3067\u30a8\u30af\u30b9\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3078\u306e\u79fb\u884cHadoop \u3084\u30a8\u30f3\u30bf\u30fc\u30d7\u30e9\u30a4\u30ba DWH \u306a\u3069\u306e\u30ec\u30ac\u30b7\u30fc\u30b7\u30b9\u30c6\u30e0\u306b\u95a2\u9023\u3059\u308b\u30c7\u30fc\u30bf\u30b5\u30a4\u30ed\u3001\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u4f4e\u4e0b\u3001\u9ad8\u3044\u30b3\u30b9\u30c8\u306b\u3046\u3093\u3056\u308a\u3057\u3066\u3044\u307e\u305b\u3093\u304b\uff1fDatabricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u79fb\u884c\u3059\u308b\u3053\u3068\u3067\u3001\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306e\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306b\u5bfe\u5fdc\u3059\u308b\u6700\u65b0\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u304c\u5b9f\u73fe\u3057\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3078\u306e\u79fb\u884c\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\n\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u4e00\u89a7\n\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u3084\u6a5f\u68b0\u5b66\u7fd2\u306b\u95a2\u3059\u308b eBook \u3084\u30d3\u30c7\u30aa\u3092\u63a2\u3059\u306b\u306f\u3001\u30ea\u30bd\u30fc\u30b9\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\n\u8a73\u3057\u304f\u898b\u308beBook \u3068\u30d6\u30ed\u30b0\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30af\u5927\u898f\u6a21\u306a\u5171\u540c\u306e\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6280\u8853\u30e2\u30c0\u30f3\u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0MLflow\uff1a\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u6a5f\u68b0\u5b66\u7fd2\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u65b0\u3057\u3044 Delta Sharing \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u306e\u8a73\u7d30\u30ac\u30fc\u30c8\u30ca\u30fc MQ DBMS & DSML 2 \u90e8\u9580\u306e\u30ea\u30fc\u30c0\u30fc\u79fb\u884c\u30ac\u30a4\u30c9\uff1aHadoop \u304b\u3089 Databricks \u3078\u306e\u79fb\u884c\u30d6\u30ed\u30b0Hadoop \u304b\u3089\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3078\u306e\u79fb\u884c\uff1a\u6210\u529f\u306e\u305f\u3081\u306e 5 \u3064\u306e\u30b9\u30c6\u30c3\u30d7\u30aa\u30f3\u30e9\u30a4\u30f3\u30a4\u30d9\u30f3\u30c8Hadoop \u304b\u3089 Databricks \u3078\u306e\u79fb\u884c\u30ac\u30a4\u30c9\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/de\/blog","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-sparkr","text":"SparkRPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSparkRAll>SparkRTry Databricks for freeGet StartedSparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follows R\u2019s syntax instead of Python. For the most part, almost everything available in Python is available in SparkR.Additional ResourcesSparkR Overview DocumentationSparkR: Interactive R Programs at ScaleIntroducing Apache Spark 3.0: Now available in Databricks Runtime 7.0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=security","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/events","text":"Eventi di Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWEventi di DatabricksScopri i prossimi meetup, webinar, convegni e altri appuntamenti di DatabricksData + AI Summit 202326-29 giugnoScegli come vivere la tua esperienza: partecipa in prima persona o segui gli interventi e le sessioni di tuo interesse da remotoRegistratiLoading...Browse All Upcoming EventsProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/customers\/hsbc","text":"Customer Story: HSBC | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYReinventing mobile banking with ML6Seconds to perform complex analytics compared to 6 hours1Delta Lake has replaced 14 databases4.5xImprovement in engagement on the app INDUSTRY: Financial services SOLUTION: Anomaly detection,customer segmentation,fraud detection,recommendation engines,transaction enrichment PLATFORM USE CASE: Delta Lake,data science,machine learning,ETL CLOUD: Azure\u201cWe\u2019ve seen major improvements in the speed we have data available for analysis. We have a number of jobs that used to take 6 hours and now take only 6 seconds.\u201d\n\u2013 Alessio Basso, Chief Architect, HSBCAs one of the largest international banks, HSBC is ushering in a new way to manage digital payments across mobile devices. They developed PayMe, a social app that facilitates cashless transactions between consumers and their networks instantly and securely. With over 39 million customers, HSBC struggled to overcome scalability limitations that blocked them from making data-driven decisions. With Databricks, they are able to scale data analytics and machine learning to feed customer-centric use cases including personalization, recommendations, network science, and fraud detection.Data science and engineering struggled to leverage dataHSBC understands the massive opportunity for them to better serve their 39+ million customers through data and analytics. Seeing an opportunity to reinvent mobile payments, they developed the PayMe, a social payments app. Since its launch in their home market of Hong Kong, they have become the #1 app in the region amassing 1.8+ million users.In an effort to provide their fast growing customer base the best possible mobile payments experience, they looked to data and machine learning to enable various desired use cases such as detecting fraudulent activity, customer 360 to inform marketing decisions, personalization, and more. However, building models that could deliver on these use cases in a secure, fast and scalable manner was easier said than done.Slow data pipelines resulted in old data: Legacy systems hampered their ability to process and analyze data at scale. They were required to manually export and sample data, which was time consuming. This resulted in the data being weeks old upon delivery to the data science team which blocked their ability to be predictive.Manual data exporting and masking: Legacy processes required a manual approval form to be filled out for every data request which was error-prone. Furthermore, the manual masking process was time consuming and did not adhere to strict data quality and protection rules.Inefficient data science: Data scientists worked in silos on their own machines and custom environments, limiting their ability to explore raw data and train models at scale. As a result, collaboration was poor and iteration on models were very slow.Data analysts struggled to leverage data: Needing access to subsets of structured data for business intelligence and reporting.Faster and more secure analytics and ML at scaleThrough the use of NLP and machine learning, HSBC is able to quickly understand the intent behind each transaction within their PayMe app. This wide range of information is then used to inform various use cases from recommendations to customers to reducing anomalous activity.With Azure Databricks, they are able to unify data analytics across data engineering, data science, and analysts.Improved operational efficiency: features such as auto-scaling clusters and support for Delta Lake has improved operations from data ingest to managing the entire machine learning lifecycle.Real time data masking with delta lake: With Databricks and Delta Lake, HSBC was able to securely provide anonymized production data in real-time to data science and data analyst teams.Performant and scalable data pipelines with Delta Lake: This has enabled them to perform real-time data processing for downstream analytics and machine learning.Collaboration across data science and engineering: Enables faster data discovery, iterative feature engineering, and rapid model development and training.Richer insights leads to the #1 appDatabricks provides HSBC with a unified data analytics platform that centralizes all aspects of their analytics process from data engineering to the productionization of ML models that deliver richer business insights.Faster data pipelines:\u00a0Automating processes and increased data processing from 6 hours to 6 seconds for complex analytics.Descriptive to predictive:\u00a0Ability to train models against their entire dataset, has empowered them to deploy predictive models to feed various use cases.From 14 databases to 1 Delta Lake:\u00a0Moved from 14 read replica databases to a single unified data store with Delta Lake.PayMe is #1 app in Hong Kong:\u00a060% market share of the Hong Kong market making PayMe the #1 app.Improved consumer engagement:\u00a0Ability to leverage network science to understand customer connections has resulted in a 4.5x improvement in engagement levels with the PayMe app.Related ContentArticleWIRED Brand Lab | When it comes to security, data is the best defenseSessionTechnical Talk at Spark + AI Summit EU 2019Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=administration","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/naveen-zutshi\/#","text":"Naveen Zutshi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNaveen ZutshiChief Information Officer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks sur Google CloudLa plateforme lakehouse ouverte rejoint le cloud ouvert pour regrouper le data engineering, la data science et l'analytiqueD\u00e9marrerDatabricks on Google Cloud est un service d\u00e9velopp\u00e9 conjointement qui vous permet de stocker toutes vos donn\u00e9es sur une plateforme Lakehouse simple et ouverte combinant le meilleur des data warehouses et des data lakes pour unifier toutes vos charges de travail d'analytique et d'IA. L'int\u00e9gration \u00e9troite avec Google Cloud Storage, BigQuery et Google Cloud AI Platform permet \u00e0 Databricks de fonctionner en toute transparence sur les services de data et d'IA sur Google Cloud.\nData engineering fiableSQL Analytics sur toutes vos donn\u00e9es \u2192Data Science collaborativeMachine learning en production\nPourquoi Databricks sur Google Cloud ?OuvertConstruit sur des normes, des API et une infrastructure ouvertes et librement accessibles afin que vous puissiez acc\u00e9der, traiter et analyser les donn\u00e9es selon vos crit\u00e8res.Optimis\u00e9D\u00e9ployez Databricks sur Google Kubernetes Engine, le premier moteur d'ex\u00e9cution de Databricks bas\u00e9 sur Kubernetes pour obtenir des r\u00e9sultats plus rapidement.Int\u00e9gr\u00e9Acc\u00e9dez en un clic \u00e0 Databricks depuis la Google Cloud Console, avec s\u00e9curit\u00e9, facturation et gestion int\u00e9gr\u00e9es.En savoir plus sur ces clients\n\u00ab\u00a0Databricks sur Google Cloud simplifie le processus de conduite de plusieurs cas d'usage sur une plateforme de calcul \u00e9volutive, r\u00e9duisant ainsi les cycles de planification n\u00e9cessaires pour fournir une solution \u00e0 chaque question business ou probl\u00e9matique que nous utilisons.\u00a0\u00bb\u2014Harish Kumar, Global Data Science Director chez ReckittInt\u00e9gration simplifi\u00e9e avec Google CloudGoogle Cloud StorageGoogle Cloud StorageFacilitez un acc\u00e8s fluide en lecture \/ \u00e9criture pour les donn\u00e9es dans Google Cloud Storage (GCS) et exploitez le format ouvert Delta Lake pour ajouter de grandes capacit\u00e9s de fiabilit\u00e9 et de performance au sein de Databricks.Google Kubernetes EngineBigQueryIdentit\u00e9 du grand nuageGoogle Cloud AI PlatformGoogle Cloud BillingLooker\u00c9cosyst\u00e8me des partenairesRessources\u00c9v\u00e8nements virtuelsAtelier virtuel\u00a0: le Data Lake ouvert \u2192Actualit\u00e9sDatabricks s'associe \u00e0 Google Cloud pour proposer sa plateforme \u00e0 des entreprises internationalesBlogs et rapportsAnnonce du lancement de Databricks sur Google CloudPr\u00e9sentation de Databricks sur Google Cloud \u2013 D\u00e9sormais d\u00e9voil\u00e9e en avant-premi\u00e8re au publicFiche technique Databricks sur Google CloudDatabricks sur Google Cloud disponible partout d\u00e8s maintenantData engineering, data science et analytique avec Databricks sur Google CloudPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Essayer gratuitement Databricks | DatabricksEssayer gratuitement DatabricksExp\u00e9rimentez pleinement la plateforme Databricks gratuitement pendant 14 jours, sur AWS, Microsoft Azure ou Google Cloud, au choix.Simplification de l'ingestion des donn\u00e9es et automatisation de l\u2019ETLImportez des donn\u00e9es depuis des centaines de sources. Utilisez une approche d\u00e9clarative simple pour cr\u00e9er des pipelines de donn\u00e9es.Collaborez dans votre langage pr\u00e9f\u00e9r\u00e9Codez en Python, R, Scala et SQL. B\u00e9n\u00e9ficiez du RBAC, d\u2019int\u00e9grations avec Git et d\u2019outils comme la r\u00e9daction collaborative et la gestion automatique des versions.Un rapport performance \/ prix jusqu'\u00e0 12 fois sup\u00e9rieur \u00e0 celui des data warehousesD\u00e9couvrez pourquoi plus de 7 000 clients dans le monde s\u2019appuient sur Databricks pour toutes leurs charges de travail de la BI \u00e0 l\u2019IA.Cr\u00e9ez votre compte Databricks1\/2Pr\u00e9nomNomE-mail professionnelEntrepriseIntitul\u00e9 de posteNum\u00e9ro de t\u00e9l\u00e9phone (facultatif)Veuillez s\u00e9lectionnerPaysContinuerAvis de confidentialit\u00e9 (mis \u00e0 jour)Conditions d'utilisationVos choix de confidentialit\u00e9Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/learn\/certification","text":"Databricks Certification and Badging | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCommunity loginAcademy loginDatabricks Certification and BadgingThe new standard for lakehouse training and certificationsValidate your data and AI skills in the Databricks Lakehouse Platform by getting Databricks certified. Whether you are new to business intelligence or looking to confirm your skills as a machine learning or data engineering professional, Databricks can help you achieve your goals.Role Progression and CertificationsData AnalystData analysts transform data into insights by creating queries, data visualizations and dashboards using Databricks SQL and its capabilities.AssociateThe Databricks Certified Data Analyst Associate certification exam assesses an individual\u2019s ability to use the Databricks SQL service to complete introductory data analysis tasks.\nLearn moreData EngineerData engineers design, develop, test and maintain batch and streaming data pipelines using the Databricks Lakehouse Platform and its capabilities.AssociateThe Databricks Certified Data Engineer Associate certification exam assesses an individual\u2019s ability to use the Databricks Lakehouse Platform to complete introductory data engineering tasks.\nLearn moreProfessionalThe Databricks Certified Data Engineer Professional certification exam assesses an individual\u2019s ability to use Databricks to perform advanced data engineering tasks.\nLearn moreML Data ScientistMachine learning practitioners develop, deploy, test and maintain machine learning models and pipelines using Databricks Machine Learning and its capabilities.AssociateThe Databricks Certified Machine Learning Associate certification exam assesses an individual\u2019s ability to use Databricks to perform basic machine learning tasks.\nLearn moreProfessionalThe Databricks Certified Machine Learning Professional certification exam assesses an individual\u2019s ability to use Databricks Machine Learning and its capabilities to perform advanced machine learning in production tasks.\nLearn moreNext StepsSelect the certification that aligns to your roleRegister for the exam or sign up for the class to prepare for the examTake the exam and celebrate your success by posting on social mediaSpecialty BadgesAs you progress through your Lakehouse learning paths, you can earn specialty badges. Specialty badges represent an achievement in a focus area, such as a specific professional services offering or deployment on one of Databricks\u2019 cloud vendors.Apache Spark Developer AssociateThe Databricks Certified Associate Developer for Apache Spark certification exam assesses the understanding of the Spark DataFrame API and the ability to apply the Spark DataFrame API to complete basic data manipulation tasks within a Spark session.\nLearn morePlatform AdministratorThis accreditation is the final assessment in the Databricks Platform Administrator specialty learning pathway.\nLearn moreHadoop Migration ArchitectThe Databricks Certified Hadoop Migration Architect certification exam assesses an individual\u2019s ability to architect migrations from Hadoop to the Databricks Lakehouse Platform.\nLearn moreNext StepsSelect the specialty badge you are interested inLearn how the programs work and how to earn the specialty badgeResourcesAccess your earned Databricks credentialsCertification FAQProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/himanshu-raja","text":"Himanshu Raja - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHimanshu Raja DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yaniv-kunda","text":"Yaniv Kunda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYaniv KundaSenior Software Architect at AkamaiBack to speakersYaniv Kunda is a Senior Software Architect at Akamai. With more than 25 years of experience in software engineering and with a particular interest in the infrastructural aspects of the systems he worked on, Yaniv has been focusing on Big Data for the past 4 years. He holds a BA in Computer Sciences from the Interdisciplinary Center Herzliya.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shasidhar-eranti\/#","text":"Shasidhar Eranti - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShasidhar ErantiSpecialist Solutions Architect at DatabricksBack to speakersShasidhar is part of Specialist Solutions Architects team at Databricks. He is an expert in designing and building batch and streaming applications at scale using Apache Spark. At Databricks he works directly with customers to build. deploy and manage end-to-end spark pipelines in production, also help guide towards Spark best practices. \nShashidhar started his Spark journey back in 2014 in Bangalore, later he worked as an independent consultant for couple of years and joined Databricks in 2018.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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File Tra{...} \u30e1\u30c0\u30ea\u30aa\u30f3\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3 \u30e1\u30c0\u30ea\u30aa\u30f3\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3068\u306f\n\u30e1\u30c0\u30ea\u30aa\u30f3\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3068\u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u30c7\u30fc\u30bf\u3092\u8ad6\u7406\u7684\u306b\u6574\u7406\u3059\u308b\u305f\u3081\u306b\u7528\u3044\u3089\u308c\u308b\u30c7\u30fc\u30bf\u8a2d\u8a08\u3092\u610f\u5473\u3057\u307e\u3059\u3002\u30c7\u30fc\u30bf\u304c\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306e 3 \u3064\u306e\u30ec\u30a4\u30e4\u30fc\uff08\u30d6\u30ed\u30f3\u30ba \u2192 \u30b7\u30eb\u30d0\u30fc \u2192 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\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u306e\u30d1\u30fc\u30bd\u30ca\u30e9\u30a4\u30ba\u3068\u306f\n\u91d1\u878d\u5546\u54c1\u3084\u30b5\u30fc\u30d3\u30b9\u306e\u30b3\u30e2\u30c7\u30a3\u30c6\u30a3\u5316\u304c\u9032\u307f\u3001\u30e1\u30c7\u30a3\u30a2\u3084\u5c0f\u58f2\u696d\u754c\u304c\u30d1\u30fc\u30bd\u30ca\u30e9\u30a4\u30ba\u3055\u308c\u305f\u4f53\u9a13\u3092\u597d\u3080\u3088\u3046\u306b\u306a\u3063\u305f\u3053\u3068\u3067\u3001\u6d88\u8cbb\u8005\u306e\u76ee\u306f\u80a5\u3048\u3066\u304d\u3066\u3044\u307e\u3059\u3002\u6d88\u8cbb\u8005\u304b\u3089\u6c42\u3081\u3089\u308c\u308b\u3082\u306e\u304c\u65e5\u3005\u5909\u5316\u3057\u3066\u3044\u304f\u4e2d\u3067\u3001\u9280\u884c\u304c\u3053\u308c\u304b\u3089\u3082\u5fc5\u8981\u3068\u3055\u308c\u7d9a\u3051\u308b\u305f\u3081\u306b\u306f\u3001\u30d1\u30fc\u30bd\u30ca\u30e9\u30a4\u30ba\u3055\u308c\u305f\u77e5\u898b\u3084\u30ec\u30b3\u30e1\u30f3\u30c9\u3001\u8ca1\u52d9\u76ee\u6a19\u306e\u8a2d\u5b9a\u3001\u30ec\u30dd\u30fc\u30c8\u6a5f\u80fd\u3068\u3044\u3063\u305f\u5f93\u6765\u306e\u9280\u884c\u696d\u52d9\u3092\u8d85\u3048\u305f\u9b45\u529b\u7684\u306a\u9280\u884c\u4f53\u9a13\u3092\u63d0\u4f9b\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u3001\u3053\u308c\u3089\u306f\u5168\u3066\u5730\u7406\u7a7a\u9593\u3084\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\uff08NLP\uff09\u306a\u3069\u306e\u9ad8\u5ea6\u306a\u5206\u6790\u6a5f\u80fd\u306b\u3088\u3063\u3066\u5b9f\u73fe\u3055\u308c\u307e\u3059\u3002\u91d1\u878d\u30b5\u30fc{...}ACID \u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3 \u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3\u0000\u3068\u306f\n\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3084\u30c7\u30fc\u30bf\u30b9\u30c8\u30ec\u30fc\u30b8\u30b7\u30b9\u30c6\u30e0\u306b\u304a\u3051\u308b\u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3\u3068\u306f\u30011 \u3064\u306e\u4f5c\u696d\u5358\u4f4d\u3068\u3057\u3066\u6271\u308f\u308c\u308b\u3042\u3089\u3086\u308b\u64cd\u4f5c\u306e\u3053\u3068\u3067\u3059\u3002\u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3\u306f\u3001\u5b8c\u5168\u306b\u5b9f\u884c\u3055\u308c\u308b\u3001\u3082\u3057\u304f\u306f\u5168\u304f\u5b9f\u884c\u3055\u308c\u306a\u3044\u304b\u306e\u3044\u305a\u308c\u304b\u3067\u3001\u30b9\u30c8\u30ec\u30fc\u30b8\u30b7\u30b9\u30c6\u30e0\u3092\u4e00\u8cab\u3057\u305f\u72b6\u614b\u306b\u4fdd\u3061\u307e\u3059\u3002\u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3\u306e\u5178\u578b\u7684\u306a\u4f8b\u3068\u3057\u3066\u3001\u9280\u884c\u306e\u9810\u91d1\u53e3\u5ea7\u304b\u3089\u73fe\u91d1\u3092\u5f15\u304d\u51fa\u3059\u51e6\u7406\u304c\u6319\u3052\u3089\u308c\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001\u9810\u91d1\u53e3\u5ea7\u304b\u3089\u73fe\u91d1\u3092\u5f15\u304d\u51fa\u3057\u305f\u304b\u3001\u3082\u3057\u304f\u306f\u5168\u304f\u5f15\u304d\u51fa\u3055\u306a\u304b\u3063\u305f\u304b\u3001\u3069\u3061\u3089\u304b\u306e\u51e6\u7406\u304c\u767a\u751f\u3057\u3001\u4e2d\u9593\u306e\u72b6\u614b\u306f\u3042\u308a\u307e\u305b\u3093\u3002\nACID {...}AdaGrad \u6a5f\u68b0\u5b66\u7fd2\u3084\u6df1\u5c64\u5b66\u7fd2\u306b\u304a\u3051\u308b\u6700\u9069\u5316\u306e\u305f\u3081\u306e\u6700\u3082\u4e00\u822c\u7684\u306a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e 1 \u3064\u306b\u3001\u52fe\u914d\u964d\u4e0b\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002\u52fe\u914d\u964d\u4e0b\u6cd5\u306f\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\n\u52fe\u914d\u964d\u4e0b\u6cd5\u306e\u7a2e\u985e\n\u73fe\u5728\u3001\u6a5f\u68b0\u5b66\u7fd2\u3084\u6df1\u5c64\u5b66\u7fd2\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306b\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u52fe\u914d\u964d\u4e0b\u6cd5\u306f\u3001\u4e3b\u306b3\u7a2e\u985e\u3042\u308a\u307e\u3059\u3002\n\u30d0\u30c3\u30c1\u52fe\u914d\u964d\u4e0b\u6cd5\n3 \u7a2e\u985e\u306e\u52fe\u914d\u964d\u4e0b\u6cd5\u306e\u4e2d\u3067\u3001\u30d0\u30c3\u30c1\u52fe\u914d\u964d\u4e0b\u6cd5\u306f\u4e00\u756a\u5bb9\u6613\u306a\u624b\u6cd5\u3067\u3059\u3002\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5404\u30c7\u30fc\u30bf\u306e\u8aa4\u5dee\u3092\u8a08\u7b97\u3057\u307e\u3059\u304c\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u306e\u8a08\u7b97\u304c\u5168\u3066\u7d42\u4e86\u3059\u308b\u307e\u3067\u30e2\u30c7\u30eb{...}Apache Hive Apache Hive \u3068\u306f\nApache Hive \u306f\u3001Apache Hadoop \u5206\u6563\u30d5\u30a1\u30a4\u30eb\u30b7\u30b9\u30c6\u30e0&nbsp;(HDFS)&nbsp;\u304b\u3089\u62bd\u51fa\u3055\u308c\u305f\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u53d6\u308a\u3001\u66f8\u304d\u8fbc\u307f\u3001\u304a\u3088\u3073\u7ba1\u7406\u3092\u884c\u3046\u305f\u3081\u306b\u8a2d\u8a08\u3055\u308c\u305f\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u3067\u3001\u3088\u308a\u898f\u6a21\u306e\u5927\u304d\u3044&nbsp;Hadoop \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u5074\u9762\u3082\u6301\u3061\u5408\u308f\u305b\u3066\u3044\u307e\u3059\u3002\nApache Hive\u306e\u8c4a\u5bcc\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3068\u7d99\u7d9a\u7684\u306a\u30a2\u30c3\u30d7\u30c7\u30fc\u30c8\u306b\u3088\u308a\u3001Apache Hive\u306f\u30a2\u30af\u30bb\u30b9\u3057\u3084\u3059\u3044\u65b9\u6cd5{...}Apache Kudu Apache Kudu \u3068\u306f\nApache Kudu \u3068\u306f\u3001Apache&nbsp;Hadoop&nbsp;\u5411\u3051\u306b\u958b\u767a\u3055\u308c\u305f\u7121\u6599\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u5217\u6307\u5411\u30b9\u30c8\u30ec\u30fc\u30b8\u30b7\u30b9\u30c6\u30e0\u3067\u3059\u3002\u69cb\u9020\u5316\u30c7\u30fc\u30bf\u7528\u30a8\u30f3\u30b8\u30f3\u3067\u3001\u5404\u884c\u3078\u306e\u4f4e\u9045\u5ef6\u3067\u30e9\u30f3\u30c0\u30e0\u306a\u30df\u30ea\u79d2\u30b9\u30b1\u30fc\u30eb\u306e\u30a2\u30af\u30bb\u30b9\u306b\u52a0\u3048\u3066\u3001\u512a\u308c\u305f\u30a2\u30af\u30bb\u30b9\u30d1\u30bf\u30fc\u30f3\u5206\u6790\u3082\u30b5\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002\u5e83\u304f\u666e\u53ca\u3057\u3066\u3044\u308b&nbsp;Hadoop \u5206\u6563\u30d5\u30a1\u30a4\u30eb\u30b7\u30b9\u30c6\u30e0\uff08HDFS\uff09\u3068 NoSQL \u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e HBase \u9593\u3092\u3064\u306a\u3050\u305f\u3081\u306b\u4f5c\u6210\u3055\u308c\u305f\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30f3\u3067\u3059\u3002\nHadoo{...}Apache Kylin Apache Kylin \u3068\u306f\nApache Kylin \u3068\u306f\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u5bfe\u8a71\u578b\u5206\u6790\u306e\u305f\u3081\u306e\u5206\u6563\u578b\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30aa\u30f3\u30e9\u30a4\u30f3\u5206\u6790\u51e6\u7406\uff08OLAP\uff09\u30a8\u30f3\u30b8\u30f3\u3067\u3059\u3002Apache Kylin \u306f&nbsp;Hadoop&nbsp;\u3084 Spark \u3067SQL \u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3068\u591a\u6b21\u5143\u5206\u6790\uff08OLAP\uff09\u3092\u63d0\u4f9b\u3059\u308b\u3088\u3046\u8a2d\u8a08\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3055\u3089\u306b\u3001ODBC \u30c9\u30e9\u30a4\u30d0\u3001JDBC \u30c9\u30e9\u30a4\u30d0\u3001REST API \u3092\u4ecb\u3057\u3066 BI \u30c4\u30fc\u30eb\u3068\u5bb9\u6613\u306b\u7d71\u5408\u3057\u307e\u3059\u30022014\u5e74\u306b eBay \u304c\u69cb\u7bc9\u3057\u305f Apache Kylin {...}Apache Spark Apache Spark \u3068\u306f\nApache Spark \u306f\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306b\u4f7f\u7528\u3059\u308b\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u5206\u6790\u30a8\u30f3\u30b8\u30f3\u3067\u3059\u3002\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u5206\u6790\u3068\u30c7\u30fc\u30bf\u51e6\u7406\u306e\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306b\u52a0\u3048\u3066\u3001\u4e21\u65b9\u306e\u30d0\u30c3\u30c1\u51e6\u7406\u304c\u53ef\u80fd\u3067\u3059\u3002Apache Spark \u306f 2009 \u5e74\u306b\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5927\u5b66\u30d0\u30fc\u30af\u30ec\u30fc\u6821\u306e\u7814\u7a76\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3068\u3057\u3066\u958b\u767a\u3055\u308c\u307e\u3057\u305f\u3002\u305d\u308c\u307e\u3067\u7814\u7a76\u8005\u306f\u3001Hadoop&nbsp;\u30b7\u30b9\u30c6\u30e0\u3067\u306e\u30b8\u30e7\u30d6\u51e6\u7406\u3092\u9ad8\u901f\u5316\u3059\u308b\u65b9\u6cd5\u3092\u6a21\u7d22\u3057\u3066\u3044\u307e\u3057\u305f\u3002Apache Spark \u306f Hadoop&nbsp;MapRedu{...}Catalyst\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6 Catalyst \u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u3068\u306f\u3001Spark SQL \u3067\u4e3b\u8981\u306a\u5f79\u5272\u3092\u679c\u305f\u3059\u6700\u9069\u5316\u6a5f\u80fd\u3067\u3059\u3002Scala \u306e\u30d1\u30bf\u30fc\u30f3\u30de\u30c3\u30c1\u30f3\u30b0\u3084\u6e96\u30af\u30a9\u30fc\u30c8\u306a\u3069\u306e\u9ad8\u5ea6\u306a\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u306e\u6a5f\u80fd\u3092\u65ac\u65b0\u306a\u65b9\u6cd5\u3067\u5229\u7528\u3057\u3001\u62e1\u5f35\u53ef\u80fd\u306a\u30af\u30a8\u30ea\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u3092\u69cb\u7bc9\u3057\u307e\u3059\u3002Catalyst \u306f Scala \u306e\u95a2\u6570\u578b\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u69cb\u9020\u306b\u57fa\u3065\u3044\u3066\u304a\u308a\u3001\u6b21\u306e 2 \u3064\u306e\u4e3b\u8981\u306a\u76ee\u7684\u3092\u60f3\u5b9a\u3057\u3066\u8a2d\u8a08\u3055\u308c\u3066\u3044\u307e\u3059\u3002\nSpark SQL\u3078\u306e\u65b0\u3057\u3044\u6700\u9069\u5316\u6280\u8853\u3068\u6a5f\u80fd\u306e\u8ffd\u52a0\u3092\u5bb9\u6613\u306b\u3059\u308b\n\u5916\u90e8\u306e\u958b\u767a\u8005\u3067\u3082\u30aa\u30d7\u30c6\u30a3\u30de\u30a4\u30b6\u306e\u62e1\u5f35\u3092\u5b9f\u884c\u3067\u304d\u308b\u3088{...}Convolutional Layer\uff1a\u7573\u307f\u8fbc\u307f\u5c64 \u6df1\u5c64\u5b66\u7fd2\u306b\u304a\u3044\u3066\u3001\u7573\u307f\u8fbc\u307f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\uff08CNN \u307e\u305f\u306f ConvNet\uff09\u306f\u30c7\u30a3\u30fc\u30d7\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\uff11\u3064\u306e\u624b\u6cd5\u3067\u3059\u3002\u753b\u50cf\u5185\u306e\u30d1\u30bf\u30fc\u30f3\u8a8d\u8b58\u306b\u901a\u5e38\u4f7f\u7528\u3055\u308c\u307e\u3059\u304c\u3001\u7a7a\u9593\u30c7\u30fc\u30bf\u5206\u6790\u3001\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30d3\u30b8\u30e7\u30f3\u3001\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u3001\u4fe1\u53f7\u51e6\u7406\u306a\u3069\u3055\u307e\u3056\u307e\u306a\u7528\u9014\u306b\u5bfe\u3059\u308b\u5c0e\u5165\u4e8b\u4f8b\u3082\u3042\u308a\u307e\u3059\u3002\u7573\u307f\u8fbc\u307f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306f\u4eba\u9593\u306e\u8133\u5185\u306e\u30cb\u30e5\u30fc\u30ed\u30f3\u7d50\u5408\u30d1\u0000\u30bf\u30fc\u30f3\u306b\u985e\u4f3c\u3057\u3001\u8996\u899a\u91ce\u306e\u7d44\u7e54\u69cb\u9020\u306b\u7740\u60f3\u3092\u5f97\u307e\u3057\u305f\u3002\u4eba\u5de5\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u95a2\u9023\u306e\u3053\u306e\u30bf\u30a4\u30d7\u306f\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u6700\u3082\u91cd\u8981\u306a\u64cd\u4f5c\u306e\u4e00\u3064\u3067\u3042\u308b\u300c\u7573\u307f\u8fbc\u307f\u300d\u304b\u3089\u540d{...}Databricks Runtime Databricks \u30e9\u30f3\u30bf\u30a4\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u304c\u7ba1\u7406\u3059\u308b\u30de\u30b7\u30f3\u306e\u30af\u30e9\u30b9\u30bf\u4e0a\u3067\u5b9f\u884c\u3055\u308c\u308b\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30a2\u30fc\u30c6\u30a3\u30d5\u30a1\u30af\u30c8\u306e\u30bb\u30c3\u30c8\u3067\u3059\u3002Spark \u306f\u3082\u3061\u308d\u3093\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u5206\u6790\u306e\u64cd\u4f5c\u6027\u3084\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3001\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u306a\u3069\u3092\u5927\u5e45\u306b\u5411\u4e0a\u3055\u305b\u308b\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u3084\u66f4\u65b0\u30d7\u30ed\u30b0\u30e9\u30e0\u3082\u6570\u591a\u304f\u8ffd\u52a0\u3055\u308c\u3066\u3044\u307e\u3059\u3002Databricks \u30e9\u30f3\u30bf\u30a4\u30e0\u304c\u4ed6\u306e\u30e9\u30f3\u30bf\u30a4\u30e0\u3088\u308a\u3082\u512a\u308c\u3066\u3044\u308b\u70b9\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002\n\u512a\u308c\u305f\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\uff1aDatabricks I\/O\u30e2\u30b8\u30e5\u30fc\u30eb\uff08DBIO\uff09\u306f\u3001\u5782\u76f4\u7d71\u5408\u30b9\u30bf\u30c3\u30af\u3092\u6d3b\u7528\u3057\u3066\u30af\u30e9\u30a6\u30c9\u3067{...}DataFrames DataFrame \u3068\u306f\nDataFrame&nbsp;\u306e\u6982\u5ff5\u306f\u3001\u591a\u304f\u306e\u8a00\u8a9e\u3084\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u5171\u901a\u3057\u3066\u3044\u307e\u3059\u3002DataFrame \u306f\u3001\u67d4\u8edf\u304b\u3064\u0000\u76f4\u611f\u7684\u306b\u30c7\u30fc\u30bf\u306e\u4fdd\u5b58\u3084\u64cd\u4f5c\u304c\u3067\u304d\u308b\u305f\u3081\u3001\u6700\u65b0\u306e\u30c7\u30fc\u30bf\u5206\u6790\u3067\u6700\u3082\u4e00\u822c\u7684\u306b\u4f7f\u7528\u3055\u308c\u308b\u30c7\u30fc\u30bf\u69cb\u9020\u306e 1 \u3064\u3067\u3059\u3002\nDataFrame \u306b\u306f\u30b9\u30ad\u30fc\u30de\u3068\u547c\u3070\u308c\u308b\u9752\u5199\u771f\u304c\u542b\u307e\u308c\u3066\u304a\u308a\u3001\u5404\u5217\u306e\u540d\u524d\u3068\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u304c\u5b9a\u7fa9\u3055\u308c\u3066\u3044\u307e\u3059\u3002Spark DataFrame \u306b\u306f\u3001\u6587\u5b57\u5217\u578b\u3084\u6574\u6570\u578b\u306a\u3069\u306e\u6c4e\u7528\u7684\u306a\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u3068\u3001\u69cb\u9020\u578b\u306a\u3069\u306e Spark \u56fa\u6709\u306e\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u3092{...}DNA \u30b7\u30fc\u30b1\u30f3\u30b9 DNA \u30b7\u30fc\u30b1\u30f3\u30b9\u3068\u306f\nDNA \u30b7\u30fc\u30b1\u30f3\u30b9\u3068\u306f\u3001DNA\uff08\u30c7\u30aa\u30ad\u30b7\u30ea\u30dc\u6838\u9178\uff09\u306e\u30cc\u30af\u30ec\u30aa\u30c1\u30c9\u306e\u6b63\u78ba\u306a\u914d\u5217\u3092\u6c7a\u5b9a\u3059\u308b\u30d7\u30ed\u30bb\u30b9\u3067\u3059\u3002\u5869\u57fa\u3068\u3057\u3066\u3082\u77e5\u3089\u308c\u308b4\u3064\u306e\u5316\u5b66\u69cb\u6210\u8981\u7d20\uff08\u30a2\u30c7\u30cb\u30f3\u3001\u30b0\u30a2\u30cb\u30f3\u3001\u30b7\u30c8\u30b7\u30f3\u3001\u30c1\u30df\u30f3\uff09\u306e\u9806\u5e8f\u306eDNA\u30b7\u30fc\u30b1\u30f3\u30b7\u30f3\u30b0\u306f\u3001DNA\u5206\u5b50\u5185\u3067\u767a\u751f\u3057\u307e\u3059\u3002DNA \u30b7\u30fc\u30b1\u30f3\u30b7\u30f3\u30b0\u306e\u6700\u521d\u306e\u624b\u6cd5\u306f\u30011970\u5e74\u4ee3\u534a\u3070\u306b\u30d5\u30ec\u30c3\u30c9\u30fb\u30b5\u30f3\u30ac\u30fc\uff08Fred Sanger\uff09\u3001\u30a6\u30a9\u30eb\u30bf\u30fc\u30fb\u30ae\u30eb\u30d0\u30fc\u30c8\uff08Walter Gilbert\uff09\u3001\u30a2\u30e9\u30f3\u30fb\u30de\u30af\u30b5\u30e0\uff08Allan Maxam\uff09\u306b\u3088\u3063\u3066\u958b\u767a\u3055\u308c\u307e\u3057\u305f\u3002\u914d\u5217\u6c7a\u5b9a\u3055{...}ETL\uff1a\u62bd\u51fa\u30fb\u5909\u63db\u30fb\u30ed\u30fc\u30c9 \nDelta Live Tables\nDelta Live Tables\uff08DLT\uff09\u306f\u3001\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u3068\u7ba1\u7406\u3092\u5bb9\u6613\u306b\u3057\u3001\u4fe1\u983c\u6027\u3092\u5411\u4e0a\u3055\u305b\u3066 Delta Lake \u306b\u9ad8\u54c1\u8cea\u30c7\u30fc\u30bf\u3092\u3082\u305f\u3089\u3057\u307e\u3059\u3002\n&nbsp;\nDatabricks ETL \u306e\n\u8a73\u7d30\n&nbsp;\nETL \u3068\u306f\n\u7d44\u7e54\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u3001\u30c7\u30fc\u30bf\u30bd\u30fc\u30b9\u306e\u5897\u52a0\u3001\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u306e\u591a\u69d8\u5316\u306b\u4f34\u3044\u3001\u5206\u6790\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u3001\u6a5f\u68b0\u5b66\u7fd2\u306b\u53d6\u308a\u7d44\u307f\u3001\u30c7\u30fc\u30bf\u3092\u6d3b\u7528\u3057\u3066\u30d3\u30b8\u30cd\u30b9\u306e\u6c17\u3065\u304d\u3092\u5f15\u304d\u51fa{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Hadoop Hadoop \u3068\u306f\n\u300cHadoop\u300d\u3068\u306f\u4f55\u3092\u610f\u5473\u3059\u308b\u306e\u3067\u3057\u3087\u3046\u304b\u3002\u300cHadoop\u300d\u3068\u306f\u4f55\u306e\u7565\u306a\u306e\u3067\u3057\u3087\u3046\u304b\uff1fHadoop \u306f\u3001High Availability Distributed Object Oriented Platform \u306e\u7565\u3067\u3059\u3002\u305d\u3057\u3066\u3001\u3053\u308c\u3053\u305d\u304c Hadoop \u30c6\u0000\u0000\u30af\u30ce\u30ed\u30b8\u30fc\u304c\u958b\u767a\u8005\u306b\u63d0\u4f9b\u3059\u308b\u3082\u306e\u3067\u3059\u3002\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u6307\u5411\u30bf\u30b9\u30af\u306e\u4e26\u5217\u5206\u6563\u306b\u3088\u308b\u9ad8\u53ef\u7528\u6027\u3092\u5b9f\u73fe\u3057\u307e\u3059\u3002\nApache Hadoop \u3068\u306f\u3001\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e Java \u30d9\u30fc\u30b9\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u3001\u30d3\u30c3{...}Hadoop \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0 Hadoop&nbsp;\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3068\u306f\nApache Hadoop \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3068\u306f\u3001Apache Hadoop \u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u3055\u307e\u3056\u307e\u306a\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u3092\u6307\u3057\u307e\u3059\u3002\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3060\u3051\u3067\u306a\u304f\u3001\u88dc\u8db3\u30c4\u30fc\u30eb\u306e\u5168\u3066\u304c\u542b\u307e\u308c\u307e\u3059\u3002Hadoop \u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u6700\u3082\u3088\u304f\u77e5\u3089\u308c\u3066\u3044\u308b\u30c4\u30fc\u30eb\u306b\u306f\u3001HDFS\u3001Hive\u3001Pig\u3001YARN\u3001MapReduce\u3001Spark\u3001HBase Oozie\u3001Sqoop\u3001Zookeeper\u3001\u306a\u3069\u304c\u3042\u308a\u307e\u3059\u3002\u958b\u767a\u8005\u304c\u983b\u7e41\u306b\u4f7f\u7528\u3059\u308b\u4e3b\u8981\u306a Hadoop \u30a8\u30b3{...}Hadoop \u30af\u30e9\u30b9\u30bf Hadoop \u30af\u30e9\u30b9\u30bf\u3068\u306f\nApache&nbsp;Hadoop&nbsp;\u3068\u306f\u3001\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e Java \u30d9\u30fc\u30b9\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3001\u4e26\u5217\u30c7\u30fc\u30bf\u51e6\u7406\u30a8\u30f3\u30b8\u30f3\u3067\u3059\u3002\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\uff08MapReduce&nbsp;\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306a\u3069\uff09\u3092\u4f7f\u7528\u3057\u3066\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u5206\u6790\u51e6\u7406\u30bf\u30b9\u30af\u3092\u4e26\u5217\u5b9f\u884c\u3067\u304d\u308b\u5c0f\u3055\u306a\u30bf\u30b9\u30af\u306b\u5206\u5272\u3057\u3001Hadoop \u30af\u30e9\u30b9\u30bf\u5168\u4f53\u306b\u5206\u6563\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002Hadoop \u30af\u30e9\u30b9\u30bf\u3068\u306f\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u5bfe\u3057\u3066\u3053\u306e\u3088\u3046\u306a\u4e26\u5217\u8a08\u7b97\u3092\u5b9f\u884c\u3059\u308b\u305f\u3081\u306b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u5316\u3055\u308c\u305f\u3001\u30ce\u30fc\u30c9\u3068\u547c\u3070\u308c\u308b\u30b3{...}Hadoop \u5206\u6563\u30d5\u30a1\u30a4\u30eb\u30b7\u30b9\u30c6\u30e0\uff08HDFS\uff09 HDFS\nHDFS \uff08 Hadoop \u5206\u6563\u30d5\u30a1\u30a4\u30eb\u30b7\u30b9\u30c6\u30e0\uff09\u306f\u3001 Hadoop \u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3067\u4f7f\u7528\u3055\u308c\u308b\u4e3b\u8981\u306a\u30b9\u30c8\u30ec\u30fc\u30b8\u30b7\u30b9\u30c6\u30e0\u3067\u3059\u3002\u3053\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306f\u3001\u30ce\u30fc\u30c9\u9593\u306e\u30c7\u30fc\u30bf\u8ee2\u9001\u3092\u9ad8\u901f\u306b\u884c\u3046\u3053\u3068\u3067\u52d5\u4f5c\u3057\u307e\u3059\u3002\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u3092\u53d6\u308a\u6271\u3044\u3001\u4fdd\u5b58\u3059\u308b\u5fc5\u8981\u306e\u3042\u308b\u4f01\u696d\u3067\u3088\u304f\u5229\u7528\u3055\u308c\u3066\u3044\u307e\u3059\u3002HDFS \u306f\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u3092\u7ba1\u7406\u3057\u3001\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u89e3\u6790\u3092\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u624b\u6bb5\u3068\u3057\u3066\u3001\u591a\u304f\u306e Hadoop \u30b7\u30b9\u30c6\u30e0\u306b\u304a\u3044\u3066\u91cd\u8981\u306a\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u3068\u306a\u3063\u3066\u3044\u307e\u3059\u3002\nHDFS \u3092\u5229\u7528\u3057\u3066\u3044\u308b\u4f01\u696d\u306f\u4e16\u754c\u4e2d\u306b{...}Hive \u65e5\u4ed8\u95a2\u6570 \u30cf\u30a4\u30d6\u65e5\u4ed8\u95a2\u6570\u3068\u306f\nHive\u3067\u306f\u3001\u30c7\u30fc\u30bf\u306e\u51e6\u7406\u3084\u7167\u4f1a\u3092\u884c\u3046\u969b\u306b\u5f79\u7acb\u3064\u591a\u304f\u306e\u7d44\u307f\u8fbc\u307f\u95a2\u6570\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u95a2\u6570\u304c\u63d0\u4f9b\u3059\u308b\u6a5f\u80fd\u306b\u306f\u3001\u6587\u5b57\u5217\u64cd\u4f5c\u3001\u65e5\u4ed8\u64cd\u4f5c\u3001\u578b\u5909\u63db\u3001\u6761\u4ef6\u6f14\u7b97\u5b50\u3001\u6570\u5b66\u95a2\u6570\u306a\u3069\u304c\u3042\u308a\u307e\u3059\u3002\nHIVE 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\u3068&nbsp;Tensorflow&nbsp;\u4e0a\u306b\u69cb\u7bc9\u3055\u308c\u305f\u6df1\u5c64\u5b66\u7fd2\u306e\u305f\u3081\u306e\u30cf\u30a4\u30ec\u30d9\u30eb\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3059\u3002Keras \u306f\u3001Python \u3067\u8a18\u8ff0\u3055\u308c\u3001\u6df1\u5c64\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u7bc4\u56f2\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u30af\u30ea\u30fc\u30f3\u3067\u4fbf\u5229\u306a\u65b9\u6cd5\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002Keras \u306f\u3001\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u958b\u767a\u3068\u30c6\u30b9\u30c8\u306b\u95a2\u3057\u3066\u6700\u3082\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u9ad8\u30ec\u30d9\u30eb\u306e\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af API \u306e 1 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\u3067\u30c7\u30fc\u30bf\u5206\u6790\u3092\u884c\u3046\u305f\u3081\u306e\u30aa\u30fc\u30d7\u30f3\u30bd{...}Parquet Parquet \u3068\u306f\nApache Parquet \u306f\u3001\u52b9\u7387\u7684\u306a\u30c7\u30fc\u30bf\u306e\u4fdd\u5b58\u3068\u691c\u7d22\u306e\u305f\u3081\u306b\u8a2d\u8a08\u3055\u308c\u305f\u3001\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u5217\u6307\u5411\u30c7\u30fc\u30bf\u30d5\u30a1\u30a4\u30eb\u5f62\u5f0f\u3067\u3059\u3002\u8907\u96d1\u306a\u30c7\u30fc\u30bf\u3092\u4e00\u62ec\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u52b9\u7387\u7684\u306a\u30c7\u30fc\u30bf\u5727\u7e2e\u3068\u7b26\u53f7\u5316\u65b9\u5f0f\u3092\u63d0\u4f9b\u3057\u3001\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u5411\u4e0a\u3055\u305b\u307e\u3059\u3002Apache Parquet \u306f\u3001\u30d0\u30c3\u30c1\u3068\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306e\u4e21\u65b9\u306e\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3067\u5171\u901a\u306e\u4ea4\u63db\u5f62\u5f0f\u3068\u306a\u308b\u3088\u3046\u306b\u8a2d\u8a08\u3055\u308c\u3066\u304a\u308a\u3001Hadoop&nbsp;\u3067\u5229\u7528\u53ef\u80fd\u306a\u4ed6\u306e\u5217\u6307\u5411\u30b9\u30c8\u30ec\u30fc\u30b8\u30d5\u30a1\u30a4\u30eb\u5f62\u5f0f\u3067\u3042\u308b RCFile \u3084 ORC \u306b\u4f3c\u3066\u3044\u307e\u3059\u3002\n{...}PyCharm PyCharm \u3068\u306f\u3001\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u3067\u4f7f\u7528\u3055\u308c\u308b\u7d71\u5408\u958b\u767a\u74b0\u5883\uff08IDE\uff09\u3067\u3059\u3002\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e Python \u7528\u306b\u4f5c\u6210\u3055\u308c\u3066\u3044\u307e\u3059\u3002PyCharm \u3092\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u3067\u4f7f\u7528\u3059\u308b\u5834\u5408\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u306f PyCharm \u306f Python \u306e\u4eee\u60f3\u74b0\u5883\u3092\u4f5c\u6210\u3057\u307e\u3059\u304c\u3001Conda \u74b0\u5883\u306e\u4f5c\u6210\u3084\u65e2\u5b58\u74b0\u5883\u306e\u4f7f\u7528\u8a2d\u5b9a\u304c\u53ef\u80fd\u3067\u3059\u3002\n{...}PySpark PySpark \u3068\u306f\nApache Spark \u306f\u3001\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e Scala \u3067\u8a18\u8ff0\u3055\u308c\u3066\u3044\u307e\u3059\u3002PySpark \u3068\u306f\u3001Spark \u3092\u5b9f\u884c\u3059\u308b\u305f\u3081\u306e Python API \u3067\u3059\u3002Apache Spark \u3068Python \u306e\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u305f\u3081\u306b\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u307e\u3057\u305f\u3002PySpark \u306f\u3001Apache Spark \u3068\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e Python \u3067\u306e Resilient Distributed Dataset\uff08RDD\uff09\u3068\u306e\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u3082\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u304a\u308a\u3001\u3053\u308c\u306f Py4{...}Spark API Spark\u306b\u306f\u3001DataFrame\u3001Dataset\u3001RDD\u306e3\u3064\u306eAPI\u304c\u3042\u308a\u307e\u3059\u3002\n\u30ec\u30b8\u30ea\u30a8\u30f3\u30c8\u306a\u5206\u6563\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8(RDD)\u3068\u306f\n\u30ec\u30b8\u30ea\u30a8\u30f3\u30c8\u306a\u5206\u6563\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8(RDD)\u306f\u3001\u5206\u6563\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u3092\u7528\u3044\u305f\u30ec\u30b3\u30fc\u30c9\u30b3\u30ec\u30af\u30b7\u30e7\u30f3\u3067\u3059\u3002\u30d5\u30a9\u30fc\u30eb\u30c8\u30c8\u30ec\u30e9\u30f3\u30c8\u3067\u4e0d\u5909\u306a\u6027\u8cea\u3092\u6709\u3057\u3066\u3044\u307e\u3059\u3002RDD\u306f\u3001\u4f4e\u30ec\u30d9\u30ebAPI\u3068\u306e\u4e26\u5217\u64cd\u4f5c\u304c\u53ef\u80fd\u3067\u3001\u9045\u5ef6\u6a5f\u80fd\u306b\u3088\u308aSpark\u306e\u64cd\u4f5c\u3092\u8fc5\u901f\u5316\u3057\u307e\u3059\u3002\u307e\u305f\u3001RDD\u306f2\u3064\u306e\u64cd\u4f5c\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002\n\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30e1\u30fc\u30b7\u30e7\u30f3 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\u591a\u304f\u306e\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3001\u30a2\u30ca\u30ea\u30b9\u30c8\u3001\u4e00\u822c\u7684\u306a BI \u30e6\u30fc\u30b6\u30fc\u306f\u3001\u30c7\u30fc\u30bf\u306e\u89e3\u6790\u306b\u5bfe\u8a71\u578b\u306e SQL \u30af\u30a8\u30ea\u306b\u6d3b\u7528\u3057\u3066\u3044\u307e\u3059\u3002Spark SQL \u3068\u306f\u3001\u69cb\u9020\u5316\u30c7\u30fc\u30bf\u51e6\u7406\u306e\u305f\u3081\u306eSpark\u30e2\u30b8\u30e5\u30fc\u30eb\u3067\u3059\u3002DataFrames \u3068\u547c\u3070\u308c\u308b\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u306e\u62bd\u8c61\u5316\u304c\u53ef\u80fd\u3067\u3001\u5206\u6563\u578b SQL \u30af\u30a8\u30ea\u30a8\u30f3\u30b8\u30f3\u3068\u3057\u3066\u3082\u6a5f\u80fd\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u65e2\u5b58\u306e\u30c7\u30d7\u30ed\u30a4\u3084\u30c7\u30fc\u30bf\u3067\u672a\u4fee\u6b63\u306e&nbsp;Hadoop&nbsp;Hive \u30af\u30a8\u30ea\u3092\u6700\u5927 100 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RDD\u3092\u30b7\u30ea\u30a2\u30eb\u5316\u3057\u3066\u683c\u7d0d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u307e\u305f\u3001\u30c7\u30fc\u30bf\u306e\u30b7\u30ea\u30a2\u30e9\u30a4\u30ba\u306f\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306b\u3082\u5f71\u97ff\u3057\u307e\u3059\u3002Spark\u306e\u6027\u80fd\u3092\u5411{...}Sparse Tensor Python \u306b\u306f\u3001\u591a\u6b21\u5143\u914d\u5217\u3092\u64cd\u4f5c\u3059\u308b NumPy \u3068\u547c\u3070\u308c\u308b\u30d3\u30eb\u30c8\u30a4\u30f3\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u3042\u308a\u307e\u3059\u3002PyTensor \u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u958b\u767a\u3059\u308b\u306b\u306f\u3001NumPy \u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u304c\u7b2c\u4e00\u306e\u8981\u4ef6\u3068\u306a\u308a\u307e\u3059\u3002Sptensor \u306f\u3001Sparse Tensor \u3092\u8868\u3059\u30af\u30e9\u30b9\u3067\u3059\u3002Sparse Tensor 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These streams are triggered by a{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow Google \u306f\u30012015\u5e7411\u6708\u306b\u6a5f\u68b0\u5b66\u7fd2\u306e\u305f\u3081\u306e\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u3067\u516c\u958b\u3057\u3001TensorFlow&nbsp;\u3068\u540d\u4ed8\u3051\u307e\u3057\u305f\u3002CPU\u3001GPU\u3001GPU \u30af\u30e9\u30b9\u30bf\u3067\u306e\u6df1\u5c64\u5b66\u7fd2\u3001\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3001\u4e00\u822c\u7684\u306a\u6570\u5024\u8a08\u7b97\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002TensorFlow 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Apache Spark \u30b5\u30fc\u30d3\u30b9\u3068\u3057\u3066\u306e Apache Spark\uff08Apache Spark as Spark-as-a-Service\uff09\u3068\u306f\nApache Spark \u306f\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u306e\u9ad8\u901f\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u51e6\u7406\u3092\u5b9f\u73fe\u3059\u308b\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30af\u30e9\u30b9\u30bf\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3059\u3002Spark \u306f\u3001\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5927\u5b66\u30d0\u30fc\u30af\u30ec\u30fc\u6821\u306e AMPLab \u3067 2009 \u5e74\u306b\u7814\u7a76\u304c\u958b\u59cb\u3055\u308c\u3066\u4ee5\u6765\u3001\u76ee\u899a\u307e\u3057\u3044\u767a\u5c55\u3092\u9042\u3052\u3066\u304d\u307e\u3057\u305f\u3002Apache Spark \u306f\u73fe\u5728\u300150 \u3092\u8d85\u3048\u308b\u7d44\u7e54\u304b\u3089 200 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MLlib\u3001\u30b0\u30e9\u30d5\u51e6\u7406\u7528\u306e G{...}\u30de\u30c6\u30ea\u30a2\u30e9\u30a4\u30ba\u30c9\u30d3\u30e5\u30fc \u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e Delta \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3068\u30de\u30c6\u30ea\u30a2\u30e9\u30a4\u30ba\u30c9\u30d3\u30e5\u30fc\n\u6982\u8981\nDelta \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306f\u3001\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u3092\u7ba1\u7406\u3059\u308b API \u3068 UI \u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u304c\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c1\u30fc\u30e0\u306b\u3088\u308b ETL 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/why-attend","text":"Why Attend - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWhy AttendExplore everything Data + AI Summit has to offer \u2014 from the latest innovations and technologies to thought-provoking panel discussions to networking opportunities where you can connect with other data professionals in your industry.Register nowSession informationWith 10 amazing tracks and over 20 technologies to learn about, get the right experience for your level.\n\u00a0\nData Lakehouse ArchitectureThe decisions you make about your core data architecture will affect the reliability, performance and utility of your data analytics, data science and machine learning. Increasingly, many organizations are adopting the data lakehouse to improve their data platform. Has the ability to more easily combine structured, unstructured and real-time data workloads created new opportunities for data teams? Has ACID reliability on data lakes simplified how data is used? In this track, get answers to these questions and find out how to adopt a data lakehouse, migrate from data lakes and data warehouses, and integrate lakehouses with other data platforms.\nTechnologies\/topic ideas: lakehouse architecture, Delta Lake, Photon, platform security and privacy, serverless, cost management, data warehouse, data lake, Apache Iceberg, Data Mesh\nData GovernanceData governance, security and compliance are critical \u2014 they help guarantee that all data, BI and ML assets are maintained and managed securely across the enterprise and you\u2019re compliant with regulatory frameworks. In this track, learn best practices, frameworks, processes, roles, policies and standards for data governance of structured and unstructured data across clouds.\nTechnologies\/topic ideas: data governance, multicloud, Unity Catalog, security, compliance, privacy\nData SharingWhen enterprises can easily exchange data with their customers, partners, suppliers and internal lines of business, they can better collaborate, innovate and unlock value from that data. In this track, discover best practices for sharing data across data platforms and clouds, ways to avoid replication and lock-in, and how to distribute data products through marketplaces.\nTechnologies\/topic ideas: sharing and collaboration, Delta Sharing, data cleanliness, data cleanrooms, data marketplaces\nData Engineering If you want to optimize data processing and reduce costs, this session is for you. You\u2019ll learn how to use a combination of systems and processes to ingest, orchestrate and transform raw data for analytics and machine learning. Dive into best practices for data architectures, software engineering, ETL, data management, data quality, DataOps and orchestration.\nTechnologies\/topic ideas: data pipelines, orchestration, CDC, medallion architecture, Delta Live Tables, dbt, Databricks Workflows, ETL\/ELT, DataOps, Parquet, Apache Spark internals\nData Streaming Today\u2019s organization needs to respond in real time as events unfold. In this track, learn how data streaming can help you drive faster decision-making, make more accurate predictions and improve customer experiences. Explore best practices for implementing real-time data pipelines with your favorite tools and languages, find out how to reduce complexity for real-time data workflows and eliminate silos to support all your real-time use cases.\nTechnologies\/topic ideas: Apache Spark Structured Streaming, real-time ingestion, real-time ETL, real-time ML, real-time analytics, real-time applications, Delta Live Tables\nDSML: Production ML\/MLOpsOvercome the challenges of putting ML projects into production and operationalizing them at scale. In this track, you\u2019ll find out how to scale ML in production and apply MLOps best practices across the end-to-end machine learning lifecycle.\u00a0\nTechnologies\/topic areas: MLOps, Feature Stores, organizational ML, MLflow, Model Serving and more\nDSML: ML Use Cases\/TechnologiesMachine learning continues to disrupt industries and accelerate business outcomes across use cases and industries. In this track, discover how to apply ML to solve business challenges, explore technologies and best practices, and learn how to integrate data science with the rest of your organization.\u00a0\nTechnologies\/topic areas: PyTorch, TensorFlow, Keras, XGBoost, fast.ai, scikit-learn, Python and R ecosystems, deep learning, notebooks, LLMs and more\nData Warehouses, BI and Visualization Data analytics is a vital component of business decision-making. In this track, find out how to build analytics pipelines and integrations and learn about tooling and infrastructure for SQL analytics, BI and visualization. \u00a0\nTechnologies\/topic ideas: ANSI SQL, Redash, Databricks SQL, Tableau, Power BI, visualization techniques, Spark SQL and DataFrames, data integration, data warehouse and analytics\nResearchIn this track \u2014 dedicated to academic and advanced industrial research \u2014 explore large-scale data analytics and machine learning systems, the hardware that powers them (GPUs, I\/O storage devices, etc.) and how these systems are applied to use cases like genomics, astronomy, image scanning, disease detection, vaccine research and more.\nData StrategyChoosing a data lakehouse platform is only the first step in implementing your data strategy. Success requires a thoughtful approach to people and processes. In this track, you\u2019ll find out how to align goals, identify the right use cases, organize and enable teams, mitigate risk and operate at scale so you can be even more successful with data, analytics and AI.\nTechnologies\/topic ideas: data management, data governance, strategy, data teams, data mesh, data democratization\u00a0\nContent tailored to your roleData + AI Summit has something for everyone \u2014 explore, learn and connect with us and the data, analytics and AI community.\n\u00a0\n\u00a0\nData EngineerIncrease efficiency, control costs and reduce data risks \u2014 all in a day\u2019s work for today\u2019s data engineer. Broaden your knowledge and expand your skills by learning from industry experts and your peers how to deliver high-quality, reliable data for every use case from BI to AI.\nExplore sessionsData ScientistSuddenly, AI is everywhere and that\u2019s putting pressure on data scientists and ML engineers to quickly deliver results. Learn how lakehouse and tools like MLflow can accelerate productionization of models, increase productivity, reduce risk and increase ROI on new models.\nExplore sessionsData AnalystData analytics has moved beyond the warehouse. Join the global community of data analysts at Data + AI Summit and discover ways to support your stakeholders in making informed and timely decisions, achieve line of business KPIs and reduce rework risks.\nExplore sessionsIT Decision MakerData and AI are now mission critical for every business. Learn how the lakehouse architecture unifies data, analytics and AI on a single platform for better performance, lower TCO and faster innovation.\nExplore sessionsIndustry ExperiencesJoin and learn along with your industry peers in these specialized sessions focused on the unique challenges, use cases, and the data, analytics and AI requirements of your sector.\n\u00a0\nFinancial ServicesLearn how to minimize risk, deliver superior customer experience and accelerate innovation on lakehouse.\nDownload PDF\nGovernment and Public SectorLearn how lakehouse is helping to unlock the full potential of data to deliver mission objectives and better serve citizens.\nDownload PDF\nHealthcare and Life SciencesLearn ways to accelerate research and improve patient outcomes on lakehouse.\nDownload PDF\nManufacturingLearn how the lakehouse helps optimize supply chains, boost product innovation, increase operational efficiencies, predict fulfillment needs and reduce overall costs.\nDownload PDF\nCommunications, Media & EntertainmentLearn ways to accelerate audience and advertiser outcomes \u2014 360\u00b0 view of audience, lower churn, increased ARPU \u2014 with lakehouse.\nDownload PDF\nRetail and Consumer GoodsLearn how lakehouse is helping to harness the full power of data so retailers, suppliers and partners can collaborate across the value chain.\nDownload PDF\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/legal-subscription","text":"Databricks Legal Communication Subscription | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Legal Communication SubscriptionSign up here to receive notifications when Databricks updates either the Service Specific Terms or the Subprocessors\u00a0ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/keras-model","text":"What is the Keras Model?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWKeras ModelAll>Keras ModelTry Databricks for freeGet StartedWhat is a Keras Model?Keras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.\u00a0Keras has become one of the most used high-level neural networks APIs when it comes to developing and testing neural networks. Creating layers for neural networks as well as setting up complex architectures are now a breeze due to the Keras high-level API. A Keras model is made up of a sequence or a standalone graph. There are several fully configurable modules that can be combined to create new models. Some of these configurable modules that you can plug together are neural layers, cost functions, optimizers, initialization schemes, dropout, loss, \u00a0activation functions, and regularization schemes. One of the main advantages that come with modularity is that you can easily add new features as separate modules. As a result, Keras is very flexible and well-suited for innovative research. There are two ways you can develop a Keras model: sequential and functional. Sequential API ModeThe Sequential API model is the simplest model and it comprises a linear pile of layers that allows you to configure models layer-by-layer for most problems. The sequential model is very simple to use, however, it is limited in its topology. The limitation comes from the fact that you are not able to configure models with shared layers or have multiple inputs or outputs.Functional APIAlternatively, the Functional API is ideal for creating complex models, that require extended flexibility. It allows you to define models that feature layers connect to more than just the previous and next layers. Models are defined by creating instances of layers and connecting them directly to each other in pairs, Actually, with this model you can connect layers to any other layer. With this model creating complex networks such as siamese networks, residual networks, multi-input\/multi-output models, directed acyclic graphs (DAGs), and models with shared layers becomes possible. \u00a0Additional ResourcesKeras DocumentationHow to Use MLflow to Experiment a Keras Network Model: Binary Classification for Movie ReviewsHow to Use MLflow To Reproduce Results and Retrain Saved Keras ML ModelsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ankit-mathur\/#","text":"Ankit Mathur - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnkit MathurTech Lead, Model Serving GPUs at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brendan-barsness","text":"Brendan Barsness - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrendan BarsnessData and Analytics Architect at DeloitteBack to speakersBrendan Barsness is an advanced analytics consultant helping organizations apply data and AI solutions. He develops technical architectures and drives the deployment and adoption of cloud resources and services to meet the scalable demand for enterprise analytics and data management. Brendan is a Databricks Solutions Architect Champion at Deloitte and currently supports the State Department\u2019s Center for Analytics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/donghwa-kim","text":"Donghwa Kim - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDonghwa KimSr. Director of IT Architecture at Ontada, a McKesson CompanyBack to speakersDonghwa Kim is the Sr. Director of Architecture at Ontada, a McKesson company. He is responsible for delivering the next generation Data and Analytics platform using Databricks Lakehouse. Prior to joining Ontada, he worked as the enterprise architect for migrating a large scale on-prem data warehouse into Databricks at Veterans Affairs (VA) and at Centers for Medicare and Medicaid Services (CMS). He has over 20 years of IT experiences within healthcare and finance industries. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/meena-ram\/#","text":"Meena Ram - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMeena RamSr Director, Enterprise Data and Records Management Office at CIBCBack to speakersMeena Ram knows the Value of Data and has successfully bridged the gaps between business and technology stakeholders over the past 15 years. \nMeena Ram is the Head of Enterprise Data Management at Canadian Imperial Bank of Commerce (CIBC).\nOverseeing CIBC\u2019s Data practice across Canada and US Region. Before leading CIBC\u2019s Enterprise Data Management Office, Meena played a key role in setting the vision and strategy of Enterprise Data hubs to support analytics, working on complex data structures and delivering multi-million dollar migrations in Capital Markets. Prior to CIBC, Meena was a Data and Analytics Consultant for Deloitte where she working on various high profile institutions both in the US and Canada providing advisory and development solutions. Meena was a Business Intelligence and ETL developer for CGI\u2019s Wealth Management servicing 4 major clients. In the UK, Meena was managing multiple Data Warehouses for Citibank\u2019s credit card platforms. Meena holds a Bachelor in Software Engineering and a Masters in Artificial Intelligence from Manchester University. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners","text":"Partenaires | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires DatabricksDatabricks compte plus de 1200+ partenaires dans le monde qui fournissent des solutions et des services de donn\u00e9es, d'analytique et d'IA \u00e0 nos clients communs en utilisant la plateforme Lakehouse de Databricks. Ces partenaires vous permettent d'exploiter Databricks pour unifier toutes vos charges de travail de donn\u00e9es et d'IA afin d'obtenir des insights plus pertinents.\u00ab Databricks g\u00e8re la quantit\u00e9 de donn\u00e9es tandis que Tableau acc\u00e9l\u00e8re la visualisation. Ces solutions forment un tandem parfait au c\u0153ur de notre plateforme, offrant \u00e0 nos clients la performance dont ils ont besoin pour fournir des capacit\u00e9s de v\u00e9hicule autonome de pointe. \u00bb\u2014 Patrick McAuliffe, Lead Engineer, IncitePartenaires cloudDatabricks fonctionne sur AWS, Microsoft Azure, Google Cloud et Alibaba Cloud, avec une int\u00e9gration profonde aux services d'infrastructure, de donn\u00e9es et d'IA de chaque fournisseur.Partenaires technologiquesLes partenaires technologiques int\u00e8grent leurs solutions \u00e0 Databricks pour offrir des fonctionnalit\u00e9s compl\u00e9mentaires en mati\u00e8re d'ETL, d'ingestion de donn\u00e9es, de BI, de ML et de gouvernance.Partenaires consultingLes partenaires consultants sont des experts qui occupent une position unique pour vous aider \u00e0 \u00e9laborer, mettre en \u0153uvre et faire \u00e9voluer des initiatives en mati\u00e8re de donn\u00e9es, d'analytique et d'IA avec DatabricksDevenir partenaireNos partenaires travaillent avec Databricks pour mettre au point et fournir des solutions innovantes \u00e0 destination des entreprises. Rejoignez le programme de partenariat Databricks et acc\u00e9dez \u00e0 des outils, des formations, des acc\u00e9l\u00e9rateurs de solutions et des programmes de mise sur le march\u00e9.En savoir plusProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/company\/board-of-directors","text":"Databricks Board of Directors | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLeadershipWith a long-term vision, our leadership team leverages decades of experience to chart a new course for data and AIMeet our teamExecutive teamFoundersBoard of directorsIon StoicaCo\u2013founder and Executive ChairBen HorowitzCo\u2013founder of Andreessen HorowitzElena DonioBoard MemberAli GhodsiCo\u2013founder and Chief Executive OfficerPete SonsiniGeneral Partner at New Enterprise AssociatesJonathan ChadwickBoard MemberMatei ZahariaCo\u2013founder and Chief TechnologistScott ShenkerProfessor of Computer Science at UC BerkeleyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=munich%2C%20germany","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Experimente o Databricks | DatabricksExperimente o Databricks gratuitamente Experimente a plataforma Databricks completa gratuitamente por 14 dias em sua nuvem AWS, Microsoft Azure ou Google Cloud.Simplique a ingest\u00e3o de dados e automatize processos de ETLImporte dados de centenas de fontes. Utilize uma abordagem asseverativa e simples para construir pipelines de dados.Colabore em sua linguagem preferidaCode em Python, R, Scala e SQL com colabora\u00e7\u00e3o, versionamento autom\u00e1tico, integra\u00e7\u00f5es com Git e controles de acesso (RBAC) Pre\u00e7o\/Performance at\u00e9 12x superior a data warehouses em nuvemDescubra porque mais de 7000 clientes de todo mundo confiam na Databricks para todos os seus workloads de Dados, de BI a AI.Crie sua conta Databricks1\/2Primeiro NomeSegundo NomeEmailEmpresaT\u00edtuloTelefone (Opcional)SelecionarPa\u00edsContinuarAviso de privacidade (atualizado)Termos de UsoSuas op\u00e7\u00f5es de privacidadeSeus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/geoffrey-freeman\/#","text":"Geoffrey Freeman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeoffrey FreemanSolutions Architect at T-MobileBack to speakersGeoffrey Freeman has spent most of his career working in massive scale online data delivery services. He is currently a solution architect for T-Mobile's procurement division.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jitendra-malik","text":"Jitendra Malik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI Research at University of California at BerkeleyBack to speakersJitendra Malik was born in Mathura, India in 1960. He received the B.Tech degree in Electrical Engineering from Indian Institute of Technology, Kanpur in 1980 and the PhD degree in Computer Science from Stanford University in 1985. In January 1986, he joined the university of California at Berkeley, where he is currently the Arthur J. Chick Professor in the Department of Electrical Engineering and Computer Sciences. He is also on the faculty of the department of Bioengineering, and the Cognitive Science and Vision Science groups. During 2002-2004 he served as the Chair of the Computer Science Division, and as the Department Chair of EECS during 2004-2006 as well as 2016-2017. In 2018 and 2019, he served as Research Director and Site Lead of Facebook AI Research in Menlo Park.\nProf. Malik's research group has worked on many different topics in computer vision, computational modeling of human vision, computer graphics and the analysis of biological images. Several well-known concepts and algorithms arose in this research, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. He has mentored more than 70 PhD students and postdoctoral fellows.\nHe received the gold medal for the best graduating student in Electrical Engineering from IIT Kanpur in 1980 and a Presidential Young Investigator Award in 1989. At UC Berkeley, he was selected for the Diane S. McEntyre Award for Excellence in Teaching in 2000 and a Miller Research Professorship in 2001. He received the Distinguished Alumnus Award from IIT Kanpur in 2008. His publications have received numerous best paper awards, including five test of time awards - the Longuet-Higgins Prize for papers published at CVPR (twice) and the Helmholtz Prize for papers published at ICCV (three times). He received the 2013 IEEE PAMI-TC Distinguished Researcher in Computer Vision Award, the 2014 K.S. Fu Prize from the International Association of Pattern Recognition, the 2016 ACM-AAAI Allen Newell Award, the 2018 IJCAI Award for Research Excellence in AI, and the 2019 IEEE Computer Society Computer Pioneer Award. He is a fellow of the IEEE and the ACM. He is a member of the National Academy of Engineering and the National Academy of Sciences, and a fellow of the American Academy of Arts and Sciences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Databricks Customer Stories | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks CustomersDiscover how innovative companies across every industry are leveraging the Databricks Lakehouse Platform for successSee all customersExplore the Burberry storyFeatured Stories\n\n\nCustomer Story\n\nAT&T democratizes data to prevent fraud, reduce churn and increase CLV\nDatabricks Lakehouse has helped AT&T accelerate AI across operations, including decreasing fraud by 70%\u201380%\n\nRead more\n\n\nCustomer Story\n\nShell innovates with energy solutions for a cleaner world\nDatabricks Lakehouse helps to democratize data and modernize operations globally\n\nRead more\n\n\nCustomer Story\n\nABN AMRO transforms banking on a global scale\nABN AMRO puts data and Al into action with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nRolls-Royce delivers a greener future for air travel\nRolls-Royce decreases carbon through real-time data collection with Databricks Lakehouse\n\nWatch video\n\n\nCustomer Story\n\nDelivering integrity and efficiency for the U.S. Postal Service\nUSPS OIG supports efficient postal service to millions with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nWalgreens personalizes pharmacy care to improve patient outcomes\nDatabricks Lakehouse helps Walgreens personalize patient experiences for over 825 million prescriptions filled annually\n\nRead moreExplore all customersThe Data Team EffectData teams are the united force that are solving the world\u2019s toughest problems.Be the next success storyContact usResourcesCustomer StoryLearn how Databricks enables Cond\u00e9 Nast to deliver personalized content to its customers.Learn moreWebinarLearn how Apple and Disney+ unified analytics and AI for successWatch nowPodcastHear about the role of data and AI in healthcare equity from the CDAO at HumanaWatch nowReady to get started?Try for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/accenture-cloud-data-migration","text":"Cloud Data Migration by Accenture | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionCloud Data Migration by AccentureMigration solution developed by Accenture and powered by the Databricks Lakehouse PlatformGet startedLess guesswork, more valueAccenture\u2019s Cloud Data Migration\u00a0helps you navigate any complexity, from building landing zones in the Cloud Continuum to regulating data sovereignty. Accenture works with you to determine the right cloud strategy, operating model, roadmap and additional ecosystem partners. They then help you accelerate migration and modernization to the cloud so that it is secure, cost-effective and agile. Accenture\u2019s comprehensive cloud migration framework brings industrialized capabilities together with exclusive preconfigured, industry-specific tools, methods and automation across all cloud models and proven delivery methods. With Accenture\u2019s Cloud Data Migration Service, you will benefit from:Increased innovation, agility and flexibilityEasing of rising resource demands and better consumption managementReduction in cost, immediate business results and cloud scalabilityGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/p\/whitepaper\/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025","text":"Visione dei CIO al 2025: Colmare il divario fra BI e AI - DatabricksReportVisione dei CIO al 2025Colmare il divario fra BI e AIIndagine globale fra i CIO sull'adozione dell'AI orientata al valore aziendaleScopri come le principali imprese e organizzazioni stanno risolvendo le sfide pi\u00f9 complesse di gestione dei dati per sfruttare al meglio l'AI. Il nuovo studio di MIT Technology Review raccoglie le opinioni di 600 CIO in 18 Paesi e 14 settori industriali.Come operano i CIO per dare priorit\u00e0 all'adozione dell'AI? Come investono nel miglioramento della loro strategia di gestione dei dati?Trova le risposte a queste domande nelle interviste approfondite con alti dirigenti (C-level) di Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global, Marks & Spencer e altre aziende.I CIO hanno evidenziato alcuni trend principali:secondo il 72%, i dati sono la sfida pi\u00f9 grande per l'AI, mentre il 68% ritiene cruciale unificare la piattaforma di gestione dei dati per analisi e AIil 94% dichiara di utilizzare gi\u00e0 l'AI in alcune linee di business e oltre la met\u00e0 prevede che l'AI si diffonda su larga scala entro il 2025il 72% ritiene che il multicloud sia fondamentale e molti sostengono l'utilizzo di standard aperti per mantenere una flessibilit\u00e0 strategicaRichiedi il reportProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/manbir-paul\/#","text":"Manbir Paul - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingManbir PaulVP of Engineering, Data Insights and MarTech at SephoraBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/ebook\/data-analytics-and-ai-governance","text":"Data, Analytics and AI Governance | DatabrickseBookData, Analytics and AI GovernanceHow to build an effective governance strategy for your data lakehouseData, analytics and AI governance is perhaps the most important yet challenging aspect of any data and AI democratization effort. For your data analytics and AI needs, you\u2019ve probably deployed two different systems \u2014 data warehouses for business intelligence and data lakes for AI. And now you\u2019ve created data silos with data movement across two systems, each with a different governance model.But data isn\u2019t limited to files or tables. You also have assets like dashboards, ML models, and notebooks, each with their own permission models, making it difficult to manage access permissions for all these assets consistently.The problem gets bigger when your data assets exist across multiple clouds with different access management solutions. What you need is a unified approach to simplify governance for all your data on any cloud.Read this eBook to find out:Why your organization needs a modern approach to data governance that covers the full breadth of data use cases \u2014 from BI to MLWhat the key components are for a successful data governance frameworkData governance best practices for a data lakehouseHow you can unify governance for your data, analytics and AI use cases with the Databricks Lakehouse PlatformGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/faraz-yasrobi","text":"Faraz Yasrobi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFaraz YasrobiSoftware Engineer at GrammarlyBack to speakersFaraz Yasrobi s a software engineer with over 7 years of experience in the data domain. Specializing in data infrastructure, engineering, storage, governance, and security. Faraz is currently a tech lead in Grammarly\u2019s data platform team and has been leading the data democratization project over the past two years.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/weston-hutchins\/#","text":"Weston Hutchins - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWeston HutchinsProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2019\/12\/18\/make-your-data-lake-ccpa-compliant.html","text":"CCPA Compliance and Data Lakes: Guide to Protecting Data PrivacySkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorMake Your Data Lake CCPA Compliant with a Unified Approach to Data and Analyticsby Raela Wang, Justin Olsson, Jeffrey Hirschey and Michael OrtegaDecember 18, 2019 in ProductShare this postWith more digital data being captured every day, there has been a rise of various regulatory standards such as the General Data Protection Regulation (GDPR) and recently the California Consumer Privacy Act (CCPA). These privacy laws and standards are aimed at protecting consumers from businesses that improperly collect, use, or share their personal information, and is changing the way businesses have to manage and protect the consumer data they collect and store.Similar to the GDPR, the CCPA empowers individuals to request:what personal information is being captured,how personal information is being used, andto have that personal information deleted.Additionally, the CCPA encompasses information about \u2018households\u2019. This has potential to significantly expand the scope of personal information subject to these requests. Failure to comply in a timely manner can result in statutory fines and statutory damages (where a consumer need not even prove damages) that can rise quickly. The challenge for companies doing business in California or otherwise subject to the CCPA, then, is to ensure they can quickly find, secure, and delete that personal information.Many companies wrongfully think that the data privacy processes and controls put in place for GDPR compliance will guarantee complete compliance with the CCPA\u2013and while the things you may have done to prepare for the GDPR are helpful and a great start\u2013they are unlikely to be sufficient. Companies need to focus on understanding their need for compliance and must determine which processes and controls can effectively prevent the misuse and unauthorized sale of consumer data.Are you prepared for CCPA?CCPA requires businesses to potentially delete all personal information about a consumer upon request. Many organizations today are using or plan to use a data lake for storing the vast majority of their data in order to have a comprehensive view of their customers and business and power downstream data science, machine learning, and business analytics. The lack of structure of a data lake makes it challenging to locate and remove individual records to remain compliant with these regulatory requirements.This is critical when responding to a consumer\u2019s deletion request, and if a business receives more than just a few consumer rights requests in a short period of time, the resources spent to comply with the requests could be significant. Businesses that fail to comply with CCPA requirements by January 1, 2020 could be subject to lawsuits and civil penalties. The CCPA also contains a \u201clookback\u201d period applying it to actions and personal information since January 1, 2019, making it vital to get these solutions in place quickly.Taking your data security beyond the data lakeWhen it comes to adhering to CCPA requirements, your data lake should enable you to respond to consumer rights requests within prescribed timelines without handicapping your business. Unfortunately, most data lakes lack the data management and data manipulation capabilities to quickly locate and remove records, which makes this challenging.Fortunately, Databricks offers a solution. The Databricks Unified Data Analytics Platform simplifies data access and engineering, while fostering a collaborative environment that supports analytics and machine learning. As part of the platform, Databricks offers a Unified Data Service that ensures reliability and scalability for your data pipelines, data lakes, and data analytics workflows.One of the main components of the Databricks Unified Data Service is Delta Lake, an open-source storage layer that brings enhanced data reliability, performance, and lifecycle management to your data lake. With improved data management, organizations can start to think \u201cbeyond the data lake\u201d and leverage more advanced analytics techniques and technologies to extend their data for downstream business needs including data privacy protection and CCPA compliance.Start building a CCPA-friendly data lake with Delta LakeDelta Lake provides your data lake with a structured data management system including transactional capabilities. This enables you to easily and quickly search, modify, and clean your data using standard DML statements (e.g. DELETE, UPDATE, MERGE INTO).To get started, ingest your raw data with the Spark APIs that you\u2019re familiar with and write them out as Delta Lake tables. Doing this also adds metadata to your files. If your data is already in Parquet format, you also have the option to convert the parquet files in place to a Delta Lake table without rewriting any of the data. Delta uses an open file format (parquet) so there are no worries of being locked in as you can quickly and easily convert your data back into another format if you need to.Once ingested, you can easily search and modify individual records within your Delta Lake tables. The final step is to make Delta Lake your single source of truth by erasing any underlying raw data. This removes any lingering records from your raw data sets. We suggest setting up a retention policy with AWS or Azure of thirty days or less to automatically remove raw data so that no further action is needed to delete the raw consumer data to meet CCPA response timelines.How do I delete data in my data lake using Delta Lake?You can find and delete any personal information related to a consumer by running two commands:DELETE FROM data WHERE email = '[email\u00a0protected]';VACUUM data;The first command identifies records that contain the string \u201c[email\u00a0protected]\u201d stored in the column email, and deletes the data containing these records by rewriting the respective underlying files with the consumer\u2019s unique personal data removed and marking the old files as deleted.The second command cleans up the Delta table, removing any stale records that have been logically deleted and are outside of the default retention period. With the default retention period of 7 days, this means that files marked for deletion will linger around until you run the VACUUM command at least 7 days later. You could easily set up a scheduled job with the Databricks Job Scheduler to run the VACUUM command for you in an automated fashion. You might also be familiar with Delta Lake\u2019s time travel capabilities, which allows you to keep historical versions of your Delta Lake table in case you need to query an earlier version of the table. Note that when you run VACUUM, you will lose the ability to time travel back to a version older than the default 7-day data retention period.After running these commands, you can now safely state that you have removed the necessary consumer data and records from your data lake.How else does Databricks help me with CCPA consumer rights requests?Once a user's personal information has been removed from the data lake, it is also important to remove this personal information from the tools used by your data teams. Often times these tools reside locally on the data scientist\u2019s or engineer\u2019s laptop. A better more secure solution is to use Databricks with its hosted Data Science Workspace where data teams can prep, explore and model data collaboratively in a shared notebook environment. This improves team productivity while creating a secured, centralized environment for the entire analytics workflow.To help you meet CCPA compliance requirements, Databricks provides you with privacy protection tools to permanently remove personal information, either on a per-command or per-notebook level.After you delete a notebook, it is moved to trash. If you don\u2019t take further action, it will be permanently deleted within 30 days - allowing you to be confident it has been deleted within the prescribed timelines for both CCPA and GDPR.If for any reason you need to do this more quickly, we also offer the ability to permanently delete individual items in the trash:deleting all items in a particular user\u2019s trash:or purging all deleted items in a workspace on command, which includes deleted notebook cells, notebook comments or MLFlow experiments:You also have the option to purge Databricks notebook revision history, which is useful to ensure that old query results are permanently deleted:Getting Started with CCPA Compliance for Data and AnalyticsWith the Databricks Unified Data Analytics Platform and Delta Lake, you can bring enhanced data security, reliability, performance, and lifecycle management to your data lake while delivering on all your analytics needs. Organizations can now quickly find and remove individual records from a data lake to meet CCPA access requests and compliance requirements without hindering their business.Learn more about Delta Lake and the Databricks Unified Data Analytics Platform. Sign-up for your free Databricks trial \u00a0now.Try Databricks for freeGet StartedSee all Product postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/accelerators","text":"Aceleradores de solu\u00e7\u00f5es da Databricks \u2013 Entregando valor de dados e IA com mais rapidez \u2013 DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWSolu\u00e7\u00f5es para cada setorForne\u00e7a os dados e os resultados de IA que mais importam com mais rapidezComece sua avalia\u00e7\u00e3o gratuitaAceleradores de solu\u00e7\u00f5es da DatabricksEconomize horas de processo de descoberta, design, desenvolvimento e testes com os aceleradores de solu\u00e7\u00f5es da Databricks. Nossos guias dedicados \u2014 notebooks totalmente funcionais e pr\u00e1ticas recomendadas \u2014 aceleram os resultados para seus casos de uso mais comuns e impactantes. V\u00e1 da ideia \u00e0 prova de conceito (PoC) em apenas duas semanas.\n\u00a0\nComece a usar os aceleradores de solu\u00e7\u00f5es com sua avalia\u00e7\u00e3o gratuita da Databricks ou conta existente.\n\u00a0\nComece sua avalia\u00e7\u00e3o gratuita hoje mesmoExplorar aceleradoressearchHide filtersIndustrySortDatabricksRemo\u00e7\u00e3o automatizada de PHIfeaturednewDatabricksPrevis\u00f5es de demanda refinadasfeatured\ud83d\udd25DatabricksDisponibilidade nas prateleirasfeaturedDatabricksDetec\u00e7\u00e3o de toxicidade em jogosfeaturedDatabricksAjuste de riscos do MedicareSplunkAn\u00e1lise cibern\u00e9tica (Conector Splunk)DatabricksAn\u00e1lise de desempenho ESG\ud83d\udd25DatabricksAn\u00e1lise de imagem de patologia digitalDatabricksAn\u00e1lise de sobreviv\u00eancia e valor do tempo de vidaDatabricksAn\u00e1lises de ponto de venda em tempo realnewDatabricksAn\u00e1lises geoespaciais para identificar fraudesDatabricksAtribui\u00e7\u00e3o multi-touchDatabricksClassifica\u00e7\u00e3o de comerciantesDatabricksClassifica\u00e7\u00e3o de propens\u00e3onewDatabricksCombate \u00e0 lavagem de dinheiroDatabricksConstru\u00e7\u00e3o de coortes usando gr\u00e1ficos de conhecimentoDatabricksCorrespond\u00eancia aproximada de itensDatabricksDetec\u00e7\u00e3o de amea\u00e7as com DNSDatabricksDetec\u00e7\u00e3o de efeitos colaterais de medicamentosnewDatabricksDeterminantes sociais da sa\u00fadeDatabricksEfic\u00e1cia geral do equipamentoDatabricksEstoque de seguran\u00e7aDatabricksEstudos de associa\u00e7\u00e3o em todo o genomaDatabricksEvid\u00eancias do mundo realDatabricksFundamentos da vis\u00e3o computacionalDatabricksG\u00eameos digitaisDatabricksGera\u00e7\u00e3o de rotas escal\u00e1veisDatabricksGerenciamento de reten\u00e7\u00e3oDatabricksGerenciamento de riscosDatabricksInteroperabilidade de FHIR com dbigniteDatabricksInteroperabilidade de HL7v2 com SmolderDatabricksManuten\u00e7\u00e3o preditiva (IoT)DatabricksMecanismo de recomenda\u00e7\u00e3oDatabricksModerniza\u00e7\u00e3o de plataformas de investimentoDatabricksOtimiza\u00e7\u00e3o da separa\u00e7\u00e3o de pedidosDatabricksOtimiza\u00e7\u00e3o de licita\u00e7\u00f5es em tempo realDatabricksOtimiza\u00e7\u00e3o de P&D com gr\u00e1ficos de conhecimentonewDatabricksPreven\u00e7\u00e3o de fraudes financeiras em tempo realDatabricksPrevis\u00e3o de perda de assinantesDatabricksPrevis\u00e3o de vendas e atribui\u00e7\u00e3o de an\u00fancios\ud83d\udd25DatabricksQualidade de experi\u00eancia em v\u00eddeoDatabricksRelat\u00f3rios regulat\u00f3riosDatabricksResolu\u00e7\u00e3o da entidade do clienteDatabricksRisco de reputa\u00e7\u00e3oDatabricksSegmenta\u00e7\u00e3o de clientesDatabricksS\u00edntese de dados reais para oncologiaDatabricksTranspar\u00eancia de pre\u00e7osnewDatabricksValor vital\u00edcio do cliente\ud83d\udd25Perguntas frequentesQuanto custam os aceleradores de solu\u00e7\u00e3o?Os aceleradores de solu\u00e7\u00e3o est\u00e3o dispon\u00edveis gratuitamente para todos os clientes Databricks.Preciso ser um cliente Databricks para usar um acelerador de solu\u0000\u00e7\u00f5es?Voc\u00ea pode implementar os aceleradores de solu\u00e7\u00f5es com uma avalia\u00e7\u00e3o gratuita da Databricks ou com sua conta existente.O que esperar de um acelerador de solu\u00e7\u00f5es?Os aceleradores de solu\u00e7\u00f5es foram criados para ajudar voc\u00ea a economizar tempo nos processos de descoberta, design, desenvolvimento e testes. Nosso objetivo: acelerar o in\u00edcio de seus casos de uso de dados e IA fornecendo os recursos apropriados (notebooks, modelos comprovados e pr\u00e1ticas recomendadas). Voc\u00ea pode ir da ideia \u00e0 prova de conceito (PoC) em apenas duas semanas.Veja como nossos clientes usam a DatabricksExplore hist\u00f3rias de clientesProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matteo-quattrocchi\/#","text":"Matteo Quattrocchi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatteo QuattrocchiDirector, Policy-EMEA at BSABack to speakersMatteo is Director, Policy \u2014 EMEA at BSA | The Software Alliance in Brussels. In this role, he works with BSA members to develop and advance policy positions on a range of key issues, with a focus on artificial intelligence, copyright and government access to data. Prior to joining BSA, Matteo worked at the U.S. Mission to the EU in the Public Affairs Office, and in lobbying and law firms. Matteo holds an LL.M. from Georgetown University, and a Master\u2019s in European Law at LUISS (Italy).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/manufacturing-industry-solutions","text":"Solu\u00e7\u00f5es para o setor de manufatura \u2013 DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDescubra o Lakehouse para manufaturaReduza custos, aumente a produtividade e unifique seu ecossistema de dados na \u00fanica plataforma de dados criada para a maneira como os fabricantes usam os dadosInscrever-seEntre em contatoMenor TCO. Melhor desempenho. Maior escalabilidade.Lakehouse para manufaturaQuando voc\u00ea pode unificar todos os seus dados, fun\u00e7\u00f5es anal\u00edticas e cargas de trabalho de IA \u2014 com compartilhamento e governan\u00e7a integrados \u2014 equipes internas e externas t\u00eam acesso aos dados de que precisam, quando precisam.Impacto em toda a cadeia de valorEngajamento do clienteResultados precisos e experi\u00eancias sem atritos para os clientesCom uma vis\u00e3o de 360 graus dos clientes, opera\u00e7\u00f5es e ativos, voc\u00ea pode oferecer o mais alto tempo de atividade, qualidade de servi\u00e7o e valor econ\u00f4mico em todo o ciclo de vida do produto, potencializando resultados personalizados para os clientes, presta\u00e7\u00e3o proativa de servi\u00e7os de campo e solu\u00e7\u00f5es diferenciadas de miss\u00e3o cr\u00edtica.Efici\u00eancia operacionalProdutividade dos funcion\u00e1riosInova\u00e7\u00e3o de produtosSolu\u00e7\u00f5es e parceiros de produ\u00e7\u00e3oSolu\u00e7\u00f5es de an\u00e1lises de dados e IA sem compromisso criadas especificamente para fabricantesOs aceleradores de solu\u00e7\u00f5es da Databricks s\u00e3o guias criados especificamente para acelerar os resultados de fabrica\u00e7\u00e3o usando notebooks totalmente funcionais e pr\u00e1ticas recomendadas. Economize tempo de descoberta, design, desenvolvimento e testes em casos de uso, como g\u00eameos digitais, efic\u00e1cia geral do equipamento, previs\u00e3o e muito mais.Efic\u00e1cia geral do equipamento e monitoramento de KPIObtenha monitoramento de equipamentos de ponta a ponta com alto desempenho e escalabilidade\nIngira e processe dados incrementalmente de sensores\/dispositivos IoT em diversos formatos e calcule KPIs e m\u00e9tricas de superf\u00edcie para gerar insights valiosos.Comece agoraPrevis\u00e3o em n\u00edvel parcialPreveja a demanda no n\u00edvel da pe\u00e7a para uma fabrica\u00e7\u00e3o simplificada\nRealize a previs\u00e3o de demanda no n\u00edvel da pe\u00e7a, em vez do n\u00edvel agregado, para minimizar as interrup\u00e7\u00f5es em sua cadeia de suprimentos e aumentar as vendas.Comece agoraG\u00eameos digitaisAumente a efici\u00eancia operacional e melhore a tomada de decis\u00f5es\nProcesse dados do mundo real em tempo real, calcule insights em grande escala e entregue m\u00faltiplas aplica\u00e7\u00f5es downstream, al\u00e9m de otimizar as opera\u00e7\u00f5es da f\u00e1brica com decis\u00f5es baseadas em dados.Comece agoraExplore os aceleradores de manufaturaTemos parceria com as principais empresas de consultoria para oferecer solu\u00e7\u00f5es inovadoras e dedicadas a cada setor de neg\u00f3cios. As solu\u00e7\u00f5es Databricks Brickbuilder ajudam a reduzir custos e maximizar o valor dos seus dados. Elas s\u00e3o apoiadas por d\u00e9cadas de experi\u00eancia no setor e projetadas para a Plataforma Databricks Lakehouse para atender \u00e0s suas necessidades.Manufatura inteligente Use seus dados, estimule a interoperabilidade e forne\u00e7a insights aprimorados em escala usando fun\u00e7\u00f5es anal\u00edticas e IA.Saiba maisInspetor de qualidadeAutomatize seu controle de qualidade com vis\u00e3o do computador para detectar defeitos, objetos estranhos, anomalias ou configura\u00e7\u00e3o incorreta.Saiba maisGest\u00e3o preditiva de risco de fornecimentoImpulsione a visibilidade granular dos fluxos de pedidos e desempenho dos fornecedores para aumentar a efici\u00eancia, gerenciar exce\u00e7\u00f5es e melhorar a resili\u00eancia.Saiba maisVer todas as solu\u00e7\u00f5es de parceiros\"O Databricks Lakehouse nos permite reduzir a barreira de entrada para o acesso aos dados em toda a nossa organiza\u00e7\u00e3o. Com isso, podemos construir os ve\u00edculos el\u00e9tricos mais inovadores e confi\u00e1veis do mundo.\"\n\u2013 Wassym Bensaid, vice-presidente de desenvolvimento de software da Rivian\n\u201cAo longo dos anos, o uso da Databricks aumentou consideravelmente. No in\u00edcio, a Databricks era nossa plataforma de big data e IA, mas o escopo foi ampliado. Uma classe totalmente nova de engenheiros e data scientists cidad\u00e3os est\u00e1 usando hoje como uma ferramenta moderna de business intelligence para tomar decis\u00f5es de neg\u00f3cios com mais informa\u00e7\u00f5es.\u201d\n\u2014 Daniel Jeavons, Diretor Geral, Centro de Excel\u00eancia para An\u00e1lises Avan\u00e7adas, Shell\n\"A plataforma Databricks nos ajudou a minimizar os riscos \u00e0 disponibilidade de motores, reduzir os prazos de entrega de pe\u00e7as de reposi\u00e7\u00e3o e gerar mais efici\u00eancia no giro de estoque. Tudo isso nos permite fornecer o TotalCare, o principal programa de manuten\u00e7\u00e3o Power-by-the-Hour (PBH) do setor de avia\u00e7\u00e3o.\"\n\u2014 Stuart Hughes, diretor de informa\u00e7\u00e3o e digital da Rolls-Royce Civil Aerospace\nRecursose-booksColoque seus dados de ERP para trabalharWebinarsMelhorar a manuten\u00e7\u00e3o preditiva para fabricantes com dados e IAe-booksQuatro for\u00e7as impulsionando a produ\u00e7\u00e3o inteligenteTudo pronto para come\u00e7ar?Adorar\u00edamos saber seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteEntre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rahul-pandey\/#","text":"Rahul Pandey - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRahul PandeySolution Architect at adidasBack to speakersRahul is working on Data Engineering and Data Science projects as a Solution Architect at Adidas. His goal is to build cost-effective and efficient architecture designs. He is motivated to raise awareness about sustainability in AI within Data Science teams.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/julien-le-dem\/#","text":"Julien Le Dem - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJulien Le DemChief Architect at AstronomerBack to speakersJulien Le Dem is the Chief Architect of Astronomer and Co-Founder of Datakin. He co-created Apache Parquet and is involved in several open source projects including OpenLineage, Marquez (LFAI&Data), Apache Arrow, Apache Iceberg and a few others. Previously, he held senior roles at Wework, Dremio, Twitter where he also obtained a two-character Twitter handle (@J_) and Yahoo, where he received his Hadoop initiation. His French accent makes his talks particularly attractive.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erni-durdevic","text":"Erni Durdevic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErni DurdevicSpecialist Solutions Architect (Geospatial) at DatabricksBack to speakersErni is a Big Data specialist helping Databricks customers to develop breakthrough applications at scale.\nHe is specialised in Data Engineering, focusing on geospatial and time series data workloads. He is the co-creator of DiscoverX, an active contributor to the open-source geospatial library Mosaic, and an enthusiastic member of the Geospatial SME group at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sarah-pollitt","text":"Sarah Pollitt - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSarah PollittGroup Product Manager at MatillionBack to speakersSarah has over 10 years experience in data management and software delivery in a wide variety of major industries. \nSarah is passionate about supporting people make their lives easier with data, supporting women in tech and ensuring equity in the Product and Technology spaceLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/xuefu-wang\/#","text":"Xuefu Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingXuefu WangSr. Data Scientist at The Trade DeskBack to speakersXuefu Wang is a Sr. Data Scientist at The Trade Desk, the world's largest demand-side platform for accessing premium advertisement inventories across multiple channels. He has a PhD in statistics and previously worked in data science at JP Morgan ChaseLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/product\/aws?itm_data=menu-item-awsProduct","text":"AWS \uae30\ubc18 Databricks \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 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\uace0\uac1d \uacbd\ud5d8 \uac1c\uc778\ud654\neBook \ub2e4\uc6b4\ub85c\ub4dcHotels.com: \uba38\uc2e0 \ub7ec\ub2dd\uc73c\ub85c \uace0\uac1d \uacbd\ud5d8 \ucd5c\uc801\ud654\n\uc0ac\ub840 \uc5f0\uad6c \ub2e4\uc6b4\ub85c\ub4dcHP: \ub370\uc774\ud130 \uc900\ube44\uc5d0\uc11c \ub525 \ub7ec\ub2dd\uae4c\uc9c0 \u2014 HP\uc5d0\uc11c Databricks\ub97c \ud65c\uc6a9\ud558\uc5ec \ubd84\uc11d\uc744 \ud1b5\ud569\ud55c \ubc29\ubc95\n\uc628\ub514\ub9e8\ub4dc \uc6e8\ube44\ub098 \uc2dc\uccad\ucd94\ucc9c \ud1b5\ud569AWS GravitonAWS GravitonDatabricks \ud074\ub7ec\uc2a4\ud130\ub294\u00a0AWS Graviton\u00a0\uc778\uc2a4\ud134\uc2a4\ub97c \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \uc774\ub4e4 \uc778\uc2a4\ud134\uc2a4\ub294 AWS\uc5d0\uc11c Arm64 \uba85\ub839 \uc138\ud2b8 \uc544\ud0a4\ud14d\ucc98\ub97c \uae30\ubc18\uc73c\ub85c \uc124\uacc4\ud55c Graviton \ud504\ub85c\uc138\uc11c\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. AWS\uc5d0\uc11c\ub294 \uc774\ub4e4 \ud504\ub85c\uc138\uc11c\ub97c \uc0ac\uc6a9\ud558\ub294 \uc778\uc2a4\ud134\uc2a4 \uc720\ud615\uc740 Amazon EC2\uc758 \uc5b4\ub5a4 \uc778\uc2a4\ud134\uc2a4 \uc720\ud615\ubcf4\ub2e4\ub3c4 \uac00\uc7a5 \uc6b0\uc218\ud55c \uac00\uc131\ube44\ub97c \uc790\ub791\ud55c\ub2e4\uace0 \ub9d0\ud569\ub2c8\ub2e4.\u00a0\uc790\uc138\ud788 \uc77d\uae30AWS SecurityAmazon RedshiftAWS Glue\uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub864\uc544\uc6c3\uc0ac\uc6a9 \uc0ac\ub840\uac1c\ubcc4 \ub9de\ucda4\ud615 \ucd94\ucc9c \uc5d4\uc9c4\n\uc2e4\uc2dc\uac04\uc73c\ub85c \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uace0 \uac00\uc7a5 \uad00\ub828\uc774 \uae4a\uc740 \uc81c\ud488\uacfc \uc11c\ube44\uc2a4 \ucd94\ucc9c\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc720\uc804\uccb4 \uc11c\uc5f4 \ubd84\uc11d\n\uae30\uc220 \uc2a4\ud0dd\uc744 \ud604\ub300\ud654\ud558\uc5ec \uac00\uc7a5 \ube60\ub978 \ub300\uaddc\ubaa8 DNASeq \ud30c\uc774\ud504\ub77c\uc778\uc73c\ub85c \ud658\uc790 \ubc0f \uc758\uc0ac\ub97c \uc704\ud55c \ud658\uacbd\uc744 \uac1c\uc120\ud569\ub2c8\ub2e4.\uc0ac\uae30 \ud0d0\uc9c0 \ubc0f \uc608\ubc29\n\uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \uc2a4\ud2b8\ub9bc\uacfc \ub354\ubd88\uc5b4 \uc644\uc804\ud55c \uacfc\uac70 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\uc5ec \uc775\uba85 \ubc0f \uc758\uc2ec\uc2a4\ub7ec\uc6b4 \uae08\uc735 \uac70\ub798\ub97c \ube60\ub974\uac8c \ucc3e\uc544\ub0c5\ub2c8\ub2e4.\ub9ac\uc18c\uc2a4\ubc31\uc11c\ub370\uc774\ud130 \ub808\uc774\ud06c \ub9c8\uc774\ub2dd\uc744 \ud1b5\ud55c \ubd84\uc11d \uc778\uc0ac\uc774\ud2b8\uae08\uc735 \uc11c\ube44\uc2a4 \uc0b0\uc5c5\uc5d0\uc11c \ube45\ub370\uc774\ud130\uc640 AI \ud1b5\ud569\ud558\ub461 \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc758 \uc228\uaca8\uc9c4 \uac00\uce58\uc6e8\ube44\ub098Databricks \ubc0f AWS\ub85c \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \ubc0f \ubd84\uc11d \ud50c\ub7ab\ud3fc \ud604\ub300\ud654\ub370\uc774\ud130 \uc911\uc2ec\uc801 \uc2a4\ud0c0\ud2b8\uc5c5\uc774 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \uad6c\ucd95\ud558\ub294 \uc774\uc720Quby\uc5d0\uc11c \uc2e4\uc2dc\uac04 \ubd84\uc11d \uae30\ub2a5\uc73c\ub85c \ube60\ub978 \uc758\uc0ac \uacb0\uc815 \uc9c0\uc6d0LoyaltyOne\uc5d0\uc11c Delta Lake\ub85c \ub370\uc774\ud130 \ubd84\uc11d \ud30c\uc774\ud504\ub77c\uc778 \ub2e8\uc21c\ud654 \ubc0f \ud655\uc7a5\ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uc7a0\uc7ac\ub825 \uc2e4\ud604DoorDash \ubc0f Grammarly\uc758 \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uad6c\ucd95\uc0b0\uc5c5Prognos\uc5d0\uc11c AI\/ML\uc744 \ud65c\uc6a9\ud558\uc5ec \ubaa8\uc9d1\ub2e8 \uaddc\ubaa8 \uc784\uc0c1 \uc2e4\ud5d8 \ub370\uc774\ud130\uc5d0\uc11c \uc2e4\uc6a9\uc801\uc778 \uc778\uc0ac\uc774\ud2b8 \ucd94\ucd9c\uc815\ubd80 \uae30\uad00\uc5d0\uc11c \uba38\uc2e0 \ub7ec\ub2dd\uc73c\ub85c \ub370\uc774\ud130 \ubd84\uc11d\uc744 \ud601\uc2e0\ud558\ub294 \ubc29\ubc95\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-secures-strategic-investment-q-tel-deliver-cloud-based-apache-spark-platform","text":"Databricks Secures Strategic Investment From In-Q-Tel to Deliver Cloud-Based Apache Spark PlatformPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Secures Strategic Investment From In-Q-Tel to Deliver Cloud-Based Apache Spark PlatformPartnership Will Empower the U.S. Intelligence Community to Perform Critical Missions Using Apache Spark\nJune 21, 2016Share this postSAN FRANCISCO, CA--(Marketwired - Jun 21, 2016) - Databricks, the company behind Apache Spark, today announced a strategic partnership agreement with and investment from In-Q-Tel, Inc. (IQT). IQT is the investment organization that identifies innovative technologies to support the mission of the U.S. Intelligence Community. Through this strategic partnership, Databricks will extend Apache Spark's position as the leading processing engine built for speed, ease of use, and sophisticated analytics by delivering a cloud-based Spark platform that supports the operational requirements of the U.S. Intelligence Community.\nDatabricks is focused on the singular mission of making big data simple. The Databricks platform is a fully managed development and production system for advanced analytics powered by Spark. It empowers individuals and organizations to seamlessly transition from data ingest through exploration to production. Enterprises utilize Databricks to achieve a wide variety of objectives, including integrating disparate data silos, synthesizing actionable insights in real-time, and deploying advanced analytics solutions.\n\"Enterprises today know there is untapped value in their data, especially within the intelligence community, but selecting the tools to unlock that value is often a complex process. Databricks, powered by Apache Spark, is built for developers, data scientists, data engineers and other IT professionals to get up and running very quickly via one end-to-end platform,\" said Ion Stoica, Executive Chairman at Databricks. \"This investment by IQT further validates Databricks' mission and reflects the need for big data simplicity and accessibility that we're seeing among several industries, including federal.\"\n\"A partnership with Databricks continues IQT's tradition of working with world-class analytics companies,\" said Dan Gwak, Partner, IQT Investments. \"We are proud to partner with Databricks to advance the intelligence mission.\"\nAbout In-Q-Tel\nIn-Q-Tel is the not-for-profit, strategic investor that works to identify, adapt, and deliver innovative technology solutions to support the missions of the U.S. Intelligence Community. Launched in 1999 as a private, independent organization, IQT's mission is to identify and partner with companies developing cutting-edge technologies that serve the national security interests of the United States. For more information, visit http:\/\/www.iqt.org.\nAbout Databricks\nDatabricks' vision is to empower anyone to easily build and deploy advanced analytics solutions. The company was founded by the team who created Apache\u00ae Spark\u2122, a powerful open source data processing engine built for sophisticated analytics, ease of use, and speed. Databricks is the largest contributor to the open source Apache Spark project providing 10x more code than any other company. The company has also trained over 20,000 users on Apache Spark, and has the largest number of customers deploying Spark to date. Databricks provides a just-in-time data platform, to simplify data integration, real-time experimentation, and robust deployment of production applications. Databricks is venture-backed by Andreessen Horowitz and NEA. For more information, contact [email\u00a0protected].\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/audience\/digital-native","text":"Neg\u00f3cios e aplicativos nativos digitais | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLakehouse para empresas nascidas na nuvemCrie recursos de dados, an\u00e1lises e IA e dimensione-os mais rapidamente em uma \u00fanica plataforma de dados de alto desempenho\nComece agoraAssista \u00e0s demonstra\u00e7\u00f5esQuanto mais r\u00e1pido voc\u00ea cresce, mais complexos seus dados se tornam. Inove mais rapidamente na Plataforma Databricks Lakehouse \u2014 uma abordagem simples e econ\u00f4mica para dados, an\u00e1lises e IA, tornando mais produtivas milhares de empresas nativas digitais e startups.Inove com a flexibilidade do c\u00f3digo aberto\nUse seus dados onde e como quiser, sem depender de provedor. Os desenvolvedores do Apache Spark\u2122 criaram um lakehouse baseado em formatos abertos e APIs.\nExplorar projetos de c\u00f3digo abertoCrie cargas de trabalho de dados escal\u00e1veis\nObtenha um desempenho confi\u00e1vel e extremamente r\u00e1pido em cargas ETL \u2013 streaming e batch \u2013 e deixe a Databricks gerenciar sua infraestrutura.\nExplorar data engineeringAcesse insights de dados mais rapidamente\nImporte, transforme e consulte todos os seus dados em um s\u00f3 lugar. Pare de gerenciar servidores. Escale de acordo com suas necessidades de serverless. Rela\u00e7\u00e3o custo\/desempenho at\u00e9 12 vezes melhor.\nExplorar Databricks SQLDesenvolva aplicativos de \u00faltima gera\u00e7\u00e3o com ML\nAcelere o ciclo de vida do ML desde a experimenta\u00e7\u00e3o at\u00e9 a produ\u00e7\u00e3o. Otimize sua produtividade com ferramentas como notebooks colaborativos, MLflow e MLOps.\nExplorar os recursos de MLComece a usar a DatabricksExperimente Databricks\nComece sua avalia\u00e7\u00e3o gratuita de 14 dias com Databricks on AWS em apenas algumas etapas. Acesse recursos para toda a sua equipe de dados.\nComece gratuitamenteDesenvolva suas habilidades\nBeneficie-se de treinamentos e certifica\u00e7\u00f5es adaptados \u00e0s suas necessidades em v\u00e1rios campos: an\u00e1lise de dados, data engineering, data science e machine learning.\nReceba treinamentoOtimize os custos\nReduza os custos de infraestrutura em at\u00e9 40% e ganhe produtividade com um servi\u00e7o gerenciado. Conhe\u00e7a nossos planos pr\u00e9-pagos e com desconto.\nVer pre\u00e7osSuporte t\u00e9cnico\nObtenha respostas mais rapidamente com a ajuda dos nossos especialistas Databricks. Voc\u00ea poder\u00e1 desenvolver sem demora sua solu\u00e7\u00e3o de dados com nossos notebooks de autoatendimento.\nExplorar notebooksProgramas integradosCrie seus aplicativos orientados a dados no lakehouse e acelere o crescimento de seus neg\u00f3cios com DatabricksDatabricks para startupsComece rapidamente com o programa de inicializa\u00e7\u00e3o. Descubra como obter cr\u00e9ditos gratuitos, consultoria especializada e suporte para acessar o mercado.Saiba maisParceiros incorporados\u00a0Torne-se um parceiro integrado para obter acesso a benef\u00edcios t\u00e9cnicos, de entrada no mercado e de co-marketing para ajudar a dimensionar seu alcance e expandir seus neg\u00f3cios.Saiba maisNeg\u00f3cios de \u00faltima gera\u00e7\u00e3o desenvolvidos na DatabricksArquiteturas de solu\u00e7\u00f5es para neg\u00f3cios digitais nativosPipelines ETL escalon\u00e1veis e de alto desempenhoCrie uma plataforma de data engineering e ETL de ponta a ponta: voc\u00ea estar\u00e1 livre para extrair insights valiosos de todas as suas nuvens. Voc\u00ea n\u00e3o precisar\u00e1 mais criar e manter pipelines ou executar cargas ETL.Aproveite as ferramentas prontas para produ\u00e7\u00e3o, incluindo Delta Live Tables, Unity Catalog e Workflows.Aproveite a integra\u00e7\u00e3o robusta do Git, ferramentas de orquestra\u00e7\u00e3o e verifica\u00e7\u00f5es de qualidade de dados.Unifique opera\u00e7\u00f5es em batch e streaming em uma arquitetura simplificada e facilite o desenvolvimento e o teste de pipelines de dados.Garanta a qualidade e otimize o salto de dados com o Delta Lake, um protocolo de arquivos de c\u00f3digo aberto utiliz\u00e1vel pelo Apache Spark, Trino, Presto, Flink e muitos outros.Comece agoraAn\u00e1lises SQL e data warehousingImporte, transforme e consulte todos os seus dados em um s\u00f3 lugar para fornecer insights de neg\u00f3cios em tempo real.Execute todos os seus aplicativos SQL e BI em escala, com uma rela\u00e7\u00e3o custo\/desempenho at\u00e9 12 vezes melhor. Garanta a governan\u00e7a e a seguran\u00e7a dos dados.Gerencie high concurrency com balanceamento de carga totalmente gerenciado e escalabilidade de recursos de compute.Use formatos abertos e APIs, bem como suas ferramentas conhecidas de ingest\u00e3o, transforma\u00e7\u00e3o e BI com conectores personalizados.Reduza o esfor\u00e7o de gerenciamento de recursos com compute serverless.Comece agoraMachine learning inovadorMelhore a produtividade e a colabora\u00e7\u00e3o dentro do lakehouse e acelere seus projetos de ML e data science.Aproveite as ferramentas e op\u00e7\u00f5es de colabora\u00e7\u00e3o com a abordagem transparente do AutoML.Prepare, processe e gerencie dados, recursos e modelos com simplicidade de autoatendimento com a Feature Store hospedada.Harmonize o ciclo de vida de ML, desde a experimenta\u00e7\u00e3o at\u00e9 a produ\u00e7\u00e3o, com MLflow, e acompanhe as altera\u00e7\u00f5es nos par\u00e2metros, m\u00e9tricas e itera\u00e7\u00f5es do modelo ao longo do tempo.Implante modelos em batch ou serverless, por meio de endpoints REST em tempo real.Comece agoraParcerias de tecnologia\nDescubra e integre seus dados favoritos e ferramentas e servi\u00e7os de IA diretamente da plataforma Databricks\nExplorar o Partner ConnectSolu\u00e7\u00f5es para cada setorOs l\u00edderes da pr\u00f3xima gera\u00e7\u00e3o criam suas solu\u00e7\u00f5es de an\u00e1lise de dados e IA com DatabricksExplorar solu\u00e7\u00f5es por setorVarejo e bens de consumo\nTome decis\u00f5es em tempo real e otimize a experi\u00eancia do cliente.\nSaiba maisServi\u00e7os financeiros\nPrepare-se para o futuro de seus servi\u00e7os financeiros baseados em dados e IA.\nSaiba maisJogos\nAproveite o poder dos dados e da IA para revelar experi\u00eancias de jogo extraordin\u00e1rias.\nSaiba maisComunica\u00e7\u00f5es, m\u00eddia e entretenimento\u00a0\nCrie conte\u00fado orientado por dados e IA para proporcionar um n\u00edvel mais alto de experi\u00eancia do usu\u00e1rio.\nSaiba maisTecnologia e software\nDesenvolva solu\u00e7\u00f5es de \u00faltima gera\u00e7\u00e3o com recursos avan\u00e7ados de dados e ML.\nSaiba maisTecnologia de sa\u00fade\nOfere\u00e7a melhores resultados a pacientes com dados e IA.\nSaiba maisGuia t\u00e9cnicoResolvendo desafios de dados comunsPara Startups e Neg\u00f3cios Nativos DigitaisSaiba como oferecer suporte a casos de uso de dados \u00e0 medida que voc\u00ea escala, aumentando a efici\u00eancia de custos e a produtividade. Voc\u00ea se beneficiar\u00e1 de diagramas de arquitetura, solu\u00e7\u00f5es passo a passo e guias de in\u00edcio r\u00e1pido. Voc\u00ea tamb\u00e9m encontrar\u00e1 casos de uso da vida real de empresas l\u00edderes como Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable e Zipline.Obtenha sua c\u00f3piaRecursose-booksO que \u00e9 lakehouse?e-book: The Big Book of Data EngineeringThe Big Book of Machine Learning Use CasesGuia definitivo do Delta LakeDelta Lake: A base do seu lakehousee-book: The Big Book of MLOpsGuia da equipe de dados para a Databricks Lakehouse PlatformGuias de in\u00edcio r\u00e1pidoExecutar cargas de trabalho ETLPipelines de dados com Delta Live TablesGuia SQL: Queries and dashboardsIn\u00edcio r\u00e1pido de data scienceIn\u00edcio r\u00e1pido de machine learningBlogsAn\u00fanciosC\u00f3digo abertoInsights por setorSolu\u00e7\u00f5esTudo pronto para come\u00e7ar?Obtenha um teste gratuitoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/resources\/ebook\/a-new-approach-to-data-sharing","text":"A New Approach to Data Sharing | DatabrickseBookShare live data across platformsExplore the new Delta Sharing solutionHomegrown data-sharing solutions based on SFTP or APIs aren\u2019t scalable and saddle you with operational overhead. Off-the-shelf data-sharing solutions only work on specific sharing networks, promoting vendor lock-in and can be costly. Databricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform without any replication so you can reach your customers where they are. Get the whole story in this eBook.You\u2019ll discover how you can:Share live data from where it lives, without replicating or moving it to another systemEasily share existing data in Delta Lake and Apache Parquet formats. Recipients don\u2019t have to be on the Databricks platform, the same cloud or a cloud at all.Drive collaboration with your partners, suppliers and lines of businessMeet governance, security and compliance needs while sharing assetsAccelerate time to value by consuming shared data directly from the tools of your choiceGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rob-saker","text":"Rob Saker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRob SakerGlobal VP, Retail and Manufacturing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeffrey-hess\/#","text":"Jeffrey Hess - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey HessLead Technologist at Booz Allen HamiltonBack to speakersJeff is a Lead Technologist at Booz Allen Hamilton responsible for standardizing enterprise data environments and has led multiple large-scale transformation projects to help stakeholders make the most of their data. Jeff oversees the entire data ecosystem, from moving and storing data, transforming and prepping data, visualizing data, and securing data. Jeff began as a business intelligence developer and continued to grow his passion for analytics, leading to a diverse skillset that sets his clients up for success.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/databricks-weekly-demo","text":"Databricks Events | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks EventsExplore upcoming Databricks meetups, webinars, conferences and more.Join Generation AIJune 26\u201329Learn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowLoading...Browse All Upcoming EventsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPromozione per Databricks SQL \u2014 Risparmia oltre il 40%Approfitta della promozione di 15 mesi su Serverless SQL e sul nuovissimo SQL ProMaggiori informazioniDatabricks SQLIl data warehouse migliore \u00e8 il lakehouseCominciaGuarda la demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks SQL (DB SQL) \u00e8 un data warehouse serverless su Databricks Lakehouse Platform che consente di eseguire tutte le applicazioni SQL e BI su larga scala, con un rapporto prezzo\/prestazioni fino a 12 volte migliore, un modello di governance unificato, formati e API aperti, e i tuoi strumenti preferiti... senza vincoli.Miglior rapporto prezzo\/prestazioniRiduci i costi, ottieni il miglior rapporto prezzo\/prestazioni ed elimina la necessit\u00e0 di gestire, configurare o scalare l'infrastruttura cloud con tecnologie serverless.Governance integrataCrea un'unica copia di tutti i dati utilizzando standard aperti e un livello di governance unificato per tutti i team di gestione dei dati utilizzando SQL standard.Ricco ecosistemaUtilizzando SQL e strumenti come Fivetran, dbt, Power BI o Tableau insieme a Databricks, tutti i dati possono essere acquisiti, trasformati e interrogati sul posto.Abbatti i silosOgni analista sar\u00e0 in grado di accedere pi\u00f9 velocemente ai dati pi\u00f9 recenti per effettuare analisi a valle in tempo reale e passare senza difficolt\u00e0 da BI a ML.Come funziona?Integrazioni dirette con l'ecosistema\u00a0Facilit\u00e0 d'uso\u00a0Prestazioni nel mondo reale\u00a0Governance centralizzata\u00a0Un data lake aperto e affidabile come fondamentaAcquisisci, trasforma e orchestra facilmente i dati da qualsiasi luogoLavora con i tuoi dati ovunque si trovino. Le funzionalit\u00e0 \"chiavi in mano\" consentono ad analisti e tecnici dell'analisi di acquisire facilmente i dati da qualsiasi sorgente, da sistemi di storage in cloud ad applicazioni aziendali come Salesforce, Google Analytics o Marketo, utilizzando Fivetran. Basta un clic. Poi si possono gestire facilmente le dipendenze e trasformare i dati sul posto con funzionalit\u00e0 ETL integrate sul lakehouse, oppure utilizzando i propri strumenti preferiti come dbt su Databricks SQL per avere il massimo delle prestazioni.\u00a0\u201cLa combinazione fra Databricks e Fivetran ci ha consentito di costruire una pipeline di dati moderna e robusta in pochissimo tempo. Fivetran aveva tutti i connettori e le integrazioni che ci servivano.\u201d\u2014 Justin Wille, Director of Insights and Analytics, Kreg ToolMaggiori informazioniAnalisi e BI moderne con i tuoi strumenti preferitiLavora in modo completamente integrato con gli strumenti BI pi\u00f9 diffusi come Tableau, Power BI e Looker. Ora gli analisti possono utilizzare i loro strumenti preferiti per ricavare nuove informazioni approfondite e dettagliate dai dati pi\u00f9 completi e aggiornati. Databricks SQL consente a ogni analista di cercare, trovare e condividere velocemente nuove informazioni attraverso l'editor SQL integrato, visualizzazioni e dashboard.\u00a0\u201cAvendo i dati a portata di mano, siamo molto pi\u00f9 fiduciosi perch\u00e9 sappiamo di utilizzare i dati pi\u00f9 recenti e completi per alimentare i nostri dashboard e report di Power BI.\u201d\u2014 Jake Stone, Senior Manager, Business Analytics, ButcherBoxMaggiori informazioniElimina la gestione delle risorse con il calcolo serverlessDatabricks SQL serverless elimina la necessit\u00e0 di gestire, configurare o scalare l'infrastruttura cloud sul lakehouse, liberando il team di gestione dei dati per svolgere le mansioni per cui \u00e8 pi\u00f9 idoneo. I warehouse SQL di Databricks forniscono un'elaborazione SQL istantanea ed elastica, scollegata dallo storage, e si ridimensionano automaticamente per offrire concorrenze illimitate senza interruzioni, per gestire un numero elevato di casi d'uso contemporanei.\u00a0\u201cDatabricks SQL Serverless ci consente di sfruttare la potenza di Databricks SQL, oltre a essere molto pi\u00f9 efficiente con la nostra infrastruttura.\u201d\u2014 R. Tyler Croy, Director of Platform Engineering, ScribdMaggiori informazioniConcepito fin dall'inizio per ottenere il massimo delle prestazioniDatabricks SQL contiene migliaia di ottimizzazioni per offrire le prestazioni migliori per tutti gli strumenti, i tipi di query e le applicazioni nel mondo reale. \u00c8 compreso il motore di query vettorializzato di nuova generazione Photon che, insieme ai warehouse SQL, offre un rapporto prezzo\/prestazioni fino a 12 volte migliore rispetto ad altri data warehouse in cloud.\u00a0\u201cLa Databricks Lakehouse Platform ci consente di effettuare analisi che riducono da settimane a minuti i tempi necessari per ricavare informazioni sul comportamento del pubblico radiotelevisivo.\u201d\u2014 Stephane Caron, Sr. Director of Business Intelligence, CBC\/Radio-CanadaMaggiori informazioniConserva e gestisci tutti i dati centralmente con SQL standardCrea un'unica copia di tutti i dati utilizzando il formato aperto Delta Lake per evitare vincoli ed esegui analisi e processi ETL\/ELT sul posto direttamente sul tuo lakehouse, senza pi\u00f9 spostare i dati o creare copie in sistemi scollegati. Poi scopri, proteggi e gestisci facilmente tutti i dati con governance granulare, provenienza dei dati e SQL standard su tutti i cloud con Databricks Unity Catalog.\u00a0\u201cDatabricks \u00e8 fondamentale per la nostra attivit\u00e0, perch\u00e9 la sua architettura lakehouse ci fornisce un ambiente unificato per accedere, conservare e condividere dati fruibili.\u201d\u2014 Jagan Mangalampalli, Director of Big Data, PunchhMaggiori informazioniBasato su un'infrastruttura di dati comune, supportata dalla piattaforma lakehouseDatabricks Lakehouse Platform \u00e8 la soluzione di data warehousing pi\u00f9 completa per le moderne esigenze di analisi, e molto altro. Prestazioni di alto livello a una frazione del costo dei data warehouse in cloud. Tempi pi\u00f9 rapidi per trasformare i dati grezzi in informazioni fruibili su larga scala e per unificare batch e streaming. Inoltre, il lakehouse consente ai team di gestione dei dati di passare senza difficolt\u00e0 dall'analisi descrittiva a quella predittiva per estrapolare nuove informazioni.\u00a0\u201cDatabricks ha messo a disposizione un'unica piattaforma per tutti i nostri team di gestione e analisi dei dati, che possono accedere ai dati presenti in tutta l'organizzazione di ABN AMRO, fornendo soluzioni basate su ML che promuovono l'automazione e l'estrapolazione di informazioni approfondite e dettagliate in tutta l'azienda.\u201d\u2014 Stefan Groot, Head of Analytics Engineering, ABN AMROMaggiori informazioniMigrazione a DatabricksStanco dei silos di dati, della lentezza e dei costi esorbitanti di sistemi obsoleti come Hadoop e i data warehouse aziendali? Migra a Databricks Lakehouse, la piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI.Migrazione a DatabricksIntegrazioniIntegrazioni dirette con l'ecosistema garantiscono la massima flessibilit\u00e0 ai team di gestione dei dati. I dati critici per l'azienda possono essere acquisiti con Fivetran e trasformati \"sul posto\" con dbt per estrapolare nuove informazioni con Power BI, Tableau o Looker, tutto senza trasferire i dati in un data warehouse tradizionale.Acquisizione ed ETL di datiGovernance dei datiBI e dashboard+ Qualsiasi altro client compatibile con Apache Spark\u2122\ufe0f\u201cOggi pi\u00f9 che mai, le organizzazioni hanno bisogno di una strategia dei dati che offra velocit\u00e0 e agilit\u00e0 adattabili. Con la rapida migrazione dei dati aziendali verso il cloud, vediamo un crescente interesse per l'analisi sul data lake. Databricks SQL offre un'esperienza completamente nuova ai clienti, che possono estrapolare informazioni da enormi quantit\u00e0 di dati, con le prestazioni, l'affidabilit\u00e0 e la scalabilit\u00e0 di cui hanno bisogno. Siamo orgogliosi di collaborare con Databricks per offrire questa opportunit\u00e0.\u201d\u2014 Francois ajenstat, Chief product officer, TableauReferenzeScopri di pi\u00f9Delta LakePartner ConnectUnity CatalogDelta Live TablesContenuti associati\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video sui vantaggi del lakehouse.\nEsplora risorseeBookCostruire il Data Lakehouse, di Bill Inmon, padre del data warehousePerch\u00e9 il lakehouse \u00e8 il nuovo data warehouseGovernance di dati, analisi e intelligenza artificialeThe Big Book of Data EngineeringMigrazione da data warehouse a data lakehouse per principiantiEventiI meccanismi interni del lakehouse dai Data + AI World TourWebinar sulle best practice di ottimizzazione delle prestazioni sul lakehouse: viaggio nella vita di una queryCorso gratuito di Databricks SQL \u2013 Su richiestaIl data warehouse migliore \u00e8 il lakehouseBlogDatabricks stabilisce il record ufficiale di prestazioni di data warehouseAnnunciata la disponibilit\u00e0 in commercio di Databricks SQLEvoluzione del linguaggio Sql in Databricks: Ansi Standard di default e migrazioni pi\u00f9 facili dai data warehouseImplementare dbt su Databricks \u00e8 ancora pi\u00f9 sempliceTecniche di modellazione dei data warehouse e implementazione su Databricks Lakehouse PlatformCome costruire una soluzione per l'analisi del marketing con Fivetran e dbt su Databricks LakehousePronto per cominciare?Prova gratuitaEntra nella communityProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/legal\/advisory-services-schedule","text":"Advisory Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAdvisory Services ScheduleThis Schedule sets forth terms related to the Advisory Services and is incorporated as part of the Master Cloud Services Agreement (\"MCSA\"). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Other Schedules do not apply to the services ordered under this Schedule unless expressly referenced as being applicable. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Additional Definitions.\u201cCustomer Materials\u201d means the information and materials you provide to Databricks for Databricks to perform the Advisory Services.Advisory Services.Generally. Subject to the Order, Databricks will provide Advisory Services to facilitate your use of the Databricks platform. Unless otherwise agreed by the parties, Advisory Services will expire one year after the Start Date indicated on the Order and will be booked on the basis of 8-hour service days.Intellectual Property.License. Upon your payment of all Fees under an applicable Order, Databricks grants you a non-exclusive, perpetual, fully paid-up, royalty-free license to use, copy, modify, or create derivative works based on any Advisory Services work product delivered by Databricks to you under the Order (the \u201cDeliverables\u201d). If and to the extent Databricks incorporates any Databricks Materials (as defined below) into the Deliverables, Databricks grants to you a non-exclusive, perpetual, fully paid-up, royalty-free license to use, copy, modify or create derivative works based on such Databricks Materials, solely as incorporated into the Deliverables and solely for your internal business use as reasonably necessary to use the Deliverables for their intended purposes. For the avoidance of doubt, no part of the Platform Services will be deemed to be incorporated into the Deliverables.Databricks Materials. Subject to your rights in your Confidential Information, Databricks will exclusively own all rights, title and interest in and to: (i) the Deliverables; and (ii) any software programs, tools, utilities, processes, inventions, devices, methodologies, specifications, documentation, techniques, training materials, and other materials of any kind used or developed by Databricks or its personnel in connection with performing the Advisory Services, or any other Databricks Services (collectively \u201cDatabricks Materials\u201d), including all Intellectual Property Rights in any of the foregoing.No Maintenance. Unless otherwise set forth in an Order the Deliverables are not subject to any maintenance, support or updates after the termination of the Order.Requirements; Limitations. Databricks will provide the Advisory Services remotely or at a mutually agreed location. While on Customer\u2019s premises, Databricks will adhere to reasonable policies provided by Customer in writing in advance. For the avoidance of doubt, no such policies will be deemed to modify the terms of the Agreement.Use of Workspace during Performance of Advisory Services. You may be required to use a Workspace in order to receive Advisory Services. Your use of the Workspace constitutes acceptance of the Platform Services terms of the MCSA unless the Workspace is provided as part of a Databricks Powered Service.Your Obligations; Customer Materials.\u00a0Your Responsibilities. You:\nare responsible for taking reasonable steps at all times to maintain the security, protection and backup of all Customer Materials, including within the Platform Services and any Customer Systems;acknowledge that: (i) Databricks does not provide data backup services; and that (ii) Databricks is not responsible for any loss, destruction, alteration, unauthorized disclosure or corruption of Customer Materials not caused by the gross negligence or willful misconduct of Databricks or any third party under the control of Databricks;agree not to provide Databricks with access to more data than is reasonably necessary to permit Databricks to perform the Advisory Services; andacknowledge that successful delivery of the Advisory Services depends on your full and timely cooperation. You agree to make available any reasonably requested personnel and\/or information in a timely manner to allow Databricks to perform such services.Restrictions on Use. You will not:\ncopy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of any Deliverables provided to you in object code, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;use the Databricks Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party's possible purchase of any Databricks product or service; ortransfer or assign any of your rights hereunder except as permitted under Section 12.5 (Assignment) of the MCSA.Customer Materials. You represent and warrant to Databricks that Customer Materials will not contain:\nany data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement; orexcept as otherwise specified in an Order, any (x) bank, credit card or other financial account numbers or login credentials, (y) social security, tax, driver\u2019s license or other government-issued identification numbers, or (z) health information identifiable to a particular individual.Data Protection. Databricks will maintain appropriate administrative, physical, and technical safeguards according to ISO\/IEC 27001:2013 (the \u201cISMS Standard\u201d) for protection of the security and confidentiality of Customer Materials under Databricks\u2019 control. Unless specified otherwise in an Order, Databricks engages in the performance of Advisory Services with the expectation that Customer is not engaging Databricks for the purpose of having Databricks act as a data processor for Customer. Nevertheless, except with respect to free Advisory Services, unless you have entered into the\u00a0DPA, the terms of the\u00a0DPA are hereby incorporated by reference and will apply to the extent Databricks is deemed to act as Customer\u2019s data processor during the performance of Advisory Services when the Customer Materials include Personal Data, as defined in the\u00a0DPA. This Schedule and the\u00a0DPA do not govern the protection of Customer Content and Databricks does not act as a data processor with respect to any data processed by or within a Databricks Powered Service.Expenses. You agree to reimburse Databricks for reasonable travel and lodging expenses actually incurred by Databricks.Warranties; Disclaimer.Warranties. Databricks warrants that the Advisory Services will be provided in a professional and workmanlike manner consistent with industry standards. You must notify Databricks of any warranty deficiencies within ninety (90) days from performance of the deficient Advisory Services. Unless set forth in an Order Databricks makes no guarantee as to whether the Advisory Services will be completed within any specific time frame.Disclaimer. THE WARRANTIES IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING THE DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS SPECIFICALLY DISCLAIMS ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE WITH RESPECT TO ANY OF THE FOREGOING. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (i) SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \"AS-IS\" AND WITHOUT WARRANTY OF ANY KIND BY DATABRICKS; (ii) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE DATABRICKS SERVICES; AND (iii) DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE.Exclusive Remedy. FOR ANY BREACH OF THE WARRANTY AT SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE RE-PERFORMANCE OF THE DEFICIENT SERVICES, OR, IF DATABRICKS CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE COMMENCEMENT OF THE DEFICIENCY.Last Updated August 12, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-pycharm","text":"What is PyCharm?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPyCharmAll>PyCharmTry Databricks for freeGet StartedPyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to create a Conda environment or use an existing one.To play this video, click here and accept cookiesAdditional ResourcesHow to Use MLflow, TensorFlow, and Keras with PyCharmDatabricks Connect (Including PyCharm) DocumentationBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#cda9bebf8da9acb9acafbfa4aea6bee3aea2a0","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c2bbf0f750a8d\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cyrielle-simeone","text":"Cyrielle Simeone - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCyrielle SimeonePrincipal Product Marketing Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/financial-services","text":"Lakehouse pour les services financiers | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLakehouse pour les services financiersAlimenter l'institution des services financiers de demain articul\u00e9s autour des donn\u00e9es et de l'IAD\u00e9marrerPlanifier une d\u00e9moLes services financiers et leurs\nquatre d\u00e9fis en mati\u00e8re de donn\u00e9esGouvernance et gestion des donn\u00e9es\nDe par l'absence d'agilit\u00e9 des donn\u00e9es et de reproductibilit\u00e9 des mod\u00e8les, il est difficile de r\u00e9pondre aux exigences r\u00e9glementaires propres aux services financiers.Des insights clients plus approfondis\nLes silos de donn\u00e9es emp\u00eachent de fournir un aper\u00e7u complet des comportements clients, des opportunit\u00e9s de vente crois\u00e9e ainsi que les insights n\u00e9cessaires \u00e0 une hyper-personnalisation \u00e0 grande \u00e9chelle.Des d\u00e9cisions en temps r\u00e9el\nLa d\u00e9pendance vis-\u00e0-vis d'un seul fournisseur ainsi que des outils incoh\u00e9rents entravent la capacit\u00e9 d'effectuer une analytique en temps r\u00e9el qui stimule et d\u00e9mocratise les d\u00e9cisions financi\u00e8res plus fines et pertinentes.Un acc\u00e8s aux donn\u00e9es de tiers\nLes technologies existantes ne permettent pas d'exploiter les insights clients et financiers \u00e0 partir de datasets non structur\u00e9s et alternatifs qui se d\u00e9veloppent rapidement. Elles n'offrent pas non plus de capacit\u00e9s de partage de donn\u00e9es ouvertes pour favoriser la collaboration.Lakehouse pour les services financiersUne plateforme unifi\u00e9e d'IA et de donn\u00e9es\nUne plateforme unique qui rassemble toutes vos charges de travail de donn\u00e9es et d'analytique afin de permettre de profondes innovations pour les institutions de services financiers modernes.\n\u00a0\nSolutions partenaires\nLes plus grands fournisseurs de solutions du monde participent au Lakehouse pour les services financiers. Profitez d'offres pr\u00e9d\u00e9finies qui acc\u00e9l\u00e8rent la transformation data-driven.\nDes outils pour acc\u00e9l\u00e9rer les r\u00e9sultats commerciaux\nDatabricks et ses partenaires ont cr\u00e9\u00e9 toute une gamme d'acc\u00e9l\u00e9rateurs de solutions pour les services financiers qui facilitent le traitement des cas d'usage courants dans ce domaine, de l'investissement ESG \u00e0 la pr\u00e9vention de la fraude.\nCollaboration dans le secteur\nActivez un partage des donn\u00e9es s\u00e9curis\u00e9 et ouvert gr\u00e2ce \u00e0 notre \u00e9cosyst\u0000\u00e8me de donn\u00e9es \u2014 comprenant S&P Global, Intercontinental Exchange, FactSet et Nasdaq \u2014 afin de lib\u00e9rer des innovations favorisant la cr\u00e9ation de valeur durable.\nTransformer les services financiers avec\nLakehouse\n\u00ab\u00a0La vision du Nasdaq en mati\u00e8re de donn\u00e9es et d'IA est aliment\u00e9e par Lakehouse de Databricks. Nous l'utilisons pour traiter d'\u00e9normes quantit\u00e9s de donn\u00e9es financi\u00e8res et alternatives complexes afin de cr\u00e9er des donn\u00e9es et des insights pour nos clients. Par ailleurs, Databricks joue un r\u00f4le essentiel dans nos efforts en vue de moderniser la transmission et la consommation de donn\u00e9es. Databricks nous permet de transmettre des donn\u00e9es directement dans des espaces de travail analytiques, afin que nos clients puissent analyser et int\u00e9grer rapidement des donn\u00e9es critiques sans avoir \u00e0 d\u00e9placer des t\u00e9raoctets.\u00a0\u00bb\u2014 Bill Dague, Head of Nasdaq Data Link, NasdaqPourquoi choisir Lakehouse pour les services financiers\u00a0?\nRegroupez les donn\u00e9es et l'IA sur une plateforme ouverte et collaborative vous permettant de minimiser les risques, d'offrir des exp\u00e9riences client enrichies et d'acc\u00e9l\u00e9rer l'innovationApproche manag\u00e9e de la conformit\u00e9 et de la gestion des risques\nSimplifiez la complexit\u00e9 des rapports r\u00e9glementaires,\nde la gestion des risques et de la conformit\u00e9 en rationalisant en toute s\u00e9curit\u00e9\nl'acquisition, le traitement et la transmission des donn\u00e9es pour\nmettre en \u0153uvre de meilleures pratiques de gouvernance.Produits et services personnalis\u00e9s\nRegroupez toute une gamme de donn\u00e9es \u2014 allant des donn\u00e9es du march\u00e9 aux donn\u00e9es alternatives \u2014\npour des exp\u00e9riences hyper-personnalis\u00e9es favorisant les\nopportunit\u00e9s de vente crois\u00e9e, la satisfaction client et la part de\nportefeuille.Des insights en temps r\u00e9el pour des d\u00e9cisions plus avis\u00e9es\nInt\u00e9grez rapidement toutes vos sources de donn\u00e9es \u00e0 l'\u00e9chelle pour prendre de meilleures d\u00e9cisions\nd'investissement, d\u00e9tecter rapidement les nouveaux m\u00e9canismes de fraude\net apporter des capacit\u00e9s en temps r\u00e9el aux pratiques de gestion des risques\n.Une mon\u00e9tisation et un partage de donn\u00e9es ouvertes\nRassemblez de grandes quantit\u00e9s de donn\u00e9es internes et tierces\npour partager des solutions financi\u00e8res innovantes, mon\u00e9tiser de nouveaux produits de donn\u00e9es\net fournir des capacit\u00e9s d'analytique avanc\u00e9es \u00e0 n'importe quel cloud ou outil\nsans vous enfermer dans des technologies exclusives\n.T\u00e9l\u00e9charger l'ebookPartenaires et solutionsAller vers des formats ouverts et la standardisation des donn\u00e9es pour l'analytique et l'IAGestion des risquesIncorporez rapidement des donn\u00e9es \u00e0 des mod\u00e8les de valeur \u00e0 risque pour identifier les risques \u00e9mergents et les menaces potentielles.D\u00e9marrerModernisation des activit\u00e9s \u00ab\u00a0cartes\u00a0\u00bb historiques et des portefeuilles de services bancaires c\u0153urs de m\u00e9tierMettez rapidement sur pied une fonction de conversion des donn\u00e9es enti\u00e8rement configurable et industrialis\u00e9e provenant de syst\u00e8mes externes.D\u00e9marrerPersonnage 360\u00c9laborez des profils client complets et unifi\u00e9s au sein d'un mod\u00e8le de donn\u00e9es intelligentD\u00e9marrerD\u00e9couvrez toutes les solutions partenairesLa cybers\u00e9curit\u00e9 \u00e0 l'\u00e9chelleD\u00e9tectez rapidement les menaces, \u00e9tudiez leur impact et r\u00e9duisez les risques gr\u00e2ce \u00e0 Splunk et DatabricksD\u00e9marrerLa notation ESGAdoptez une vision quantitative de la durabilit\u00e9 et veillez \u00e0 ce que les entreprises soient responsables de leurs actionsD\u00e9marrerUne gestion moderne des risquesAdopter une approche plus agile de la gestion des risques en unifiant les donn\u00e9es et l'IA dans le Lakehouse.D\u00e9marrerIdentifiez la fraude gr\u00e2ce \u00e0 l'analytique g\u00e9ospatiale et \u00e0 l'IAUtilisez des donn\u00e9es g\u00e9ospatiales pour mieux comprendre les comportements d'achat des clients, tant sur le plan de leur identit\u00e9 que de leur mode de paiementD\u00e9marrerUn enrichissement des transactions gr\u00e2ce aux cat\u00e9gories de marchandsAutomatisez l'enrichissement des transactions pour mieux comprendre les comportements de vos clients et favoriser l'hyper-personnalisationD\u00e9marrerDes mod\u00e8les d'IA bas\u00e9s sur des r\u00e8gles pour lutter contre la fraude financi\u00e8reModernisez les strat\u00e9gies de pr\u00e9vention des fraudes pour r\u00e9duire les frais d'exploitation et augmenter la confiance des clientsD\u00e9marrerUne transmission des rapports r\u00e9glementaires fiable et dans les tempsCombinez les mod\u00e8les de donn\u00e9es du secteur des services financiers avec le cloud pour permettre des normes de gouvernance \u00e9lev\u00e9es avec des frais de d\u00e9veloppement r\u00e9duitsD\u00e9marrerModernisation des plateformes de donn\u00e9es d'investissementUtilisez toute la puissance des donn\u00e9es des march\u00e9s financiers pour vous concentrer sur la fourniture de produits aux clientsD\u00e9marrerLutte contre le blanchiment d'argent (AML)Activez les cas d'usage articul\u00e9s autour de l'IA, comme l'appariement flou et l'analytique d'images, pour lutter contre le blanchiment d'argent et le financement du terrorismeD\u00e9marrerVoir toutes les solutionsLakehouse pour les services financiers en pratiqueR\u00e9ussir ensemble\u00a0: comment les donn\u00e9es + l'IA favorisent la collaboration au sein du LakehouseS'INSCRIRE MAINTENANT \u2192Ressources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez la biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les donn\u00e9es et l'IA pour le secteur des services financiers.\nExplorer les ressourceseBooks et infographies[Infographie] Des donn\u00e9es pour ancrer une nouvelle \u00e8re de la gestion des risquesD\u00e9couvrez comment exploiter facilement les avantages des donn\u00e9es et de l'IA dans les services financiersTirer parti des donn\u00e9es alternatives et tierces dans les services financiers \u2192Faire de l'ESG une r\u00e9alit\u00e9 gr\u00e2ce \u00e0 l'analytique des donn\u00e9es et \u00e0 l'IA \u2192 Pr\u00e9venir la fraude gr\u00e2ce aux donn\u00e9es et \u00e0 l'IA\u00a0: une introduction pour les menaces modernes \u2192 Vid\u00e9os et t\u00e9l\u00e9chargementsDes m\u00e9thodologies d'investissement ESG explicables et transparentes \u2192Cybers\u00e9curit\u00e9 dans les services financiers \u2192Acc\u00e9l\u00e9rer l'innovation ax\u00e9e sur les donn\u00e9es et l'IA dans les services financiers \u2192Analytique ESG: vid\u00e9o explicative \u2192Moderniser la gestion des risques \u2192Des plateformes d'investissement modernes avec Lakehouse pour les services financiers \u2192Fiche solution des plans de Lakehouse de l\u2019industrieBlogsAcc\u00e9l\u00e9rateur pour les banques et les fintechs utilisant les transactions par carte de cr\u00e9ditUne approche data-driven de l'environnement, du social et de la gouvernance \u2192Cr\u00e9er une plateforme moderne de gestion des risques dans le domaine des services financiers \u2192Utiliser vos donn\u00e9es pour stopper les fraudes sur les cartes de cr\u00e9dit\u00a0: Capital One et autres bonnes pratiques \u2192Strat\u00e9gies de modernisation des plateformes de donn\u00e9es d'investissement \u2192Am\u00e9liorer l'exp\u00e9rience client gr\u00e2ce \u00e0 l'enrichissement des transactions \u2192 Les points cl\u00e9s du sommet Data + AI 2022 pour les services financiers \u2192Lakehouse pour les services financiersPr\u00eat \u00e0 vous lancer\u00a0?Nous serions ravis de conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.ESSAYER GRATUITEMENT DATABRICKSPlanifier une d\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-plans-increase-local-headcount-india-more-50-support","text":"Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 May 5, 2023Share this post\nShowcases Dolly 2.0 the world\u2019s first truly open instruction-tuned LLM at its inaugural Data + AI World Tour in India\nRecently appointed India Country Manager Anil Bhasin to drive further adoption of the lakehouse platform\n\nBengaluru, India, 5 May 2023 - Databricks, the data and AI company, announced strong data lakehouse adoption in India and plans to increase its local headcount by more than 50% this year, adding roles such as technical specialists, sales and support engineers, and go-to-market resources, to its team of over 250, to support business growth and drive customer success. The company also announced the launch of a new R&D hub in Bengaluru later this year.\nAcross the Asia Pacific region, the company is experiencing 90% year-over-year business growth.\nDatabricks has pioneered the data lakehouse, which is an open and unified data management architecture that combines the flexibility, cost-efficiency and scalability of data lakes with the data management features of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data.\nThe company gathered data and AI experts and visionaries at its inaugural Data + AI World Tour in Bengaluru today, to connect, share best practices, and get a first look at the company\u2019s latest product innovations. This includes the recent launch of Dolly 2.0, the world\u2019s first open-source, instruction-following large language model (LLM), fine-tuned on a human-generated instruction dataset licensed for research and commercial use.\u00a0\nDolly 2.0 is a 12B parameter language model based on the EleutherAI pythia model family and fine-tuned exclusively on a new, high-quality human generated instruction following dataset, crowdsourced among Databricks employees. Databricks is open-sourcing the entirety of Dolly 2.0, including the training code, the dataset, and the model weights, all suitable for commercial use. This means that any organization can create, own, and customize powerful LLMs that can talk to people, without paying for API access or sharing data with third parties.\nRecently, Databricks also announced the appointment of Anil Bhasin as the Country Manager for India to drive further lakehouse adoption across the country. A tech industry veteran, Bhasin brings more than 30 years of experience to the role and joined Databricks from UiPath where he served as the Managing Director and VP of the company\u2019s India and South Asia business. Previously, Bhasin was the Regional Vice President for Palo Alto Networks.\n\u201cI\u2019m thrilled to be leading the Databricks India business at such a pivotal point in history where business leaders in India are awakening to the power of data and AI to transform their businesses. I firmly believe that data and AI adoption will accelerate our country\u2019s transformation to help India become the most data-driven economy by transforming enterprises to become more data-forward,\u201d said Anil Bhasin, Vice President and Country Manager for Databricks India. \u00a0\nData-forward companies including InMobi, Swiggy, Dream11, Air India, MakeMyTrip, Meesho, Narayana Health, Myntra, CRED, Parle and many more are harnessing the value of their data and applying AI to optimize their business operations and drive innovations through the lakehouse platform.\u00a0\n\"Any travel product, almost always, is a very nuanced purchase \u2013 it\u2019s very contextual and experiential by its very nature. Given that, the travel ecosystem has multiple variables that must be evaluated \u2013 in batch, and, more importantly, in real-time - before a specific set of products can be personalized and recommended to the customer. Databricks has been our trusted partner in unifying data to bolster our ML ecosystem, which helps us deliver quick and effective results in \u201cnear-real-time\u201d. The Lakehouse Architecture has helped us launch multiple successful consumer-led innovations,\" said Piyush Kumar, Vice President, Technology Development, MakeMyTrip.\u00a0\n\"We have chosen Databricks Lakehouse Platform as our ideal modern data architecture because we wanted a unified data platform that eliminates data silos within our organization and achieves cost optimization with the increasing amount of data that we are collecting. I am confident that Databricks will be a key enabler in our overall digitization journey, powering faster business analytics to support and enable our business functions to make data-driven business-critical decisions and firm strategies, to ultimately delight our customers from all classes and age groups to enjoy our products to the fullest,\u201d said Sanjay Joshi, CIO of Parle Products Pvt. Ltd.\nDatabricks also recognized and celebrated outstanding data teams and individuals using data and AI to transform their industry at the inaugural Databricks India Innovation Awards.\u00a0\nCongratulations to the winners of the India Data + AI Awards 2023:\u00a0\n\nData + AI Award for Disruptive Innovation: recognizes the data and AI team that embodies innovation and impact \u2014 creating new markets and value propositions by employing data and AI technologies, and inspiring the global data and AI community.\nWinner: MakeMyTrip\nData + AI Award for Driving a Data-First Culture: recognizes the data and AI team that evangelizes the culture of data-driven decision making, delivering data into the hands of empowered users across the organization \u2014 making every team a data team.\nWinner: Dream11\nData + AI Visionary Award for Shaping the Future: honors the data and AI team that recognizes the potential of data and AI to transform their organization, and turning that vision into reality, unlocking significant value for the business.\nWinner: Meesho\u00a0\nData + AI Award for Societal Impact: honors the data and AI team that spurs positive social change which benefits society at large.\nWinner: Navi\nData + AI Award for Redefining Customer Experience: honors the team that leverages data and AI to deliver seamless, personalized and omnichannel customer experiences.\nWinner: InMobi\n\nAbout Databricks\nDatabricks is the data and AI company. More than 9,000 organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, H&M, and over 50% of the Fortune 500 \u2014 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on\u00a0Twitter,\u00a0LinkedIn\u00a0and\u00a0Facebook.\nContact: [email\u00a0protected]\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lucas-dos-santos-celestino\/#","text":"Lucas dos Santos Celestino - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLucas dos Santos CelestinoPlatform Product Manager at AB InbevBack to speakersCurrently working for Anheuser-Busch InBev (Brazil) as Platform Product Manager with expertise in software development, cloud architecture\/infrastructure, UX design, product operations and agile methods.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jay-yang","text":"Jay Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJay YangPrincipal Data Engineer at ProcoreBack to speakersJay Yang is a Principal Data Engineer at Procore, where he leads the Data and Analytics Platform team. With more than 17 years of industry experience, Jay excels in creating high-performance data platforms designed to support the company's reporting, analytics, and machine-learning applications. As a strong advocate for data accessibility, he is committed to unlocking the potential of data and generating value for businesses.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chen-guo","text":"Chen Guo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChen GuoStaff Software Engineer at CoinbaseBack to speakersChen Guo is a staff software engineer from the Data Platform & Service team at Coinbase. His current work focuses on designing and developing SOON (Spark cOntinuOus iNgestion), a unified streaming ingestion framework, and SONAS (SOON as a Service). Before Coinbase, he worked at LinkedIn's Big Data Infrastructure team to build cloud-based ingestion and offline processing infrastructure using Azure Data Factory and contributed to Apache Gobblin. When not working, he loves reading and sports.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=hangzhou%2C%20china","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/safety-stock","text":"Solution Accelerator - How to build: Safety stock | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: Safety stockIncrease sales by ensuring adequate inventory across the supply chain, while minimizing carrying costsCreate fine-grained and viable estimates of buffer stock for raw material, work-in-progress or finished goods inventory items that can be scaled across the supply chain. Free up working capital that would be tied up in inventory and reallocate to more productive uses.Read the full write-upDownload all notebooksBenefits and business valueEnsure buffer inventoryRapidly run safety-stock analysis across all plants and distribution centers multiple times per day\nUnderstand stock patterns over timeEfficiently store past forecasts to analyze over-repeated periods using machine learning\nFree up working capitalMinimize excess inventory while maintaining service levels, to improve financial flexibility\nReference ArchitectureData usedT-log, POS, or shipment sales data. Inventory data, promotions, weather, and other causal data sets.Deliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vikas-reddy-aravabhumi","text":"Vikas Reddy Aravabhumi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVikas Reddy AravabhumiStaff Backline Engineer at DatabricksBack to speakersVikas Reddy Aravabhumi is an experienced Staff Backline engineer with over 12 years of industry experience. He specializes in resolving Big data problems for customers through the use of Structured Streaming, spark SQL, Delta Lake and DLT. Additionally, he has extensive expertise in implementing Structured Streaming frameworks. Prior to joining Databricks, he worked as a technical lead assisting consulting and R&D companies in deploying their big data ETL pipelines using Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/technology?itm_data=TechnologyPartnersProgram-FooterCTA-Find","text":"Databricks Technology Partners - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Technology PartnersConnect with Databricks Technology Partners to integrate data ingestion, business intelligence and governance capabilities with the Databricks Lakehouse Platform.\u201cWith Databricks and Fivetran, we will be able to significantly improve marketing insights in the future. From a technical standpoint, the two tools interact harmoniously together and the integration feels very native.\u201d\u2014 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP at Paul HewittDatabricks Technology Partners integrate their solutions with Databricks to provide complementary capabilities for ETL, data ingestion, business intelligence, machine learning and governance.These integrations enable customers to leverage the Databricks Lakehouse Platform\u2019s reliability and scalability to innovate faster while deriving valuable data insights.Partner ConnectBring together all your data, analytics and AI tools on one open platform. With Partner Connect, Databricks provides a fast and easy way to connect your existing tools to your lakehouse using validated integrations, and helps you discover and try new solutions.Become a partnerLearn moreLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/robin-sutara","text":"Robin Sutara - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRobin SutaraField CTO at DatabricksBack to speakersFrom repairing Apache helicopters near the Korean DMZ to the corporate battlefield, Robin has demonstrated success in navigating the high stress, and sometimes combative, complexities of data-led transformations. She has consulted with hundreds of organisations on data strategy, data culture, and building diverse data teams. Robin has had an eclectic career path in technical and business functions with more than two decades in tech companies, including Microsoft and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks su Google CloudLa piattaforma lakehouse aperta incontra il cloud aperto per unificare data engineering, data science e analisiCominciaDatabricks su Google Cloud \u00e8 un servizio sviluppato congiuntamente che consente di conservare tutti i dati su una piattaforma lakehouse semplice e aperta, che unisce il meglio di data warehouse e data lake per unificare tutti i carichi di lavoro di analisi e AI. Grazie alla stretta integrazione con Google Cloud Storage, BigQuery e Google Cloud AI Platform, Databricks pu\u00f2 girare perfettamente su tutti i servizi di gestione dati e AI su Google Cloud.\nData engineering affidabileAnalisi SQL su tutti i datiCollaborative Data ScienceMachine learning in produzione\nPerch\u00e9 Databricks su Google Cloud?ApertaSoluzione basata su standard aperti, API aperte e infrastruttura aperta, per poter accedere, elaborare e analizzare i dati alle tue condizioni.OttimizzatoImplementa Databricks su Google Kubernetes Engine, il primo ambiente runtime di Databricks basato su Kubernetes con qualsiasi cloud, per ottenere informazioni approfondite pi\u00f9 velocemente.IntegratoAccedi a Databricks con un clic dalla Google Cloud Console, con sicurezza, fatturazione e gestione integrate.Impara dall'esperienza di questi clienti\n\u201cDatabricks su Google Cloud semplifica il processo di gestire qualsiasi quantit\u00e0 di casi d'uso su una piattaforma di calcolo scalabile, accorciando i cicli di pianificazione necessari per fornire una risposta a ogni domanda o problema\u201d.\u2014Harish Kumar, Global Data Science Director di ReckittIntegrazione snella con Google CloudGoogle Cloud StorageGoogle Cloud StorageConsenti l'accesso diretto in lettura\/scrittura a dati in Google Cloud Storage (GCS) e sfrutta il formato aperto Delta Lake per aggiungere affidabilit\u00e0 e prestazioni evolute all'interno di Databricks.Google Kubernetes EngineBigQueryIdentit\u00e0 in grande stileGoogle Cloud AI PlatformGoogle Cloud BillingCercatoreEcosistema di partnerRisorseEventi virtualiVirtual Workshop: Il data lake apertoNotizieDatabricks collabora con Google Cloud per fornire la sua piattaforma a imprese di tutto il mondoBlog e reportAnnuncio del lancio di Databricks su Google CloudPresentazione di Databricks su Google Cloud \u2013 Ora in anteprima pubblicaScheda tecnica di Databricks su Google CloudDatabricks su Google Cloud \u00e8 ora disponibile per tuttiData engineering, data science e analisi con Databricks su Google CloudPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thet-ko\/#","text":"Thet Ko - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThet KoPrincipal Data Engineer at SEEKBack to speakersThet Ko has 10+ years experience working across the full stack from cloud infrastructure, databases, backend systems to front end development. He is currently a Principal Engineer at SEEK responsible for supporting over 165 engineers and scientists scale their analysis on Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/databricks-subprocessors","text":"Databricks Subprocessors | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks SubprocessorsDatabricks engages certain subprocessors in connection with providing the Platform Services or Support Services. A subprocessor is a Databricks affiliate (\u201cDatabricks Affiliate'') or a third-party engaged by Databricks, Inc. or a Databricks Affiliate to process personal data on behalf of Databricks\u2019 customers. Capitalized terms used herein have the same meaning as defined in the Master Cloud Services Agreement or other written agreement you have with Databricks (\u201cAgreement\u201d).Subscribe to be notified when we add new Subprocessors.Third-party SubprocessorsEntity NamePurposeEntity CountryAmazon Web Services, Inc.Cloud Service ProviderUnited StatesAmazon Data Services Ireland LtdCloud Service ProviderIrelandGoogle LLCCloud Service ProviderUnited StatesMicrosoft CorporationCloud Service ProviderUnited StatesIntercom R&D Unlimited CompanyProvide a platform for Databricks to send messages to our customers.IrelandOktaGenerate OAuth tokens (if customer does not choose to provide their own) to connect with customer-selected third parties.United StatesTwilio Inc.Provide customer communications, including in-product messaging and email.United StatesAtlassian Pty Ltd.Customer support and ticket handling.AustraliaMicrosoft CorporationCustomer support (in Microsoft Teams).United Statessalesforce.com, inc.Customer support ticketing.United StatesSlack Technologies, Inc.Customer support.United StatesSupportLogic, Inc.Monitor quality of service in responding to support tickets.United StatesDatabricks AffiliatesThe following entities are members of the Databricks Group. Accordingly, they may function as Subprocessors to provide the Databricks Services.Entity NameEntity CountryDatabricks Federal LLCUnited StatesDatabricks B.V.The NetherlandsDatabricks U.K. LimitedUnited KingdomDatabricks Australia Pty LtdAustraliaDatabricks SARLFranceDatabricks GmBHGermanyDatabricks Asiapac Unified Analytics Pte. Ltd.SingaporeDatabricks Japan K.K.JapanDatabricks India Private LimitedIndiaDatabricks Canada ULCCanadaDatabricks Italy S.r.l.ItalyDatabricks Sweden ABSwedenDatabricks Switzerland GmbHSwitzerlandDatabricks Spain S.L.SpainDatabricks Korea LLCSouth KoreaDatabricks New Zealand LimitedNew ZealandDatabricks Costa Rica SRLCosta Rica\u00a0Last Modified: March 31, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/larry-feinsmith","text":"Larry Feinsmith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLarry FeinsmithHead of Global Tech Strategy, Innovation and Partnerships at JP Morgan Chase & Co.Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/p\/whitepaper\/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025","text":"CIO \ube44\uc804 2025: BI\uc640 AI\uc758 \uac04\uadf9 \uba54\uc6b0\uae30 - Databricks\ubcf4\uace0\uc11cCIO \ube44\uc804 2025BI\uc640 AI\uc758 \uac04\uadf9 \uba54\uc6b0\uae30\ube44\uc988\ub2c8\uc2a4 \uac00\uce58 \uc911\uc2ec AI \ub3c4\uc785\uc5d0 \ub300\ud55c \uae00\ub85c\ubc8c CIO \uc870\uc0ac\ucd5c\uace0\uc758 \uae30\uc5c5\uacfc \uc870\uc9c1\uc5d0\uc11c AI\ub97c \ub9c8\uc2a4\ud130\ud558\ub294 \ub370 \uac00\uc7a5 \ud070 \ub370\uc774\ud130 \ubb38\uc81c\ub97c \uc5b4\ub5bb\uac8c \uadf9\ubcf5\ud558\ub294\uc9c0 \uc54c\uc544\ubcf4\uc138\uc694. MIT Technology Review\uc758 \uc0c8\ub85c\uc6b4 \uc870\uc0ac \ubcf4\uace0\uc11c\uc5d0\uc11c\ub294 18\uac1c \uad6d\uac00\uc640 14\uac1c \uc5c5\uc885\uc758 CIO 600\uba85\uc774 \uc81c\uacf5\ud558\ub294 \uc778\uc0ac\uc774\ud2b8\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.CIO\ub294 AI \ub3c4\uc785\uc758 \uc6b0\uc120\uc21c\uc704\ub97c \uc5b4\ub5bb\uac8c \uacb0\uc815\ud558\ub098\uc694? \ub370\uc774\ud130 \uc804\ub7b5\uc744 \uac1c\uc120\ud558\uae30 \uc704\ud574 \uc5b4\ub5a4 \ud22c\uc790\ub97c \ud558\ub098\uc694?Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global, Marks & Spencer \ub4f1\uc758 \ucd5c\uace0\uc704 \uacbd\uc601\uc790\uc640\uc758 \uc2ec\uce35 \uc778\ud130\ubdf0\uc5d0\uc11c \uadf8 \ub2f5\uc744 \ud655\uc778\ud574 \ubcf4\uc138\uc694.CIO \uad00\uc810\uc5d0\uc11c \uc8fc\uc694 \uc870\uc0ac \uacb0\uacfc \ub458\ub7ec\ubcf4\uae30:72%\uac00 AI\uc5d0\uc11c \uac00\uc7a5 \ud070 \ubb38\uc81c\uac00 \ub370\uc774\ud130\ub77c\uace0 \ub2f5\ubcc0, 68%\uac00 \ubd84\uc11d \ubc0f AI\uc758 \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ud1b5\ud569\uc774 \uc911\uc694\ud558\ub2e4\uace0 \ub2f5\ubcc094%\uac00 \uc774\ubbf8 LOB\uc5d0\uc11c AI\ub97c \uc0ac\uc6a9\ud558\uace0 \uc788\ub2e4\uace0 \ub2f5\ubcc0, \uc808\ubc18 \uc774\uc0c1\uc774 2025\ub144\uacbd\uc5d0 AI\uac00 \ubcf4\ud3b8\ud654\ub420 \uac83\uc73c\ub85c \uc608\uc0c172%\uac00 \uba40\ud2f0\ud074\ub77c\uc6b0\ub4dc\uac00 \uc911\uc694\ud558\ub2e4\uace0 \uc0dd\uac01\ud558\uace0 \ub300\ubd80\ubd84\uc774 \uc804\ub7b5\uc801 \uc720\uc5f0\uc131\uc744 \uc720\uc9c0\ud558\uae30 \uc704\ud574 \uac1c\ubc29\uc801 \ud45c\uc900\uc744 \uc9c0\uc9c0\ubcf4\uace0\uc11c \ubc1b\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/the-5-steps-of-hadoop-migration","text":"Step-by-step Guide to Hadoop Migration | DatabricksOn DemandStep-by-Step Guide to Hadoop MigrationAvailable On DemandMigrating from Hadoop to a modern, cloud-based data and AI platform is a priority for more and more organizations. Join this event to learn the 5 key steps for a successful migration:How to ingest data and metadata \u2014 and how to keep that data synchronized until you are ready to EOL your on-premises solutionHow to convert your code from Hive to Apache SparkTMHow to transition your existing security (utilizing systems like Apache Ranger) to online securityHow to administer a unified data and analytics platform to remove the DevOps burdenHow to enable BI and SQL access on your cloud-based platformMigrating to a unified data and analytics platform can save you money immediately. Attendees will receive a detailed framework to help evaluate the cost and impact of migration on your organization \u2014 a great tool to help you make the case for migration.SpeakersRon GuerreroSolutions ArchitectDatabricksPardeep KumarSolutions ArchitectDatabricksMubashir KaziaSolutions ArchitectDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-debrabant","text":"Justin DeBrabant - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin DeBrabantSVP of Product at ActionIQBack to speakersJustin is Senior Vice President of Product at ActionIQ. He spent his formative years building large distributed systems to support data science and analytics and holds a Ph.D. in Databases from Brown University where he researched the forefront of modern data systems. For the last 10+ years, he has been passionate about building data-driven products that help realize the value of customer data by delivering truly customer-centric experiences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sreekanth-ratakonda","text":"Sreekanth Ratakonda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSreekanth RatakondaPrincipal Solutions Architect at LabcorpBack to speakersSreekanth Ratakonda is a principal solutions architect at Labcorp, where he is responsible for building robust Data and Analytics platform and Data products. He has over 15 years of experience in solving complex business challenges in various functional domains utilizing several technologies and frameworks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta SharingAn open standard for secure sharing of data assetsGet StartedWatch DemoDatabricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform.Key benefitsOpen cross-platform sharingAvoid vendor lock-in, and easily share existing data in Delta Lake and Apache Parquet formats to any data platform.Share live data with no replicationShare live data across data platforms, clouds or regions without replicating or copying it to another system.Centralized governanceCentrally manage, govern, audit and track usage of the shared data on one platform.Marketplace for data productsBuild and package data products, including data sets, ML models and notebooks once and distribute anywhere through a central marketplace.Privacy-safe data cleanroomsEasily collaborate with your customers and partners on any cloud via a secure hosted environment while safeguarding data privacy.How it worksNative integration with the Databricks platformNative integration with the\u00a0Unity Catalog\u00a0allows you to centrally manage and audit shared data across organizations. This lets you confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs.Easily manage sharesCreate and manage providers, recipients, and shares with a simple-to-use UI, SQL commands or REST APIs with full CLI and Terraform supportDiscover and access data products through an open marketplaceEasily discover, evaluate and gain access to data products including data sets, machine learning models, dashboards and notebooks from anywhere, without the need to be on the Databricks platform.Privacy-safe data cleanroomsCollaborate with your customers and partners on any cloud in a privacy-safe environment. Securely share data from your data lakes without data replication. Meet collaborators on their preferred cloud and provide them the flexibility to run complex computations and workloads in any language \u2014 SQL, R, Scala, Java and Python. Guide collaborators through common use cases using predefined templates, notebooks and dashboards, accelerating time to insights.Use casesInternal line of business sharingBuild Data Mesh with Delta Sharing to securely share data with business units and subsidiaries across clouds or regions without copying or replicating the data.B2B SharingData monetizationCustomers\u201cDelta Sharing helped us streamline our data delivery process for large data sets. This enables our clients to bring their own compute environment to read fresh curated data with little-to-no integration work, and enables us to continue expanding our catalog of unique, high-quality data products.\u201d\u2014 William Dague, Head of Alternative Data\u201cAs a data company, giving our customers access to our data sets is critical. The Databricks Lakehouse Platform with Delta Sharing really streamlines that process, allowing us to securely reach a much broader user base regardless of cloud or platform.\u201d\u2014 Felix Cheung, VP of Engineering\u201cLeveraging the powerful capabilities of Delta Sharing from Databricks enables Pumpjack Dataworks to have a faster onboarding experience, removing the need for exporting, importing and remodeling of data, which brings immediate value to our clients. Faster results yield greater commercial opportunity for our clients and their partners.\u201d\u2014 Corey Zwart, Head of Engineering\u201cWith Delta Sharing, our clients can access curated data sets nearly instantly and integrate them with analytics tools of their choice. The dialogue with our clients shifts from a low-value, technical back-and-forth on ingestion to a high-value analytical discussion where we drive successful client experiences. As our client relationships evolve, we can seamlessly deliver new data sets and refresh existing ones through Delta Sharing to keep clients appraised of key trends in their industries.\u201d\u2014 Anup Segu, Data Engineering Tech LeadAn open ecosystemAccess the latest published version directly from the provider in easy-to-use SQL, Python or BI tools.ResourcesKeynote and Webinar[Keynote] Data Governance and sharing on the lakehouse at Data + AI Summit 2022[On-demand Webinar] Accelerate Business Value With Delta SharingBlogsAnnouncing General Availability of Delta SharingIntroducing Delta Sharing: An Open Protocol for Secure Data SharingTop Three Data Sharing Use Cases With Delta SharingSolution Sheet & eBook[eBook] Explore the new Delta Sharing SolutionDelta Sharing: An open standard for secure data sharingRise of the Data Lakehouse by Bill Inmon, father of the data warehouseReady to get started with Databricks?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/survival-analysis-for-churn-and-lifetime-value","text":"Survival Analysis for Churn and Lifetime Value | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorSurvival Analysis for Churn and Lifetime ValuePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedPredict churn and calculate lifetime valueSurvival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.Identify which factors contribute most to extending the customer lifecyclePredict which customers are at risk of churningOptimize marketing spend based on the ratio of lifetime value to cost of acquisitionDownload notebookResourcesWebinarWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-bell","text":"Scott Bell - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott BellPrincipal Consultant and Databricks SME at RapidDataBack to speakersScott is currently a Principal Consultant & Databricks SME with RapidData focusing on the Azure Data Platforms, Data Architecture, Integration Engineering and Analytics. Previously, he was a senior consultant and UK&I Databricks SME at Avanade a top global partner with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/04\/05\/announcing-generally-availability-of-databricks-delta-live-tables-dlt.html","text":"Announcing General Availability of Databricks\u2019 Delta Live Tables (DLT) - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing General Availability of Databricks\u2019 Delta Live Tables (DLT)by Michael Armbrust, Awez Syed, Paul Lappas, Erika Ehrli, Sam Steiny, Richard Tomlinson, Andreas Neumann and Mukul MurthyApril 5, 2022 in Platform BlogShare this postToday, we are thrilled to announce that Delta Live Tables (DLT) is generally available (GA) on the Amazon AWS and Microsoft Azure clouds, and publicly available on Google Cloud! In this blog post, we explore how DLT is helping data engineers and analysts in leading companies easily build production-ready streaming or batch pipelines, automatically manage infrastructure at scale, and deliver a new generation of data, analytics, and AI applications.\nCustomers win with simple streaming and batch ETL on the LakehouseProcessing streaming and batch workloads for ETL is a fundamental initiative for analytics, data science and ML workloads \u2013 a trend that is continuing to accelerate given the vast amount of data that organizations are generating. But processing this raw, unstructured data into clean, documented, and trusted information is a critical step before it can be used to drive business insights. We\u2019ve learned from our customers that turning SQL queries into production ETL pipelines typically involves a lot of tedious, complicated operational work. Even at a small scale, the majority of a data engineer\u2019s time is spent on tooling and managing infrastructure rather than transformation. We also learned from our customers that observability and governance were extremely difficult to implement and, as a result, often left out of the solution entirely. This led to spending lots of time on undifferentiated tasks and led to data that was untrustworthy, not reliable, and costly.\nThis is why we built Delta LiveTables, the first ETL framework that uses a simple declarative approach to building reliable data pipelines and automatically managing your infrastructure at scale so data analysts and engineers can spend less time on tooling and focus on getting value from data. DLT allows data engineers and analysts to drastically reduce implementation time by accelerating development and automating complex operational tasks.\nDelta Live Tables is already powering production use cases at leading companies around the globe. From startups to enterprises, over 400 companies including ADP, Shell, H&R Block, Jumbo, Bread Finance, JLL and more have used DLT to power the next generation of self-served analytics and data applications:\nADP: \u201cAt ADP, we are migrating our human resource management data to an integrated data store on the Lakehouse. Delta Live Tables has helped our team build in quality controls, and because of the declarative APIs, support for batch and real-time using only SQL, it has enabled our team to save time and effort in managing our data.\u201d - Jack Berkowitz, Chief Data Officer at ADPAudantic: \u201cOur goal is to continue to leverage machine learning to develop innovative products that expand our reach into new markets and geographies. Databricks is a foundational part of this strategy that will help us get there faster and more efficiently. Delta Live Tables is enabling us to do some things on the scale and performance side that we haven\u2019t been able to do before - with an 86% reduction in time-to-market. We now run our pipelines on a daily basis compared to a weekly or even monthly basis before \u2014 that's an order of magnitude improvement.\u201d - Joel Lowery, Chief Information Officer at AudanticShell: \u201cAt Shell, we are aggregating all our sensor data into an integrated data store. Delta Live Tables has helped our teams save time and effort in managing data at [the multi-trillion-record scale] and continuously improving our AI engineering capability. With this capability augmenting the existing lakehouse architecture, Databricks is disrupting the ETL and data warehouse markets, which is important for companies like ours. We are excited to continue to work with Databricks as an innovation partner.\u201d - Dan Jeavons, General Manager Data Science at ShellBread Finance: \"Delta Live Tables enables collaboration and removes data engineering resource blockers, allowing our analytics and BI teams to self-serve without needing to know Spark or Scala. In fact, one of our data analysts -- with no prior Databricks or Spark experience -- was able to build a DLT pipeline to turn file streams on S3 into usable exploratory datasets within a matter of hours using mostly SQL.\" - Christina Taylor, Senior Data Engineer at Bread FinanceModern software engineering for ETL processingDLT allows analysts and data engineers to easily build production-ready streaming or batch ETL pipelines in SQL and Python. It simplifies ETL development by uniquely capturing a declarative description of the full data pipelines to understand dependencies live and automate away virtually all of the inherent operational complexity. With DLT, engineers can concentrate on delivering data rather than operating and maintaining pipelines, and take advantage of key benefits:\nAccelerate ETL development: Unlike solutions that require you to manually hand-stitch fragments of code to build end-to-end pipelines, DLT makes it possible to declaratively express entire data flows in SQL and Python. In addition, DLT natively enables modern software engineering best practices like the ability to develop in environment(s) separate from production, the ability to easily test it before deploying, deploy and manage environments using parameterization, unit testing and documentation. As a result, you can simplify the development, testing, deployment, operations and monitoring of ETL pipelines with first-class constructs for expressing transformations, CI\/CD, SLAs and quality expectations, and seamlessly handling batch and streaming in a single API.Automatically manage infrastructure: DLT was built from the ground-up to automatically manage your infrastructure and automate complex and time-consuming activities. Sizing clusters for optimal performance given changing, unpredictable data volumes can be challenging and lead to overprovisioning. DLT automatically scales compute to meet performance SLAs by providing the user with the option to set the minimum and maximum number of instances and let DLT size up the cluster according to cluster utilization. In addition, tasks like orchestration, error handling and recovery, and performance optimization are all handled automatically. With DLT, you can focus on data transformation instead of operations.Data confidence: Deliver reliable data with built-in quality controls, testing, monitoring and enforcement to ensure accurate and useful BI, Data Science, and ML. DLT makes it easy to create trusted data sources by including first-class support for data quality management and monitoring tools using a feature called Expectations. Expectations help prevent bad data from flowing into tables, track data quality over time, and provide tools to troubleshoot bad data with granular pipeline observability so you get a high-fidelity lineage diagram of your pipeline, track dependencies, and aggregate data quality metrics across all of your pipelines.Simplified batch and streaming: Provide the freshest\/up-to-date data for apps with data self-optimized and auto-scaling data pipelines for batch or streaming processing and choose optimal cost-performance. Unlike other products that force you to deal with streaming and batch workloads separately, DLT supports any type of data workload with a single API so data engineers and analysts alike can build cloud-scale data pipelines faster and without needing to have advanced data engineering skills.Since the preview launch of DLT, we have enabled several enterprise capabilities and UX improvements. We have extended our UI to make it easier to schedule DLT pipelines, view errors, manage ACLs, improved table lineage visuals, and added a data quality observability UI and metrics. In addition, we have released support for Change Data Capture (CDC) to efficiently and easily capture continually arriving data, as well as launched a preview of Enhanced Auto Scaling that provides superior performance for streaming workloads.\nGet started with Delta Live Tables on the LakehouseWatch the demo below to discover the ease of use of DLT for data engineers and analysts alike:\nTo play this video, click here and accept cookiesIf you already are a Databricks customer, simply follow the guide to get started. Read the release notes to learn more about what\u2019s included in this GA release. If you are not an existing Databricks customer, sign up for a free trial and you can view our detailed DLT Pricing here.\nWhat's nextSign up for our Delta Live Tables Webinar with Michael Armbrust and JLL on April 14th to dive in and learn more about Delta Live Tables at Databricks.com.Try Databricks for freeGet StartedRelated posts5 Steps to Implementing Intelligent Data Pipelines With Delta Live TablesSeptember 8, 2021 by Awez Syed and Amit Kara in Platform Blog\nGet an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake Many IT organizations are...\nAnnouncing the Launch of Delta Live Tables on Google CloudSeptember 2, 2021 by Awez Syed and Sam Steiny in Platform Blog\nToday, we are excited to announce the availability of Delta Live Tables (DLT) on Google Cloud. With this launch, enterprises can now use...\nDatabricks Delta Live Tables Announces Support for Simplified Change Data CaptureFebruary 10, 2022 by Michael Armbrust, Paul Lappas and Amit Kara in Platform Blog\n\u200bAs organizations adopt the data lakehouse architecture, data engineers are looking for efficient ways to capture continually arriving data. Even with the right t...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-karasick","text":"Matthew Karasick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew KarasickChief Product Officer at HabuBack to speakersMatt is passionate about finding ways to use data to achieve the wins that data-powered technology can create between companies and consumers.\nHe has spent his career helping companies do more with data. He has held product leadership positions at DoubleClick, Trilogy, Acerno, Akamai, and most recently at Indeed. After working closely together with Matt Kilmartin at Akamai, Matt (Karasick) worked with the Krux team as a consultant, where he helped create Krux for Marketers.\nMatt believes that, when done correctly and with sustainable mutual value as the measuring stick, interests between consumers and companies are always aligned.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joseph-sarsfield","text":"Joseph Sarsfield - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoseph SarsfieldMachine Learning Engineer at Marks & SpencerBack to speakersJoseph started working for M&S in June 2021 as Senior Machine Learning Engineer. He is interested in building production-ready models at scale that utilize his ML and programming background. Previously he has designed and deployed data quality models for a National Healthcare Service program and worked on human-pose estimation algorithms using depth sensors. He has a Ph.D. in machine learning and enjoys hiking in his spare time.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nitu-nivedita\/#","text":"Nitu Nivedita - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNitu NiveditaManaging Director at AccentureBack to speakersNitu Nivedita is a Managing Director within Accenture\u2019s Applied Intelligence group specializing in Artificial Intelligence, Machine Learning and Cloud Computing for scaling AI. Nitu is also the product and engineering lead for Human.AI (which is portfolio of many AI assets and engineering teams focused on building AI solutions for the Future of Work). In this role, Nitu provides technical leadership for accelerating large-scale digital transformation journeys in client organizations, building enterprise-wide AI solutions that deliver game-changing results and creating sustainable value. Nitu is passionate about technology, business and innovation. She leads a 50+ global solution team of software engineers, data scientists, ML engineers, architects, and product managers to help clients scale AI faster, innovate with cutting-edge multi-cloud technologies and thereby create 360-degree value for our communities \nNitu has a Bachelor\u2019s of Technology (B.Tech) degree in Computer Science Engineering from National Institute of Technology, India. She has an MBA from Cornell University, New York and SDA Bocconi, Italy. She received the \u2018Award of Excellence\u2019 for achieving highest academic excellence during Computer Science Engineering, top of Dean\u2019s list during MBA, and she was the Director of \u2018Girls in Tech\u2019 - a global organization which helps young female professionals and school-aged girls to become interested in technology, coding, and more \nNitu has been a founding member of Accenture's \u201cWomen in AI\u201d forum. She has been awarded and\/or nominated as a finalist for multiple Global AI & Technology Leadership Awards by various global organizations (VentureBeat, Women in AI etc), 2021Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/cloud-partners","text":"Databricks Cloud-Partneranbieter | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks Cloud-PartnerDatabricks Lakehouse l\u00e4uft in jeder gro\u00dfen Public Cloud und ist eng in die Sicherheits-, Rechen-, Speicher-, Analytics- und KI-Services integriert, die von den Cloud-Anbietern bereitgestellt werden. Dadurch erhalten Sie die Flexibilit\u00e4t, die Sie brauchen, um den Cloud-Anbieter Ihrer Wahl zu nutzen, wann und wie Sie es m\u00f6chten.Azure Databricks ist ein gemeinsam entwickelter Erstanbieterservice von Databricks und Microsoft. Beginnen Sie mit einem einzigen Klick im Azure-Portal und integrieren Sie die Sicherheits- und Datenservices von Azure nativ.Mehr InformationenMit Databricks auf AWS k\u00f6nnen Sie alle Ihre S3-Daten auf einer einfachen, offenen Lakehouse-Plattform speichern und verwalten, die das Beste aus Data Warehouses und Data Lakes kombiniert, um alle Ihre Analytics- und KI-Workloads zusammenzuf\u00fchren.Mehr InformationenDatabricks on Google Cloud bringt die offene Lakehouse-Plattform in die Open Cloud, um Data Engineering, Data Science und Analytics zusammenzuf\u00fchren und eine Integration in Google Cloud Storage, BigQuery und die Google Cloud AI Platform zu erm\u00f6glichen.Mehr InformationenCloud-Regionen\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0\u25cfAlibabaProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
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{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=berlin%2C%20germany","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/advertising-marketing","text":"Databricks for Advertising and Marketing TechnologiesSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for Advertising and MarketingDrive intelligent client outcomes and better manage margins with data analytics and AIGet startedSchedule a demoMeet Data Lakehouse: The best of both worlds in one platformA data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It\u2019s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all of your data and cloud platforms.Learn moreWhy Databricks for Advertising and Marketing Technologies?Optimize the entire lifecycle of a campaign\nWith Lakehouse, teams can more effectively understand audience segments for targeting, optimize inventory in real time and track the full lifecycle of an ad.Drive stronger business outcomes through collaboration\nDatabricks\u2019 collaborative workspace means teams can innovate and deploy data and AI solutions faster.Unlock real-time insights\nWith optimized streaming ingest, pre-built offerings with top solution providers, and real-time model serving with MLflow, accelerate consumer and advertiser outcomes for your business.Rapidly innovate on predictive use cases\nDatabricks has a collaborative notebook environment with managed runtime for machine learning models, as well as Solution Accelerators for common use cases including audience segmentation, multitouch attribution, real-time bidding and more.Databricks for Advertising and Marketing Use CasesUse Databricks\u00a0to optimize advertising performance, deliver intelligent client outcomes and improve AI across your marketing tech stack.Agency and ad tech operations\nHelping companies manage margin on work and add data-focused rigor to their operations\nClient profitability\nMargin analysis\nSales forecasting\nTalent retention\nPredictive resource utilization\nMedia performance\nTrack campaign efficacy and channel performance, and leverage recommendations to remediate underperformance\nPlanning and media mix modeling\nMultitouch attribution\nCampaign performance and optimization\nTaxonomy recommendation\nCreative optimization\nUnderstand what creative is resonating during campaign execution and streamline work for creative teams\nA\/B testing\nContent performance\nSEO performance\nCreative workflow optimization\nTransforming Advertising and Marketing With Lakehouse\n\u201cDatabricks is really an important part of our AI strategy. As we continue to digitize our business, and explore opportunities and challenges through AI and machine learning, we will continue to activate Databricks throughout the rest of the business.\u201d\n\u2014 Mainak Mazumdar, Chief Research Officer at NielsenPartners and solutionsMultitouch attributionMeasure ad effectiveness and optimize marketing spend with better channel attributionGet startedSurvival analysis\/LTVPredict which consumers are at risk of churning and what factors extend to consumer lifecycleGet startedPropensity to churnEffectively manage retention, understand lifecycle and reduce your churn rateGet startedBehavioral segmentationCreate advanced segments to drive better purchasing predictions based on behaviorsGet startedSales forecasting and attributionIncrease advertising outcomes by optimizing and focusing on the best-performing channelsGet startedRecommendationsIncrease conversions and engagement with personalized omnichannel recommendationsGet startedComputer vision\/LabelboxAnnotate images and videos to help drive contextual ad targeting in the Lakehouse\n\u00a0\nComing soon\nVideo quality of experienceAnalyze batch and streaming data to ensure a performant streaming content experienceGet startedReal-time biddingLearn how to predict ad viewability in real time to enhance your RTB strategyGet startedSee all solutionsDatabricks for advertising and marketing in actionCustomer StoryDelivering revenue-generating experiences with data and MLLearn moreCustomer TalkExtreme-scale ad tech using Spark and DatabricksLearn moreCustomer TalkHow Adobe does 2 million records per second using Apache Spark\u2122Learn moreResourceseBooks and downloadsData-Driven Innovation in Media & EntertainmentLakehouse for Media & Entertainment Solution SheetThe Big Book of Media & Entertainment Use CasesWebinarsPushing Boundaries: Advanced M&E Case StudiesIntro to Databricks Solution Accelerators for M&ECustomer Lifetime ValuePredicting Churn to Improve Customer RetentionBlogsThe Emergence of the Composable Customer Data PlatformHow DPG Delivers High-Quality and Marketable Segments to AdvertisersReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/beth-mattson\/#","text":"Beth Mattson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeth MattsonSenior Data Engineer at Our Family WizardBack to speakersPragmatic data engineer with a keen interest in data as actionable information, always striving to provide users opportunities for data discovery, creativity, and iteration. Background spans healthcare to software start-ups.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/open-source","text":"Open Source | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWOpen sourceDatabricks engineers are the original creators of some of the world\u2019s most popular open source data technologiesJoin a meetupOur most popular open source projectsApache Spark\u2122Apache Spark is a unified engine for executing data engineering, data science and ML workloads.\nWhat is Apache Spark?\nComparing Spark and Databricks\nVisit spark.apache.org\nDelta LakeDelta Lake lets you build a lakehouse architecture on top of storage systems such as AWS S3, ADLS, GCS and HDFS.\nLearn more about Delta Lake\nVisit delta.io\nTech Talks: Getting Started with Delta Lake\nMLflowMLflow manages the ML lifecycle, including experimentation, reproducibility, deployment and a central model registry.\nManaged MLflow on Databricks\nVisit mlflow.org\nTech Talks: Managing the ML Lifecycle\nRedashRedash enables anyone to leverage SQL to explore, query, visualize, and share data from both big and small data sources.\nVisit Redash on GitHub\nDelta SharingDelta Sharing is the industry\u2019s first open protocol for secure data sharing, making it simple to share data with other organizations.\nVisit Delta Sharing\nDatabricks supports these additional popular open source technologiesTensorFlowDatabricks supports TensorFlow, a library for deep learning and general computation on clusters\nTensorFlow on Databricks\nPyTorch\u2122Facebook, the creator of PyTorch, and Databricks have collaborated on integrations\nPyTorch on Databricks\nKeras\u2122Deep learning API written in Python, running on top of TensorFlow. Available in Databricks Runtime for ML\nKeras on Databricks\nRStudioAn open source suite of tools for collaborative data science using R \u200b\nR programming on big data\nscikit-learnWidely used Python package for machine learning built on top of NumPy, SciPy and Matplotlib\u200b\u200b\nScikit-learn on Databricks\nXGBoostA distributed gradient boosting library that has bindings in languages such as Python, R and C++XGBoost on DatabricksTerraformHashiCorp Terraform is a popular open source tool for creating safe and predictable cloud infrastructure across several cloud providers. Databricks Terraform provider allows customers to manage their entire Databricks workspaces along with the rest of their infrastructure using a flexible, powerful tool. Using Terraform also encourages customers to adopt best practices with infrastructure as code (IaC)Terraform on DatabricksReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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NOW\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u6570\u5343\u4e07\u306e\u672c\u756a\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u304c\u65e5\u3005 Databricks \u4e0a\u3067\u5b9f\u884c\u3055\u308c\u3066\u3044\u307e\u3059\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306f\u3001\u30d0\u30c3\u30c1\uff0f\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3001\u5909\u63db\u3092\u5bb9\u6613\u306b\u3057\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u30a4\u30f3\u30d5\u30e9\u306e\u7ba1\u7406\u3092\u81ea\u52d5\u5316\u3059\u308b\u3053\u3068\u3067\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u672c\u756a\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u307e\u305f\u3001Databricks 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Databricks \u306f\u3001\u3042\u3089\u3086\u308b ETL \u696d\u52d9\u306e\u30ef\u30f3\u30b9\u30c8\u30c3\u30d7\u30b7\u30e7\u30c3\u30d7\u306b\u306a\u308a\u3064\u3064\u3042\u308a\u307e\u3059\u3002\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u6d3b\u7528\u3059\u308c\u3070\u3059\u308b\u307b\u3069\u3001\u30e6\u30fc\u30b6\u30fc\u3001\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u7ba1\u7406\u8005\u306e\u4e21\u65b9\u306e\u8ca0\u62c5\u3092\u524a\u6e1b\u3067\u304d\u307e\u3059\u3002\u300dYipitData \u793e \u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30de\u30cd\u30fc\u30b8\u30e3\u30fc Hillevi Crognale \u6c0f\u4ed5\u7d44\u307f\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u306e\u7c21\u7d20\u5316ETL \u51e6\u7406\u306e\u81ea\u52d5\u5316\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u30a8\u30f3\u30c9\u30c4\u30fc\u30a8\u30f3\u30c9\u306e\u89b3\u5bdf\u30fb\u76e3\u8996\u6b21\u4e16\u4ee3\u306e\u30c7\u30fc\u30bf\u51e6\u7406\u30a8\u30f3\u30b8\u30f3\u30ac\u30d0\u30ca\u30f3\u30b9\u3001\u4fe1\u983c\u6027\u3001\u6027\u80fd\u3092\u652f\u3048\u308b\u57fa\u76e4\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u306e\u7c21\u7d20\u5316\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u30c7\u30fc\u30bf\u3092\u53d6\u308a\u8fbc\u307f\u3001\u5206\u6790\u3001AI\u3001\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3092\u4e00\u5143\u7ba1\u7406\u3067\u304d\u307e\u3059\u3002\u30aa\u30fc\u30c8\u30ed\u30fc\u30c0\u306f\u3001\u30b9\u30b1\u30b8\u30e5\u30fc\u30eb\u3055\u308c\u305f\u30b8\u30e7\u30d6\u3084\u9023\u7d9a\u3057\u305f\u30b8\u30e7\u30d6\u306b\u304a\u3044\u3066\u3001\u30af\u30e9\u30a6\u30c9\u30b9\u30c8\u30ec\u30fc\u30b8\u306b\u30ed\u30fc\u30c9\u3055\u308c\u305f\u30d5\u30a1\u30a4\u30eb\u306b\u5bfe\u3057\u3066\u5897\u5206\u51e6\u7406\u3092\u81ea\u52d5\u3067\u884c\u3044\u307e\u3059\u3002\u30c7\u30fc\u30bf\u306e\u72b6\u614b\u306b\u3064\u3044\u3066\u306e\u8a73\u7d30\u3092\u624b\u52d5\u3067\u7ba1\u7406\u3059\u308b\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u6570\u5341\u5104\u898f\u6a21\u306e\u65b0\u3057\u3044\u30d5\u30a1\u30a4\u30eb\u3067\u3082\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u30ea\u30b9\u30c8\u3059\u308b\u3053\u3068\u306a\u304f\u52b9\u7387\u7684\u306b\u8ffd\u8de1\u3057\u3001\u30bd\u30fc\u30b9\u30c7\u30fc\u30bf\u304b\u3089\u30b9\u30ad\u30fc\u30de\u3092\u81ea\u52d5\u7684\u306b\u63a8\u6e2c\u3057\u3001\u6642\u9593\u306e\u7d4c\u904e\u3068\u3068\u3082\u306b\u30b9\u30ad\u30fc\u30de\u3092\u9032\u5316\u3055\u305b\u308b\u3053\u3068\u3082\u53ef\u80fd\u3067\u3059\u3002\u30a2\u30ca\u30ea\u30b9\u30c8\u306f COPY INTO \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001SQL \u3092\u4ecb\u3057\u3066 Delta Lake \u3078\u306e\u30d0\u30c3\u30c1\u30d5\u30a1\u30a4\u30eb\u306e\u53d6\u308a\u8fbc\u307f\u3092\u5bb9\u6613\u306b\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002\u300c\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u751f\u7523\u6027\u304c 40% \u5411\u4e0a\u3057\u307e\u3057\u305f\u3002\u65b0\u3057\u3044\u0000\u0000\u30a2\u30a4\u30c7\u30a2\u306e\u958b\u767a\u306b\u304b\u304b\u308b\u6642\u9593\u3092\u6570\u65e5\u304b\u3089\u6570\u5206\u306b\u77ed\u7e2e\u3057\u3001\u30c7\u30fc\u30bf\u306e\u53ef\u7528\u6027\u3068\u7cbe\u5ea6\u304c\u9ad8\u307e\u3063\u3066\u3044\u307e\u3059\u3002\u300dGousto \u793e\u00a0\u6700\u9ad8\u6280\u8853\u8cac\u4efb\u8005 Shaun Pearce \u6c0f\u8a73\u3057\u304f\u898b\u308bETL \u51e6\u7406\u306e\u81ea\u52d5\u5316\u53d6\u308a\u8fbc\u3093\u3060\u672a\u52a0\u5de5\u30c7\u30fc\u30bf\u306f\u3001\u5206\u6790\u3084 AI \u306b\u5229\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002Databricks \u306f\u3001Delta Live Tables\uff08DLT\uff09\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3001\u30a2\u30ca\u30ea\u30b9\u30c8\u306b\u5f37\u529b\u306a ETL \u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002DLT \u306f\u3001\u30d0\u30c3\u30c1\u30c7\u30fc\u30bf\u3084\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u306b ETL \u304a\u3088\u3073 ML \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u69cb\u7bc9\u3059\u308b\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u4f7f\u7528\u3057\u305f\u521d\u306e ETL \u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3059\u3002\u30a4\u30f3\u30d5\u30e9\u7ba1\u7406\u3001\u30bf\u30b9\u30af\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3001\u30a8\u30e9\u30fc\u51e6\u7406\u3084\u30ea\u30ab\u30d0\u30ea\u3001\u6027\u80fd\u306e\u6700\u9069\u5316\u3068\u3044\u3063\u305f\u8907\u96d1\u306a\u904b\u7528\u30bf\u30b9\u30af\u3092\u81ea\u52d5\u5316\u3057\u307e\u3059\u3002\u30a8\u30f3\u30b8\u30cb\u30a2\u306f DLT \u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u3092\u30b3\u30fc\u30c9\u3068\u3057\u3066\u6271\u3046\u3053\u3068\u304c\u3067\u304d\u3001\u30c6\u30b9\u30c8\u3001\u76e3\u8996\u3001\u6587\u66f8\u5316\u306a\u3069\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u9069\u7528\u3057\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u5927\u898f\u6a21\u306b\u5c55\u958b\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3Databricks Workflows \u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u30cd\u30a4\u30c6\u30a3\u30d6\u3067\u3001\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306b\u5bfe\u5fdc\u3059\u308b\u30d5\u30eb\u30de\u30cd\u30fc\u30b8\u30c9\u578b\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u30b5\u30fc\u30d3\u30b9\u3067\u3059\u3002Delta Live Tables \u3068\u3001\u30b8\u30e7\u30d6\u306e SQL\u3001Spark\u3001\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u3001dbt\u3001ML \u30e2\u30c7\u30eb\u306a\u3069\u3092\u542b\u3080\u591a\u69d8\u306a\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306e\u30d5\u30eb\u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u57fa\u76e4\u3068\u306a\u308b\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3068\u306e\u7dca\u5bc6\u306a\u7d71\u5408\u306b\u3088\u308a\u3001\u4e3b\u8981\u306a\u30af\u30e9\u30a6\u30c9\u4e0a\u3067\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u4f5c\u6210\u3057\u3066\u5b9f\u884c\u3059\u308b\u3068\u540c\u6642\u306b\u3001\u30a8\u30f3\u30c9\u30e6\u30fc\u30b6\u30fc\u306b\u30b7\u30f3\u30d7\u30eb\u3067\u8a73\u7d30\u306a\u4e00\u5143\u5316\u3055\u308c\u305f\u76e3\u8996\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u300c\u79c1\u305f\u3061\u306e\u4f7f\u547d\u306f\u3001\u5730\u7403\u306b\u96fb\u529b\u3092\u4f9b\u7d66\u3059\u308b\u65b9\u6cd5\u3092\u5909\u9769\u3059\u308b\u3053\u3068\u3067\u3059\u3002\u30a8\u30cd\u30eb\u30ae\u30fc\u5206\u91ce\u306e\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u306f\u3001\u305d\u306e\u5909\u9769\u3092\u9054\u6210\u3059\u308b\u305f\u3081\u306b\u30c7\u30fc\u30bf\u3001\u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30b5\u30fc\u30d3\u30b9\u3001\u8abf\u67fb\u0000\u0000\u3092\u5fc5\u8981\u3068\u3057\u3066\u3044\u307e\u3059\u3002Databricks \u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306f\u3001\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u304c\u5fc5\u8981\u3068\u3059\u308b\u5206\u6790\u60c5\u5831\u3092\u63d0\u4f9b\u3059\u308b\u30b9\u30d4\u30fc\u30c9\u3068\u67d4\u8edf\u6027\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u300d\u30a6\u30c3\u30c9\u30de\u30c3\u30b1\u30f3\u30b8\u30fc\u793e\u00a0\u30c7\u30fc\u30bf\u90e8\u9580 VP Yanyan Wu \u6c0f\u8a73\u3057\u304f\u898b\u308b\u30a8\u30f3\u30c9\u30c4\u30fc\u30a8\u30f3\u30c9\u306e\u89b3\u5bdf\u30fb\u76e3\u8996\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u3088\u3063\u3066\u3001\u30c7\u30fc\u30bf\u3068 AI 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\u3084\u52d5\u753b\u306a\u3069\u306e\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u304c\u898b\u3064\u304b\u308a\u307e\u3059\u3002\n\u8a73\u3057\u304f\u898b\u308beBook\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u69cb\u7bc9\uff08\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u63d0\u5531\u8005 Bill Inmon \u8457\uff09\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u30ac\u30d0\u30ca\u30f3\u30b9Data Management 101\uff08\u30c7\u30fc\u30bf\u7ba1\u7406\u306e\u57fa\u790e\uff09\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30afeBook\uff1a\u65b0\u3057\u3044 Delta Sharing \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u306e\u8a73\u7d30\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u304b\u3089\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3078\u306e\u79fb\u884c \u2015 \"For Dummies\" \u30b7\u30ea\u30fc\u30ba\u30a4\u30d9\u30f3\u30c8Delta Live Tables \u3092\u6d3b\u7528\u3057\u305f\u30c7\u30fc\u30bf\u5909\u63db\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u3092\u7c21\u5358\u306b\u3059\u308b\u65b9\u6cd5DATA + AI SUMMIT 2022\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3092\u30e2\u30c0\u30ca\u30a4\u30ba\u30d6\u30ed\u30b0Delta Live Tables \u306e\u4e00\u822c\u63d0\u4f9b\u958b\u59cb\u3092\u767a\u8868Databricks Workflows \u306e\u3054\u7d39\u4ecbDatabricks \u3068 Apache Spark \u5411\u3051 2021 \u5e74\u306b\u958b\u767a\u3055\u308c\u305f\u69cb\u9020\u5316\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u65b0\u6a5f\u80fd\u306e\u6982\u8981Databricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u304a\u3051\u308b\u534a\u69cb\u9020\u5316\u30c7\u30fc\u30bf\u306e\u7ba1\u7406\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3059\u308b 10 \u306e\u5f37\u529b\u306a\u6a5f\u80fd\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u306b\u53c2\u52a0\u3059\u308bAWSAzureGCP\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/it\/partnerconnect","text":"Partner Connect | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPartner ConnectScopri e integra facilmente soluzioni per dati, analisi e AI con il lakehouseGuarda le demoPartner Connect aiuta a scoprire strumenti di gestione e analisi dei dati e di AI sulla piattaforma Databricks, integrandoli velocemente con gli strumenti gi\u00e0 in uso. Con Partner Connect, per l'integrazione di nuovi strumenti bastano pochi clic e le funzionalit\u00e0 del lakehouse possono essere ampliate velocemente.Collegare al lakehouse gli strumenti per la gestione di dati e AIConnetti facilmente i tuoi strumenti preferiti per dati e AI al lakehouse e alimenta qualsiasi caso d'uso di analisiSoluzioni validate per dati e AI per nuovi casi d'usoUn portale unico con le soluzioni validate di aziende partner per costruire pi\u00f9 velocemente le prossime applicazioni di gestione dei datiImpostazione in pochi clic con integrazioni predefinitePartner Connect semplifica le integrazioni configurando automaticamente le risorse (inclusi cluster, token e file di connessione) per la connessione con le soluzioni dei nostri partnerPrimi passi come partnerI partner di Databricks sono in una posizione unica per offrire ai clienti analisi approfondite pi\u00f9 velocemente. Sfrutta le risorse di sviluppo e le partnership di Databricks per crescere insieme alla nostra piattaforma aperta in cloud.Diventa partner\u201cSfruttando la nostra partnership di lunga data, Partner Connect ci consente di sviluppare un'esperienza integrata fra le nostre aziende e i clienti. Con Partner Connect, offriamo un'esperienza ottimizzata che semplifica pi\u00f9 che mai la vita alle migliaia di clienti di Databricks, sia coloro che gi\u00e0 utilizzano Fivetran, sia coloro che ci scoprono tramite Partner Connect, per estrapolare informazioni dai loro dati, scoprire nuovi casi d'uso dell'analisi ed estrarre valore dal loro lakehouse pi\u00f9 velocemente, collegando con facilit\u00e0 centinaia di sorgenti di dati al lakehouse\u201d.\u2014 George Fraser, CEO di FivetranDemofivetranConnettere dati da oltre 180 app popolari, incluse app SaaS (Salesforce, Google Analytics ecc.) all'interno del lakehousedbtPrimi passi con dbt Cloud e Databricks per la trasformazione dei datiPower BIPorta i vantaggi delle prestazioni e della tecnologia Databricks Lakehouse a tutti gli utentitableauMetti a disposizione di tutti gli utenti un data lakehouse per analisi moderne collegando Tableau Desktop a Databricks SQLRiverySemplifica il percorso dei dati dall'acquisizione alla trasformazione, fino al trasferimento in Delta LakeLabelboxPrepara facilmente dati non strutturati per AI e analisi nel lakehouseProphecyCostruire e implementare pipeline Spark e Delta utilizzando un'interfaccia visuale drag-and-dropArcioneConnetti le sorgenti di dati al lakehouse con una piattaforma di replica distribuita basata su CDCProva gratuitaRisorseBlogFeb 2023 - Annuncio di nuove integrazioni per i partner in Partner Connect2022 settembre - Introduzione di nuove integrazioni per i partner in Partner ConnectGiugno 2022 - Annuncio di nuove integrazioni per i partner in Partner ConnectSviluppa la tua attivit\u00e0 su Databricks con Partner ConnectDocumentazioneGuida a Partner Connect di DatabricksPronto per saperne di pi\u00f9?Sfrutta le risorse di sviluppo e le partnership di Databricks per crescere insieme alla nostra piattaforma aperta in cloud.Diventa partnerContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jules-damji","text":"Jules Damji - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJules DamjiLead Developer Advocate at AnyscaleBack to speakersJules S. Damji is a lead developer advocate at Anyscale Inc, an MLflow contributor, and co-author of Learning Spark, 2nd Edition. He is a hands-on developer with over 25 years of experience and has worked at leading companies, such as Sun Microsystems, Netscape, @Home, Opsware\/LoudCloud, VeriSign, ProQuest, Hortonworks, and Databricks, building large-scale distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/reynold-xin","text":"Reynold Xin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingReynold XinCo-founder and Chief Architect at DatabricksBack to speakersReynold is an Apache Spark\u2122 PMC member and the top contributor to the project. He initiated and led efforts such as DataFrames and Project Tungsten. He is also a co-founder and Chief Architect at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-neo","text":"Jonathan Neo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan NeoData Engineer at CanvaBack to speakersJonathan is a Data Engineer at Canva where he is building data platforms that scale for petabytes of data and hundreds of internal users. Prior to Canva, he has spent the last 5 years building a dozen data platforms for ASX-listed enterprises, and startups. Jonathan is also the Founder of Data Engineer Camp, a 16 week intensive bootcamp to cultivate the next generation of data engineers, with students working at companies like Microsoft, Tencent, and Fidelity International.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vika-smilansky\/#","text":"Vika Smilansky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVika SmilanskyDirector of Product Marketing at ThoughtSpotBack to speakersVika is a Director of Product Marketing at ThoughtSpot, leading customer marketing as well as messaging and positioning for ThoughtSpot\u2019s embedded analytics platform, ThoughtSpot Everywhere. Before joining Thoughtspot in 2019, she worked in Product Marketing on data integration solutions at Oracle. Vika holds a Master in Communication Management from the University of Southern California.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/audience\/digital-native","text":"Digital-Native-Unternehmen und -Anwendungen | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse f\u00fcr Unternehmen, die in der Cloud geboren wurdenSchnellere Entwicklung und Skalierung von Daten-, Analytics- und KI-Funktionen auf einer leistungsstarken Datenplattform\nErste SchritteDemos ansehenJe schneller Sie wachsen, desto komplexer werden Ihre Daten. Schnellere Innovationen auf der Databricks Lakehouse-Plattform \u2013 ein einfacher, kosteneffizienter Ansatz f\u00fcr Daten, Analysen und KI, der Tausende von digital nativen Unternehmen und Start-ups produktiver macht.Innovation mit Open-Source-Flexibilit\u00e4t\nNutzen Sie Ihre Daten doch, wie und wo Sie wollen \u2013 ganz ohne Anbieterbindung. Daf\u00fcr haben die Entwickler von Apache Spark\u2122 ein Lakehouse geschaffen, das offene Formate und APIs unterst\u00fctzt.\nOpen-Source-Projekte anzeigenSkalierbare Daten-Workloads aufbauen\nSorgen Sie f\u00fcr rasante und zuverl\u00e4ssige Leistung bei ETL-Workloads \u2013 f\u00fcr Streaming und Batch-Daten. W\u00e4hrenddessen verwaltet Databricks Ihre Infrastruktur automatisch.\nData Engineering anzeigenSchneller auf Daten zugreifen\nAlle Daten erfassen, transformieren und abfragen \u2013 komplett von zentraler Stelle aus. Schluss mit dem Verwalten von Servern \u2013 bei Bedarf skalieren Sie eben per Serverless. Bis zu 12\u00a0Mal besseres Preis-Leistungs-Verh\u00e4ltnis.\nDatabricks SQL anzeigenNext-Gen-Apps mit ML entwickeln\nBeschleunigen Sie den ML-Lebenszyklus vom Experiment bis zur Produktion. Steigern Sie die Produktivit\u00e4t mit Tools wie kollaborativen Notebooks, MLflow und MLOps.\nML-Funktionen anzeigenErste Schritte mit DatabricksDatabricks testen\nStarten Sie Ihre 14-t\u00e4gige kostenlose Testversion mit Databricks on AWS in wenigen einfachen Schritten. Suchen und finden Sie Ressourcen f\u00fcr sich und Ihr gesamtes Datenteam.\nJetzt kostenfrei testenKompetenzen entwickeln\nAbsolvieren Sie auf Ihre Bed\u00fcrfnisse zugeschnittene Schulungen und Zertifizierungen, einschlie\u00dflich Data Analytics, Data Engineering, Data Science und Machine Learning.\nSchulungen abrufenKosten optimieren\nMit einem verwalteten Dienst k\u00f6nnen Sie die Infrastrukturkosten um bis zu 40\u00a0% senken und gleichzeitig Ihre Produktivit\u00e4t steigern. Informieren Sie sich \u00fcber unsere nutzungsbasierte Abrechnung und die erm\u00e4\u00dfigten Tarife.\nPreise anzeigenTechnischer Support\nMit unseren Databricks-Experten erhalten Sie notwendige Antworten schneller. Au\u00dferdem k\u00f6nnen Sie Ihre Datenl\u00f6sung mit unseren Selfservice-Notebooks im Handumdrehen entwickeln.\nNotebooks anzeigenAufbauprogrammeErstellen Sie Ihre datengesteuerten Anwendungen auf dem Lakehouse und beschleunigen Sie Ihr Gesch\u00e4ftswachstum mit DatabricksDatabricks f\u00fcr StartupsStarten Sie schnell mit dem Startprogramm. Erfahren Sie, wie Sie kostenlose Guthaben, Expertenratschl\u00e4ge und Unterst\u00fctzung bei der Markteinf\u00fchrung erhalten.Mehr InformationenAufbaupartner\u00a0Werden Sie ein integrierter Partner, um Zugang zu technischen, Markteinf\u00fchrungs- und Co-Marketing-Vorteilen zu erhalten, mit denen Sie Ihre Reichweite vergr\u00f6\u00dfern und Ihr Gesch\u00e4ft ausbauen k\u00f6nnen.Mehr InformationenUnternehmen der n\u00e4chsten Generation, die auf Databricks setzenL\u00f6sungsarchitekturen f\u00fcr Digital-Native-UnternehmenLeistungsstarke, skalierbare ETL-PipelinesErstellen Sie eine konsistente Data-Engineering- und ETL-Plattform, um sich in jeder Cloud ganz der Gewinnung wertvoller Erkenntnisse zu widmen. Nie wieder Pipelines entwickeln und warten, nie wieder ETL-Workloads ausf\u00fchren.Nutzen Sie produktionsfertige Tools wie Delta Live Tables, Unity Catalog und Workflows.Genie\u00dfen Sie robuste Git-Integration, Orchestrierung und Datenqualit\u00e4tskontrollen.Vereinheitlichen Sie Batch- und Streaming-Operationen in einer vereinfachten Architektur und optimieren Sie Entwicklung und Tests von Daten-Pipelines.Gew\u00e4hrleisten Sie h\u00f6chste Datenqualit\u00e4t und verbessertes Data Skipping mit Delta Lake \u2013 einem Open-Source-Dateiprotokoll, das von Apache Spark, Trino, Presto, Flink u.\u00a0a. verwendet werden kann.Erste SchritteSQL-Analytics und Data WarehousingDaten erfassen, transformieren und abfragen von zentraler Stelle aus \u2013 so gewinnen Sie im Nu gesch\u00e4ftliche Echtzeiterkenntnisse.F\u00fchren Sie auch umfangreichste SQL- und BI-Anwendungen aus \u2013 mit einem bis zu 12\u00a0Mal besseren Preis-Leistungs-Verh\u00e4ltnis. Au\u00dferdem garantieren Sie so Data Governance und Sicherheit.Bew\u00e4ltigen Sie High Concurrency mit vollst\u00e4ndig verwaltetem Load Balancing und Skalierung der Compute-Ressourcen.Nutzen Sie offene Formate und APIs sowie Erfassung, Transformation und BI-Tools nach Wahl mit ma\u00dfgeschneiderten Konnektoren.Reduzieren Sie den Aufwand f\u00fcr das Ressourcenmanagement mit Serverless Compute.Erste SchritteInnovatives Machine LearningBeschleunigen Sie ML und Data Science durch Ausbau von Produktivit\u00e4t und Kollaboration im Lakehouse.Nutzen Sie Tools und Optionen f\u00fcr die Zusammenarbeit mit Glass-Box-AutoML.Mit einem gehosteten Feature Store k\u00f6nnen Sie Daten und Funktionen im Self-Service vorbereiten, verarbeiten und verwalten und auch Ihre Modelle managen.Standardisieren Sie den ML-Lebenszyklus vom Experiment bis zur Produktion mithilfe von MLflow, um Modellparameter, Metriken und Iterationen im zeitlichen Verlauf zu beobachten.Stellen Sie Modelle im Batch oder mit Serverless-Echtzeit-REST-Endpoints bereit.Erste SchritteTechnologiepartner\nEntdecken und integrieren Sie Ihre Lieblingsdaten und KI-Tools und -Dienste direkt auf der Databricks-Plattform.\nPartner Connect erkundenBranchenl\u00f6sungenNext-Generation-Branchenf\u00fchrer entwickeln Datenanalyse- und KI-L\u00f6sungen mit DatabricksL\u00f6sungen nach Branche erkundenEinzelhandel und Konsumg\u00fcter\nF\u00f6rdern Sie Echtzeitentscheidungen und verbessern Sie das Kundenerlebnis.\nMehr InformationenFinanzdienstleistungen\nMachen Sie Ihre daten- und KI-gesteuerten Finanzdienstleistungen fit f\u00fcr die Zukunft.\nMehr InformationenGaming\nNutzen Sie die Leistungsst\u00e4rke von Daten und KI, um Spielerlebnisse auf einem noch nie dagewesenen Niveau zu erschlie\u00dfen.\nMehr InformationenKommunikation, Medien und Unterhaltung\u00a0\nErstellen Sie daten- und KI-gest\u00fctzte Medien f\u00fcr ein Benutzererlebnis in beispielloser Qualit\u00e4t.\nMehr InformationenTechnologie und Software\nEntwickeln Sie L\u00f6sungen der n\u00e4chsten Generation mit erweiterten Daten- und ML-Funktionen.\nMehr InformationenTechnologie im Gesundheitswesen\nMit der Leistungsf\u00e4higkeit von Daten und KI erzielen Sie bessere Ergebnisse f\u00fcr Ihre Patienten.\nMehr InformationenTechnischer LeitfadenL\u00f6sung gemeinsamer DatenherausforderungenF\u00fcr Startups und Digital NativesErfahren Sie, wie Sie Datenanwendungsf\u00e4lle bei der Skalierung unterst\u00fctzen und gleichzeitig die Kosteneffizienz und Produktivit\u00e4t steigern k\u00f6nnen. Sie profitieren von Architekturdiagrammen, Schritt-f\u00fcr-Schritt-L\u00f6sungen und Schnellstartanleitungen. Sie finden auch Anwendungsf\u00e4lle aus der Praxis von f\u00fchrenden Unternehmen wie Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable und Zipline.Holen Sie sich Ihr ExemplarRessourcenE-BooksWas ist ein Lakehouse?Das gro\u00dfe Buch des Data EngineeringDas Big Book der Machine-Learning-Anwendungsf\u00e4lleDer ultimative Leitfaden zu Delta LakeDelta Lake \u2013 die Grundlage f\u00fcr unser LakehouseDas gro\u00dfe Buch der MLOpsDatenteam-Leitfaden zur Databricks Lakehouse-PlattformSchnellstart-Leitf\u00e4denETL-Workloads ausf\u00fchrenDatenpipelines mit Delta Live TablesSQL-Leitfaden: Querys und DashboardsData Science-SchnellstartMachine Learning-SchnellstartBlogsAnk\u00fcndigungenOpen-SourceBranchenerkenntnisseL\u00f6sungenM\u00f6chten Sie loslegen?Kostenlose Testversion abrufenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pravin-darbare","text":"Pravin Darbare - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPravin DarbareVice President of Data Analytics at WorkdayBack to speakersComing soonLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/shell","text":"Customer Story: Shell | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYDelivering innovative energy solutions for a cleaner worldMillionsof dollars saved in potential engine repair costs250Data team members supporting 160+ high-value use cases9xFaster \u2013 5 minutes to validate a label reduced from 45 minutesRead storyWatch video INDUSTRY: Energy and utilities SOLUTION: Data-driven ESG,demand forecasting,predictive maintenance,safety stock analysis,threat detection PLATFORM USE CASE: Lakehouse,Delta Lake,data science,machine learning,ETL,Databricks SQL CLOUD: Azure\u201cThe usage of Databricks over the years has broadened significantly. We started out using Databricks as a big data and AI platform but the scope has broadened. We have an entirely different class of citizen engineers and data scientists who are using it as a modern business intelligence tool to make smarter business decisions.\u201d\n\u2014 Daniel Jeavons, General Manager \u2013 Advanced Analytics CoE, ShellShell has been at the forefront of creating a cleaner tomorrow by investing in digital technologies to tackle climate change and become a net-zero emissions energy business. Across the business, they are turning to data and AI to improve operational efficiencies, drive customer engagement, and tap into new innovations like renewable energy. Hampered by large volumes of data, Shell chose Databricks to be one of the foundational components of its Shell.ai platform. Today, Databricks empowers hundreds of Shell\u2019s engineers, scientists and analysts to innovate together as part of their ambition to deliver cleaner energy solutions more rapidly and efficiently.The challenges of extracting insights at scaleThroughout its 100-plus-year history, Shell has generated pioneering ideas that have influenced the way we consume energy.\u201cWe, as an industry, are going through a massive transition,\u201d explained Dan Jeavons, GM of data science at Shell. \u0000\u0000\u201cDigital technology is absolutely core to making our existing business more effective and efficient. As the industry continues to expand into new areas of energy that are more sustainable and reduce environmental impact, data and digital technology are now table stakes.\u201dWhile digital transformation is a primary initiative for every energy company, challenges remain with legacy technology infrastructure, the complexities of an exponential growth in data, and the lack of data engineering and science skills needed to build data-powered solutions.Shell has met these challenges head-on by creating a Data Science Centre of Excellence (CoE), where teams continually work to identify the highest value use cases across the entire value chain. However, although they were identifying opportunities to innovate with data, Shell had the challenge to scale its data infrastructure for analytics, big data processing and machine learning.Unifying data and AI across the enterprise to fuel innovationShell chose the Databricks Lakehouse Platform as one of the key tools within the Shell.ai Platform. Databricks provides Shell\u2019s data team with a scalable, fully managed platform that unifies all their data, analytics and AI workloads. The interactive workspace has not only democratized access to data but has fostered cross-team collaboration across data engineering, data science and the analyst team.\u201cShell has been undergoing a digital transformation as part of our ambition to deliver more and cleaner energy solutions. As part of this, we have been investing heavily in our data lake architecture. Our ambition has been to enable our data teams to rapidly query our massive datasets in the simplest possible way. The ability to execute rapid queries on petabyte scale datasets using standard BI tools is a game changer for us. Our co-innovation approach with Databricks has allowed us to influence the product roadmap and we are excited to see this come to market,\u201d said Dan.This low barrier of entry has opened up analytics beyond machine learning, including business intelligence and reporting. In fact, Shell\u2019s focus on data and analytics has enabled over 250 data analysts (or citizen data scientists), and 800 citizen data scientists to be more productive with all the data available to them.Transforming Shell into the energy company of the futureShell\u2019s CoE is now able to explore and deploy new data-driven solutions focused on improving supply chain operations as well as unlocking high-valued use cases that bring to life differentiated capabilities for their customers and their own businesses.From an operations perspective, one of the biggest challenges any major industrial company faces is efficiently managing its inventory and supply chain. Shell stocks thousands of spare parts across its global facilities, and its inventory analysts were struggling to understand what level of spare parts they should hold in their warehouses. With Databricks, Shell was able to leverage its full historic data set to run 10,000+ inventory simulations across all its parts and facilities. Shell\u2019s inventory prediction models now run in 45 minutes \u2014 down from 48 hours \u2014 significantly improving stocking practices and saving a lot of money annually.Shell has also developed a recommendation engine for its new loyalty program called Go+ used by 1.5 million customers. Running on Azure and Databricks, the AI software can look at the full transaction history of a customer and use the information to tailor the offers and rewards to the preferences of the individual, combining their data with other aggregated data.Data and AI have also unlocked new opportunities for Shell to engage with customers. Shell Remote Sense is a new initiative focused on optimizing the durability and performance of large-scale engines on ships and cruise liners. Shell processes over 750,000 lubricant samples per annum and delivers customer insights about lube oil quality and how it\u2019s performing. This not only saves customers potentially millions of dollars in the cost of repair or engine downtime, but Shell also saves significantly on time and operational costs.A data-driven culture that delivers resultsToday Shell is redefining its boundaries of the oil and gas industry through data and AI. With Databricks as a key component of the Shell.ai platform, Shell is able to run data analytics and deploy machine learning models that improve operational efficiencies.Using a common platform has empowered engineers, data scientists and analysts to be more agile, collaborative and data driven. Shell currently has over 160 AI projects running, and it\u2019s only just getting started. In the coming years, Shell aims to make leaps in technological advancements powered by data and AI \u2014 from trillions of IoT sensors all generating data to 3-D printed equipment and parts that will disrupt the global supply chain and greatly reduce costs\u2014 and Databricks is a key part of the Shell.ai platform that will make this a reality.Related ContentCase StudyETL and Data Lake with Delta Live TablesVideoAI and Sustainability 2021 Web Summit PanelArticleCIO Magazine: Shell sees AI as fuel for its sustainability goalsReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-lai","text":"Justin Lai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin LaiDistinguished Data Architect at BlackBerryBack to speakersJustin is Software Architect at BlackBerry for over 12 years and have experience working in many areas ranging from low level network stack on BlackBerry Devices, Android application development, to Cloud Data engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stephen-shelton","text":"Stephen Shelton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStephen SheltonVice President, Business Intelligence at Pluto TVBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rashmi-kansakar\/#","text":"Rashmi Kansakar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRashmi KansakarDirector, Data & Cloud Architect at 84.51Back to speakersAs Director of Data & Cloud Architect at 84.51\u02da, Rashmi is responsible for designing next-generation data solutions focusing on identifying needs and opportunities to elevate & harmonize data into valuable data assets. He helps to build scalable technology to drive insights and science to understand Kroger\u2019s customers better and improve the shopping experience. Rashmi is as an Adjunct Professor at the University of Cincinnati, where he shares his knowledge and expertise with the next generation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/data-engineering","text":"\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub9e4\uc77c \uc218\ucc9c \ub9cc \uac1c\uc758 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ub85c\ub4dc\uac00 Databricks\uc5d0\uc11c \uc2e4\ud589\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uc218\uc9d1\ud558\uace0 \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks\uc5d0\uac8c \uc778\ud504\ub77c\uc758 \ub300\uaddc\ubaa8 \uc790\ub3d9 \uad00\ub9ac\ub97c \ub9e1\uae30\uace0 \uc548\uc815\uc801\uc778 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c\ub97c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud558\uc138\uc694. \uae30\ubcf8 \ub370\uc774\ud130 \ud488\uc9c8 \ud14c\uc2a4\ud2b8 \uae30\ub2a5\uacfc \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uac1c\ubc1c \ubaa8\ubc94 \uc0ac\ub840 \uc9c0\uc6d0\uc73c\ub85c \ud300 \uc0dd\uc0b0\uc131\uc744 \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ubc30\uce58\uc640 \uc2a4\ud2b8\ub9ac\ubc0d \ud1b5\ud569\ud558\ub098\uc758 \ud1b5\ud569 API\ub97c \uc0ac\uc6a9\ud558\ub294 \ub2e8\uc77c \ud50c\ub7ab\ud3fc\uc744 \ud1b5\ud574 \uc0ac\uc77c\ub85c\ub97c \uc81c\uac70\ud558\uace0 \ub300\uaddc\ubaa8\ub85c \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uc218\uc9d1, \ubcc0\ud658 \ubc0f \uc99d\ubd84 \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \uac00\uce58 \ucc3d\ucd9c\uc5d0 \uc9d1\uc911Databricks\uac00 \uc778\ud504\ub77c\uc640 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c\uc758 \uc6b4\uc601 \ubd80\ubb38\uc744 \uc790\ub3d9\uc73c\ub85c \uad00\ub9ac\ud558\ubbc0\ub85c \uace0\uac1d\uc740 \ud234\ub9c1\uc774 \uc544\ub2c8\ub77c \uac00\uce58 \ucc3d\ucd9c\uc5d0 \uc9d1\uc911\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \ub3c4\uad6c\uc640 \uc5f0\uacb0\uac1c\ubc29\uc801 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130 \uc218\uc9d1, ETL\/ELT, \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc5d0 \uc0ac\uc6a9\ud558\uace0 \uc2f6\uc740 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ub3c4\uad6c\ub97c \uc5f0\uacb0\ud558\uace0 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc \uae30\ubc18\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \uc790\uc0b0\uc744 \uad6c\ucd95 \ubc0f \uacf5\uc720\ud558\ub294 \ub370 \uac00\uc7a5 \uc801\uc808\ud55c \uae30\ubc18\uc744 \uc81c\uacf5\ud558\uba70, \uc774\ub7ec\ud55c \ub370\uc774\ud130 \uc790\uc0b0\uc740 \uc911\uc559\uc5d0\uc11c \uad00\ub9ac\ud558\uace0 \uc548\uc815\uc801\uc774\uba74\uc11c\ub3c4 \ub9e4\uc6b0 \ube60\ub978 \uc18d\ub3c4\ub97c \uc790\ub791\ud569\ub2c8\ub2e4.\u201c\uc6b0\ub9ac\uc5d0\uac8c Databricks\ub294 \ubaa8\ub4e0 ETL \uc791\uc5c5\uc744 \ucc98\ub9ac\ud558\ub294 \uc6d0\uc2a4\ud1b1 \uc0f5\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \ub9ce\uc774 \uc0ac\uc6a9\ud560\uc218\ub85d \uc0ac\uc6a9\uc790\uc640 \ud50c\ub7ab\ud3fc \uad00\ub9ac\uc790 \ubaa8\ub450\uc5d0\uac8c \ud6e8\uc52c \ud3b8\ub9ac\ud574\uc9d1\ub2c8\ub2e4.\u201d\u2014 Hillevi Crognale, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uad00\ub9ac\uc790, YipitData\uc5b4\ub5bb\uac8c \uc791\ub3d9\ud558\ub098\uc694?\ub370\uc774\ud130 \uc218\uc9d1 \uac04\uc18c\ud654\uc790\ub3d9 ETL \ucc98\ub9ac\uc548\uc815\uc801\uc778 \uc6cc\ud06c\ud50c\ub85c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc804\uccb4\uc801 \uad00\ucc30 \uae30\ub2a5 \ubc0f \ubaa8\ub2c8\ud130\ub9c1\ucc28\uc138\ub300 \ub370\uc774\ud130 \ucc98\ub9ac \uc5d4\uc9c4\uac70\ubc84\ub10c\uc2a4, \uc548\uc815\uc131 \ubc0f \uc131\ub2a5\uc758 \uae30\ubc18\ub370\uc774\ud130 \uc218\uc9d1 \uac04\uc18c\ud654\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ub370\uc774\ud130\ub97c \uc785\ub825\ud558\uace0 \ud55c \uacf3\uc5d0\uc11c \ubd84\uc11d, AI \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc9c0\uc6d0\ud574 \ubcf4\uc138\uc694.Auto Loader\ub294 \ud074\ub77c\uc6b0\ub4dc \uc2a4\ud1a0\ub9ac\uc9c0\uc5d0 \uc800\uc7a5\ub418\ub294 \ud30c\uc77c\uc744 \uc99d\ubd84 \ubc29\uc2dd\uc73c\ub85c \uc790\ub3d9 \ucc98\ub9ac\ud558\ubbc0\ub85c \uc0c1\ud0dc \uc815\ubcf4\ub97c \uc608\uc57d \uc791\uc5c5\uc774\ub098 \uc5f0\uc18d\uc801 \uc791\uc5c5\uc73c\ub85c \uad00\ub9ac\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4. \ub514\ub809\ud130\ub9ac\uc5d0\uc11c \ubaa8\ub2c8\ud130\ub9c1\ud558\uc9c0 \uc54a\uc544\ub3c4 \uc0c8\ub85c\uc6b4 \ud30c\uc77c\uc744 \ud6a8\uc728\uc801\uc73c\ub85c \ucd94\uc801\ud558\uba70(\uc218\uc2ed\uc5b5 \uac1c\uae4c\uc9c0 \ud655\uc7a5 \uac00\ub2a5), \uc18c\uc2a4 \ub370\uc774\ud130\uc5d0\uc11c \uc2a4\ud0a4\ub9c8\ub97c \uc790\ub3d9 \ucd94\ub860\ud558\uc5ec \ub098\uc911\uc5d0 \ubcc0\uacbd\uc774 \ubc1c\uc0dd\ud558\uba74 \uadf8\uc5d0 \ub9de\ucdb0 \uc870\uc815\ud569\ub2c8\ub2e4. COPY INTO \uba85\ub839\uc744 \uc0ac\uc6a9\ud558\uba74 \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 SQL\uc744 \ud1b5\ud574 \uc190\uc27d\uac8c Delta Lake\ub85c \ubc30\uce58 \ud30c\uc77c\uc744 \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u201c\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc758 \uc0dd\uc0b0\uc131\uc774 40% \ud5a5\uc0c1\ub418\uc5b4\uc11c \uc0c8\ub85c\uc6b4 \uc544\uc774\ub514\uc5b4\ub97c \uac1c\ubc1c\ud558\uae30\uae4c\uc9c0 \uac78\ub9ac\ub294 \uc2dc\uac04\uc774 \uba70\uce60\uc5d0\uc11c \uba87 \ubd84\uc73c\ub85c \ub2e8\ucd95\ub41c \ub370\ub2e4, \ub370\uc774\ud130 \uac00\uc6a9\uc131\uacfc \uc815\ud655\uc131\uc774 \ub192\uc544\uc84c\uc2b5\ub2c8\ub2e4.\u201d\u2014 Shaun Pearce, \ucd5c\uace0 \uae30\uc220 \ucc45\uc784\uc790,\u00a0Gousto\uc790\uc138\ud788\uc790\ub3d9 ETL \ucc98\ub9ac\ud30c\uc77c\uc774 \uc218\uc9d1\ub418\uace0 \ub098\uba74 \ubd84\uc11d\uacfc AI\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \uac00\uacf5\ub418\uc9c0 \uc54a\uc740 \ub370\uc774\ud130\ub97c \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4. Databricks\ub294 Delta Live Tables(DLT)\ub85c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8, \uc560\ub110\ub9ac\uc2a4\ud2b8\uc5d0\uac8c \uac15\ub825\ud55c ETL \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. DLT\ub294 \uac04\ub2e8\ud55c \uc120\uc5b8\uc801 \ubc29\uc2dd\uc73c\ub85c \ubc30\uce58 \ub610\ub294 \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uc704\ud55c ETL \ubc0f ML \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\ub294 \ucd5c\ucd08\uc758 \ud504\ub808\uc784\uc6cc\ud06c\uc774\uba70, \uc778\ud504\ub77c \uad00\ub9ac\ub098 \uc791\uc5c5 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158, \uc624\ub958 \ucc98\ub9ac, \ubcf5\uad6c\uc640 \uac19\uc740 \uc6b4\uc601 \ubcf5\uc7a1\uc131\uacfc \uc131\ub2a5 \ucd5c\uc801\ud654\ub97c \uc790\ub3d9\ud654\ud569\ub2c8\ub2e4. DLT\ub97c \uc0ac\uc6a9\ud558\ub294 \uc5d4\uc9c0\ub2c8\uc5b4\ub294 \ub370\uc774\ud130\ub97c \ucf54\ub4dc\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\uace0, \ud14c\uc2a4\ud2b8, \ubaa8\ub2c8\ud130\ub9c1 \ubc0f \ubb38\uc11c\ud654 \ub4f1\uc758 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubaa8\ubc94 \uc0ac\ub840\ub97c \uc801\uc6a9\ud558\uc5ec \ub300\uaddc\ubaa8\ub85c \uc548\uc815\uc801\uc778 \ud30c\uc774\ud504\ub77c\uc778\uc744 \ubc30\ud3ec\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\uc548\uc815\uc801\uc778 \uc6cc\ud06c\ud50c\ub85c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158Databricks Workflows\ub294 \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ub124\uc774\ud2f0\ube0c\uc778 AI\uc5d0 \ub300\ud55c \uc644\uc804 \uad00\ub9ac\ud615 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158 \uc11c\ube44\uc2a4\uc785\ub2c8\ub2e4. Delta Live Tables, Jobs for SQL, Spark, \ub178\ud2b8\ubd81, dbt, ML \ubaa8\ub378 \ub4f1\uc744 \ud3ec\ud568\ud55c \uc804\uccb4 \uc218\uba85 \uc8fc\uae30\uc5d0 \ub300\ud574 \ub2e4\uc591\ud55c \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud569\ub2c8\ub2e4. \uae30\uc874 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uacfc \uae34\ubc00\ud788 \ud1b5\ud569\ub418\ubbc0\ub85c \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc548\uc815\uc801\uc778 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc0dd\uc131 \ubc0f \uc2e4\ud589\ud558\uba74\uc11c\ub3c4 \ucd5c\uc885 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uac04\ub2e8\ud558\uac8c \uc2ec\uce35\uc801 \uc911\uc559 \uc9d1\uc911\ud615 \ubaa8\ub2c8\ud130\ub9c1\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\uc6b0\ub9ac\uc758 \uc784\ubb34\ub294 \uc9c0\uad6c\uc5d0 \uc804\ub825\uc744 \uacf5\uae09\ud558\ub294 \ubc29\uc2dd\uc744 \ubcc0\ud654\uc2dc\ud0a4\ub294 \uac83\uc785\ub2c8\ub2e4. \uc5d0\ub108\uc9c0 \ubd80\ubb38\uc758 \uace0\uac1d\uc740 \uc774\ub7ec\ud55c \ubcc0\ud654\ub97c \ub2ec\uc131\ud558\uae30 \uc704\ud574 \ub370\uc774\ud130, \ucee8\uc124\ud305 \uc11c\ube44\uc2a4 \ubc0f \uc5f0\uad6c\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. Databricks \uc6cc\ud06c\ud50c\ub85c\ub294 \uace0\uac1d\uc774 \ud544\uc694\ub85c \ud558\ub294 \uc778\uc0ac\uc774\ud2b8\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\ub294 \uc18d\ub3c4\uc640 \uc720\uc5f0\uc131\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\u2014 Yanyan Wu, \ub370\uc774\ud130 \ubd80\ubb38 \ubd80\uc0ac\uc7a5,\u00a0Wood Mackenzie\uc790\uc138\ud788\uc804\uccb4\uc801 \uad00\ucc30 \uae30\ub2a5 \ubc0f \ubaa8\ub2c8\ud130\ub9c1\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ubaa8\ub4e0 \ub370\uc774\ud130\uc640 AI \uc218\uba85 \uc8fc\uae30\uc5d0 \ub300\ud55c \uac00\uc2dc\uc131\uc744 \uc81c\uacf5\ud558\ubbc0\ub85c, \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\uc640 \uc6b4\uc601 \ud300\uc5d0\uc11c \uc2e4\uc2dc\uac04\uc73c\ub85c \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c \uc0c1\ud0dc\ub97c \ud655\uc778\ud558\uace0, \ub370\uc774\ud130 \ud488\uc9c8\uc744 \uad00\ub9ac\ud558\uba70, \uacfc\uac70\uc758 \ud2b8\ub80c\ub4dc\ub97c \ud30c\uc545\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks Workflows\uc5d0\uc11c\ub294 \ud504\ub85c\ub355\uc158 \uc791\uc5c5\uacfc Delta Live Tables \ud30c\uc774\ud504\ub77c\uc778\uc758 \uc0c1\ud0dc\uc640 \uc131\ub2a5\uc744 \ucd94\uc801\ud558\ub294 \ub370\uc774\ud130 \ud50c\ub85c \uadf8\ub798\ud504 \ubc0f \ub300\uc2dc\ubcf4\ub4dc\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ubca4\ud2b8 \ub85c\uadf8\ub294 Delta Lake \ud14c\uc774\ube14\ub85c \ub178\ucd9c\ub418\uc5b4, \ubaa8\ub4e0 \uac01\ub3c4\uc5d0\uc11c \uc131\ub2a5\uacfc \ub370\uc774\ud130 \ud488\uc9c8, \uc548\uc815\uc131 \uc9c0\ud45c\ub97c \ubaa8\ub2c8\ud130\ub9c1\ud558\uace0 \uc2dc\uac01\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ucc28\uc138\ub300 \ub370\uc774\ud130 \ucc98\ub9ac \uc5d4\uc9c4Databricks \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc740 Apache Spark API\uc640 \ud638\ud658\ub418\ub294 \ucc28\uc138\ub300 \uc5d4\uc9c4\uc778 Photon\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uc5ec \uc218\ucc9c \uac1c\uc758 \ub178\ub4dc\ub85c \uc790\ub3d9 \ud655\uc7a5\ud558\uba74\uc11c\ub3c4 \ub3c5\ubcf4\uc801\uc778 \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.Spark Structured Streaming\uc740 \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ucc98\ub9ac\uc5d0 \ud558\ub098\uc758 \ud1b5\ud569\ub41c API\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ucf54\ub4dc\ub97c \ubcc0\uacbd\ud558\uac70\ub098 \uc0c8\ub85c\uc6b4 \uae30\uc220\uc744 \ubc30\uc6b0\uc9c0 \uc54a\uace0\ub3c4 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \uc190\uc27d\uac8c \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \ub3c4\uc785\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ucd5c\ucca8\ub2e8 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4, \uc548\uc815\uc131 \ubc0f \uc131\ub2a5Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \uc0ac\uc6a9\ud558\uba74 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \uae30\ubcf8 \uad6c\uc131 \uc694\uc18c(Unity Catalog \ubc0f Delta Lake)\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4. ACID \ud2b8\ub79c\uc7ad\uc158\uc744 \ud1b5\ud574 \uc548\uc815\uc131\uc744 \uc81c\uacf5\ud558\uace0 \ud655\uc7a5 \uac00\ub2a5\ud55c \uba54\ud0c0\ub370\uc774\ud130\ub97c \ub9e4\uc6b0 \ube60\ub978 \uc18d\ub3c4\ub85c \ucc98\ub9ac\ud558\ub294 \uc624\ud508 \uc18c\uc2a4 \uc2a4\ud1a0\ub9ac\uc9c0 \ud615\uc2dd\uc778 Delta Lake\ub85c \uac00\uacf5\ub418\uc9c0 \uc54a\uc740 \ub370\uc774\ud130\ub97c \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4. \uc5ec\uae30\uc5d0 Unity Catalog\ub97c \uacb0\ud569\ud558\uba74 \ubaa8\ub4e0 \ub370\uc774\ud130\uc640 AI \uc790\uc0b0\uc5d0 \uc138\ubd84\ud654\ub41c \uac70\ubc84\ub10c\uc2a4\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\uc744 \ubfd0\ub9cc \uc544\ub2c8\ub77c, \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc77c\uad00\uc801\uc778 \ub370\uc774\ud130 \ud0d0\uc0c9, \uc561\uc138\uc2a4, \uacf5\uc720 \ubaa8\ub378\uc744 \uc801\uc6a9\ud558\uc5ec \uac70\ub108\ubc88\uc2a4 \ubc29\uc2dd\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4. \ub610\ud55c, Unity Catalog\ub294 \ub2e4\ub978 \uc870\uc9c1\uacfc \uac04\ub2e8\ud558\uace0 \uc548\uc804\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\ub294 \uc5c5\uacc4 \ucd5c\ucd08\uc758 \uc624\ud508 \ud504\ub85c\ud1a0\ucf5c\uc778 Delta Sharing\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130 \uc0ac\uc77c\ub85c, \ub290\ub9b0 \uc131\ub2a5, Hadoop\uc774\ub098 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub192\uc740 \ube44\uc6a9\uc5d0 \uc9c0\uce58\uc168\ub098\uc694? \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc138\uc694.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud1b5\ud569\ub370\uc774\ud130 \ud300\uc5d0 \ucd5c\ub300\uc758 \uc720\uc5f0\uc131\uc744 \uc81c\uacf5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Partner Connect \ubc0f \uae30\uc220 \ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud65c\uc6a9\ud558\uc5ec \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ub3c4\uad6c\uc640 \ub9e4\ub044\ub7fd\uac8c \ud1b5\ud569\ud574 \ubcf4\uc138\uc694. \uc608\ub97c \ub4e4\uc5b4 Fivetran\uc73c\ub85c \ube44\uc988\ub2c8\uc2a4\uc5d0 \uc911\uc694\ud55c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\uace0, dbt\ub85c \ubc14\ub85c \ubcc0\ud658\ud558\uc5ec, Apache Airflow\ub85c \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \uc218\uc9d1 \ubc0f ETL+ \uc5ec\ud0c0 \ubaa8\ub4e0 Apache Spark\u2122\ufe0f \ud638\ud658 \ud074\ub77c\uc774\uc5b8\ud2b8\uace0\uac1d \uc0ac\ub840\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30Delta Lake\uc6cc\ud06c\ud50c\ub85c\uc6b0Delta Live \ud14c\uc774\ube14Delta Sharing\uad00\ub828 \ucf58\ud150\uce20\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ud1b5\ud574 Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \ud65c\uc6a9\ud558\ub294 \uc7a5\uc810\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0 Bill Inmon\uc774 \uad6c\ucd95\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uad00\ub9ac \uae30\ucd08\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 Big Book\uc0c8\ub85c\uc6b4 Delta Sharing \uc194\ub8e8\uc158 \uc54c\uc544\ubcf4\uae30\uc655\ucd08\ubcf4\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc774\ubca4\ud2b8Delta Live Tables\ub85c \ub370\uc774\ud130 \ubcc0\ud658 \ucc98\ub9ac\uac04\ud3b8\ud55c \ub370\uc774\ud130 \uc218\uc9d1 \uc6e8\ube44\ub098 \uc2dc\ub9ac\uc988DATA + AI SUMMIT 2022\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \ud604\ub300\ud654\ube14\ub85c\uadf8Databricks Delta Live Tables(DLT) \uc815\uc2dd \ucd9c\uc2dcDatabricks Workflows \uc18c\uac1c2021\ub144\uc5d0 Databricks \ubc0f Apache Spark\uc6a9\uc73c\ub85c \uac1c\ubc1c\ub41c \uc0c8\ub85c\uc6b4 \uad6c\uc870\ud654 \uc2a4\ud2b8\ub9ac\ubc0d \uae30\ub2a5 \uc804\uccb4 \uac1c\uad00Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc18\uad6c\uc870\ud654\ub41c \ub370\uc774\ud130 \uacfc\ub2c8\ub97c \ub2e8\uc21c\ud654\ud558\uae30 \uc704\ud55c 10\uac00\uc9c0 \uac15\ub825\ud55c \uae30\ub2a5\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ucee4\ubba4\ub2c8\ud2f0 \uac00\uc785AWSAzureGCP\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/de\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/prashanth-babu","text":"Prashanth Babu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPrashanth BabuLead Product Specialist at DatabricksBack to speakersPrashanth is a Lead Product Specialist Solutions Architect at Databricks. He has more than a decade experience working on Big Data. Prior to that for a decade, he was a Java architect for a product. He has been using Spark since 2014 and joined Databricks in Sep 2018. He focuses on all things Data Engineering working closely with both the Product Management and the (EMEA) Field Engineering teams. Also leads EMEA Delta and Performance SME at Databricks and has been working with many enterprises advising them on Databricks Lakehouse best practices and guiding them expedite build, productionize and deploy their pipelines at scale.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/austin-ford\/#","text":"Austin Ford - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAustin FordStaff Product Manager at DatabricksBack to speakersAustin is a product leader and former mathematician from Columbus, Mississippi. He is currently a Sr. Product Manager at Databricks in San Francisco and is responsible for the Databricks Notebook and the data science development experience in Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ananya-ghosh","text":"Ananya Ghosh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnanya GhoshBusiness Application Owner for Databricks at Nationwide InsuranceBack to speakersAnanya Ghosh has over 15 years of experience in DW\/DI\/BI tools and technologies. Currently she plays the role of Business Application Owner for Capture & Curate platforms including Databricks. Prior to that, she worked as a Databricks Data Engineer and Workspace Administrator for about 2 yrs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/esg","text":"ESG Performance Analytics - 2021 | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorAnalyze ESG PerformancePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedTake a quantitative and AI-driven view into sustainability performanceBetter understand and quantify the sustainability and societal impact of investment in a company, or embed better ESG in your own organization with these two Solution Accelerators:Analyze ESG performance\nUnderstand and quantify the sustainability and societal impact of any investment or businessOperationalize ESG in your organization\nEmbed ESG into your company's strategy to adapt and optimize your operational modelGet the notebookResourcesBlogLearn moreExplainer videoLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jackie-brosamer\/#","text":"Jackie Brosamer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJackie BrosamerDirector of Software Engineering at BlockBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/timothy-ahrens","text":"Timothy Ahrens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTimothy AhrensMessaging Design Division Chief at Department of StateBack to speakersTim Ahrens is a civil service employee with the U.S. Department of State and currently serves as the Division Chief for the Information Resource Management Operations Messaging Systems Office, Messaging Design Division. As MD Division Chief, he leads business process re-engineering, design, development, agile delivery, and tier 3 operational support for five enterprise products: SMART, eRecords, FOIA technology stack, CDS, and the CfA Data.State technology platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/pricing","text":"Pricing - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPricingConference\n\n\n\n\n\n\n\n\n\n\n\nFull Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1795 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nGroup DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1295 IN-PERSONEACH\n\n\n\n\n\n\n\n\n\n\n\nGOV\/EDU\/NFPDiscounted pass for Government\/Education\/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1395 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\nVirtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event.\n $0 VIRTUALTraining\n\n\n\n\n\n\n\n\n\n\nTwo-Day CourseThis includes a two-day course and the certification exam.\n$1125 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nFull-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic.\n$750 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nHalf-Day TrainingA 4-hour, in-depth session covering your chosen topic.\n$375 IN-PERSONCertification\n\n\n\n\n\n\n\n\n\n\n\nCertification ExamRegister for training and take a certification exam onsite for free.\n$0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/industries\/manufacturing-industry-solutions","text":"\uc81c\uc870 \uc0b0\uc5c5 \uc194\ub8e8\uc158 \u2013 DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 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\uc5ec\ub7ec \ub2e4\uc6b4\uc2a4\ud2b8\ub9bc \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \uc81c\uacf5\ud558\uace0 \uc774\ub97c \ubc14\ud0d5\uc73c\ub85c \ub370\uc774\ud130 \uae30\ubc18 \uc758\uc0ac \uacb0\uc815\uc744 \uc218\ud589\ud558\uc5ec \uacf5\uc7a5 \uc6b4\uc601\uc744 \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\ub9ac\ud14c\uc77c \uc561\uc140\ub7ec\ub808\uc774\ud130 \ub458\ub7ec\ubcf4\uae30Databricks\ub294 \uc8fc\uc694 \ucee8\uc124\ud305 \uae30\uc5c5\uacfc \ud611\ub825\ud558\uc5ec \ud601\uc2e0\uc801\uc778 \uc5c5\uc885\ubcc4 \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud588\uc2b5\ub2c8\ub2e4. Databricks Brickbuilder Solutions\ub294 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uace0 \ub370\uc774\ud130\uc5d0\uc11c \ub354 \ub9ce\uc740 \uac00\uce58\ub97c \ucc3d\ucd9c\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4. \uc218\uc2ed \ub144 \uac04 \ucd95\uc801\ub41c \uc5c5\uacc4 \uacbd\ud5d8\uc744 \ub178\ud558\uc6b0 \uc0bc\uc544 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uae30\ubc18\uc73c\ub85c \uac1c\ubc1c\ud55c Brickbuilder Solutions\ub294 \uace0\uac1d\uc758 \uc694\uad6c \uc0ac\ud56d\uc744 \uc815\ud655\ud788 \ud574\uacb0\ud574\uc90d\ub2c8\ub2e4.\uc9c0\ub2a5\uc801 \uc81c\uc870 \ubd84\uc11d \ubc0f AI\ub97c \ud1b5\ud574 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\uace0 \uc0c1\ud638 \uc6b4\uc6a9\uc131\uc744 \ucd09\uc9c4\ud558\uba70 \ud5a5\uc0c1\ub41c \uc778\uc0ac\uc774\ud2b8\ub97c \ub300\uaddc\ubaa8\ub85c \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ud488\uc9c8 \uac80\uc0ac\uae30\ucef4\ud4e8\ud130 \ube44\uc804\uc73c\ub85c \ud488\uc9c8 \uad00\ub9ac\ub97c \uc790\ub3d9\ud654\ud558\uc5ec \uacb0\ud568, \uc774\ubb3c\uc9c8, \uc774\uc0c1\uce58 \ub610\ub294 \uc798\ubabb\ub41c \uc124\uc815\uc744 \u0000\uac10\uc9c0\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\uc608\uce21 \uac00\ub2a5\ud55c \uacf5\uae09 \uc704\ud5d8 \uad00\ub9ac\uc8fc\ubb38 \ud750\ub984 \ubc0f \uacf5\uae09\uc5c5\uccb4 \uc131\uacfc\uc5d0 \ub300\ud55c n\uacc4\uce35 \uac00\uc2dc\uc131\uc744 \ud655\ubcf4\ud558\uc5ec \ud6a8\uc728\uc131\uc744 \ub192\uc774\uace0 \uc608\uc678 \uc0ac\u0000\ud56d\uc744 \uad00\ub9ac\ud558\uba70 \ubcf5\uc6d0\ub825\uc744 \uac15\ud654\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ubaa8\ub4e0 \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158 \ubcf4\uae30\"Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 \uc870\uc9c1 \uc804\ubc18\uc758 \ub370\uc774\ud130 \uc561\uc138\uc2a4\uc5d0 \ub300\ud55c \uc9c4\uc785 \uc7a5\ubcbd\uc744 \ub0ae\ucdb0 \uc804 \uc138\uacc4\uc5d0\uc11c \uac00\uc7a5 \ud601\uc2e0\uc801\uc774\uace0 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \uc804\uae30 \uc790\ub3d9\ucc28\ub97c \uc81c\uc870\ud560 \uc218 \uc788\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\"\n\u2013 Wassym Bensaid, Rivian \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uac1c\ubc1c \ubd80\ubb38 \ubd80\uc0ac\uc7a5\n\"\uc9c0\ub09c \uc218\ub144 \ub3d9\uc548 Databricks\ub294 \ud65c\uc6a9\uc758 \ud3ed\uc774 \uc0c1\ub2f9\ud788 \ub113\uc5b4\uc84c\uc2b5\ub2c8\ub2e4. Databricks\ub97c \ube45\ub370\uc774\ud130 \ubc0f AI \ud50c\ub7ab\ud3fc\uc73c\ub85c \uc0ac\uc6a9\ud558\uae30 \uc2dc\uc791\ud588\uc9c0\ub9cc, \uadf8 \ubc94\uc704\uac00 \ub354\uc6b1 \ud655\uc7a5\ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc774\uc81c \uc644\uc804\ud788 \ub2e4\ub978 \ubd84\uc57c\uc758 \uc2dc\ubbfc \uc5d4\uc9c0\ub2c8\uc5b4\uc640 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\ub4e4\uc774 \uc774 \ud50c\ub7ab\ud3fc\uc744 \ud604\ub300\uc801\uc778 \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4 \ub3c4\uad6c\ub85c \ud65c\uc6a9\ud574 \ub354\uc6b1 \ud604\uba85\ud55c \ube44\uc988\ub2c8\uc2a4 \uacb0\uc815\uc744 \ub0b4\ub9ac\uace0 \uc788\uc2b5\ub2c8\ub2e4.\"\n\u2014Daniel Jeavons, \uace0\uae09 \ubd84\uc11d CoE \ub300\ud45c \uc774\uc0ac, Shell\n\"Databricks \ud50c\ub7ab\ud3fc\uc740 \uc5d4\uc9c4 \uac00\uc6a9\uc131\uc5d0 \ub300\ud55c \uc704\ud5d8\uc744 \ucd5c\uc18c\ud654\ud558\uace0 \uc608\ube44 \ubd80\ud488\uc758 \ub9ac\ub4dc \ud0c0\uc784\uc744 \ub2e8\ucd95\ud558\uba70 \uc7ac\uace0 \ud68c\uc804\uc758 \ud6a8\uc728\uc131\uc744 \ub192\uc77c \uc218 \uc788\uac8c \ud574\uc8fc\uc5c8\uc2b5\ub2c8\ub2e4. \uadf8\ub9ac\uace0 \uadf8 \ub355\ubd84\uc5d0 \ud56d\uacf5 \uc5c5\uacc4\ub97c \uc120\ub3c4\ud558\ub294 PBH(Power-by-the-Hour) \uc720\uc9c0\ubcf4\uc218 \ud504\ub85c\uadf8\ub7a8\uc778 TotalCare\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\"\n\u2014 Stuart Hughes, Rolls-Royce Civil Aerospace \ucd5c\uace0 \uc815\ubcf4 \ubc0f \ub514\uc9c0\ud138 \ucc45\uc784\uc790,\n\ub9ac\uc18c\uc2a4eBookERP \ub370\uc774\ud130 \ud65c\uc6a9\uc6e8\ube44\ub098\ub370\uc774\ud130 + AI\ub97c \ud65c\uc6a9\ud558\uc5ec \uc81c\uc870\uae30\uc5c5\uc758 \uc608\uce21\uc801 \uc720\uc9c0\uad00\ub9ac \uac1c\uc120eBook\uc9c0\ub2a5\uc801 \uc81c\uc870\ub97c \ucd09\uc9c4\ud558\ub294 \ub124 \uac00\uc9c0 \uc694\uc778\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uadc0\uc0ac\uc758 \ube44\uc988\ub2c8\uc2a4 \ubaa9\ud45c\ub97c \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uace0 \uc11c\ube44\uc2a4 \ud300\uc5d0\uc11c \uadc0\uc0ac\uc758 \uc131\uacf5\uc744 \ub3c4\uc6b8 \ubc29\ubc95\uc744 \ud568\uaed8 \uc54c\uc544\ubcf4\uace0\uc790 \ud569\ub2c8\ub2e4.Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\ubb38\uc758\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/glossary\/spark-tuning","text":"What is Spark Tuning?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark TuningAll>Spark TuningTry Databricks for freeGet StartedWhat is Spark Performance Tuning?Spark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also prevents bottlenecking of resources in Spark. What is Data Serialization?In order, to reduce memory usage you might have to store spark RDDs in serialized form. Data serialization also determines a good network performance. You will be able to obtain good results in Spark performance by:Terminating those jobs that run long.Ensuring that jobs are running on a precise execution engine.Using all resources in an efficiently.Enhancing the system\u2019s performance timeSpark supports two serialization libraries, as follows:Java SerializationKryo SerializationWhat is Memory Tuning?While tuning memory usage, there are three aspects that stand out:The entire dataset has to fit in memory, consideration of memory used by your objects is the must.By having an increased high turnover of objects, the overhead of garbage collection becomes a necessity.You\u2019ll have to take into account the cost of accessing those objects.What is Data Structure Tuning?One option to reduce memory consumption is by staying away from java features that could overhead. Here are a few ways to do this:In case the RAM size is less than 32 GB, the JVM flag should be set to \u2013xx:+ UseCompressedOops. This operation will build a pointer of four bytes instead of eight.Nested structures can be dodged by using several small objects as well as pointers.Instead of using strings for keys you could use numeric IDs and enumerated objectsWhat is Garbage Collection Tuning?In order to avoid the large \u201cchurn\u201d related to the RDDs that have been previously stored by the program, java will dismiss old objects in order to create space for new ones. However, by using data structures that feature fewer objects the cost is greatly reduced. One such example would be the employment an array of Ints instead of a linked list. Alternatively, you could use objects in the serialized form, so you will only have a single object for each RDD partition.What is Memory Management?An efficient memory use is essential to good performance. Spark uses memory mainly for storage and execution. Storage memory is used to cache data that will be reused later. On the other hand, execution memory is used for computation in shuffles, sorts, joins, and aggregations. Memory contention poses three challenges for Apache Spark:How to arbitrate memory between execution and storage?How to arbitrate memory across tasks running simultaneously?How to arbitrate memory across operators running within the same task?Instead of avoiding statically reserving memory in advance, you could deal with memory contention when it arises by forcing members to spill.Additional Resources8 Steps for a Developer to Learn Apache Spark with Delta LakeThe Data Engineer's Guide to Apache Spark and Delta LakeComparing Apache Spark and DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/advisory-services-schedule","text":"Advisory Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAdvisory Services ScheduleThis Schedule sets forth terms related to the Advisory Services and is incorporated as part of the Master Cloud Services Agreement (\"MCSA\"). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Other Schedules do not apply to the services ordered under this Schedule unless expressly referenced as being applicable. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Additional Definitions.\u201cCustomer Materials\u201d means the information and materials you provide to Databricks for Databricks to perform the Advisory Services.Advisory Services.Generally. Subject to the Order, Databricks will provide Advisory Services to facilitate your use of the Databricks platform. Unless otherwise agreed by the parties, Advisory Services will expire one year after the Start Date indicated on the Order and will be booked on the basis of 8-hour service days.Intellectual Property.License. Upon your payment of all Fees under an applicable Order, Databricks grants you a non-exclusive, perpetual, fully paid-up, royalty-free license to use, copy, modify, or create derivative works based on any Advisory Services work product delivered by Databricks to you under the Order (the \u201cDeliverables\u201d). If and to the extent Databricks incorporates any Databricks Materials (as defined below) into the Deliverables, Databricks grants to you a non-exclusive, perpetual, fully paid-up, royalty-free license to use, copy, modify or create derivative works based on such Databricks Materials, solely as incorporated into the Deliverables and solely for your internal business use as reasonably necessary to use the Deliverables for their intended purposes. For the avoidance of doubt, no part of the Platform Services will be deemed to be incorporated into the Deliverables.Databricks Materials. Subject to your rights in your Confidential Information, Databricks will exclusively own all rights, title and interest in and to: (i) the Deliverables; and (ii) any software programs, tools, utilities, processes, inventions, devices, methodologies, specifications, documentation, techniques, training materials, and other materials of any kind used or developed by Databricks or its personnel in connection with performing the Advisory Services, or any other Databricks Services (collectively \u201cDatabricks Materials\u201d), including all Intellectual Property Rights in any of the foregoing.No Maintenance. Unless otherwise set forth in an Order the Deliverables are not subject to any maintenance, support or updates after the termination of the Order.Requirements; Limitations. Databricks will provide the Advisory Services remotely or at a mutually agreed location. While on Customer\u2019s premises, Databricks will adhere to reasonable policies provided by Customer in writing in advance. For the avoidance of doubt, no such policies will be deemed to modify the terms of the Agreement.Use of Workspace during Performance of Advisory Services. You may be required to use a Workspace in order to receive Advisory Services. Your use of the Workspace constitutes acceptance of the Platform Services terms of the MCSA unless the Workspace is provided as part of a Databricks Powered Service.Your Obligations; Customer Materials.\u00a0Your Responsibilities. You:\nare responsible for taking reasonable steps at all times to maintain the security, protection and backup of all Customer Materials, including within the Platform Services and any Customer Systems;acknowledge that: (i) Databricks does not provide data backup services; and that (ii) Databricks is not responsible for any loss, destruction, alteration, unauthorized disclosure or corruption of Customer Materials not caused by the gross negligence or willful misconduct of Databricks or any third party under the control of Databricks;agree not to provide Databricks with access to more data than is reasonably necessary to permit Databricks to perform the Advisory Services; andacknowledge that successful delivery of the Advisory Services depends on your full and timely cooperation. You agree to make available any reasonably requested personnel and\/or information in a timely manner to allow Databricks to perform such services.Restrictions on Use. You will not:\ncopy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of any Deliverables provided to you in object code, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;use the Databricks Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party's possible purchase of any Databricks product or service; ortransfer or assign any of your rights hereunder except as permitted under Section 12.5 (Assignment) of the MCSA.Customer Materials. You represent and warrant to Databricks that Customer Materials will not contain:\nany data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement; orexcept as otherwise specified in an Order, any (x) bank, credit card or other financial account numbers or login credentials, (y) social security, tax, driver\u2019s license or other government-issued identification numbers, or (z) health information identifiable to a particular individual.Data Protection. Databricks will maintain appropriate administrative, physical, and technical safeguards according to ISO\/IEC 27001:2013 (the \u201cISMS Standard\u201d) for protection of the security and confidentiality of Customer Materials under Databricks\u2019 control. Unless specified otherwise in an Order, Databricks engages in the performance of Advisory Services with the expectation that Customer is not engaging Databricks for the purpose of having Databricks act as a data processor for Customer. Nevertheless, except with respect to free Advisory Services, unless you have entered into the\u00a0DPA, the terms of the\u00a0DPA are hereby incorporated by reference and will apply to the extent Databricks is deemed to act as Customer\u2019s data processor during the performance of Advisory Services when the Customer Materials include Personal Data, as defined in the\u00a0DPA. This Schedule and the\u00a0DPA do not govern the protection of Customer Content and Databricks does not act as a data processor with respect to any data processed by or within a Databricks Powered Service.Expenses. You agree to reimburse Databricks for reasonable travel and lodging expenses actually incurred by Databricks.Warranties; Disclaimer.Warranties. Databricks warrants that the Advisory Services will be provided in a professional and workmanlike manner consistent with industry standards. You must notify Databricks of any warranty deficiencies within ninety (90) days from performance of the deficient Advisory Services. Unless set forth in an Order Databricks makes no guarantee as to whether the Advisory Services will be completed within any specific time frame.Disclaimer. THE WARRANTIES IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING THE DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS SPECIFICALLY DISCLAIMS ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE WITH RESPECT TO ANY OF THE FOREGOING. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (i) SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \"AS-IS\" AND WITHOUT WARRANTY OF ANY KIND BY DATABRICKS; (ii) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE DATABRICKS SERVICES; AND (iii) DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE.Exclusive Remedy. FOR ANY BREACH OF THE WARRANTY AT SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE RE-PERFORMANCE OF THE DEFICIENT SERVICES, OR, IF DATABRICKS CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE COMMENCEMENT OF THE DEFICIENCY.Last Updated August 12, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gaurav-saraf\/#","text":"Gaurav Saraf - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGaurav SarafProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/hotels-com","text":"Hotels com - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYPersonalized hotel recommendations with deep learning INDUSTRY: Travel and hospitality SOLUTION: Customer retention,recommendation engines PLATFORM USE CASE: Data science,machine learning,ETL CLOUD: AWS\u201cAgility and flexibility were critical for us to successfully support our data science and engineering goals. Moving to Databricks\u2019 Unified Analytics Platform to run 100% of our workflows has been a huge boost for our business and our customers.\u201d\n\u2014Matt Fryer VP, Chief Data Science Officer, Hotels.comHotels.com is a premier website for booking accommodations online with 90 websites in 41 languages, listing over 325,000 hotels in approximately 19,000 locations. Their travel booking app has been downloaded over 70 million times helping global travelers find the perfect place to stay.The ChallengesHotels.com hosts millions of photos for the 325,000+ hotels on their website. Every day thousands of new photos are uploaded by properties and customers alike. These photos need to be rapidly analyzed to avoid duplicative and low-quality images and then classified (e.g. kitchen, pool, gym) so they can be logically sorted. Finally, as customers search the site, hotel recommendations need to be personalized to help customers find the perfect hotel for their needs. Achieving this requires massive compute power and advanced analytics.Leverage machine learning to drive consumer experience:\u00a0Massive volume of image files corresponding to each property listing included duplicates and lacked organization for ranking and classification. Needed to build in real-time scoring and become more efficient at deploying machine learning\/deep learning models into production.Build a more robust and faster data pipeline:\u00a0On premise Hadoop cluster using SQL and SAS to do data science at scale was slow and limiting \u2013 taking 2 hours to process the data pipeline on only 10% of the data.Increase customer conversions:\u00a0Being able to understand customer trends in real-time to develop strategies to drive conversion and lifetime value.The SolutionDatabricks has helped Hotels.com to realize its goal of becoming \u201cdata science focused\u201d so that they can anticipate customer behavior and provide a more optimized user experience.Cluster Management:\u00a0Able to scale volume of data significantly without adding infrastructure complexity.Interactive Workspace:\u00a0Foster a culture of collaboration among data science teams within Hotels.com as well as other business units within Expedia.Databricks Runtime:\u00a0Increase processing performance of streaming data even at scale.\u201cAgility and flexibility were critical for us to successfully support our data science and engineering goals. Moving to Databricks\u2019 Unified Analytics Platform to run 100% of our workflows has been a huge boost for our business and our customers.\u201d\u2014 Matt Fryer VP, Chief Data Science Officer, Hotels.comThe ResultsAccelerate ETL at scale:\u00a0Able to increase the volume of data processed by 20x without impacting performance.Optimized user experience:\u00a0Highly accurate and effective display of images within the context of property searches by customers.Increased sales efficiency:\u00a0Providing the right hotel with the right images based on searches has resulted in higher conversions.Related ContentWhitepapersSlides Keynote SlidesReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Prova Databricks gratis | DatabricksProva Databricks gratisProva la piattaforma Databricks completa per 14 giorni su AWS, Microsoft Azure o Google Cloud.Semplifica l\u2019acquisizione dei dati e automatizza i processi ETLAcquisisci i dati da centinaia di sorgenti. Usa un semplice approccio dichiarativo per costruire le pipeline di dati.Collabora nella lingua che preferisciScrivi codice in Python, R, Scala e SQL con co-creazione, gestione automatica delle versioni, integrazioni Git e controllo degli accessi per ruoli (RBAC).Rapporto prezzo\/prestazioni 12 volte migliore rispetto ai data warehouse in cloudScopri perch\u00e9 oltre 7.000 clienti in tutto il mondo si affidano a Databricks per tutti i loro carichi di lavoro, dalla BI all\u2019AI.Crea il tuo account Databricks1\/2NomeCognomeE-mail aziendaleAziendaTitolo professionaleTelefono (Optional)Si prega di selezionareNazioneContinuaInformativa sulla privacy (aggiornata)Condizioni d'usoLe vostre scelte sulla privacyI vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/glossary\/hive-date-function","text":"What is a Hive Date Function?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHive Date FunctionAll>Hive Date FunctionTry Databricks for freeGet StartedWhat is a Hive Date Function?Hive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditional operators, mathematical functions, and several others.Types of Built-in Functions in HIVEDate FunctionsMainly used to perform operations on date data types such as adding the number of days to the date or other similar operations.Mathematical FunctionsThese functions are primarily used to perform mathematical calculations.Conditional FunctionsThese functions are used to test conditions and returns a value based on whether the test condition is true or false.String FunctionsThese are used to perform operations on strings such as finding the length of a string etc.Collection FunctionsThese functions are used to find the size of the complex types like array and map. There is one collection function and that is SIZE. The SIZE function's main usage is to find the number of elements in an array and map.Type Conversion FunctionThis function's usage is to convert the data from one type to another. The only type conversion function is CAST.Table Generating FunctionsThese functions can be used to turn a single row into multiple rows. EXPLODE is the only table generated function. This function uses an array as an input and outputs the elements of the array into separate rows.Date TypesAre highly formatted; in their case, each date value contains the century, year, month, day, hour, minute, and second. These functions are used to perform operations on date data types like adding the number of days to the date, conversion of Date types from one type to another type etc. Below are the most commonly used Hadoop Hive DateTime functions:Function NameReturn TypeDescriptionUnix_TimestampBigIntIt will get current Unix timestamp in seconds.To_date(string timestamp)StringIt will fetch and give the date part of a timestamp string:year(string date)INTIt will fetch and give the year part of a date or a timestamp string.quarter (date\/timestamp\/string)INTThe function quarter was introduced in Hive 1.3, and it will fetch and give the quarter of the year for a date, timestamp, or string in the range 1 to 4month(string date)INTIt will give the month part of a date or a timestamp string.hour(string date)INTThe hour function will fetch and gives the hour of the timestampminute(string date)INTThis function will return \u00a0minute from the timestampDate_sub(string starting date, int days)stringThe DATE_SUB function subtracts the number of days to the specified dateCurrent_datedateIt will return the current date at the start of query evaluation.LAST _day(string date)stringIt will fetch and give the last day of the month which the date belongs totrunc(string date, string format)stringThis function strips off fields from a TIMESTAMP valueAdditional ResourcesExperiences Migrating Hive Workload to SparkSQLFunctions DocumentationBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks escolhe l\u00edder | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks escolhe l\u00edderSistemas de gerenciamento de banco de dados na nuvemDatabricks foi nomeada l\u00edder no 2022 Gartner\u00ae Magic Quadrant\u2122 CDBMSA Databricks tem o orgulho de anunciar que a Gartner nos nomeou l\u00edder no 2022 Magic Quadrant para Sistemas de Gerenciamento de Banco de Dados na Nuvem pelo segundo ano consecutivo.Acreditamos que esse reconhecimento valida nossa vis\u00e3o para o lakehouse como uma plataforma \u00fanica e unificada para gerenciamento e engenharia de dados \u2013 bem como an\u00e1lise e IA.Baixe o relat\u00f3rio para saber por que a Gartner nomeou a Databricks l\u00edder e para obter mais informa\u00e7\u00f5es sobre os benef\u00edcios que uma plataforma de lakehouse pode trazer para sua organiza\u00e7\u00e3o.Acesse o relat\u00f3rio Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/de\/company\/board-of-directors","text":"Board of Directors von Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWF\u00fchrungUnser F\u00fchrungsteam verfolgt eine langfristige Vision und nutzt dabei unsere jahrzehntelange Erfahrung, um einen neuen Kurs f\u00fcr Daten und KI zu entwickeln.Unser TeamLeitungsteamGr\u00fcnderBoard of DirectorsIon StoicaMitbegr\u00fcnder und gesch\u00e4ftsf\u00fchrender VorsitzenderBen HorowitzMitbegr\u00fcnder von Andreessen HorowitzElena DonioMitglied im Board of DirectorsAli GhodsiMitbegr\u00fcnder und Chief Executive OfficerPete SonsiniGeneral Partner bei New Enterprise AssociatesJonathan ChadwickMitglied im Board of DirectorsMatei ZahariaMitbegr\u00fcnder und Chief TechnologistScott ShenkerProfessor f\u00fcr Informatik an der UC BerkeleyProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/glossary\/predictive-maintenance","text":"Predictive MaintenancePlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPredictive MaintenanceAll>Predictive MaintenanceTry Databricks for freeGet StartedWhat is predictive maintenance?Predictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rather than on a fixed schedule, so that you can maximize uptime and productivity. It is all about predicting & preventing failures and performing the right maintenance routines in order to reduce costly equipment downtimes.With IoT and sensor data streaming from equipment, predictive maintenance enables Manufacturers to effectively predict machine outages. The data detects variances, understands warning signals, and identifies any patterns that may indicate a potential breakdown. Manufacturers can use analytics and machine learning to accurately predict the odds of a machine going down. This enables early and corrective measures to be planned (i.e., spare parts ordering, repair scheduling, etc.) and introduced in the most effective way, thereby avoiding unplanned downtime and costly staff and resources.Why is predictive maintenance important?Using IoT and data analytics to predict and prevent breakdowns can reduce overall downtime by 50%. (McKinsey)What are Databricks\u2019 differentiated capabilities?Databricks\u2019 Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader and Photon to enable customers to make data available for real-time decisions.Lakehouse for MFG supports the largest data jobs at near real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.A Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for real-time stream ingestion of data and analytics on streaming data. Data warehouses require the extraction, transformation, loading, and additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest of data sets to power real-time decisions in BI tools.Additional ResourcesPredictive Maintenance interactive eBookDatabricks solutions for ManufacturingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bin-mu\/#","text":"Bin Mu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBin MuVice President and Head of Data & Analytics at AdobeBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/08\/09\/low-latency-streaming-data-pipelines-with-delta-live-tables-and-apache-kafka.html","text":"Declarative Streaming Data Pipelines with Delta Live Tables and Apache Kafka - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorLow-latency Streaming Data Pipelines with Delta Live Tables and Apache Kafkaby Frank MunzAugust 9, 2022 in ProductShare this postDelta Live Tables (DLT) is the first ETL framework that uses a simple declarative approach for creating reliable data pipelines and fully manages the underlying infrastructure at scale for batch and streaming data. Many use cases require actionable insights derived from near real-time data. Delta Live Tables enables low-latency streaming data pipelines to support such use cases with low latencies by directly ingesting data from event buses like Apache Kafka, AWS Kinesis, Confluent Cloud, Amazon MSK, or Azure Event Hubs.This article will walk through using DLT with Apache Kafka while providing the required Python code to ingest streams. The recommended system architecture will be explained, and related DLT settings worth considering will be explored along the way.Streaming platformsEvent buses or message buses decouple message producers from consumers. A popular streaming use case is the collection of click-through data from users navigating a website where every user interaction is stored as an event in Apache Kafka. The event stream from Kafka is then used for real-time streaming data analytics. Multiple message consumers can read the same data from Kafka and use the data to learn about audience interests, conversion rates, and bounce reasons. The real-time, streaming event data from the user interactions often also needs to be correlated with actual purchases stored in a billing database.Apache KafkaApache Kafka is a popular open source event bus. Kafka uses the concept of a topic, an append-only distributed log of events where messages are buffered for a certain amount of time. Although messages in Kafka are not deleted once they are consumed, they are also not stored indefinitely. The message retention for Kafka can be configured per topic and defaults to 7 days. Expired messages will be deleted eventually.This article is centered around Apache Kafka; however, the concepts discussed also apply to many other event busses or messaging systems.Streaming data pipelinesIn a data flow pipeline, Delta Live Tables and their dependencies can be declared with a standard SQL Create Table As Select (CTAS) statement and the DLT keyword \"live.\"When developing DLT with Python, the @dlt.table decorator is used to create a Delta Live Table. To ensure the data quality in a pipeline, DLT uses Expectations which are simple SQL constraints clauses that define the pipeline's behavior with invalid records.Since streaming workloads often come with unpredictable data volumes, Databricks employs enhanced autoscaling for data flow pipelines to minimize the overall end-to-end latency while reducing cost by shutting down unnecessary infrastructure.Delta Live Tables are fully recomputed, in the right order, exactly once for each pipeline run.In contrast, streaming Delta Live Tables are stateful, incrementally computed and only process data that has been added since the last pipeline run. If the query which defines a streaming live tables changes, new data will be processed based on the new query but existing data is not recomputed. Streaming live tables always use a streaming source and only work over append-only streams, such as Kafka, Kinesis, or Auto Loader. Streaming DLTs are based on top of Spark Structured Streaming.You can chain multiple streaming pipelines, for example, workloads with very large data volume and low latency requirements.Direct Ingestion from Streaming EnginesDelta Live Tables written in Python can directly ingest data from an event bus like Kafka using Spark Structured Streaming. You can set a short retention period for the Kafka topic to avoid compliance issues, reduce costs and then benefit from the cheap, elastic and governable storage that Delta provides.As a first step in the pipeline, we recommend ingesting the data as is to a bronze (raw) table and avoid complex transformations that could drop important data. Like any Delta Table the bronze table will retain the history and allow to perform GDPR and other compliance tasks.Ingest streaming data from Apache KafkaWhen writing DLT pipelines in Python, you use the @dlt.table annotation to create a DLT table. There is no special attribute to mark streaming DLTs in Python; simply use spark.readStream() to access the stream. Example code for creating a DLT table with the name kafka_bronze that is consuming data from a Kafka topic looks as follows:\nimport dlt\nfrom pyspark.sql.functions import *\nfrom pyspark.sql.types import *\n\nTOPIC = \"tracker-events\"\nKAFKA_BROKER = spark.conf.get(\"KAFKA_SERVER\")\n# subscribe to TOPIC at KAFKA_BROKER\nraw_kafka_events = (spark.readStream\n    .format(\"kafka\")\n    .option(\"subscribe\", TOPIC)\n    .option(\"kafka.bootstrap.servers\", KAFKA_BROKER)\n    .option(\"startingOffsets\", \"earliest\")\n    .load()\n    )\n\n@dlt.table(table_properties={\"pipelines.reset.allowed\":\"false\"})\ndef kafka_bronze():\n  return raw_kafka_eventspipelines.reset.allowedNote that event buses typically expire messages after a certain period of time, whereas Delta is designed for infinite retention.This might lead to the effect that source data on Kafka has already been deleted when running a full refresh for a DLT pipeline. In this case, not all historic data could be backfilled from the messaging platform, and data would be missing in DLT tables. To prevent dropping data, use the following DLT table property:pipelines.reset.allowed=falseSetting pipelines.reset.allowed to false prevents refreshes to the table but does not prevent incremental writes to the tables or new data from flowing into the table.CheckpointingIf you are an experienced Spark Structured Streaming developer, you will notice the absence of checkpointing in the above code. In Spark Structured Streaming checkpointing is required to persist progress information about what data has been successfully processed and upon failure, this metadata is used to restart a failed query exactly where it left off.Whereas checkpoints are necessary for failure recovery with exactly-once guarantees in Spark Structured Streaming, DLT handles state automatically without any manual configuration or explicit checkpointing required.Mixing SQL and Python for a DLT PipelineA DLT pipeline can consist of multiple notebooks but one DLT notebook is required to be either entirely written in SQL or Python (unlike other Databricks notebooks where you can have cells of different languages in a single notebook).Now, if your preference is SQL, you can code the data ingestion from Apache Kafka in one notebook in Python and then implement the transformation logic of your data pipelines in another notebook in SQL.Schema mappingWhen reading data from messaging platform, the data stream is opaque and a schema has to be provided.The Python example below shows the schema definition of events from a fitness tracker, and how the value part of the Kafka message is mapped to that schema.\nevent_schema = StructType([ \\\n    StructField(\"time\", TimestampType(),True)      , \\\n    StructField(\"version\", StringType(),True), \\\n    StructField(\"model\", StringType(),True)     , \\\n    StructField(\"heart_bpm\", IntegerType(),True), \\\n    StructField(\"kcal\", IntegerType(),True)       \\\n  ])\n\n\n# temporary table, visible in pipeline but not in data browser, \n# cannot be queried interactively\n@dlt.table(comment=\"real schema for Kakfa payload\",\n           temporary=True)\n\n\ndef kafka_silver():\n  return (\n    # kafka streams are (timestamp,value)\n    # value contains the kafka payload\n        \n    dlt.read_stream(\"kafka_bronze\")\n    .select(col(\"timestamp\"),from_json(col(\"value\")\n    .cast(\"string\"), event_schema).alias(\"event\"))\n    .select(\"timestamp\", \"event.*\")     \n  )\nBenefitsReading streaming data in DLT directly from a message broker minimizes the architectural complexity and provides lower end-to-end latency since data is directly streamed from the messaging broker and no intermediary step is involved.Streaming Ingest with Cloud Object Store IntermediaryFor some specific use cases you may want offload data from Apache Kafka, e.g., using a Kafka connector, and store your streaming data in a cloud object intermediary. In a Databricks workspace, the cloud vendor-specific object-store can then be mapped via the Databricks Files System (DBFS) as a cloud-independent folder. Once the data is offloaded, Databricks Auto Loader can ingest the files.Auto Loader can ingest data with with a single line of SQL code. The syntax to ingest JSON files into a DLT table is shown below (it is wrapped across two lines for readability).\n-- INGEST with Auto Loader\ncreate or replace streaming live table raw\nas select * FROM cloud_files(\"dbfs:\/data\/twitter\", \"json\")\nNote that Auto Loader itself is a streaming data source and all newly arrived files will be processed exactly once, hence the streaming keyword for the raw table that indicates data is ingested incrementally to that table.Since offloading streaming data to a cloud object store introduces an additional step in your system architecture it will also increase the end-to-end latency and create additional storage costs. Keep in mind that the Kafka connector writing event data to the cloud object store needs to be managed, increasing operational complexity.Therefore Databricks recommends as a best practice to directly access event bus data from DLT using Spark Structured Streaming as described above.Other Event Buses or Messaging SystemsThis article is centered around Apache Kafka; however, the concepts discussed also apply to other event buses or messaging systems. DLT supports any data source that Databricks Runtime directly supports.Amazon KinesisIn Kinesis, you write messages to a fully managed serverless stream. Same as Kafka, Kinesis does not permanently store messages. The default message retention in Kinesis is one day.When using Amazon Kinesis, replace format(\"kafka\") with format(\"kinesis\") in the Python code for streaming ingestion above and add Amazon Kinesis-specific settings with option(). For more information, check the section about Kinesis Integration in the Spark Structured Streaming documentation.Azure Event HubsFor Azure Event Hubs settings, check the official documentation at Microsoft and the article Delta Live Tables recipes: Consuming from Azure Event Hubs.SummaryDLT is much more than just the \"T\" in ETL. With DLT, you can easily ingest from streaming and batch sources, cleanse and transform data on the Databricks Lakehouse Platform on any cloud with guaranteed data quality.Data from Apache Kafka can be ingested by directly connecting to a Kafka broker from a DLT notebook in Python. Data loss can be prevented for a full pipeline refresh even when the source data in the Kafka streaming layer expired.Get startedIf you are a Databricks customer, simply follow the guide to get started. Read the release notes to learn more about what's included in this GA release. If you are not an existing Databricks customer, sign up for a free trial, and you can view our detailed DLT Pricing here.Join the conversation in the Databricks Community where data-obsessed peers are chatting about Data + AI Summit 2022 announcements and updates. Learn. Network.Last but not least, enjoy the Dive Deeper into Data Engineering session from the summit. In that session, I walk you through the code of another streaming data example with a Twitter live stream, Auto Loader, Delta Live Tables in SQL, and Hugging Face sentiment analysis.Try Databricks for freeGet StartedRelated postsAnnouncing General Availability of Databricks\u2019 Delta Live Tables (DLT)April 5, 2022 by Michael Armbrust, Awez Syed, Paul Lappas, Erika Ehrli, Sam Steiny, Richard Tomlinson, Andreas Neumann and Mukul Murthy in Platform Blog\nToday, we are thrilled to announce that Delta Live Tables (DLT) is generally available (GA) on the Amazon AWS and Microsoft Azure clouds...\nDelta Live Tables Announces New Capabilities and Performance OptimizationsJune 29, 2022 by Paul Lappas and Michael Armbrust in Product\nSince the availability of Delta Live Tables (DLT) on all clouds in April (announcement), we've introduced new features to make development easier, enhanced...\n5 Steps to Implementing Intelligent Data Pipelines With Delta Live TablesSeptember 8, 2021 by Awez Syed and Amit Kara in Platform Blog\nGet an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake Many IT organizations are...\nSee all Product postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/financial-services","text":"Lakehouse for Financial Services - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLakehouse for Financial ServicesPowering the data and AI\u2013driven financial services institution of the futureGet startedSchedule a demoFour data challenges in financial servicesData governance and management\nLack of data agility and model reproducibility makes it challenging to meet the regulatory requirements unique to financial services.Deeper customer insights\nData silos prevent a complete view of customer behaviors, cross-selling opportunities and the insights needed for hyper-personalization at scale.Real-time decisions\nVendor lock-in and disjointed tools hinder the ability to do real-time analytics that drive and democratize smarter financial decisions.Access to third-party data\nLegacy technologies can\u2019t harness financial and customer insights from fast-growing unstructured and alternative data sets and don\u2019t offer open data sharing capabilities to fuel collaboration.Lakehouse for Financial ServicesUnified data and AI platform\nA single platform that brings together all your data and analytics workloads to enable transformative innovations for modern financial services institutions.\n\u00a0\nPartner solutions\nThe world\u2019s leading solution providers are building for the Lakehouse for Financial Services. Take advantage of pre-built offerings that accelerate data-driven transformation.\nTools to accelerate business outcomes\nDatabricks and its partners have created a full range of Solution Accelerators that make it easy to tackle common financial services use cases, from ESG investing to fraud prevention.\nIndustry collaboration\nEnable secure and open data sharing with our data ecosystem \u2014 featuring S&P Global, Intercontinental Exchange, FactSet and Nasdaq \u2014 to unlock innovations that drive sustainable value creation.\nTransforming financial services with\nLakehouse\n\u201cNasdaq\u2019s data and AI vision is powered by Databricks Lakehouse. We use it to process huge amounts of complex financial and alternative data to create data and insights for our clients. Databricks is also an important part of our efforts to modernize data delivery and consumption. It enables us to seamlessly deliver data directly into analytical workspaces, so our clients can analyze and integrate mission-critical data quickly without having to move terabytes of data around.\u201d\n\u2014 Bill Dague, Head of Nasdaq Data Link, NasdaqWhy Lakehouse for Financial Services?\nUnify data and AI on an open and collaborative platform that empowers you to minimize risk, deliver superior customer experiences and accelerate innovationGoverned approach to risk management and compliance\nSimplify the complexity of regulatory reporting, risk management and compliance by securely streamlining the acquisition, processing and transmission of data to empower better data governance practices.Personalized products and services\nUnify a variety of data \u2014 from market to alternative data \u2014 enabling hyper-personalized experiences that drive cross-selling opportunities, customer satisfaction and share of wallet.Real-time insights, smarter decisions\nRapidly ingest all your data sources at scale to make better investment decisions, quickly detect new fraud patterns and bring real-time capabilities to risk management practices.Open data sharing and data monetization\nBring together vast amounts of internal and third-party data to share innovative financial solutions, monetize new data products and deliver advanced analytics capabilities to any cloud or tool without getting locked into proprietary technologies.Download the eBookPartners and solutionsMove toward open formats and the standardization of data for analytics and AIRisk ManagementRapidly deploy data into value-at-risk models to keep up with emerging risks and threats.Get startedLegacy Cards and Core Banking Portfolios ModernizationEnable rapid conversion from external source systems and achieve a fully configurable and industrialized conversion capability.Get startedPersona 360Complete, unify and fully capture customer profiles in a smart data model.Get startedSee all partner solutionsCybersecurity at scaleRapidly detect threats, investigate the impact and reduce risks with Splunk and DatabricksGet startedESG scoringTake a quantitative view into sustainability and ensure companies are accountable for their actionsGet startedModern risk managementAdopt a more agile approach to risk management by unifying data and AI in the LakehouseGet startedIdentify fraud with geospatial analytics and AIUse geospatial data to better understand customer spending behaviors in terms of both who they are and how they bankGet startedTransaction enrichment with merchant classificationAutomate transaction enrichment to better understand your customers\u2019 behaviors and drive hyper-personalizationGet startedRule-based AI models to combat financial fraudModernize fraud-prevention strategies to reduce operational costs and increase customer trustGet startedTimely and reliable transmission of regulatory reportsCombine financial services industry data models with the cloud to enable high governance standards with low development overheadGet startedModernizing investment data platformsUse the full power of financial market data to focus on product delivery for customersGet startedAnti-money laundering (AML)Enable AI-driven use cases like fuzzy match and image analytics to combat money laundering and financial terrorismGet startedSee all solutionsLakehouse for Financial Services in actionSimplify secured deployment of Lakehouse with integrated industry best practices, unified governance and design patternsExplore nowResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on data and AI for financial services.\nExplore resourceseBooks and Infographics[Infographic] Data to Anchor a New Age of Risk ManagementLearn how to easily tap into the power of data and AI in financial servicesLeveraging alternative and third-party data in financial servicesTaking ESG from buzzword to reality with data analytics and AI Preventing fraud with Data + AI: A primer for modern threats Videos and downloadsExplainable and Transparent ESG Investment MethodologiesCybersecurity in Financial ServicesAccelerate Data and AI-Driven Innovation in Financial ServicesESG analytics: explainer videoModernizing risk managementModern Data Investment Platforms with Lakehouse for Financial ServicesIndustry Lakehouse Blueprints Solution SheetBlogsAccelerator for banks and fintechs using credit card transactionsA data-driven approach to environmental, social and governanceBuilding a modern risk management platform in financial servicesUsing your data to stop credit card fraud: Capital One and other best practicesStrategies for modernizing investment data platformsImproving the customer experience with transaction enrichment Key Takeaways for Financial Services at Data + AI Summit 2022Lakehouse for Financial ServicesReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/blog","text":"O Blog DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLoading...ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/glossary","text":"Glossaries Archive | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGlossaryA-ZsearchACID Transactions What is a transaction?\nIn the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a cons{...}AdaGrad Gradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.\nTypes of Gradient Descent\nThere are three primary types of gradient descent {...}Alternative Data What is Alternative Data?\nAlternative data is information gathered by using alternative sources of data that others are not using; &nbsp;non-traditional information sources. Analysis of alternative data can provide insights beyond that which an in{...}Anomaly Detection Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like{...}Apache Hive What is Apache Hive?\nApache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.\nWith exten{...}Apache Kudu What is Apache Kudu?\nApache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows to{...}Apache Kylin What is Apache Kylin?\nApache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/S{...}Apache Spark What Is Apache Spark?\nApache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.&nbsp;Apache Spark started in 2009 as a research project at {...}Apache Spark as a Service What is Apache Spark as a Service?\nApache Spark is an open source cluster computing framework for fast real-time large-scale data processing.&nbsp;Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently ra{...}Artificial Neural Network What is an Artificial Neural Network?\nAn artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.\nHow Do Artificial Neural Networks Work?\nArtificial Neural Networks can be best viewed{...}Automation Bias What is Automation Bias?\nAutomation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, {...}Bayesian Neural Network What Are Bayesian Neural Networks?\nBayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology {...}Big Data Analytics The Difference Between Data and Big Data Analytics\nPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relat{...}Bioinformatics Bioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.\nBioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data.{...}Catalyst Optimizer At the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional program{...}Complex Event Processing What is Complex Event Processing [CEP]?\nComplex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being s{...}Continuous Applications Continuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate{...}Convolutional Layer In deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language {...}Data Analysis Platform What is a Data Analysis Platform?\nA data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visua{...}Data Governance What is Data Governance?\nData governance is the oversight to ensure data brings value and supports the business strategy. Data governance is more than just a tool or a process. It aligns data-related requirements to the business strategy using a f{...}Data Lakehouse What is a Data Lakehouse?\nA data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business int{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Data Sharing What is data sharing?\nData sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or external{...}Data Vault What is a data vault?\nA data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.\nHubs represent core business concepts, {...}Data Warehouse What is a data warehouse?\nA data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business i{...}Databricks Runtime Databricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of {...}DataFrames What is a DataFrame?\nA DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are {...}Datasets Datasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recal{...}Deep Learning What is Deep Learning?\nDeep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referre{...}Demand Forecasting What is demand forecasting?\nDemand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.\nRet{...}Dense Tensor Dense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software prod{...}Digital Twin What is a Digital Twin?\nThe classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers {...}DNA Sequence What is a DNA Sequence?\nThe DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). &nbsp;Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine {...}Extract Transform Load (ETL) What is ETL?\nAs the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to pr{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Genomics Genomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DN{...}Hadoop Cluster What Is a Hadoop Cluster?\nApache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by{...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hadoop Ecosystem What is the Hadoop Ecosystem?\nApache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of{...}Hash Buckets In computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from whic{...}Hive Date Function What is a Hive Date Function?\nHive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditi{...}Hosted Spark What is Hosted Spark?\nApache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Py{...}Jupyter Notebook What is a Jupyter Notebook?\nA Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.\nWhat are Jupyter Notebooks used fo{...}Keras Model What is a Keras Model?\nKeras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.&nbsp;Keras has become one of {...}Lakehouse for Retail What is Lakehouse for Retail?\nLakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.\nLakehouse fo{...}Lambda Architecture What is Lambda Architecture?\nLambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solv{...}Machine Learning Library (MLlib) Apache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and mod{...}Machine Learning Models What is a machine learning Model?\nA machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recogni{...}Managed Spark What is Managed Spark?\nA managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, m{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}Materialized views Delta Pipelines \/ Materialized Views in Databricks Delta\nIntro\nDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve dat{...}Medallion Architecture What is a medallion architecture?\nA medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through ea{...}ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and c{...}MLOps What is MLOps?\nMLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. M{...}Model Risk Management Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and{...}Neural Network What is a Neural Network?\nA neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an outpu{...}Open Banking What is Open Banking?\nOpen banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of custo{...}Orchestration What is Orchestration?\nOrchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of {...}Overall Equipment Effectiveness What is Overall Equipment Effectiveness?\nOverall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to{...}pandas DataFrame \nWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as ef{...}Parquet What is Parquet?\nApache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in {...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}Predictive Analytics What is Predictive Analytics?\nPredictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.\nHow Does Predictive Analytics Work?\nPredictive analytics {...}Predictive Maintenance What is predictive maintenance?\nPredictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rath{...}PyCharm PyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to crea{...}PySpark What is PySpark?\nApache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface wi{...}Real-Time Retail What is real-time data for Retail?\nReal-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. {...}Resilient Distributed Dataset (RDD) \nRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API {...}Snowflake Schema What is a snowflake schema?\nA snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and re{...}Spark API If you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDs\nWhat are Resilient Distributed Datasets?\nRDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are {...}Spark Applications Spark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; res{...}Spark Elasticsearch What is Spark Elasticsearch?\nSpark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and r{...}Spark SQL Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can al{...}Spark Streaming Apache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Stre{...}Spark Tuning What is Spark Performance Tuning?\nSpark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also preven{...}Sparklyr What is Sparklyr?\nSparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little l{...}SparkR SparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follow{...}Sparse Tensor Python offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library. Sptensor is a class that represents the sparse tensor. A spa{...}Star Schema What is a star schema?\nA star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The st{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a stre{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API What is the Tensorflow Estimator API?\nEstimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow {...}Transformations What Are Transformations?\nIn Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d {...}Tungsten What is the Tungsten Project?\nTungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance{...}Unified AI Framework Unified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute r{...}Unified Data Analytics Unified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it e{...}Unified Data Analytics Platform Databricks' Unified Data Analytics Platform&nbsp;helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at mass{...}Unified Data Warehouse What is a Unified Data Warehouse?\nA unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in {...}What Is Hadoop? Apache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them{...}ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/data-science","text":"Data Science | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData ScienceCollaborative data science at scaleTry for freeSchedule a demoDive deeper into Data Science on DatabricksDatabricks NotebooksIDE IntegrationsDatabricks WorkflowsReposMachine LearningStreamline the end-to-end data science workflow \u2014 from data prep to modeling to sharing insights \u2014 with a collaborative and unified data science environment built on an open\u00a0lakehouse\u00a0foundation. Get quick access to clean and reliable data, preconfigured compute resources,\u00a0IDE integration, multi-language support, and built-in advanced visualization tools for maximum flexibility for data analytics teams.Collaboration across the entire data science workflowWrite code in Python, R, Scala and SQL, explore data with interactive visualizations and discover new insights with Databricks Notebooks. Confidently and securely share code with coauthoring, commenting, automatic versioning, Git integrations, and role-based access controls.Focus on the data science, not the infrastructureYou don\u2019t have to be limited by how much data fits on your laptop anymore or how much compute is available to you. Quickly migrate your local environment to the cloud and connect notebooks to your own personal compute and auto-managed clusters.Use your favorite local IDE with scalable computeThe choice of an IDE is very personal and affects productivity significantly.\u00a0Connect your favorite IDE\u00a0to Databricks, so that you can still benefit from limitless data storage and compute. Or simply use RStudio or JupyterLab directly from within Databricks for a seamless experience.Get data ready for data scienceClean and catalog all your data \u2014 batch,\u00a0streaming, structured or unstructured \u2014 in one place with\u00a0Delta Lake\u00a0and make it discoverable to your entire organization via a centralized data store. As data comes in, automatic quality checks ensure data meets expectations and is ready for analytics. As data evolves with new data and further transformations, data versioning ensures you can meet compliance needs.Low-code, visual tools for data explorationUse\u00a0visual tools\u00a0natively from within Databricks notebooks to prepare, transform and analyze your data, enabling teams across expertise levels to work with data. Once done with your data transformations and visualizations, you can generate the code that\u2019s running in the background \u2014 saving you time from writing boilerplate code so you can spend more time on high-value work.Discover and share new insightsEasily share and export results by quickly turning your analysis into a dynamic\u00a0dashboard. The dashboards are always up to date and can also run interactive queries. Cells, visualizations or notebooks can be shared with role-based access control and exported in multiple formats, including HTML and IPython Notebook.Migrate to DatabricksTired of the data silos, slow performance and high costs associated with legacy systems like Hadoop and enterprise data warehouses? Migrate to the Databricks Lakehouse: the modern platform for all your data, analytics and AI use cases.Migrate to DatabricksResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on data science and machine learning topics.\nExplore resourcesReports and eBooksThe Big Book of Data ScienceThe Art of Collaborative Data Science at ScaleModern Cloud Data PlatformMLflow \u2013 An open source machine learning platformExplore the new Delta Sharing solutionDatabricks named a Leader in 2021 Gartner\u00ae Magic Quadrant\u2122 in both DBMS and DSMLMigration Guide: Hadoop to DatabricksBlogs5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse ArchitectureVirtual EventsStep-by-step Guide to Hadoop MigrationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-carbin\/#","text":"Michael Carbin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer Science at Massachusetts Institute of TechnologyBack to speakersMichael Carbin is an associate professor in MIT\u2019s Department of Electrical Engineering and Computer Science and a principal investigator at the Computer Science and Artificial Intelligence Laboratory, where he leads the Programming Systems Group. His group investigates the semantics, design, and implementation of systems that operate in the presence of uncertainty in their environment (perception), implementation (neural networks or approximate transformations), or execution (unreliable hardware). Carbin has received a Sloan Research Fellowship, a Facebook Research Award, a Google Faculty Research Award and an NSF Career Award. He earned a BS in computer science at Stanford University and an MS and PhD in electrical engineering and computer science from MITLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ifigeneia-derekli\/#","text":"Ifigeneia Derekli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIfigeneia DerekliField Engineering Manager & Unity Catalog Specialist at DatabricksBack to speakersField Engineering Manager at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vuong-nguyen\/#","text":"Vuong Nguyen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVuong NguyenSenior Solutions Architect at DatabricksBack to speakersA Senior Solutions Architect at Databricks based in London, with a strong passion to help customers with their data governance, data sharing and platform automation needs. Regular contributor to open source projects such as the Databricks Terraform Provider and Delta Sharing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matei-zaharia\/#","text":"Matei Zaharia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflow at DatabricksBack to speakersMatei Zaharia is a Cofounder and Chief Technologist at Databricks as well as an Assistant Professor of Computer Science at Stanford. He started the Apache Spark project during his PhD at UC Berkeley in 2009, and has worked broadly on other widely used data and machine learning software, including MLflow, Delta Lake and Apache Mesos. He works on a wide variety of projects in data management and machine learning at Databricks and Stanford. Matei\u2019s research was recognized through the 2014 ACM Doctoral Dissertation Award, an NSF CAREER Award, and the US Presidential Early Career Award for Scientists and Engineers (PECASE).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/abhishek-patel\/#","text":"Abhishek Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAbhishek PatelHead of Databricks COE at LTIMindtreeBack to speakersAbhishek Patel heads the Databricks COE at LTIMindtree. He manages Databricks Strategy, Consulting and Tech initiatives for the COE. Abhishek Patel has over 22 years of experience helping customers build data platforms and analytical systems. He has played pivotal role in architecting and assisting customers with multiyear large-scale data modernization and migration projects to cloud data platforms like Azure and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vinod-marur\/#","text":"Vinod Marur - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVinod MarurSVP of Engineering at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/corey-zumar","text":"Corey Zumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCorey ZumarSoftware Engineer at DatabricksBack to speakersCorey has been working as a Software Engineer at Databricks for the last 4 years and has been an active contributor to and maintainer of MLflow since its first release.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rashmi-kansakar","text":"Rashmi Kansakar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRashmi KansakarDirector, Data & Cloud Architect at 84.51Back to speakersAs Director of Data & Cloud Architect at 84.51\u02da, Rashmi is responsible for designing next-generation data solutions focusing on identifying needs and opportunities to elevate & harmonize data into valuable data assets. He helps to build scalable technology to drive insights and science to understand Kroger\u2019s customers better and improve the shopping experience. Rashmi is as an Adjunct Professor at the University of Cincinnati, where he shares his knowledge and expertise with the next generation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks als Leader benannt | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks als Leader benanntCloud Database Management SystemsDatabricks von Gartner\u00ae im Magic Quadrant\u2122 CDBMS 2022 als Leader benanntDatabricks ist stolz darauf, bekannt geben zu k\u00f6nnen, dass Gartner uns im zweiten Jahr in Folge im Magic Quadrant 2022 f\u00fcr Cloud Database Management Systems als Leader benannt hat.Wir glauben, dass diese Anerkennung unsere Vision f\u00fcr das Lakehouse als eine einzige, einheitliche Plattform f\u00fcr Datenmanagement und -entwicklung sowie f\u00fcr Analytics und KI best\u00e4tigt.Laden Sie den Bericht herunter, um zu erfahren, warum Gartner Databricks als Leader benannt hat, und erhalten Sie zus\u00e4tzliche Einblicke in die Vorteile, die eine Lakehouse-Plattform f\u00fcr Ihr Unternehmen bieten kann.Den Bericht lesen Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/raghu-jayachandran","text":"Raghu Jayachandran - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRaghu JayachandranSenior Manager Enterprise Data at RaceTrac Inc.Back to speakersRaghu Jayachandran is a Senior Manager of Enterprise Data at RaceTrac Inc, a convenience store retailer. His responsibilities are data platform innovation, technology modernization, and strategizing RaceTrac data. He has been an IT professional for over 20 years and has executed data solutions for manufacturing, financial services, government agencies, and retail sectors. \nHe earned a bachelor\u2019s degree in physics, a master\u2019s degree in computer applications, and is pursuing an Executive MBA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alessandro-garavaglia\/#","text":"Alessandro Garavaglia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlessandro GaravagliaLead ML Engineer at GucciBack to speakersAlessandro holds a Ph.D. in Applied Mathematics with a dissertation about stochastic models for complex networks. He spent some years in consulting, working both as a Data Scientist and as Cloud Developer. He joined Gucci in 2021, where as Lead ML Engineer he is the architect and administrator of the Data Science Platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ellen-sulcs","text":"Ellen Sulcs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEllen SulcsDirector, Data Products & Engineering at T-MobileBack to speakersEllen Sulcs started her career at T-Mobile in 2017 building algorithms to predict the network experience of mobile devices as they were activated on T-Mobile\u2019s network. The algorithms turned into a mobile app and API and led her down a path to Product Management. In 2018, she was given the opportunity to establish a Data Product Management practice at T-Mobile which slowly evolved into leading a full-scale software and data engineering organization.\nPrior to her career at T-Mobile, Ellen dropped out of her PhD program to pursue a career as a Data Scientist in the healthcare industry. In her free time, Ellen has a child, so she doesn\u2019t have free time. But she was once an avid rower, cook and hiking enthusiast.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/mlops-virtual-event","text":"MLOps Virtual Event | DatabricksMLOps Virtual EventStandardizing MLOps at ScaleAvailable on-demandAs organizations continue to develop their machine learning (ML) practice, there\u2019s a growing need for robust and reliable platforms capable of handling the entire ML lifecycle. The emergence of MLOps is promising, but many challenges remain.Join our interactive event to hear about the latest developments from Databricks geared toward automating MLOps \u2014 including new Git and CI\/CD integrations, autologging of experiments, model explainability and model serving.We\u2019ll also cover:Best practices from domain experts to operationalize ML at scale, from experimentation to productionA checklist of the capabilities you\u2019ll need, common pitfalls, as well as technological and organizational challenges \u2014 and how to overcome themPresentations will be enhanced with demos, success stories and learnings from experts who have deployed these pipelines for predictive analytics. A live Q&A and discussion will keep this event engaging for data science practitioners and leaders alike.SpeakersTristan NixonSolutions ArchitectDATABRICKSTristan Nixon is a Solutions Architect with Databricks. He was born and raised in Toronto, Canada, where he studied Cognitive Science & A.I. under such luminaries of the field as Geoffrey Hinton, one of the fathers of neural networks. He has worked in data engineering and data science for the past 15 years, across a broad range of industries from education and telecommunications to chemicals manufacturing among others. He specializes in MLOps, natural language processing and timeseries forecasting. He now lives in sunny southern California, and is learning to sail.\nDigan ParikhSolutions ArchitectDATABRICKSDigan is a Solutions Architect at Databricks helping customers understand the Databricks platform. He cares about delivering high-value outcomes for the most important business challenges while providing an unparalleled customer experience. He\u2019s passionate about learning new technologies and recognizing how they can be leveraged to solve organizations\u2019 business problems.Watch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabian-jakobs\/#","text":"Fabian Jakobs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabian JakobsSr Staff Software Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/customer-entity-resolution","text":"Customer Entity Resolution | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorCustomer Entity ResolutionPre-built code sample data and step-by-step instructions ready to go in a Databricks notebookGet startedBuild the foundation for a customer 360The key to building personalized experiences is deriving actionable insights from every bit of information that can be gathered about a customer. Data generated through sales transactions, website browsing, product ratings, customer surveys, support center calls, third-party data purchased from data aggregators, online trackers, and more can come together to form a 360-degree view of the customer.But in order to build a true customer 360 leveraging all that data, organizations must establish common customer identities, linking together customer records across the disparate data sets so they can collect all of the common information about one customer \u2013 this is called customer entity resolution.Get started with our Solution Accelerator for Customer Entity Resolution to build the foundation for a customer 360 by:Translating text attributes (like name, address, phone number) into quantifiable numerical representationsTraining ML models to determine if these numerical labels form a matchScoring the confidence of each matchDownload notebookResourcesBlogLearn moreSolution AcceleratorLearn moreWebinarLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-conover","text":"Mike Conover - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike ConoverSoftware Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks VenturesInvesting in the future of data, analytics and AI\nDatabricks Ventures invests in innovative companies that share our view of the future for data, analytics and AI. Our inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.Portfolio company benefitsExclusive insight into the product roadmap and support for building deep technical integrationsGuidance and best practices from the network of Databricks mentorsBroader reach by partnering with Databricks go-to-market programsLakehouse Fund investment\nfocusA shared vision to build the future of data, analytics and AI on the lakehouse architectureInvestments in early to growth-stage companies in partnership with a lead investorProjects and entrepreneurs that share Databricks\u2019 commitment to open source and building on open platforms, much like the Databricks LakehouseOur PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\nLearn moreArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\nLearn moredbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\nLearn moreHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.Learn moreThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.Learn moreThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.Learn moreLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.Learn moreMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.Learn morePerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.Learn moreRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.Learn moreTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.Learn moreFAQsWhy partner with Databricks Ventures?\nDepending on the size and stage of the investment, Databricks will provide unique access to product roadmap direction, technical integration support, and go-to-market support; access to Databricks mentors for guidance and best practices; and exposure in Databricks\u2019 global go-to-market programs, including our Data + AI Summit series.What are Databricks Ventures\u2019 investment criteria?\nWe are investing in innovative founders of private companies who share our view of the future for data and AI and are committed to extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.What stages does Databricks invest in?\nWe invest in early through growth-stage private companies within the data, analytics and AI ecosystem.Does Databricks Ventures lead investment rounds?\nNo, we do not lead rounds. Our strategy is to invest alongside a lead institutional investor.What is Databricks Ventures\u2019 typical investment size?\nDatabricks Ventures takes minority positions in rounds led by institutional VCs; typical check size varies based on stage of company and size of funding round.Does Databricks take board seats?No, Databricks does not plan to take board seats in portfolio companies.Build your startup on DatabricksDatabricks for Startups offers free credits, expert advice and go-to-market support.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maria-vechtomova\/#","text":"Maria Vechtomova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaria VechtomovaML Engineer at Ahold DelhaizeBack to speakersMaria is a Senior Machine Learning Engineer at Ahold Delhaize. Maria is bridging the gap between data scientists infra and IT teams at different brands and focuses on standardization of machine learning operations across all the brands within Ahold Delhaize. During more than nine years in Data and Analytics, Maria tried herself in different roles, from data scientist to a machine learning engineer, was part of teams in various domains, and have built broad knowledge. Maria believes that a model only starts living when it is in production. For this reason, last seven years, her focus was on the automation and standardization of processes related to machine learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/events","text":"\u00c9v\u00e9nements Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOW\u00c9v\u00e9nements DatabricksRencontres, webinaires, conf\u00e9rences... d\u00e9couvrez les prochains \u00e9v\u00e9nements DatabricksData + AI Summit 202326\u201329 juinChoisissez votre exp\u00e9rience\u00a0: venez en personne ou assistez en ligne aux conf\u00e9rences et \u00e0 une s\u00e9lection de sessions en directS'inscrireLoading...Browse All Upcoming EventsProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/br\/legal\/privacynotice#dbadditionalinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/contact\/office-locations","text":"Office locations | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWorldwide locationsSpanning four continents and twelve countries, Databricks has a global presence in every major market.\nAmericasSan Francisco, CA\nWorld Headquarters\n160 Spear Street 15th Floor\nSan Francisco, CA 94105\nUSA\nSilicon Valley, CA\n351 E Evelyn Ave\nMountain View, CA 94041\nUSA\nWashington, DC\n1660 International Drive\nSuite 600\nMcLean, VA 22102\nUSA\nPlano, TX\nPlano, TX\n6900 Dallas Pkwy\nSuite 02-106\nPlano, TX 75024\nUSA\nSeattle, WA\n2033 6th Ave\nSuite 600\nSeattle, WA 98121\nUSA\nBellevue, WA\n500 108th Ave NE\nSuite 1820\nBellevue, WA 98004\nUSA\nBoston, MA\n125 High Street\nSuite 220\nBoston, MA 02110\nUSA\nBerkeley, CA\n2120 University Ave.\nSuite 722\nBerkeley, CA 94704\nUSA\nNew York City, NY\n11 W. 42nd Street\n30th Floor\nNew York, NY 10036\nUSA\nToronto, ON\n150 King Street West\nSuite 206\nToronto, ON M5H1J9\nCanada\nAtlanta, GA\n756 W Peachtree St NW\nSuite 03W114\nAtlanta, GA\n30308\nChicago, IL\n311 W. Monroe Street\nSuite 306\nChicago, IL 60606\nUSA\nDenver, CO\n1200 17th Street\nSuite 10-161\nDenver, CO 80202\nUSA\nSan Jose, CR\nAmerica Free Zone (AFZ), Building C11,\nSan Francisco,\u00a0\nHeredia, 40103\nCosta Rica\nS\u00e3o Paulo, BR\nAvenida Brigadeiro Faria Lima, no 3.729, Edif\u00edcio\nBirmann 29 (Ed. Ant\u00f4nio Alves F. 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Venkat Sivasubramanian\u6c0f\u300cUnity Catalog \u306f\u3001\u79c1\u305f\u3061\u306b\u3068\u3063\u3066\u30b2\u30fc\u30e0\u30c1\u30a7\u30f3\u30b8\u30e3\u30fc\u3068\u306a\u308a\u307e\u3057\u305f\u3002\u30a2\u30ca\u30ea\u30b9\u30c8\u306f\u3001Databricks \u306e\u30ef\u30fc\u30af\u30b9\u30da\u30fc\u30b9\u3067 AWS \u306e\u5916\u90e8\u30c6\u30fc\u30d6\u30eb\u306b\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001Delta Lake \u306e\u30c6\u30fc\u30d6\u30eb\u3068\u7d50\u5408\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002Glue \u30c6\u30fc\u30d6\u30eb\u3092\u79fb\u884c\u3059\u308b\u3053\u3068\u306a\u304f\u3001Databricks SQL \u306e\u6027\u80fd\u306e\u30e1\u30ea\u30c3\u30c8\u3092\u4eab\u53d7\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u3092\u79fb\u52d5\u3057\u306a\u304f\u3066\u3082\u3001\u30c1\u30fc\u30e0\u9593\u306e\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u300d\u30ef\u30fc\u30ca\u30fc\u30fb\u30d6\u30e9\u30b6\u30fc\u30ba\u30fb\u30c7\u30a3\u30b9\u30ab\u30d0\u30ea\u30fc \u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u90e8\u9580\u30de\u30cd\u30fc\u30b8\u30e3\u30fc Rajat Gupta \u6c0f\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u57fa\u8abf\u8b1b\u6f14\u3068\u30a6\u30a7\u30d3\u30ca\u30fc\u3010\u57fa\u8abf\u8b1b\u6f14 Data + AI Summit 2022\u3011\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u3068\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u5171\u6709[\u30aa\u30f3\u30c7\u30de\u30f3\u30c9\u30a6\u30a7\u30d3\u30ca\u30fc]\u30c7\u30fc\u30bf\u304a\u3088\u3073AI\u30ac\u30d0\u30ca\u30f3\u30b9\u3092\u7c21\u7d20\u5316\u3059\u308b\u65b9\u6cd5eBook \u3068\u30d6\u30ed\u30b0\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u30ac\u30d0\u30ca\u30f3\u30b9Unity\u30ab\u30bf\u30ed\u30b0\u306e\u30c7\u30fc\u30bf\u30ea\u30cd\u30fc\u30b8\u306e\u4e00\u822c\u63d0\u4f9b\u958b\u59cb\u3092\u767a\u8868\u30c7\u30fc\u30bf\u30ea\u30cd\u30fc\u30b8 With Unity Catalog\u306e\u63d0\u4f9b\u958b\u59cb\u3092\u767a\u8868\u30c7\u30fc\u30bf\u30ab\u30bf\u30ed\u30b0 Databricks Unity Catalog \u3068\u306f\uff1a\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u3068 AI 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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christina-taylor","text":"Christina Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristina TaylorSenior Staff Data Engineer at Catalyst SoftwareBack to speakersChristina is passionate about distributed computing, mutilcloud architecture, scalable data pipelines, the latest and greatest in the open source community. An intensely curious lifelong learner, she builds future-proof open data systems that support advanced analytics, data science, and customer facing use cases. She also has a keen interest in interdisciplinary areas such as Cloud FinOps, DevOps and MLOps. You can find her at Linux Foundation events and educational portals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/preventative-maintenance-for-heavy-equipment-with-predictive","text":"Improving Predictive Maintenance for Manufacturers with Data + AI | DatabricksWatch NowImproving Predictive Maintenance for Manufacturers with Data + AIMaintaining equipment on a shop floor, in a fleet or in the field is a complex endeavor for most companies. Each piece of equipment can generate terabytes of unstructured and semistructured data each day and be located around the globe and in the sky.Knowing when equipment needs maintenance is critical to companies. Unplanned downtime is a major disruption to our businesses. A failure of a key component can cost millions of dollars of lost production per day in addition to downstream impacts to production and customer agreements. An important way to save time and money is to use machine learning to better predict outages earlier and plan maintenance work before the failure occurs.In this session, Databricks Global Manufacturing and Logistics Leader, Rob Saker, will lead an in-depth discussion on how manufacturers are transforming their business with data and AI, taking advantage of internal and external data sources across a range of unstructured, semistructured and structured data to deliver insights in near real-time.Rob will be joined by a Databricks solution architect who will walk through how to build a real-time end-to-end data pipeline from the IoT device with streaming ingestion for any structure of data, and use Databricks ML to predict specific component failures against these data sets to ensure greater quality, efficiency and availability. And we will walk through our free Predictive Maintenance Solution Accelerator that you can use following the webinar to start improving predictive maintenance inside your organization.Agenda at a glanceIntroduction to Data + AI in Industry 4.0IoT Predictive MaintenanceQ&ASpeakerRob SakerDatabricks Global Manufacturing and Logistics LeaderDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/06\/05\/automate-continuous-integration-and-continuous-delivery-on-databricks-using-databricks-labs-ci-cd-templates.html","text":"How to Use Databricks Labs CI\/CD Tools to Automate Development Pipelines - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAutomate continuous integration and continuous delivery on Databricks using Databricks Labs CI\/CD Templatesby Michael Shtelma and Thunder ShiviahJune 5, 2020 in Engineering BlogShare this postCONTENTSOverviewWhy do we need yet another deployment framework?Simplifying CI\/CD on Databricks via reusable templatesDevelopment lifecycle using Databricks DeploymentsHow to create and deploy a new data project with Databricks Labs CI\/CD Templates in 10 minutes?Create a new project using the Databricks Labs CI\/CD Templates\u00a0 project templateLet\u2019s deploy our project to target Databricks workspaceTest Automation using Databricks Labs CI\/CD TemplatesDeploying production pipelines using Databricks DeploymentsDependency and configuration managementHow to learn moreOutlook and next stepsHow to contribute?OverviewDatabricks Labs continuous integration and continuous deployment (CI\/CD) Templates are an open source tool that makes it easy for software development teams to use existing CI tooling with Databricks Jobs. Furthermore, it includes pipeline templates with Databricks\u2019 best practices baked in that run on both Azure and AWS so developers can focus on writing code that matters instead of having to set up full testing, integration and deployment systems from scratch.CI\/CD Templates in 3 steps:pip install cookiecuttercookiecutter https:\/\/github.com\/databrickslabs\/cicd-templates.gitAnswer the interactive questions in the terminal such as which cloud you would like to use and you have a full working pipeline.pip install databricks_cli && databricks configure --tokenStart pipeline on Databricks by running .\/run_pipeline.py pipelines in your project main directoryAdd your databricks token and workspace URL to github secrets and commit your pipeline to a github repo.Your Databricks Labs CI\/CD pipeline will now automatically run tests against databricks whenever you make a new commit into the repo. When you are ready to deploy your code, make a github release and templates will automatically package and deploy your pipeline to databricks as a job.That\u2019s it! You now have a scalable working pipeline which your development team can use and develop off of. Additionally, you can always modify the template to be more specific to your team or use-case to ensure future projects can be set up with ease.\nFor the remainder of this post, we\u2019ll go into depth about why we decided to create Databricks Labs CI\/CD templates, what is planned for the future of the project, and how to contribute.Why do we need yet another deployment framework?As projects on Databricks grow larger, Databricks users may find themselves struggling to keep up with the numerous notebooks containing the ETL, data science experimentation, dashboards etc. While there are various short term workarounds such as using the %run command to call other notebooks from within your current notebook, it\u2019s useful to follow traditional software engineering best practices of separating reusable code from pipelines calling that code. Additionally, building tests around your pipelines to verify that the pipelines are also working is another important step towards production-grade development processes.Finally, being able to run jobs automatically upon new code changes without having to manually trigger the job or manually install libraries on clusters is important for achieving scalability and stability of your overall pipeline. In summary, to scale and stabilize our production pipelines, we want to move away from running code manually in a notebook and move towards automatically packaging, testing, and deploying our code using traditional software engineering tools such as IDEs and continuous integrationI tools. Indeed, more and more data teams are using Databricks as a runtime for their workloads preferring to develop their pipelines using traditional software engineering practices: using IDEs, GIT and traditional CI\/CD pipelines. These teams usually would like to cover their data processing logic with unit tests and perform integration tests after each change in their version control system.\nThe release process is also managed using a version control system: after a PR is merged into the release branch, integration tests can be performed and in a case of positive results\u00a0 deployment pipelines can be also updated. Bringing a new version of pipelines to production workspace is also a complex process since they can have different dependencies, like configuration artifacts, python and\/or maven libraries and other dependencies. In most cases, different pipelines can depend on different versions of the same artifact(s).Simplifying CI\/CD on Databricks via reusable templatesMany organizations have invested many resources into building their own CI\/CD pipelines for different projects. All those pipelines have a lot in common: basically they build, deploy and test some artifacts. In the past, developers were also investing long hours in developing different scripts for building, testing and deploying of applications before CI tools made most of those tasks obsolete: conventions introduced by CI tools made it possible to provide developers with the frameworks which can implement most of those tasks in an abstract way so that they can be applied to any project which follows these conventions. For example Maven has introduced such conventions in Java development, which made it possible to automate most of the build process, which were implemented in huge ant scripts.Databricks Labs CI\/CD Templates makes it easy to use existing CI\/CD tooling, such as Jenkins,\u00a0 with Databricks; Templates contain pre-made code pipelines created according to Databricks best practices. Furthermore, Templates allow teams to package up their CI\/CD pipelines into reusable code to ease the creation and deployment of future projects. Databricks Labs CI\/CD Templates introduces similar conventions for Data Engineering and Data Science projects which provide data practitioners using Databricks with abstract tools for implementing CI\/CD pipelines for their data applications.\nLet us go deeper into the conventions we have introduced. Most of the data processing logic including data transformations, feature generation logic, model training, etc should be developed in the python package. This logic can be utilized in a number of production pipelines that can be scheduled as jobs. The aforementioned logic can be also tested using local unit tests that test individual transformation functions and integration tests. Integration tests are run on Databricks workspace and can test the data pipelines as a whole.Development lifecycle using Databricks DeploymentsData Engineers and Data Scientists can rely on Databricks Labs CI\/CD Templates for testing and deploying the code they develop in their IDEs locally in Databricks. Databricks Labs CI\/CD Templates provides users with the reusable data project template that can be used to jumpstart the development of a new data use case. This project will have the following structure: Data ingestion, validation, and transformation logic, together with feature engineering and machine learning models, can be developed in the python package. This logic can be utilized by production pipelines and be tested using developer and integration tests. Databricks Labs CI\/CD Templates can deploy production pipelines as Databricks Jobs, including all dependencies, automatically. These pipelines must be placed in the \u2018pipelines\u2019 directory and can have their own set of dependencies, including different libraries and configuration artifacts. Developers can utilize a local mode of Apache Spark or Databricks Connect to test the code while developing in IDE installed on their laptop. In case they would like to run these pipelines on Databricks, they can use the Databricks Labs CI\/CD Templates CLI. Developers can also utilize the CLI to kick off integration tests for the current state of the project on Databricks.After that, users can push changes to GitHub, where they will be automatically tested on Databricks using GitHub Actions configuration. After each push, GitHub Actions starts a VM that checks out the code of the project and runs the local pytest tests in this VM. If these tests were successful, it will build the python wheel and deploy it along all other dependencies to Databricks and run developer tests on Databricks.\nAt the end of the development cycle, the whole project can be deployed to production by creating a GitHub release, which will kick off integration tests in Databricks and deployment of production pipelines as Databricks Jobs. In this case the CI\/CD pipeline will look similarly to the previous one, but instead of developer tests, integration tests will be run on Databricks and if they are successful, the production job specification on Databricks will be updated. How to create and deploy a new data project with Databricks Labs CI\/CD Templates in 10 minutes?Create a new project using the Databricks Labs CI\/CD Templates\u00a0 project templateInstall Cookiecutter python package: pip install cookiecutterCreate your project using our cookiecutter template: cookiecutter\u00a0 https:\/\/github.com\/databrickslabs\/cicd-templates.gitAnswer the questions\u2026After that, the new project will be created for you. It will have the following structure:\n\n    .\n    \u251c\u2500\u2500 cicd_demo\n    \u2502 \u00a0 \u251c\u2500\u2500 __init__.py\n    \u2502 \u00a0 \u251c\u2500\u2500 data\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 __init__.py\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 make_dataset.py\n    \u2502 \u00a0 \u251c\u2500\u2500 features\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 __init__.py\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 build_features.py\n    \u2502 \u00a0 \u251c\u2500\u2500 models\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 __init__.py\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 predict_model.py\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 train_model.py\n    \u2502 \u00a0 \u2514\u2500\u2500 visualization\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 __init__.py\n    \u2502 \u00a0 \u00a0 \u00a0 \u2514\u2500\u2500 visualize.py\n    \u251c\u2500\u2500 create_cluster.py\n    \u251c\u2500\u2500 deployment\n    \u2502 \u00a0 \u2514\u2500\u2500 databrickslabs_mlflowdepl-0.2.0-py3-none-any.whl\n    \u251c\u2500\u2500 deployment.yaml\n    \u251c\u2500\u2500 dev-tests\n    \u2502 \u00a0 \u251c\u2500\u2500 pipeline1\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u2502 \u00a0 \u2514\u2500\u2500 pipeline2\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u251c\u2500\u2500 docs\n    \u2502 \u00a0 \u251c\u2500\u2500 Makefile\n    \u2502 \u00a0 \u251c\u0000\u2500\u2500 commands.rst\n    \u2502 \u00a0 \u251c\u2500\u2500 conf.py\n    \u2502 \u00a0 \u251c\u2500\u2500 getting-started.rst\n    \u2502 \u00a0 \u251c\u2500\u2500 index.rst\n    \u2502 \u00a0 \u2514\u2500\u2500 make.bat\n    \u251c\u2500\u2500 integration-tests\n    \u2502 \u00a0 \u251c\u2500\u2500 pipeline1\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u2502 \u00a0 \u2514\u2500\u2500 pipeline2\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u251c\u2500\u2500 notebooks\n    \u251c\u2500\u2500 pipelines\n    \u2502 \u00a0 \u251c\u2500\u2500 pipeline1\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u2502 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u2502 \u00a0 \u2514\u2500\u2500 pipeline2\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_aws.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u251c\u2500\u2500 job_spec_azure.json\n    \u2502 \u00a0 \u00a0 \u00a0 \u2514\u2500\u2500 pipeline_runner.py\n    \u251c\u2500\u2500 requirements.txt\n    \u251c\u2500\u2500 run_pipeline.py\n    \u251c\u2500\u2500 runtime_requirements.txt\n    \u251c\u2500\u2500 setup.py\n    \u2514\u2500\u2500 tests\n    \u2514\u2500\u2500 test_smth.py\n    <\/a>The name of the project we have created is \u2018cicd_demo\u2019, so the python package name is also \u2018cicd_demo\u2019, so our transformation logic will be developed in the \u2018cicd_demo\u2019 directory. It can be used from the pipelines that will be placed in \u2018pipelines\u2019 directory. In \u2018pipelines\u2019 directory we can develop\u00a0 a number of pipelines, each of them in its own directory.Each pipeline must have an entry point python script, which must be named \u2018pipeline_runner.py\u2019. In this project, we can see two sample pipelines created. Each of these pipelines has python script and job specification json file for each supported cloud. These files can be used to define cluster specification (e.g., number of nodes, instance type, etc.), job scheduling settings, etc.\n\u2018Dev-tests\u2019 and \u2018integration-tests\u2019 directories are used to define integration tests that test pipelines in Databricks. They should also utilize the logic developed in the python package and evaluate the results of the transformations.Let\u2019s deploy our project to target Databricks workspaceDatabricks Deployments is tightly integrated with GitHub Actions. We will need to create a new GitHub repository where we can push our code and where we can utilize GitHub Actions to test and deploy our pipelines automatically. In order to integrate GitHub repository with the Databricks workspace, workspace URL and Personal Authentication token (PAT) must be configured as GitHub secrets. Workspace URL must be configured as DATABRICKS_HOST secret and token as DATABRICKS_TOKEN.Now we can initialize a new git repository in the project directory. After that, we can add all files to git and push them to the remote GitHub repository. After we have configured our tokens and proceeded with our first push GitHub Actions will run dev-test automatically on target Databricks Workspace and our first commit will be marked green if the tests are successful.\nIt is possible to initiate run of production pipelines or individual tests on Databricks from the local environment by running run_pipeline.py script:\n\n        .\/run_pipeline.py pipelines --pipeline-name test_pipeline\n    \nThis command will run test_pipeline from the pipelines folder on Databricks.Test Automation\u00a0 using Databricks DeploymentsThe newly created projects are preconfigured with two standard CI\/CD pipelines: one of them is executed for each push and runs dev-tests on Databricks workspace.Another one is run for each created GitHub release and runs integration-tests on Databricks workspace. In the case of a positive result of integration tests, the production pipelines are deployed as jobs to the Databricks workspace.Deploying production pipelines using Databricks DeploymentsIn order to deploy pipelines to production workspace, GitHub release can be created. It will automatically start integration tests and if they are positive, the production pipelines are deployed as jobs to the Databricks workspace. During the first run, the jobs will be created in Databricks workspace. During the subsequent release, the definition of existing jobs will be updated.Dependency and configuration managementDatabricks Deployments supports dependency management on two levels:Project level:\nproject level python package dependencies, which are needed during production runtime, can be placed in runtime_requiremnets.txtIt is also possible to use project level JAR or Python Whl dependencies. They can be placed in dependencies\/jars and dependencies\/wheels directories.Pipeline dependencies:\nPipeline level python\/maven\/other dependencies can be specified in job specification json directly in libraries sectionJars and wheels can be placed in dependencies\/jars and dependencies\/wheels directories respectively in pipeline folderConfiguration files can be placed in the pipeline directory. They will be logged to MLflow together with python script. During execution in Databricks the job script will receive the path to the pipeline folder as first parameter. This parameter can be used to open any files that were present in the pipeline directory.Let\u2019s discuss how we can manage dependencies using Databricks Deployments using the following example: \n\n    .\n    \u251c\u2500\u2500 dependencies\n    \u2502 \u00a0 \u251c\u2500\u2500 jars\n    \u2502 \u00a0 \u2502 \u00a0 \u2514\u2500\u2500 direct_dep.jar\n    \u2502 \u00a0 \u2514\u2500\u2500 wheels\n    \u2502 \u00a0 \u00a0 \u00a0 \u2514\u2500\u2500 someotherwheel-0.1.0-py3-none-any.whl\n    \u251c\u2500\u2500 job_spec_aws.json\n    \u251c\u2500\u2500 job_spec_azure.json\n    \u251c\u2500\u2500 pipeline_runner.py\n    \u2514\u2500\u2500 train_config.yaml\n    This pipeline has two dependencies on pipeline level: one jar file and one wheel. Train_config.yaml file contains configuration parameters that pipeline can read using the following code:\ndef read_config(name, root):\n       try:\n           filename = root.replace('dbfs:', '\/dbfs') + '\/' + name\n           with open(filename) as conf_file:\n               conf = yaml.load(conf_file, Loader=yaml.FullLoader)\n               return conf\n       except FileNotFoundError as e:\n           raise FileNotFoundError(\n               f\"{e}. Please include a config file!\")\n    \n    conf = read_config('train_config.yaml', sys.argv[1])\n    Outlook and next stepsThere are different directions of the further development of Databricks Deployments. We are thinking of extending a set of CI\/CD tools we provide the templates for. As of now it is just GitHub Actions, but we can add a template that integrates with CircleCI or\u00a0 Azure DevOps.Another direction can be supporting development of pipelines developed in Scala.How to contribute?Databricks Labs CI\/CD Templates is an open source tool and we happily welcome contributions to it. You are welcome to submit a PR!Try Databricks for freeGet StartedRelated postsAutomate continuous integration and continuous delivery on Databricks using Databricks Labs CI\/CD TemplatesJune 5, 2020 by Michael Shtelma and Thunder Shiviah in Engineering Blog\nCONTENTS Overview Why do we need yet another deployment framework? Simplifying CI\/CD on Databricks via reusable templates Development lifecycle using Databricks Deployments How...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/company\/about-us","text":"Sobre a Databricks, fundada pelos criadores originais do Apache Spark\u2122Skip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks \u00e9 a criadora do lakehouseCom origens no mundo acad\u00eamico e na comunidade de c\u00f3digo aberto, a Databricks foi fundada em 2013 pelos criadores do Apache Spark\u2122, Delta Lake e MLflow. Como a primeira e \u00fanica plataforma global de lakehouse na nuvem, a Databricks combina o melhor dos data warehouses e data lakes para oferecer uma plataforma aberta e unificada para dados e IA.\n\u00a0Explore a Plataforma LakehouseHoje, mais de 7.000 organiza\u00e7\u00f5es em todo o mundo, incluindo ABN AMRO, Cond\u00e9 Nast, Regeneron e Shell, contam com a Databricks para fornecer data engineering em grande escala, data science colaborativa, machine learning de ciclo de vida abrangente e an\u00e1lise de neg\u00f3cios.\nCom sede em S\u00e3o Francisco, escrit\u00f3rios em todo o mundo e centenas de parceiros internacionais, como Microsoft, Amazon, Tableau, Informatica, Capgemini e Booz Allen Hamilton, a Databricks tem a miss\u00e3o de simplificar e democratizar dados e IA, ajudando as equipes de dados a resolver os problemas mais complexos do mundo.Explore hist\u00f3rias de clientesVer parceirosNossos clientesVer todos os clientes\nNossa lideran\u00e7aEquipe executivaConhe\u00e7a nossa equipe executivaEquipe fundadoraConhe\u00e7a nossa equipe fundadoraConselho de Administra\u00e7\u00e3oConhe\u00e7a nossa diretoriaNossos investidoresProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bob-zhang","text":"Bob Zhang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBob ZhangSenior Technical Program Manager at MicrosoftBack to speakersBob Zhang is a Senior Technical Program Manager in Azure Data focused on Microsoft Data Integration connectivity. Bob has extensive experience working on enterprise software products and data integration and currently owns connectivity scenarios for Power Query, the data transformation and preparation technology used in Power BI, Excel, and many more Microsoft products.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/data-engineering","text":"Ingegneria dei dati | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWIngegneria dei datiSu Databricks girano ogni giorno decine di milioni di carichi di lavoro di produzioneCominciaGuarda la demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowAcquisisci e trasforma facilmente dati in batch e in streaming sulla Databricks Lakehouse Platform. Organizza flussi di lavoro in produzione affidabili mentre Databricks gestisce automaticamente l'infrastruttura su larga scala. Aumenta la produttivit\u00e0 dei team con verifiche integrate della qualit\u00e0 dei dati e supporto di best practice per lo sviluppo di software.Unificare batch e streamingElimina i silos operando su una sola piattaforma con un'unica API per acquisire, trasformare ed elaborare progressivamente dati in batch e in streaming su larga scala.Concentrati sull'estrazione di valore dai datiDatabricks gestisce automaticamente l'infrastruttura e i componenti operativi dei flussi di lavoro in produzione, consentendo agli utenti di concentrarsi sul valore invece che sugli strumenti.Connetti i tuoi strumenti preferitiUna piattaforma lakehouse aperta per connettere e utilizzare gli strumenti preferiti di data engineering per acquisizione, ETL\/ELT e orchestrazione dei dati.Costruisci un sistema basato sulla piattaforma lakehouseLa piattaforma lakehouse \u00e8 la base pi\u00f9 idonea per costruire e condividere risorse di dati affidabili, con una gestione centralizzata, massima affidabilit\u00e0 e tempi rapidi.\u201cPer noi, Databricks sta diventando una vera e propria centrale per tutto il nostro lavoro ETL. Pi\u00f9 lavoriamo con la Lakehouse Platform, pi\u00f9 diventa facile sia per gli utenti sia per gli amministratori della piattaforma\u201d.\u2014 Hillevi Crognale, Engineering Manager, YipitDataCome funziona?Acquisizione dati semplificataElaborazione ETL automatizzataOrchestrazione affidabile dei flussi di lavoroOsservabilit\u00e0 e monitoraggio a 360 gradiMotore di elaborazione dati di nuova generazioneFondamenti di governance, affidabilit\u00e0 e prestazioniAcquisizione dati semplificataAcquisisci i dati nella\u00a0Lakehouse Platform\u00a0e alimenta le applicazioni di analisi, AI e streaming da un'unica fonte.\u00a0Auto Loader elabora in modo progressivo e automatico i file che arrivano sullo storage in cloud, senza bisogno di gestire le informazioni di stato, in lavori programmati o continui. Il sistema traccia in modo efficiente i nuovi file (nell'ordine dei miliardi) senza doverli elencare in una directory e, inoltre, pu\u00f2 inferire lo schema dai dati sorgente e adattarlo ai cambiamenti che si verificano nel tempo. Il comando\u00a0COPY INTO\u00a0agevola gli analisti nell'acquisizione di file in batch in\u00a0Delta Lake\u00a0tramite SQL.\u201cAbbiamo registrato un incremento della produttivit\u00e0 del 40% nel data engineering, riducendo il tempo necessario per sviluppare nuove idee da alcuni giorni a pochi minuti e aumentando la disponibilit\u00e0 e l'accuratezza dei nostri dati\u201d.\u2014 Shaun Pearce, Chief Technology Officer,\u00a0GoustoMaggiori informazioniElaborazione ETL automatizzataUna volta acquisiti, i dati grezzi devono essere trasformati in modo che siano pronti per analisi e AI. Databricks offre potenti funzionalit\u00e0 ETL per ingegneri dei dati, data scientist e analisti con\u00a0Delta Live Tables\u00a0(DLT). DLT \u00e8 il primo framework che adotta un semplice approccio dichiarativo per costruire pipeline ETL e ML su dati in batch o in streaming, automatizzando al tempo stesso attivit\u00e0 complesse come la gestione dell'infrastruttura, l'orchestrazione dei compiti, la gestione e il ripristino di errori e l'ottimizzazione delle prestazioni. Con DLT gli ingegneri possono trattare i dati come codice e applicare best practice moderne di ingegneria software come test, gestione, monitoraggio e documentazione degli errori, per implementare pipeline affidabili su larga scala.Maggiori informazioniOrchestrazione affidabile dei flussi di lavoroDatabricks Workflows \u00e8 il servizio completamente gestito per l'orchestrazione di tutti i dati, le analisi e l'AI, nativo sulla Lakehouse Platform. Si possono orchestrare diversi carichi di lavoro per l'intero ciclo di vita, inclusi Delta Live Tables e Jobs per SQL, Spark, notebook, dbt, modelli di ML e altro ancora. La stretta integrazione con la Lakehouse Platform sottostante consente di creare ed eseguire carichi di lavoro in produzione affidabili su qualsiasi cloud, offrendo al tempo stesso un monitoraggio accurato e centralizzato, con la massima semplicit\u00e0 per gli utilizzatori finali.\"La nostra missione \u00e8 trasformare il modo in cui alimentiamo il pianeta. I nostri clienti del settore energetico hanno bisogno di dati, servizi di consulenza e ricerca per realizzare questa trasformazione. Databricks Workflows ci offre la velocit\u00e0 e la flessibilit\u00e0 necessarie per fornire gli approfondimenti di cui i nostri clienti hanno bisogno\".\u2014 Yanyan Wu, Vice President of Data,\u00a0Wood MackenzieMaggiori informazioniOsservabilit\u00e0 e monitoraggio a 360 gradiLa piattaforma lakehouse offre visibilit\u00e0 su tutto il ciclo di vita di dati e AI, consentendo agli ingegneri dei dati e ai team operativi di visualizzare lo stato di salute dei loro flussi di lavoro in produzione in tempo reale, gestire la qualit\u00e0 dei dati e osservare l'andamento storico. Databricks Workflows offre l'accesso a grafici e dashboard dei flussi di dati che tracciano la salute e le prestazioni dei lavori in produzione e delle pipeline Delta Live Tables. Anche i registri di eventi vengono mostrati come tabelle di Delta Lake, consentendo di monitorare e visualizzare prestazioni, qualit\u00e0 dei dati e metriche affidabili da diverse angolazioni.Motore di elaborazione dati di nuova generazioneL'ingegneria dei dati di Databricks si basa su\u00a0Photon, un motore di nuova generazione compatibile con le API di Apache Spark che offre un rapporto prezzo\/prestazioni\u00a0da record\u00a0e scalabilit\u00e0 automatica a migliaia di nodi.\u00a0Spark Structured Streaming offre un'unica API per elaborazione in batch e in streaming, agevolando l'adozione dello streaming sul lakehouse senza modificare il codice o acquisire nuove competenze.Maggiori informazioniGovernance dei dati, affidabilit\u00e0 e prestazioni all'avanguardiaIl data engineering su Databricks permette di beneficiare dei componenti che costituiscono le fondamenta della\u00a0Lakehouse Platform\u00a0: Unity Catalog e Delta Lake. I dati grezzi vengono ottimizzati con Delta Lake, un formato di storage open-source che garantisce affidabilit\u00e0 attraverso transazioni ACID e una gestione scalabile dei metadati con prestazioni ad altissima velocit\u00e0. Delta Lake insieme a Unity Catalog offre una governance granulare per tutte le risorse di dati e AI, semplificando le modalit\u00e0 di governance con un unico modello omogeneo per scoprire, accedere e condividere i dati su diversi cloud. Unity Catalog offre inoltre supporto nativo per Delta Sharing, il primo protocollo aperto del settore per la condivisione semplice e sicura dei dati con altre organizzazioni.Migrazione a DatabricksStanco dei silos di dati, della lentezza e dei costi esorbitanti di sistemi obsoleti come Hadoop e i data warehouse aziendali? Migra a Databricks Lakehouse, la piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI.Migrazione a DatabricksIntegrazioniAssicura la massima flessibilit\u00e0 ai team di gestione dei dati, utilizzando Partner Connect e un ecosistema di partner tecnologici per realizzare un'integrazione diretta con gli strumenti di ingegneria dei dati pi\u00f9 diffusi. Ad esempio, si possono acquisire dati critici con Fivetran, trasformarli in loco con dbt e orchestrare le pipeline con Apache Airflow.Acquisizione ed ETL di dati+ Qualsiasi altro client compatibile con Apache Spark\u2122\ufe0fReferenzeScopri di pi\u00f9Delta LakeFlussi di lavoroDelta Live TablesDelta SharingContenuti associati\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video sui vantaggi del data engineering con Databricks.\nEsplora risorseeBookCostruire il Data Lakehouse, di Bill Inmon, padre del data warehouseGovernance di dati, analisi e intelligenza artificialeTutto sulla gestione dei datiThe Big Book of Data EngineeringScopri la nuova soluzione Delta SharingMigrazione da data warehouse a data lakehouse per principiantiEventiGestire la trasformazione dei dati con Delta Live TablesSerie di webinar sull'acquisizione di dati senza problemiDATA+AI SUMMIT 2022Modernizzare il data warehouseBlogAnnuncio della disponibilit\u00e0 di Databricks Delta Live Tables (DLT)Presentazione di Databricks WorkflowsPanoramica di tutte le nuove funzionalit\u00e0 di streaming strutturato sviluppate nel 2021 per Databricks e Apache Spark10 funzionalit\u00e0 avanzate per semplificare la gestione di dati semi-strutturati nel lakehouse di DatabricksPronto per cominciare?Prova gratuitaEntra nella communityawsazureGCPProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zaheera-valani\/#","text":"Zaheera Valani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZaheera ValaniSenior Director of Engineering at DatabricksBack to speakersZaheera Valani is a Senior Director of Engineering at Databricks for the Partner and Dev Ecosystem teams, and Site Lead for Databricks Seattle area offices. Prior to Databricks, Zaheera was at Tableau for 6 years leading the Data Management organization. She started out her career as a software engineer on Microsoft Excel. She is passionate about data, analytics, engineering and has grown teams and shipped widely adopted data and analytics products during her ~20 year career in technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nadine-farah\/#","text":"Nadine Farah - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNadine FarahHead of Dev Rel at OnehouseBack to speakersNadine Farah is head of dev rel at Onehouse and an Apache Hudi contributor. She's passionate about bridging engineering, product & marketing to help drive product adoption. She previously lead Rockset's developer initiatives where she focused on building technical content to drive developer adoption for real-time analytics. At Bose, she contributed to the watchOS SDK & worked with partners to embrace spatial audio in the music and gaming industries.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/databricks-data-processing-addendum","text":"Databricks Data Processing Addendum | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Data Processing AddendumCompanies who have licensed or subscribed to Databricks Services and require a Data Processing Addendum (DPA) may download and electronically sign the Databricks DPA by clicking on the link below. Upon completion, a copy of the executed DPA will be emailed to the address designated by you during the process. By entering into a new DPA available below, you will replace your existing DPA in its entirety.Click here to sign a new DPA with Databricks in its entiretyClick here to download a sampleProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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Connect\u3068\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u306e\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3092\u6d3b\u7528\u3057\u3066\u3001\u4e00\u822c\u7684\u306a\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c4\u30fc\u30eb\u3068\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u7d71\u5408\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30ab\u30b9\u30bf\u30de\u30fc\u30b9\u30c8\u30fc\u30ea\u30fc\u300c\u52d5\u7684\u306a\u9ad8\u901f\u30c7\u30fc\u30bf\u306b\u306f Databricks \u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\u3002\u5b9f\u5e97\u8217\u3001\u30aa\u30f3\u30e9\u30a4\u30f3\u3092\u554f\u308f\u305a\u3001\u60a3\u8005\u306e\u30cb\u30fc\u30ba\u306b\u5fdc\u3048\u308b\u305f\u3081\u306e\u30b9\u30d4\u30fc\u30c9\u306e\u6539\u5584\u306b\u5927\u3044\u306b\u5f79\u7acb\u3063\u3066\u3044\u307e\u3059\u3002\u73fe\u5728\u3001Databricks 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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{"source":"https:\/\/www.databricks.com\/fr\/solutions\/accelerators","text":"Acc\u00e9l\u00e9rateurs de solutions Databricks \u2013 D\u00e9livrer plus vite la valeur des donn\u00e9es et de l'IA \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWSolutions pour l'industrieD\u00e9livrez sans attendre les donn\u00e9es et les r\u00e9sultats d'IA qui comptent le plusD\u00e9marrez votre essai gratuitAcc\u00e9l\u00e9rateurs de solutions DatabricksGagnez des heures dans vos op\u00e9rations de d\u00e9couverte, de conception, de d\u00e9veloppement et de test avec les acc\u00e9l\u00e9rateurs de solutions Databricks. Nos guides d\u00e9di\u00e9s \u2013 notebooks enti\u00e8rement fonctionnels et bonnes pratiques \u2013 acc\u00e9l\u00e8rent les r\u00e9sultats de vos cas d'usage les plus courants et les plus impactants. Passez de l\u2019id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulement.\n\u00a0\nCommencez \u00e0 utiliser les acc\u00e9l\u00e9rateurs de solutions avec votre essai Databricks gratuit ou votre compte existant.\n\u00a0\nD\u00e9marrez votre essai gratuit d\u00e8s aujourd'huiParcourir les acc\u00e9l\u00e9rateurssearchHide filtersIndustrySortDatabricksSuppression automatis\u00e9e des informations m\u00e9dicalesfeaturednewDatabricksPr\u00e9vision de la demande haute granularit\u00e9featured\ud83d\udd25DatabricksDisponibilit\u00e9featuredDatabricksD\u00e9tection de toxicit\u00e9 dans le gamingfeaturedDatabricksAjustement des risques de MedicareDatabricksAnalyse d'images de pathologiesDatabricksAnalyse de survie et valeur vie clientDatabricksAnalytique de performances ESG\ud83d\udd25DatabricksAnalytique des points de vente en temps r\u00e9elnewDatabricksAttribution multipointDatabricksClassification des marchandsDatabricksConstruction de cohortes \u00e0 l'aide de graphes de connaissancesDatabricksCorrespondance approximative d'\u00e9l\u00e9mentsSplunkCyberanalyse (Connecteur Splunk)DatabricksD\u00e9tection des \u00e9v\u00e9nements ind\u00e9sirables li\u00e9s aux m\u00e9dicamentsnewDatabricksD\u00e9tection des menaces bas\u00e9e sur le DNSDatabricksD\u00e9terminants sociaux de la sant\u00e9DatabricksEfficacit\u00e9 globale de l'\u00e9quipementDatabricks\u00c9l\u00e9ments de preuves par le r\u00e9elDatabricks\u00c9tudes d'associations \u00e0 l'\u00e9chelle du g\u00e9nomeDatabricksFondements de la reconnaissance d'imageDatabricksG\u00e9n\u00e9ration de routes \u00e9volutivesDatabricksGestion de la r\u00e9tentionDatabricksGestion des risquesDatabricksInterop\u00e9rabilit\u00e9 FHIR avec dbigniteDatabricksInterop\u00e9rabilit\u00e9 HL7v2 avec SmolderDatabricksJumeaux num\u00e9riquesDatabricksL'analyse g\u00e9ospatiale au service de l'identification de la fraudeDatabricksLutte contre le blanchiment d\u2019argentDatabricksMaintenance pr\u00e9ventive (IoT)DatabricksMoteur de recommandationsDatabricksNotation de tendancenewDatabricksOptimisation des ench\u00e8res en temps r\u00e9elDatabricksPlateforme d\u2019investissement moderneDatabricksPr\u00e9paration de commandes optimis\u00e9eDatabricksPr\u00e9vention de la fraude financi\u00e8re en temps r\u00e9elDatabricksPr\u00e9vision de la perte d'abonn\u00e9sDatabricksPr\u00e9vision des ventes et attribution publicitaire\ud83d\udd25DatabricksQualit\u00e9 de l'exp\u00e9rience vid\u00e9oDatabricksR&D Optimisation avec les graphes de connaissancesnewDatabricksRapports r\u00e9glementairesDatabricksR\u00e9solution des entit\u00e9s du clientDatabricksRisque de r\u00e9putationDatabricksSegmentation des clientsDatabricksStock de s\u00e9curit\u00e9DatabricksSynth\u00e8se de donn\u00e9es r\u00e9elles pour l'oncologieDatabricksTransparence des prixnewDatabricksValeur vie client\ud83d\udd25FAQCombien co\u00fbtent les acc\u00e9l\u00e9rateurs de solutions\u00a0?Les acc\u00e9l\u00e9rateurs de solutions\u00a0 sont disponibles gratuitement pour tous les clients Databricks.Dois-je \u00eatre client de Databricks pour utiliser un acc\u00e9l\u00e9rateur de solutions\u00a0?Vous pouvez mettre en \u0153uvre les acc\u00e9l\u00e9rateurs de solutions avec un essai gratuit de Databricks ou avec votre compte Databricks existant.Que puis-je attendre d'un acc\u00e9l\u00e9rateur de solutions\u00a0?Les acc\u00e9l\u00e9rateurs de solutions sont con\u00e7us pour vous aider \u00e0 gagner du temps dans vos op\u00e9rations de d\u00e9couverte, de conception, de d\u00e9veloppement et de test. Notre objectif\u00a0: acc\u00e9l\u00e9rer le d\u00e9marrage de vos cas d'usage de donn\u00e9es et d'IA en vous dotant des ressources appropri\u00e9es (notebooks, mod\u00e8les \u00e9prouv\u00e9s et bonnes pratiques). Vous pourrez passer de l\u2019id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulement.D\u00e9couvrez comment nos clients utilisent DatabricksD\u00e9couvrez les t\u00e9moignages clientsProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/it#yourprivacychoices","text":"L'azienda dell'architettura Data Lakehouse e AI - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLa migliore data warehouse \u00e8 un lakehouseUnifica tutti i dati, le analisi e l'AI su un'unica piattaformaComincia gratisMaggiori informazioniRiduci i costi e accelera l'innovazione sulla piattaforma lakehouseMaggiori informazioniUnificataUn'unica piattaforma per tutti i tuoi dati, gestita in modo omogeneo e disponibile per tutte le attivit\u00e0 di analisi e AIApertaBasata su standard aperti e integrata con tutti i cloud per operare direttamente all'interno del tuo moderno stack di datiScalabileScalabilit\u00e0 efficiente per ogni carico di lavoro, dalle semplici pipeline di dati ai modelli linguistici di grandi dimensioni (LLM)Organizzazioni data-driven che hanno scelto il lakehouse\nVedi tutti i clienti\nIl lakehouse unifica i team di gestione dei datiGestione e ingegneria dei datiSnellire l'acquisizione e la gestione dei datiGrazie a processi ETL automatizzati e affidabili, alla condivisione aperta e sicura dei dati e a prestazioni velocissime, Delta Lake trasforma il data lake nella destinazione finale di tutti i dati strutturati, semi-strutturati e non strutturati.Maggiori informazioni Guarda la demoData warehouseRicavare nuove informazioni dai dati pi\u00f9 completiPotendo accedere immediatamente ai dati pi\u00f9 aggiornati e completi e potendo contare sulla potenza di Databricks SQL (che offre un rapporto prezzo\/prestazioni fino a 12 volte migliore rispetto ai tradizionali data warehouse in cloud), analisti e data scientist possono ottenere nuove informazioni approfondite e dettagliate.Maggiori informazioni Guarda la demoData science e machine learningAccelerare il ML lungo tutto il ciclo di vitaIl lakehouse rappresenta le fondamenta di Databricks Machine Learning, una soluzione collaborativa nativa per la gestione dei dati, che abbraccia tutto il ciclo di vita del machine learning, dalla definizione delle funzionalit\u00e0 alla produzione. Insieme a pipeline di dati con qualit\u00e0 e prestazioni elevate, il lakehouse accelera il machine learning e la produttivit\u00e0 dei team.Maggiori informazioni Guarda la demoGovernance e condivisione dei datiUnifica la governance e la condivisione di dati, analisi e AIDatabricks mette a disposizione un modello comune di sicurezza e governance per tutte le risorse di dati, analisi e AI presenti nel lakehouse su qualsiasi cloud. Si possono cos\u00ec reperire e condividere dati su molteplici piattaforme, cloud o regioni geografiche, senza duplicazioni o vincoli, oltre a distribuire prodotti di dati attraverso un marketplace aperto.Maggiori informazioni Guarda la demoIl data warehouse \u00e8 ormai superato. Scopri perch\u00e9 il lakehouse \u00e8 diventato la nuova architettura per dati e AI.Scopri il Lakehouse\u00c8 disponibile il catalogo delle sessioniVieni a San Francisco per scoprire l'ecosistema lakehouse e i progressi delle tecnologie open-sourceScopri le sessioniScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivo.Richiedi il report600 CIO. 14 settori industriali. 18 Paesi.Questo nuovo studio conferma che la strategia di gestione dei dati \u00e8 fondamentale per il successo dell'AI. Scopri il punto di vista di altri CIO.Richiedi il reportLettura preziosa per tecnici di Machine Learning e data scientist che cercano strumenti migliori per le MLOpsRichiedi l'eBookPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/data-engineering","text":"Data Engineering | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWData EngineeringDes dizaines de millions de charges de travail de production s\u2019ex\u00e9cutent quotidiennement sur DatabricksD\u00e9marrerRegarder la d\u00e9mo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowImportez et transformez facilement des donn\u00e9es en lot et en streaming sur la plateforme Databricks Lakehouse. Orchestrez des workflows de production fiables et confiez \u00e0 Databricks la gestion automatique de votre infrastructure \u00e0 grande \u00e9chelle. Maximisez la productivit\u00e9 de vos \u00e9quipes gr\u00e2ce aux tests int\u00e9gr\u00e9s de qualit\u00e9 des donn\u00e9es et \u00e0 l'impl\u00e9mentation de bonnes pratiques de d\u00e9veloppement logiciel.Unifier batch et streaming\u00c9liminez les silos\u00a0: gr\u00e2ce \u00e0 une API unique et unifi\u00e9e, ing\u00e9rez, transformez et traitez les donn\u00e9es en lots et en streaming de mani\u00e8re incr\u00e9mentielle et \u00e0 grande \u00e9chelle, au sein d'une m\u00eame plateformeLa priorit\u00e9\u00a0: cr\u00e9er de la valeur \u00e0 partir des donn\u00e9esDatabricks g\u00e8re automatiquement votre infrastructure et les composants op\u00e9rationnels de vos workflows de production\u00a0: vous pouvez vous concentrer sur la valeur plut\u00f4t que sur les outils.Connectez vos outils pr\u00e9f\u00e9r\u00e9sLa plateforme Lakehouse ouverte connecte et exploite vos outils pr\u00e9f\u00e9r\u00e9s de data engineering pour l'ingestion des donn\u00e9es, l'ETL \/ ELT et l'orchestration.D\u00e9veloppez sur la plateforme LakehouseLa plateforme Lakehouse offre la meilleure base pour cr\u00e9er et partager des assets de donn\u00e9es fiables et ultra-rapides, avec la confiance que donne la centralisation du contr\u00f4le.\u00ab\u00a0Chez nous, Databricks est en train de devenir le centre nerveux de toutes nos t\u00e2ches ETL. Plus nous utilisons la plateforme Lakehouse, plus cela devient facile pour les utilisateurs et les administrateurs.\u00a0\u00bb\u2014 Hillevi Crognale, Responsable de l'ing\u00e9nierie, YipitDataComment \u00e7a marche\u00a0?Simplification de l'ingestion des donn\u00e9esTraitement ETL automatis\u00e9Orchestration fiable des workflowsObservabilit\u00e9 et surveillance de bout en boutMoteur de traitement des donn\u00e9es de nouvelle g\u00e9n\u00e9rationUne base robuste pour la gouvernance, la fiabilit\u00e9 et la performanceSimplification de l'ingestion des donn\u00e9esIng\u00e9rez les donn\u00e9es dans votre plateforme Lakehouse pour alimenter vos applications d'analytique, d'IA et de streaming depuis une seule et m\u00eame source.Auto Loader traite automatiquement les fichiers au fil de leur arriv\u00e9e dans le stockage cloud, par le biais de t\u00e2ches planifi\u00e9es ou continues. Vous n'avez m\u00eame pas besoin de g\u00e9rer les informations d\u2019\u00e9tat. Cette solution est capable de tracer des milliards de nouveaux fichiers sans avoir \u00e0 les indexer dans un r\u00e9pertoire. Elle sait aussi d\u00e9duire automatiquement le sch\u00e9ma des donn\u00e9es source et l'adapter au fil du temps. Pour les analystes, la commande COPY INTO simplifie l'ingestion de lots de fichiers dans Delta Lake avec SQL.\u00ab\u00a0Nous avons constat\u00e9 une hausse de 40\u00a0% de la productivit\u00e9 du data engineering\u00a0: le d\u00e9veloppement de nouvelles id\u00e9es, qui prenait plusieurs jours auparavant, se fait d\u00e9sormais en quelques minutes. Nos donn\u00e9es ont par ailleurs gagn\u00e9 en disponibilit\u00e9 et en pr\u00e9cision.\u00a0\u00bb\u2014 Shaun Pearce, Chief Technology Officer,\u00a0GoustoEn savoir plusTraitement ETL automatis\u00e9Une fois ing\u00e9r\u00e9es, les donn\u00e9es brutes doivent \u00eatre transform\u00e9es pour \u00eatre exploitables par l'analytique et l'IA. Avec Delta Live Tables (DLT), Databricks offre de puissantes fonctionnalit\u00e9s ETL pour les ing\u00e9nieurs data, les data scientists et les analystes. DLT est un framework pionnier dans sa cat\u00e9gorie. Il utilise une approche d\u00e9clarative simple pour cr\u00e9er des pipelines ETL et ML sur des donn\u00e9es en lot ou en streaming. Par ailleurs, il permet de r\u00e9duire la complexit\u00e9 op\u00e9rationnelle en automatisant la gestion de l'infrastructure, l'orchestration des t\u00e2ches, la gestion des erreurs et des reprises d'activit\u00e9, ainsi que l'optimisation des performances. Gr\u00e2ce \u00e0 DLT, les ing\u00e9nieurs peuvent traiter leurs donn\u00e9es comme du code et appliquer les bonnes pratiques de g\u00e9nie logiciel, telles que les tests, le monitoring et la documentation, afin de d\u00e9ployer des pipelines fiables \u00e0 l'\u00e9chelle.En savoir plusOrchestration fiable des workflowsDatabricks Workflows est un service d'orchestration enti\u00e8rement manag\u00e9 pour toutes vos donn\u00e9es et applications IA, ainsi que votre analytique. Il provient nativement de la plateforme Lakehouse. Orchestrez diff\u00e9rentes charges de travail couvrant l'int\u00e9gralit\u00e9 du cycle de vie\u00a0: Delta Live Tables et Jobs pour SQL, Spark, notebooks, dbt, mod\u00e8les ML et bien plus encore. Sa profonde int\u00e9gration avec la plateforme Lakehouse sous-jacente vous assure la cr\u00e9ation et l'ex\u00e9cution de charges fiables en production sur n'importe quel cloud. Les utilisateurs finaux b\u00e9n\u00e9ficient en outre d'un monitoring d\u00e9taill\u00e9 et centralis\u00e9 d'une grande simplicit\u00e9.\"Notre mission est de transformer la fa\u00e7on dont nous alimentons la plan\u00e8te en \u00e9nergie. Nos clients du secteur de l'\u00e9nergie ont besoin de donn\u00e9es, de services de conseil et de recherche pour r\u00e9aliser cette transformation. Databricks Workflows nous offre la rapidit\u00e9 et la flexibilit\u00e9 n\u00e9cessaires pour fournir \u00e0 nos clients les informations dont ils ont besoin.\"\u2014 Yanyan Wu, Vice-pr\u00e9sidente des donn\u00e9es,\u00a0Wood MackenzieEn savoir plusObservabilit\u00e9 et surveillance de bout en boutLa plateforme Lakehouse vous offre une visibilit\u00e9 sur l'ensemble du cycle de vie des donn\u00e9es et de l'IA. Elle donne ainsi aux data engineers et aux \u00e9quipes op\u00e9rationnelles une vue de l'\u00e9tat de sant\u00e9 de leurs workflows de production en temps r\u00e9el. Elle leur permet \u00e9galement de g\u00e9rer la qualit\u00e9 des donn\u00e9es et de comprendre les tendances historiques. Les workflows Databricks mettent \u00e0 votre disposition des graphiques de dataflow et des tableaux de bord pour suivre l'\u00e9tat et les performances de vos t\u00e2ches de production et de vos pipelines Delta Live Tables. Les journaux d\u2019\u00e9v\u00e9nements sont \u00e9galement pr\u00e9sent\u00e9s sous forme de tables Delta Lake. Vous pouvez ainsi surveiller et visualiser facilement les m\u00e9triques de performance, de qualit\u00e9 des donn\u00e9es et de fiabilit\u00e9 sous n\u2019importe quel angle.Moteur de traitement des donn\u00e9es de nouvelle g\u00e9n\u00e9rationLe data engineering Databricks s'appuie sur Photon, un moteur de nouvelle g\u00e9n\u00e9ration compatible avec les API Apache Spark. Il d\u00e9livre un rapport performance \/ prix record et peut automatiquement prendre en charge des milliers de n\u0153uds.Spark Structured Streaming propose une API unique et unifi\u00e9e pour le traitement en lot et en streaming, ce qui permet d'adopter le streaming sur Lakehouse sans modifier le code, ni acqu\u00e9rir de nouvelles comp\u00e9tences.En savoir plusGouvernance, fiabilit\u00e9 et performance des donn\u00e9es \u00e0 la pointeAvec le data engineering sur Databricks, vous b\u00e9n\u00e9ficiez des composants fondamentaux de la plateforme Lakehouse\u00a0: Unity Catalog et Delta Lake. Vos donn\u00e9es brutes sont optimis\u00e9es avec Delta Lake, un format de stockage open source \u00e0 la fiabilit\u00e9 assur\u00e9e par les transactions ACID, qui r\u00e9unit une gestion \u00e9volutive des m\u00e9tadonn\u00e9es et des performances ultra-rapides. Cet outil se combine \u00e0 Unity Catalog pour vous donner les moyens d'appliquer une gouvernance fine \u00e0 toutes vos donn\u00e9es et assets d\u2019IA, simplifiant ainsi leur administration. Un m\u00eame mod\u00e8le coh\u00e9rent permet de d\u00e9couvrir, consulter et partager des donn\u00e9es entre les clouds. Unity Catalog fournit \u00e9galement une prise en charge native de Delta Sharing, le premier protocole ouvert du secteur pour un partage de donn\u00e9es simple et s\u00e9curis\u00e9 avec d\u2019autres organisations.Migrer vers DatabricksVous en avez assez des silos de donn\u00e9es, de la lenteur des performances et des co\u00fbts \u00e9lev\u00e9s associ\u00e9s aux anciens syst\u00e8mes comme Hadoop et aux entrep\u00f4ts de donn\u00e9es d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de donn\u00e9es, d'analyses et d'IA.Migrer vers DatabricksInt\u00e9grationsOffrez un maximum de flexibilit\u00e9 \u00e0 vos \u00e9quipes de donn\u00e9es\u00a0: appuyez-vous sur Partner Connect et notre \u00e9cosyst\u00e8me de partenaires technologiques pour int\u00e9grer de mani\u00e8re transparente les outils les plus r\u00e9pandus de data engineering. Vous pouvez par exemple ing\u00e9rer les donn\u00e9es strat\u00e9giques avec Fivetran, les transformer in situ avec dbt et orchestrer vos pipelines avec Apache Airflow.Ingestion de donn\u00e9es et ETL+ tout autre client compatible Apache Spark\u2122T\u00e9moignages de clientsEn savoir plusDelta LakeWorkflowsDelta\u00a0Live\u00a0tablesDelta SharingContenu associ\u00e9\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les atouts du data engineering sur Databricks.\nExplorer les ressourcesEbooksCr\u00e9er le Data Lakehouse par Bill Inmon, p\u00e8re du data warehouseDonn\u00e9es, analyses et gouvernance de l'IAFondamentaux de la gestion des donn\u00e9esLe Grand Livre du Data EngineeringD\u00e9couvrez la nouvelle solution de Delta SharingLa migration d'un data warehouse vers un data lakehouse en quelques mots\u00c9v\u00e9nementsG\u00e9rez la transformation des donn\u00e9es avec Delta Live TablesS\u00e9rie de webinaires sur l'ingestion de donn\u00e9es sans tracasDATA+AI SUMMIT 2022Modernisez votre data warehouseBlogsDisponibilit\u00e9 g\u00e9n\u00e9rale de Databricks Delta Live Tables (DLT)D\u00e9couvrez les workflows DatabricksUn aper\u00e7u de toutes les nouvelles fonctionnalit\u00e9s de streaming structur\u00e9 d\u00e9velopp\u00e9es en 2021 pour Databricks et Apache Spark10 fonctionnalit\u00e9s puissantes qui simplifient la gestion des donn\u00e9es semi-structur\u00e9es dans le Lakehouse de DatabricksPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitRejoignez la communaut\u00e9AWSAzureGCPProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-mantz","text":"Chris Mantz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris MantzData Architect at SlalomBack to speakersA consultant, as well as a data architect and data engineer by training, Chris has 4 years of experience architecting Databricks solutions across a variety of industries including healthcare, transportation, and retail.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDelta SharingStandard aperto per la condivisione sicura di risorse di datiCominciaGuarda la demoDatabricks Delta Sharing offre una soluzione aperta per la condivisione sicura di dati \"live\" dal lakehouse aziendale a qualsiasi piattaforma informatica.Vantaggi chiaveCondivisione aperta fra diverse piattaformeNon vincolarti a un unico fornitore e condividi facilmente i dati esistenti nei formati Delta Lake e Apache Parquet su qualsiasi piattaforma per la gestione di dati.Condivisione di dati \"live\" senza replicheCondividi dati in diretta fra differenti piattaforme, cloud o regioni senza replicare o copiare i dati su un altro sistema.Governance centralizzataGestisci, governa, revisiona e traccia centralmente l'utilizzo di dati condivisi su un'unica piattaforma.Marketplace per prodotti di datiCostruisci e confeziona prodotti di dati, come set di dati, modelli ML e notebook, in un'unica versione che pu\u00f2 essere distribuita ovunque da un marketplace centrale.Data cleanroom con protezione sicuraCollabora facilmente con clienti e partner su qualsiasi cloud attraverso un ambiente ospitato sicuro, salvaguardando al tempo stesso la riservatezza dei dati.Come funzionaIntegrazione nativa con la piattaforma DatabricksL'integrazione nativa con Unity Catalog consente di gestire e revisionare centralmente i dati condivisi fra diverse organizzazioni. Si possono cos\u00ec condividere in modo sicuro risorse di dati con fornitori e partner, per coordinare meglio le attivit\u00e0 rispettando al tempo stesso le esigenze di sicurezza e conformit\u00e0.Facile gestione delle condivisioniCrea e gestisci fornitori, destinatari e condivisioni, con un'interfaccia utente semplice da usare, comandi SQL o API REST con pieno supporto per CLI e Terraform.Scopri e accedi a prodotti di dati in un marketplace apertoScopri, valuta e accedi facilmente a prodotti di dati come set di dati, modelli di machine learning, dashboard e notebook da qualsiasi luogo, senza operare necessariamente sulla piattaforma Databricks.Data cleanroom con protezione sicuraCollabora con clienti e partner in qualsiasi ambiente in cloud proteggendo la privacy. Condividi in modo sicuro i dati presenti nel data lake senza bisogno di repliche. Interagisci con i collaboratori sul loro cloud preferito e offri loro la flessibilit\u00e0 necessaria per eseguire calcoli complessi e carichi di lavoro in qualsiasi linguaggio: SQL, R, Scala, Java e Python. Guida i collaboratori nella realizzazione di casi d'uso comuni utilizzando template, notebook e dashboard predefiniti, per ridurre i tempi di estrazione di informazioni approfondite e dettagliate.Casi d'usoCondivisione fra linee di business interneCostruisci Data Mesh con Delta Sharing per condividere i dati in modo sicuro con unit\u00e0 operative e filiali in diversi cloud o regioni, senza copiare o replicare i dati.Condivisione B2BMonetizzazione dei datiClienti\u201cDelta Sharing ci ha aiutato a snellire il processo di fornitura di dati per grandi set di dati. In questo modo i nostri clienti possono utilizzare il loro ambiente di calcolo per leggere dati curati sempre freschi, con poco o nessun lavoro di integrazione, consentendoci di continuare ad arricchire il nostro catalogo di prodotti di dati esclusivi di alta qualit\u00e0.\u201d\u2014 William Dague, Head of Alternative Data\u201cEssendo un'azienda che produce dati, per noi \u00e8 fondamentale poter offrire ai clienti l'accesso ai nostri set di dati. Databricks Lakehouse Platform con Delta Sharing snellisce realmente tutto il processo, consentendoci di raggiungere in maniera sicura una base di utenti molto pi\u00f9 ampia indipendentemente dal cloud o dalla piattaforma.\u201d\u2014 Felix Cheung, VP of Engineering\u201cSfruttando le funzionalit\u00e0 avanzate di Delta Sharing di Databricks, Pumpjack Dataworks pu\u00f2 realizzare un'esperienza di onboarding pi\u00f9 veloce, senza bisogno di esportare, importare e rimodellare i dati, cos\u00ec da offrire ai nostri clienti un valore immediato. Risultati pi\u00f9 rapidi generano maggiori opportunit\u00e0 commerciali per i nostri clienti e partner.\u201d\u2014 Corey Zwart, Head of Engineering\u201cCon Delta Sharing, i nostri clienti hanno accesso in modo pressoch\u00e9 istantaneo a set di dati curati, con la possibilit\u00e0 di integrarli con strumenti di analisi scelti da loro. Il dialogo con i nostri clienti spazia dall'assistenza tecnica a basso valore sull'acquisizione dei dati a discussioni analitiche ad alto valore con cui offriamo al cliente esperienze di successo. Con la progressiva evoluzione dei rapporti con i nostri clienti, siamo in grado di fornire nuovi set di dati e aggiornare quelli esistenti grazie a Delta Sharing, per tenere i clienti sempre allineati con gli sviluppi dei loro rispettivi settori.\u201d\u2014 Anup Segu, Data Engineering Tech LeadUn ecosistema apertoAccedi alla versione pubblicata pi\u00f9 recente direttamente dal fornitore con strumenti SQL, Python o BI di facile utilizzo.RisorseIntervento principale e webinar[Intervento principale]Governance e condivisione dei dati sul lakehouse al Data + AI Summit 2022[Webinar on-demand]Generare valore pi\u00f9 velocemente con Delta SharingBlogAnnunciata la disponibilit\u00e0 in commercio di Delta SharingDelta Sharing: standard aperto per la condivisione sicura dei datiI tre principali casi d'uso di condivisione realizzati con Delta SharingScheda ed e-book della soluzione[eBook] Scopri la nuova soluzione Delta SharingDelta Sharing: standard aperto per la condivisione sicura dei datiRise of the Data Lakehouse di Bill Inmon, padre del data warehousePronto per cominciare con Databricks?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/data-pipelines","text":"Data Engineering | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWData EngineeringDes dizaines de millions de charges de travail de production s\u2019ex\u00e9cutent quotidiennement sur DatabricksD\u00e9marrerRegarder la d\u00e9mo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowImportez et transformez facilement des donn\u00e9es en lot et en streaming sur la plateforme Databricks Lakehouse. Orchestrez des workflows de production fiables et confiez \u00e0 Databricks la gestion automatique de votre infrastructure \u00e0 grande \u00e9chelle. Maximisez la productivit\u00e9 de vos \u00e9quipes gr\u00e2ce aux tests int\u00e9gr\u00e9s de qualit\u00e9 des donn\u00e9es et \u00e0 l'impl\u00e9mentation de bonnes pratiques de d\u00e9veloppement logiciel.Unifier batch et streaming\u00c9liminez les silos\u00a0: gr\u00e2ce \u00e0 une API unique et unifi\u00e9e, ing\u00e9rez, transformez et traitez les donn\u00e9es en lots et en streaming de mani\u00e8re incr\u00e9mentielle et \u00e0 grande \u00e9chelle, au sein d'une m\u00eame plateformeLa priorit\u00e9\u00a0: cr\u00e9er de la valeur \u00e0 partir des donn\u00e9esDatabricks g\u00e8re automatiquement votre infrastructure et les composants op\u00e9rationnels de vos workflows de production\u00a0: vous pouvez vous concentrer sur la valeur plut\u00f4t que sur les outils.Connectez vos outils pr\u00e9f\u00e9r\u00e9sLa plateforme Lakehouse ouverte connecte et exploite vos outils pr\u00e9f\u00e9r\u00e9s de data engineering pour l'ingestion des donn\u00e9es, l'ETL \/ ELT et l'orchestration.D\u00e9veloppez sur la plateforme LakehouseLa plateforme Lakehouse offre la meilleure base pour cr\u00e9er et partager des assets de donn\u00e9es fiables et ultra-rapides, avec la confiance que donne la centralisation du contr\u00f4le.\u00ab\u00a0Chez nous, Databricks est en train de devenir le centre nerveux de toutes nos t\u00e2ches ETL. Plus nous utilisons la plateforme Lakehouse, plus cela devient facile pour les utilisateurs et les administrateurs.\u00a0\u00bb\u2014 Hillevi Crognale, Responsable de l'ing\u00e9nierie, YipitDataComment \u00e7a marche\u00a0?Simplification de l'ingestion des donn\u00e9esTraitement ETL automatis\u00e9Orchestration fiable des workflowsObservabilit\u00e9 et surveillance de bout en boutMoteur de traitement des donn\u00e9es de nouvelle g\u00e9n\u00e9rationUne base robuste pour la gouvernance, la fiabilit\u00e9 et la performanceSimplification de l'ingestion des donn\u00e9esIng\u00e9rez les donn\u00e9es dans votre plateforme Lakehouse pour alimenter vos applications d'analytique, d'IA et de streaming depuis une seule et m\u00eame source.Auto Loader traite automatiquement les fichiers au fil de leur arriv\u00e9e dans le stockage cloud, par le biais de t\u00e2ches planifi\u00e9es ou continues. Vous n'avez m\u00eame pas besoin de g\u00e9rer les informations d\u2019\u00e9tat. Cette solution est capable de tracer des milliards de nouveaux fichiers sans avoir \u00e0 les indexer dans un r\u00e9pertoire. Elle sait aussi d\u00e9duire automatiquement le sch\u00e9ma des donn\u00e9es source et l'adapter au fil du temps. Pour les analystes, la commande COPY INTO simplifie l'ingestion de lots de fichiers dans Delta Lake avec SQL.\u00ab\u00a0Nous avons constat\u00e9 une hausse de 40\u00a0% de la productivit\u00e9 du data engineering\u00a0: le d\u00e9veloppement de nouvelles id\u00e9es, qui prenait plusieurs jours auparavant, se fait d\u00e9sormais en quelques minutes. Nos donn\u00e9es ont par ailleurs gagn\u00e9 en disponibilit\u00e9 et en pr\u00e9cision.\u00a0\u00bb\u2014 Shaun Pearce, Chief Technology Officer,\u00a0GoustoEn savoir plusTraitement ETL automatis\u00e9Une fois ing\u00e9r\u00e9es, les donn\u00e9es brutes doivent \u00eatre transform\u00e9es pour \u00eatre exploitables par l'analytique et l'IA. Avec Delta Live Tables (DLT), Databricks offre de puissantes fonctionnalit\u00e9s ETL pour les ing\u00e9nieurs data, les data scientists et les analystes. DLT est un framework pionnier dans sa cat\u00e9gorie. Il utilise une approche d\u00e9clarative simple pour cr\u00e9er des pipelines ETL et ML sur des donn\u00e9es en lot ou en streaming. Par ailleurs, il permet de r\u00e9duire la complexit\u00e9 op\u00e9rationnelle en automatisant la gestion de l'infrastructure, l'orchestration des t\u00e2ches, la gestion des erreurs et des reprises d'activit\u00e9, ainsi que l'optimisation des performances. Gr\u00e2ce \u00e0 DLT, les ing\u00e9nieurs peuvent traiter leurs donn\u00e9es comme du code et appliquer les bonnes pratiques de g\u00e9nie logiciel, telles que les tests, le monitoring et la documentation, afin de d\u00e9ployer des pipelines fiables \u00e0 l'\u00e9chelle.En savoir plusOrchestration fiable des workflowsDatabricks Workflows est un service d'orchestration enti\u00e8rement manag\u00e9 pour toutes vos donn\u00e9es et applications IA, ainsi que votre analytique. Il provient nativement de la plateforme Lakehouse. Orchestrez diff\u00e9rentes charges de travail couvrant l'int\u00e9gralit\u00e9 du cycle de vie\u00a0: Delta Live Tables et Jobs pour SQL, Spark, notebooks, dbt, mod\u00e8les ML et bien plus encore. Sa profonde int\u00e9gration avec la plateforme Lakehouse sous-jacente vous assure la cr\u00e9ation et l'ex\u00e9cution de charges fiables en production sur n'importe quel cloud. Les utilisateurs finaux b\u00e9n\u00e9ficient en outre d'un monitoring d\u00e9taill\u00e9 et centralis\u00e9 d'une grande simplicit\u00e9.\"Notre mission est de transformer la fa\u00e7on dont nous alimentons la plan\u00e8te en \u00e9nergie. Nos clients du secteur de l'\u00e9nergie ont besoin de donn\u00e9es, de services de conseil et de recherche pour r\u00e9aliser cette transformation. Databricks Workflows nous offre la rapidit\u00e9 et la flexibilit\u00e9 n\u00e9cessaires pour fournir \u00e0 nos clients les informations dont ils ont besoin.\"\u2014 Yanyan Wu, Vice-pr\u00e9sidente des donn\u00e9es,\u00a0Wood MackenzieEn savoir plusObservabilit\u00e9 et surveillance de bout en boutLa plateforme Lakehouse vous offre une visibilit\u00e9 sur l'ensemble du cycle de vie des donn\u00e9es et de l'IA. Elle donne ainsi aux data engineers et aux \u00e9quipes op\u00e9rationnelles une vue de l'\u00e9tat de sant\u00e9 de leurs workflows de production en temps r\u00e9el. Elle leur permet \u00e9galement de g\u00e9rer la qualit\u00e9 des donn\u00e9es et de comprendre les tendances historiques. Les workflows Databricks mettent \u00e0 votre disposition des graphiques de dataflow et des tableaux de bord pour suivre l'\u00e9tat et les performances de vos t\u00e2ches de production et de vos pipelines Delta Live Tables. Les journaux d\u2019\u00e9v\u00e9nements sont \u00e9galement pr\u00e9sent\u00e9s sous forme de tables Delta Lake. Vous pouvez ainsi surveiller et visualiser facilement les m\u00e9triques de performance, de qualit\u00e9 des donn\u00e9es et de fiabilit\u00e9 sous n\u2019importe quel angle.Moteur de traitement des donn\u00e9es de nouvelle g\u00e9n\u00e9rationLe data engineering Databricks s'appuie sur Photon, un moteur de nouvelle g\u00e9n\u00e9ration compatible avec les API Apache Spark. Il d\u00e9livre un rapport performance \/ prix record et peut automatiquement prendre en charge des milliers de n\u0153uds.Spark Structured Streaming propose une API unique et unifi\u00e9e pour le traitement en lot et en streaming, ce qui permet d'adopter le streaming sur Lakehouse sans modifier le code, ni acqu\u00e9rir de nouvelles comp\u00e9tences.En savoir plusGouvernance, fiabilit\u00e9 et performance des donn\u00e9es \u00e0 la pointeAvec le data engineering sur Databricks, vous b\u00e9n\u00e9ficiez des composants fondamentaux de la plateforme Lakehouse\u00a0: Unity Catalog et Delta Lake. Vos donn\u00e9es brutes sont optimis\u00e9es avec Delta Lake, un format de stockage open source \u00e0 la fiabilit\u00e9 assur\u00e9e par les transactions ACID, qui r\u00e9unit une gestion \u00e9volutive des m\u00e9tadonn\u00e9es et des performances ultra-rapides. Cet outil se combine \u00e0 Unity Catalog pour vous donner les moyens d'appliquer une gouvernance fine \u00e0 toutes vos donn\u00e9es et assets d\u2019IA, simplifiant ainsi leur administration. Un m\u00eame mod\u00e8le coh\u00e9rent permet de d\u00e9couvrir, consulter et partager des donn\u00e9es entre les clouds. Unity Catalog fournit \u00e9galement une prise en charge native de Delta Sharing, le premier protocole ouvert du secteur pour un partage de donn\u00e9es simple et s\u00e9curis\u00e9 avec d\u2019autres organisations.Migrer vers DatabricksVous en avez assez des silos de donn\u00e9es, de la lenteur des performances et des co\u00fbts \u00e9lev\u00e9s associ\u00e9s aux anciens syst\u00e8mes comme Hadoop et aux entrep\u00f4ts de donn\u00e9es d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de donn\u00e9es, d'analyses et d'IA.Migrer vers DatabricksInt\u00e9grationsOffrez un maximum de flexibilit\u00e9 \u00e0 vos \u00e9quipes de donn\u00e9es\u00a0: appuyez-vous sur Partner Connect et notre \u00e9cosyst\u00e8me de partenaires technologiques pour int\u00e9grer de mani\u00e8re transparente les outils les plus r\u00e9pandus de data engineering. Vous pouvez par exemple ing\u00e9rer les donn\u00e9es strat\u00e9giques avec Fivetran, les transformer in situ avec dbt et orchestrer vos pipelines avec Apache Airflow.Ingestion de donn\u00e9es et ETL+ tout autre client compatible Apache Spark\u2122T\u00e9moignages de clientsEn savoir plusDelta LakeWorkflowsDelta\u00a0Live\u00a0tablesDelta SharingContenu associ\u00e9\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les atouts du data engineering sur Databricks.\nExplorer les ressourcesEbooksCr\u00e9er le Data Lakehouse par Bill Inmon, p\u00e8re du data warehouseDonn\u00e9es, analyses et gouvernance de l'IAFondamentaux de la gestion des donn\u00e9esLe Grand Livre du Data EngineeringD\u00e9couvrez la nouvelle solution de Delta SharingLa migration d'un data warehouse vers un data lakehouse en quelques mots\u00c9v\u00e9nementsG\u00e9rez la transformation des donn\u00e9es avec Delta Live TablesS\u00e9rie de webinaires sur l'ingestion de donn\u00e9es sans tracasDATA+AI SUMMIT 2022Modernisez votre data warehouseBlogsDisponibilit\u00e9 g\u00e9n\u00e9rale de Databricks Delta Live Tables (DLT)D\u00e9couvrez les workflows DatabricksUn aper\u00e7u de toutes les nouvelles fonctionnalit\u00e9s de streaming structur\u00e9 d\u00e9velopp\u00e9es en 2021 pour Databricks et Apache Spark10 fonctionnalit\u00e9s puissantes qui simplifient la gestion des donn\u00e9es semi-structur\u00e9es dans le Lakehouse de DatabricksPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitRejoignez la communaut\u00e9AWSAzureGCPProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/luyang-wang\/#","text":"Luyang Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLuyang WangLead Distinguished Scientist at VerizonBack to speakersLu is a Lead Distinguished Scientist at Verizon, where he leads a cross functional team focus on developing large scale search & recommendation services.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/cloud-data-migration-accenture-databricks","text":"Cloud Data Migration by Accenture - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionCloud Data Migration by AccentureMigration solution developed by Accenture and powered by the Databricks Lakehouse PlatformGet startedLess guesswork, more valueAccenture\u2019s Cloud Data Migration helps you navigate any complexity, from building landing zones in the Cloud Continuum to regulating data sovereignty. Accenture works with you to determine the right cloud strategy, operating model, roadmap and additional ecosystem partners. They then help you accelerate migration and modernization to the cloud so that it is secure, cost-effective and agile. Accenture\u2019s comprehensive cloud migration framework brings industrialized capabilities together with exclusive preconfigured, industry-specific tools, methods and automation across all cloud models and proven delivery methods. With Accenture\u2019s Cloud Data Migration Service, you will benefit from:Increased innovation, agility and flexibilityEasing of rising resource demands and better consumption managementReduction in cost, immediate business results and cloud scalabilityGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/ce-termsofuse","text":"Databricks Community Edition | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Community EditionCommunity Edition Terms of ServiceWelcome to Databricks Community Edition! We are pleased to provide Databricks Community Edition (the \u201cCommunity Edition Services\u201d) at no charge to those interested in learning and exploring the use of Databricks\u2019 cloud-based data analytics platform, which enables data analysts and others to easily tap the power of Apache Spark and Databricks\u2019 other proprietary functionality. \u00a0Your use of the Community Edition Services is governed by these Terms of Service, including the Arbitration Agreement (the \u201cTerms\u201d). \u00a0If you are using the Community Edition Services on behalf of an organization, you represent and warrant that you are authorized to bind that entity to these Terms, in which case \u201cyou\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind your entity or do not agree with these Terms, you must not accept these Terms and may not use the Community Edition Services. The effective date of these Terms is the earliest to occur of the date you explicitly accept these Terms, or the date you first access or use the Community Edition Services.BY CLICKING TO ACCEPT THESE TERMS OR USING THE COMMUNITY EDITION SERVICES, YOU ARE REPRESENTING THAT YOU HAVE CAREFULLY READ, UNDERSTOOD AND AGREE TO BE BOUND BY THESE TERMS, INCLUDING WITHOUT LIMITATION THE ACCEPTABLE USE POLICY, THE SECTION TITLED \u201cYOUR DATA AND USE OF COMMUNITY EDITION - RESTRICTIONS APPLY\u201d AND THE SECTION REGARDING MANDATORY, BINDING ARBITRATION OF DISPUTES ENTITLED \u201cDISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVER\u201d.YOUR DATA AND USE OF COMMUNITY EDITION \u2013 RESTRICTIONS APPLYThere Are Strict Limits On What Your Data Can Include. \u00a0In order for us to provide the Community Edition Services to you at no charge, we have implemented certain cost saving elements within the architecture of the Community Edition Services including, among other things, the use of a multi-tenant environment with limited data security protections. \u00a0In addition, Databricks personnel have generally unrestricted access to your account (\u201cYour Account\u201d) and any data used or exposed to the Community Edition Services for the purposes of monitoring and improving the quality of the service. \u00a0Therefore, you should have no expectation of privacy regarding the data you submit or otherwise make available in any way to the Community Edition Services (collectively, \u201cYour Data\u201d) or the notebooks you create within or upload to the Community Edition Services (\u201cYour Notebooks\u201d, and collectively with Your Data, \u201cYour Content\u201d) and you must limit Your Content to only that data and other information that you can afford to lose, or have accessed, obtained or disseminated by other parties.Without limiting the foregoing, under no circumstances are you permitted to use with or make available to the Community Edition Services (such data, \u201cProhibited Data\u201d):any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by this Agreement;any data with respect to which your use and provision to Databricks pursuant to this Agreement would breach any agreement between you and any third party;any data that includes pornography, incitements to violence, terrorism or other wrongdoing, or obscene, illicit or deceptive materials of any kind;any data with respect to which its usage as contemplated herein would violate any applicable local, state, federal or other laws, regulations, orders or rules, including without limitation any privacy laws;any (w) bank, credit card or other financial account numbers or login credentials, (x) social security, tax, driver\u2019s license or other government-issued identification numbers, (y) health information identifiable to a particular individual; or (z) any data that would constitute \u201cspecial categories of data,\u201d \u201csensitive personal data,\u201d or any similar concept under applicable law; orany data that is prohibited by the Acceptable Use Policy.You Must Protect Access to Your Account and to Your Content. \u00a0You are responsible for safeguarding your password and you must make sure no one else has access to it. \u00a0Additionally, in order to facilitate the sharing and widespread use of the Community Edition Services, we enable you, at your discretion, to share with others access to Your Content. \u00a0You bear sole responsibility for protecting access to Your Content and for any and all liabilities that may result from the misuse of any sharing privileges granted by you to others. You agree and acknowledge Databricks has a passive role in the transmission, reception and use of Your Content, and Databricks does not take any initiative in the transmission, reception, or use of Your Content. Moreover, as between you and Databricks, you agree and acknowledge that you are solely responsible for your use of Your Content and that Databricks cannot supervise, control, direct, choose, verify, investigate, or evaluate Your Content or your actions with respect to Your Content that you transmit or receive using the Community Edition Services. You acknowledge that we may (but are not obligated to) remove or disable access to any of Your Content, or interrupt any or all services, at any time at our own discretion. You understand and acknowledge that we have the right (but no obligation) to do so if we believe, or are notified, that you have breached any provision of this Agreement (including copyright breach), or if we discontinue or restrict the service that enables you to transmit or receive Your Content.Limits Apply to How You Can Use the Community Edition Services. \u00a0You agree that your use of the Community Edition Services is subject to the Acceptable Use Policy.DATABRICKS\u2019 LEGAL PROTECTIONS & OTHER PROVISIONSDatabricks Intellectual Property Rights. \u00a0The Community Edition Services are protected in various ways by copyright, trademark, and other laws of the United States and other countries. \u00a0These Terms don\u2019t grant you any rights to use of Databricks\u2019 intellectual property, including trademarks, logos and other brand features, except those rights necessary for you to use the Community Edition Services as contemplated under these Terms. \u00a0Databricks welcomes your feedback but please note that we may use your comments and suggestions freely to improve the Community Edition Services or any of our other products or services, and accordingly you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Community Edition Services or otherwise use any feedback Databricks receives from you.The Community Edition Services are Provided \u201cAs Is\u201d With No Warranty. \u00a0Databricks cannot provide guarantees regarding the Community Edition Services. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, DATABRICKS MAKES NO WARRANTIES, EXPRESS OR IMPLIED, ABOUT THE SERVICES, WHICH ARE PROVIDED \u201cAS IS.\u201d \u00a0WE DISCLAIM ALL WARRANTIES OF ANY KIND, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, NON-INTERRUPTION, ACCURACY OR DATA SECURITY. \u00a0Some jurisdictions don\u2019t allow certain of these disclaimers, so they may not apply to you.We Require Your Indemnification. \u00a0You understand and agree that Databricks bears no liability whatsoever in the event you violate the restrictions and obligations imposed by these Terms regarding your use of the Community Edition Services or for the loss of, or unauthorized access to, Your Data, and that Databricks\u2019 willingness and ability to provide access to you to the Community Edition Services at no charge is contingent upon this understanding, and upon your accepting and adhering to all other provisions of these Terms. \u00a0You agree to indemnify, defend and hold harmless each of Databricks and its investors, directors, officers, employees, representatives and affiliates from any claims, costs, damages, liabilities or expenses (including reasonable attorneys\u2019 fees) arising out of any third party claim alleging that Your Data or your use of our services infringes the rights of, or has caused harm to, any party, or violates any law or regulation.Limitation on Liability. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, IN NO EVENT WILL DATABRICKS BE LIABLE FOR ANY INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE, EXEMPLARY OR CONSEQUENTIAL DAMAGES OR ANY LOSS OF USE, DATA, BUSINESS OR PROFITS, REGARDLESS OF LEGAL THEORY, REGARDLESS OF WHETHER DATABRICKS HAS BEEN WARNED OF THE POSSIBILITY OF SUCH DAMAGES, AND EVEN IF A REMEDY FAILS OF ITS ESSENTIAL PURPOSE. \u00a0ADDITIONALLY, DATABRICKS\u2019 AGGREGATE LIABILITY TO YOU FOR ALL CLAIMS RELATING TO THE SERVICES SHALL NOT EXCEED THE GREATER OF THE TOTAL OF ANY AMOUNTS YOU MAY HAVE PAID US IN FEES FOR ANY SERVICE IN THE SIX MONTHS IMMEDIATELY PRIOR TO THE EVENT FIRST GIVING RISE TO ANY SUCH LIABILITY OR $500 (FIVE HUNDRED DOLLARS). THE FOREGOING LIMITATIONS AND EXCLUSIONS SHALL NOT APPLY WITH RESPECT TO ANY LIABILITY ARISING UNDER FRAUD, FRAUDULENT MISREPRESENTATION, GROSS NEGLIGENCE, OR ANY OTHER LIABILITY THAT CANNOT BE LIMITED OR EXCLUDED BY LAW. Some jurisdictions don\u2019t allow the types of limitations in this paragraph, so they may not apply to you. \u00a0IN THESE JURISDICTIONS, EACH PARTY\u2019S LIABILITY WILL BE FURTHER LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW. You agree that this limitation of liability section is intended to allocate the risks between the parties, and that but for this limitation of liability, Databricks would not make available the Community Edition Services.Entire Agreement; No Third Party Rights. These Terms constitute the entire agreement between you and Databricks concerning the Community Edition Services and these Terms create no third party beneficiary rights.Termination, Modification, Waiver & Assignment. \u00a0Either of us may suspend or terminate your use of the Community Edition Services or delete Your Account or Your Content at any time and for any reason (including without limitation for any suspected violations of the Acceptable Use Policy); however, obligations of these Terms that by their nature should survive termination shall so survive. \u00a0In addition, we may revise these Terms from time to time, and will always post the most current version on our website. \u00a0If we elect to terminate your access to the Community Edition Services or delete Your Account or Your Content, or if a revision of these Terms meaningfully reduces your rights, we will make a reasonable attempt to notify you (by, for example, sending a message to the email address associated with your account or posting for a reasonable time period a message to the login page of the Community Edition Services) unless Databricks deems it necessary to suspend or terminate Your Account without notice. \u00a0By continuing to use or access the Community Edition Services after the revisions come into effect, you agree to be bound by the revised Terms. Databricks' failure to enforce a provision of these Terms is not a waiver of its right to do so later. If a provision of these Terms is found unenforceable, the remaining provisions of the Terms will remain in full effect and an enforceable term will be substituted reflecting our intent as closely as possible, provided that questions of unenforceability regarding the Arbitration Agreement shall be resolved according to the Severability Section of the Arbitration Agreement. \u00a0You may not assign or transfer any of your rights under these Terms, and any such attempt will be void. Databricks may assign these Terms and\/or its rights under these Terms to any of its affiliates or to any successor in interest.DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVERInformal Resolution. You agree with us that, if either of us has concerns, we must first work together to resolve any dispute informally without resorting to legal action. \u00a0You agree to contact us at [email\u00a0protected] in the event you have a dispute prior to bringing a formal claim against Databricks. \u00a0If the dispute is not resolved within 30 calendar days from the notice date, either of us may bring a claim subject to the procedures set forth below. You and Databricks agree to the jurisdiction of the Northern District of California to resolve any dispute, claim, or controversy that relates to or arises in connection with these Terms (and any non-contractual disputes\/claims relating to or arising in connection with them) and is not subject to mandatory arbitration as set forth below (the \u201cArbitration Agreement\u201d). \u00a0Any disputes not subject to mandatory arbitration are subject to the laws of the state of California, without regard to choice or conflicts of law principles.Arbitration Agreement. \u00a0If you are located within the United States, you and Databricks agree that any dispute, claim, or controversy between you and Databricks arising in connection with or relating in any way to these Terms or to your relationship with Databricks as a user of the Community Edition Services (whether based in contract, tort, statute, fraud, misrepresentation, or any other legal theory, and whether the claims arise during or after the termination of these Terms) will be determined by mandatory binding individual (not class) arbitration. You and Databricks further agree that the arbitrator shall have the exclusive power to rule on his or her own jurisdiction, including any objections with respect to the existence, scope or validity of the Arbitration Agreement or to the arbitrability of any claim or counterclaim. The Arbitration Agreement will survive termination of the Terms. \u00a0You and Databricks agree that the Federal Arbitration Act applies and governs the interpretation and enforcement of the Arbitration Agreement (despite the choice of law provision above).Exceptions to Arbitration. Notwithstanding the prior clause, you and Databricks both agree that nothing in this Arbitration Agreement will be deemed to waive, preclude, or otherwise limit either of our rights, at any time, to (1) bring an individual action in a U.S. small claims court or (2) bring an individual action seeking only temporary or preliminary individualized injunctive relief in a court of law, pending a final ruling from the arbitrator. In addition, this Arbitration Agreement doesn\u2019t stop you or us from bringing issues to the attention of federal, state, or local agencies. Such agencies can, if the law allows, seek relief against us on your behalf (or vice versa).Prohibition of Class and Representative Actions and Non-Individualized Relief. You and Databricks agree that each of us may bring claims against the other only on an individual basis and not as a plaintiff or class member in any purported class or representative action or proceeding. \u00a0Unless both you and Databricks agree otherwise, the arbitrator(s) may not consolidate or join more than one person\u2019s or party\u2019s claims and may not otherwise preside over any form of a consolidated, representative or class proceeding. \u00a0Also, the arbitrator(s) may award relief (including monetary, injunctive and declaratory relief) only in favor of the individual party seeking relief and only to the extent necessary to provide relief necessitated by that party\u2019s individual claim(s). \u00a0Any relief awarded cannot affect other Databricks customers.Arbitration Procedures. Arbitration is more informal than a lawsuit in court. \u00a0Arbitration uses a neutral arbitrator or arbitrators instead of a judge or jury, and court review of an arbitration award is very limited. \u00a0However, the arbitrator(s) can award the same damages and relief on an individual basis that a court can award to an individual. The arbitrator(s) also must follow the terms of these Terms as a court would. \u00a0The arbitration will be conducted by the American Arbitration Association (referred to as the \"AAA\") under its rules and procedures, including the AAA's Consumer Arbitration Rules (as applicable), unless you have accepted these Terms as a representative of a business entity, in which case AAA\u2019s Commercial Arbitration Rules shall govern (as applicable), in each case as modified by this Arbitration Agreement. \u00a0The AAA's rules and forms to commence arbitration are available at www.adr.org. A party who intends to seek arbitration must first send the other party, if to Databricks, by certified mail, a completed Demand for Arbitration. You should send this notice to Databricks at: Databricks, Inc., Attn: Legal Department, Re: Demand for Arbitration, 160 Spear St., Ste. 1300, San Francisco, CA 94105 USA (with a copy to [email\u00a0protected]). \u00a0Databricks will send any notice to you to the address we have on file associated with your Databricks account (which may solely be at your account email address); it is your responsibility to keep your address up to date. All information called for in the notice must be provided including a description of the nature and basis of the claims the party is asserting and the relief sought. The arbitration shall be held in the county in which you reside or at another mutually agreed location. \u00a0If the value of the relief sought is $10,000 or less, you or Databricks may elect to have the arbitration conducted by telephone or based solely on written submissions, which election shall be binding on you and Databricks subject to the discretion of the arbitrator(s) to require an in-person hearing, if the circumstances warrant. In cases where an in-person hearing is held, you and\/or Databricks may attend by telephone, unless the arbitrator(s) require otherwise. Any settlement offer made by you or Databricks shall not be disclosed to the arbitrator(s). The arbitrator(s) will decide the substance of all claims in accordance with applicable law, including recognized principles of equity, and will honor all claims of privilege recognized by law. \u00a0The arbitrator(s) shall not be bound by rulings in prior arbitrations involving different Databricks customers, but is\/are bound by rulings in prior arbitrations involving the same Databricks customer to the extent required by applicable law. The award of the arbitrator(s) shall be final and binding, and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof.Costs of Arbitration. Payment of all filing, administration, and arbitrator fees will be governed by the AAA's rules (either Consumer or Commercial, as applicable), unless otherwise stated in this Arbitration Agreement. \u00a0If the value of the relief sought by an individual is $10,000 or less, at your request, Databricks will pay all filing, administration, and arbitrator fees associated with the arbitration. Any request for payment of fees by Databricks should be submitted by mail to the AAA along with your Demand for Arbitration and Databricks will make arrangements to pay all necessary fees directly to the AAA. \u00a0If the value of the relief sought by an individual is more than $10,000 and you are able to demonstrate that the costs of accessing arbitration will be prohibitive as compared to the costs of accessing a court for purposes of pursuing litigation on an individual basis, Databricks will pay as much of the filing, administration, and arbitrator fees as the arbitrator(s) deem necessary to prevent the cost of accessing the arbitration from being prohibitive. \u00a0In the event the arbitrator(s) determine the claim(s) you assert in the arbitration to be frivolous, you agree to reimburse Databricks for all fees associated with the arbitration paid by Databricks on your behalf that you otherwise would be obligated to pay under the AAA's rules.Severability. With the exception of any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above, if a court decides that any part of this Arbitration Agreement is invalid or unenforceable, the other parts of this Arbitration Agreement shall still apply. If a court decides that any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above is invalid or unenforceable because it would prevent the exercise of a non-waivable right to pursue public injunctive relief, then any dispute regarding the entitlement to such relief (and only that relief) must be severed from arbitration and may be litigated in court; in such case you irrevocably consent to the personal jurisdiction of the state and federal courts in the Northern District of California and such dispute shall be governed by the laws of the state of California, without regard to choice or conflicts of law principles. All other disputes subject to arbitration under the terms of the Arbitration Agreement shall be arbitrated under its terms.Amendments to Arbitration Agreement. Notwithstanding any provision in the Terms to the contrary, you and we agree that if we make any amendment to this Arbitration Agreement (other than an amendment to any notice address or website link provided herein) in the future, that amendment shall not apply to any claim that was filed in a legal proceeding against Databricks prior to the effective date of the amendment. \u00a0The amendment shall apply to all other disputes or claims governed by this Arbitration Agreement that have arisen or may arise between you and Databricks. We will notify you of amendments to this Arbitration Agreement by posting the amended terms on https:\/\/www.databricks.com\/legal\/ce-termsofuse at least 30 days before the effective date of the amendments and by providing notice through email where possible. \u00a0If you do not agree to these amended terms, you may close Your Account within the 30-day period and you will not be bound by the amended terms.Last Updated April 9, 2019ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-kutay\/#","text":"John Kutay - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn KutayDirector of Product Management at StriimBack to speakersJohn Kutay, Director of Product Management at Striim\nJohn Kutay is Director of Product Management at Striim with prior experience as a software engineer, product manager, and investor. His podcast \u201cWhat's New in Data\u201d best captures his ability to understand upcoming trends in the data space with thousands of listeners across the globe. In addition, John has over 10 years of experience in the streaming data space through academic research and his work at Striim.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks MarketplaceOffener Marktplatz f\u00fcr Daten, Analytics und KIErste SchritteTo play this video, click here and accept cookiesWas ist Databricks\nMarketplace?\nDatabricks Marketplace ist ein offener Marktplatz f\u00fcr alle Ihre Daten, Analytics und KI, der auf dem Open-Source-Standard Delta Sharing basiert. Der Databricks Marketplace erweitert Ihre M\u00f6glichkeiten, Innovationen auf den Markt zu bringen und alle Ihre Analytics- und KI-Initiativen voranzutreiben.\u00a0\nSie finden dort Datens\u00e4tze sowie KI- und Analytics-Ressourcen\u00a0\u2013 wie ML-Modelle, Notebooks, Anwendungen und Dashboards\u00a0\u2013 ohne propriet\u00e4re Plattformabh\u00e4ngigkeiten, kompliziertes ETL oder teure Replikation. Dieser offene Ansatz erm\u00f6glicht es Ihnen, Daten in jeder Cloud mit den Tools Ihrer Wahl schneller einsatzbereit zu machen.Mehr als nur Daten entdeckenRealisieren Sie Innovationen und bringen Sie die KI-, ML- und Analytics-Initiativen Ihres Unternehmens voran. Greifen Sie auf mehr als nur Datens\u00e4tze zu, darunter ML-Modelle, Notebooks, Anwendungen und L\u00f6sungen.Datenprodukte schneller bewertenBereits erstellte Notebooks und Beispieldaten helfen Ihnen, schnell zu bewerten und viel mehr Vertrauen darauf zu haben, dass ein Datenprodukt f\u00fcr Ihre KI-, ML- oder Analytics-Initiativen geeignet ist.Anbieterbindung vermeidenGewinnen Sie aussagekr\u00e4ftige Informationen aus Daten in wesentlich k\u00fcrzerer Zeit und vermeiden Sie Abh\u00e4ngigkeiten durch offenes und nahtloses Teilen sowie eine Zusammenarbeit \u00fcber Clouds, Regionen oder Plattformen hinweg. Integrieren Sie die L\u00f6sung direkt in die Tools Ihrer Wahl und genau dort, wo Sie arbeiten.Ausgew\u00e4hlte Datenanbieter auf Databricks MarketplaceDatenanbieter auf dem Marketplace werden\nRessourcenVeranstaltungJetzt f\u00fcr den Data + AI Summit 2023 anmeldenREGISTRIERENE-BookEin neuer Ansatz beim Data SharingJetzt lesenE-BookDaten, Analysen und KI-GovernanceJetzt lesenKeynoteData Governance and Sharing on the Lakehouse beim Data + AI Summit 2022 BlogsAnk\u00fcndigung der \u00f6ffentlichen Vorschau auf den MarketplaceAnk\u00fcndigung von Databricks Marketplace auf dem Data + AI Summit 2022DokumentationAWSAzureGCPProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/akira-ajisaka","text":"Akira Ajisaka - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAkira AjisakaSenior Software Development Engineer at Amazon Web ServicesBack to speakersAkira Ajisaka is a Senior Software Development Engineer on the AWS Glue team at Amazon Web Services. He likes open source software and distributed systems. He is an Apache Hadoop committer and PMC member.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/satish-garla","text":"Satish Garla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSatish GarlaSr Solutions Architect at DatabricksBack to speakersSatish has a distinguished background in cloud modernization, data management, data science and financial risk management. He started his career implementing enterprise risk solutions using SAS. Satish leveraged open source tools and dotData technology to implement automated Feature Engineering and AutoML. Currently Satish works as a Sr Solutions Architect at Databricks helping enterprises with cloud and Lakehouse adoption using open source technologies such as Apache Spark, Delta and MLFlow.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/financial-services-resources\/lakehouse-for-financial-services-ebook","text":"\n\n\n\n\n\n\n\nLakehouse For Financial Services eBook | Databricks\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/de\/professional-services","text":"Databricks Professional Services | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks Professional ServicesKontaktieren Sie uns, um mehr zu erfahren.Projekte schneller erfolgreich abschlie\u00dfen \u2013 dank erstklassigem Fachwissen in den Bereichen Data Engineering, Data Science und Projektmanagement. Databricks Professional Services unterst\u00fctzen Sie in jeder Phase Ihrer Daten- und KI-Erfahrung:VorteileBei Daten und KI aufs Tempo dr\u00fccken\nUnsere Angebote und Fachservices unterst\u00fctzen Sie bei Ihrer Journey im Daten- und KI-Bereich und beschleunigen ihre Abl\u00e4ufe individuell und optimal \u2013 vom ersten Workspace-Onboarding bis zur Ausbildung von DataOps- und Center-of-Excellence-Praktiken im Unternehmensma\u00dfstab.\nIhr Projekt risiko\u00e4rmer machen\nGanz gleich, ob Sie von Legacy-Workloads auf Databricks migrieren, neue Datenprodukte oder Daten-, KI-Pipeline- und Machine-Learning-Projekte entwickeln: Als vertrauensw\u00fcrdiger Partner und Berater sorgen wir gemeinsam mit Ihnen bei jedem Schritt Ihrer Journey daf\u00fcr, dass Risiken sinken und der Mehrwert steigt.\nOperationalisierung in gro\u00dfem Umfang\nDas Entwickeln eines Proof-of-Concept f\u00fcr eine Datenpipeline oder eines Einzelknotenmodells ist noch einigerma\u00dfen \u00fcberschaubar. Schwierig wird es, wenn es darum geht, Daten- und KI-Verfahren im gesamten Unternehmen erfolgreich einzuf\u00fchren und zu skalieren. Mit unseren pr\u00e4skriptiven Angeboten und unserem Fachwissen m\u00f6chten wir Sie bei der Bew\u00e4ltigung dieser anspruchsvollen Aufgabe unterst\u00fctzen.\nAngeboteSchneller Erfolg bei Projekten mit erstklassigem Fachwissen in den Bereichen Data Engineering, Data Science und ProjektmanagementSchnellstartMachen Sie sich mit der Databricks-Plattform und ihren wichtigsten, auf Best Practices basierenden Funktionen vertraut, um Ihre Projekte deutlich zu beschleunigen.Hadoop-MigrationMit unserer pr\u00e4skriptiven Methodik maximieren Sie den Wert Ihrer bestehenden Daten- und Pipeline-Investitionen und profitieren von einer reibungslosen Migration.Ausbau des Lake HouseBeschleunigen Sie die Implementierung einer einheitlichen und vereinfachten Plattform f\u00fcr Data Analytics, Data Science und ML und legen Sie so den Grundstein f\u00fcr Ihre Lakehouse-Vision.Machine LearningMit unserer pr\u00e4skriptiven Methodik optimieren Sie unternehmensweite ML-Initiativen und steigern deren Akzeptanz.Shared Services AcceleratorKurbeln Sie Ihr unternehmensweites Betriebsmodell an und f\u00f6rdern Sie mit unserer pr\u00e4skriptiven Methodik Daten- und KI-Exzellenz.Ma\u00dfgeschneiderte ServicesWenden Sie sich an uns, um eine individuelle Leistungsbeschreibung f\u00fcr Ihre Anforderungen zu erhalten.Unsere Spezialisten f\u00fcr professionelle Services k\u00f6nnen auf eine umfangreiche Erfolgsbilanz verweisen, wenn es darum geht, komplexe, sehr spezifische und gezielte Anforderungen im gesamten Projektlebenszyklus zu erf\u00fcllen.Architekten f\u00fcr Resident Solutions | Data ScientistsWir vermitteln technische Ressourcen mit viel Erfahrung und hoher F\u00fchrungs- und Beratungskompetenz. Zur Absicherung Ihres Erfolgs greifen wir nach Bedarf auf Unterst\u00fctzung aus unserem umfangreichen Netzwerk professioneller Partner zur\u00fcck und implementieren Projekte nach Bedarf auch mit ihnen gemeinsam.Databricks- und Spark-Experten10\u00a0Jahre Erfahrung\nSolider Big-Data-Hintergrund\nPraktische F\u00e4higkeiten bei der Umsetzung\nProjektplanung und -durchf\u00fchrungUnterst\u00fctzung bei Design und Architektur\nUnterst\u00fctzung bei der Anpassung des Projekts an die F\u00e4higkeiten der Plattform\nBereitstellung von Beitr\u00e4gen zu Projektzeitpl\u00e4nen und Ressourcenbedarf\nImplementierungs- und ProduktionsplanungArchitekturl\u00f6sungen f\u00fcr Skalierbarkeit\nUnterst\u00fctzung bei der Prototypentwicklung\nAnforderungen an die DevOps-Integration in die Tat umsetzen\nUnterst\u00fctzung bei der Einf\u00fchrung eines COEEntwicklung gemeinsamer Standards und Frameworks\nAls Ressource f\u00fcr mehrere Teams zur Verf\u00fcgung stehen\nErleichterung der Interaktion mit anderen Databricks-Teams\nBetriebsmittel\u00dcbersicht \u00fcber das ErfolgskreditprogrammFormular f\u00fcr den Antrag auf Einl\u00f6sungWarum gibt es die Databricks Akademie?Der Mensch steht im Mittelpunkt des Kundenerfolgs. Mit Schulungen und Zertifizierungen der Databricks Academy \u2013 dem Team, das seinerzeit an der UC Berkeley das Spark-Forschungsprojekt ins Leben gerufen hat \u2013 bekommen Sie Data Analytics wirklich in den Griff. Mit der Databricks Academy setzen Sie einfach schneller mehr um.Jetzt Kompetenzen erweiternM\u00f6chten Sie loslegen?KontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/product-matching-with-ml","text":"How to build: Product matching with machine learning | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: Product matching with machine learningOptimize product matching to drive sales\nUse machine learning and the Databricks Lakehouse Platform for product matching that can be used by marketplaces and suppliers for various purposes. Resolve differences between product definitions and descriptions and determine which items are likely pairs and which are distinct across disparate data sets.\nRead the full write-up\nDownload notebooksBenefits and business valueOptimize your matchingUse a wide range of data formats and techniques, such as computer vision, NLP and deep learning to extract product features\nScale as neededWith rapid provisioning of cloud resources, workflows can be cost-effectively allocated with resources as needed\nDrive profitabilitySave time and create effective upsell opportunities to drive profitability\nReference ArchitectureDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/spark\/about","text":"About Spark \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache Spark\u2122Apache Spark is a lightning-fast\u00a0unified analytics engine\u00a0for big data and machine learning. It was originally developed at UC Berkeley in 2009.The largest open source project in data processing.Since its release,\u00a0Apache Spark, the unified analytics engine, has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. It has quickly become the largest open source community in big data, with over 1000 contributors from 250+ organizations.The team that started the Spark research project at UC Berkeley founded Databricks in 2013.Apache Spark is 100% open source, hosted at the vendor-independent Apache Software Foundation. At Databricks, we are fully committed to maintaining this open development model. Together with the Spark community, Databricks continues to contribute heavily to the Apache Spark project, through both development and community evangelism.Watch the videoWhat is Apache Spark - Benefits of Apache SparkSpeed\nEngineered from the bottom-up for performance, Spark can be\u00a0100x faster than Hadoop for large scale data processing\u00a0by exploiting in memory computing and other optimizations. Spark is also fast when data is stored on disk, and currently holds the world record for large-scale on-disk sorting.\nEase of Use\nSpark has easy-to-use APIs for operating on large datasets. This includes a collection of over 100 operators for transforming data and familiar data frame APIs for manipulating semi-structured data.A Unified Engine\nSpark comes packaged with higher-level libraries, including support for SQL queries, streaming data, machine learning and graph processing. These standard libraries increase developer productivity and can be seamlessly combined to create complex workflows.Try Apache Spark on the Databricks cloud for freeThe Databricks Unified Analytics Platform offers 5x performance over open source Spark, collaborative notebooks, integrated workflows, and enterprise security \u2014 all in a fully managed cloud platform.Try DatabricksThe open source Apache Spark project can be\u00a0downloaded hereProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/hadoop-ecosystem","text":"What is a Hadoop Ecosystem?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHadoop EcosystemAll>Hadoop EcosystemWhat is the Hadoop Ecosystem?Apache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of the Hadoop ecosystem include HDFS, Hive, Pig, YARN, MapReduce, Spark, HBase, Oozie, Sqoop, Zookeeper, etc. Here are the major Hadoop ecosystem components that are used frequently by developers:What is HDFS?Hadoop Distributed File System (HDFS), is one of the largest Apache projects and primary storage system of Hadoop. It employs a NameNode and DataNode architecture. It is a distributed file system able to store large files running over the cluster of commodity hardware.What is Hive?Hive is an ETL and Data warehousing tool used to query or analyze large datasets stored within the Hadoop ecosystem. Hive has three main functions: data summarization, query, and analysis of unstructured and semi-structured data in Hadoop. It features a SQL-like interface, HQL language that works similar to SQL and automatically translates queries into MapReduce jobs.What is Apache Pig?This is a high-level scripting language used to execute queries for larger datasets that are used within Hadoop. Pig's simple SQL-like scripting language is known as Pig Latin and its main objective is to perform the required operations and arrange the final output in the desired format.What is MapReduce?This is another data processing layer of Hadoop. It has the capability to process large structured and unstructured data as well as to manage very large data files in parallel by dividing the job into a set of independent tasks (sub-job).What is YARN?YARN stands for Yet Another Resource Negotiator, but it's commonly referred to by the acronym alone. It is one of the core components in open source Apache Hadoop suitable for resource management. It is responsible for managing workloads, monitoring, and security controls implementation. It also allocates system resources to the various applications running in a Hadoop cluster while assigning which tasks should be executed by each cluster nodes. YARN has two main components:Resource ManagerNode ManagerWhat is Apache Spark?Apache Spark is a fast, in-memory data processing engine suitable for use in a wide range of circumstances. Spark can be deployed in several ways, it features Java, Python, Scala, and R programming languages, and supports SQL, streaming data, machine learning, and graph processing, which can be used together in an application.Additional ResourcesStep-by-Step Migration: Hadoop to DatabricksCloud Modernization With Databricks and AWSDatabricks migration hubHidden value of Hadoop migration whitepaperIt\u2019s time to reconsider your relationship with HadoopDelta Lake and ETLMaking Apache Spark\u2122 Better with Delta LakeBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2019\/03\/07\/simplifying-genomics-pipelines-at-scale-with-databricks-delta.html","text":"Simplifying Genomics Pipelines at Scale with Databricks Delta - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorSimplifying Genomics Pipelines at Scale with Databricks Deltaby William Brandler and Frank Austin NothaftMarch 7, 2019 in Engineering BlogShare this postTry this notebook in DatabricksThis blog is the first blog in our \u201cGenomics Analysis at Scale\u201d series. In this series, we will demonstrate how the Databricks Unified Analytics Platform for Genomics enables customers to analyze population-scale genomic data. Starting from the output of our genomics pipeline, this series will provide a tutorial on using Databricks to run sample quality control, joint genotyping, cohort quality control, and advanced statistical genetics analyses.Since the completion of the Human Genome Project in 2003, there has been an explosion in data fueled by a dramatic drop in the cost of DNA sequencing, from $3B1 for the first genome to under $1,000 today.\n[1] The Human Genome Project was a $3B project led by the Department of Energy and the National Institutes of Health began in 1990 and completed in 2003.Source: DNA Sequencing Costs: DataConsequently, the field of genomics has now matured to a stage where companies have started to do DNA sequencing at population-scale. However, sequencing the DNA code is only the first step, the raw data then needs to be transformed into a format suitable for analysis. Typically this is done by gluing together a series of bioinformatics tools with custom scripts and processing the data on a single node, one sample at a time, until we wind up with a collection of genomic variants. \u00a0Bioinformatics scientists today spend the majority of their time building out and maintaining these pipelines. As genomic data sets have expanded into the petabyte scale, it has become challenging to answer even the following simple questions in a timely manner:\nHow many samples have we sequenced this month?What is the total number of unique variants detected?How many variants did we see across different classes of variation?Further compounding this problem, data from thousands of individuals cannot be stored, tracked nor versioned while also remaining accessible and queryable. Consequently, researchers often duplicate subsets of their genomic data when performing their analyses, causing the overall storage footprint and costs to escalate. \u00a0In an attempt to alleviate this problem, today researchers employ a strategy of \u201cdata freezes\u201d, typically between six months to two years, where they halt work on new data and instead focus on a frozen copy of existing data. There is no solution to incrementally build up analyses over shorter time frames, causing research progress to slow down.\nThere is a compelling need for robust software that can consume genomic data at industrial scale, while also retaining the flexibility for scientists to explore the data, iterate on their analytical pipelines, and derive new insights.\nFig 1. Architecture for end-to-end genomics analysis with DatabricksWith Databricks Delta: A Unified Management System for Real-time Big Data Analytics, the Databricks platform has taken a major step towards solving the data governance, data access, and data analysis issues faced by researchers today. With\u00a0Databricks Delta Lake, you can store all your genomic data in one place, and create analyses that update in real-time as new data is ingested. Combined with optimizations in our Unified Analytics Platform for Genomics (UAP4G) for reading, writing, and processing genomics file formats, we offer an end-to-end solution for genomics pipelines workflows. The UAP4G architecture offers flexibility, allowing customers to plug in their own pipelines and develop their own tertiary analytics. As an example, we\u2019ve highlighted the following dashboard showing quality control metrics and visualizations that can be calculated and presented in an automated fashion and customized to suit your specific requirements.\nhttps:\/\/www.youtube.com\/watch?v=73fMhDKXykU\nIn the rest of this blog, we will walk through the steps we took to build the quality control dashboard above, which updates in real time as samples finish processing. By using a Delta-based pipeline for processing genomic data, our customers can now operate their pipelines in a way that provides real-time, sample-by-sample visibility. With Databricks notebooks (and integrations such as GitHub and MLflow) they can track and version analyses in a way that will ensure their results are reproducible. Their bioinformaticians can devote less time to maintaining pipelines and spend more time making discoveries. We see the UAP4G as the engine that will drive the transformation from ad-hoc analyses to production genomics on an industrial scale, enabling better insights into the link between genetics and disease.\nRead Sample DataLet\u2019s start by reading variation data from a small cohort of samples; the following statement reads in data for a specific sampleId and saves it using the Databricks Delta format (in the delta_stream_output folder).\nspark.read. \\\nformat(\"parquet\"). \\\n      load(\"dbfs:\/annotations_etl_parquet\/sampleId=\" + \"SRS000030_SRR709972\"). \\\n      write. \\\n      format(\"delta\"). \\\n      save(delta_stream_outpath)\nNote, the annotations_etl_parquet folder contains annotations generated from the 1000 genomes dataset stored in parquet format. \u00a0\u00a0The ETL and processing of these annotations were performed using Databricks\u2019 Unified Analytics Platform for Genomics.Start Streaming the Databricks Delta TableIn the following statement, we are creating the exomes Apache Spark DataFrame which is reading a stream (via readStream) of data using the Databricks Delta format. \u00a0This is a continuously running or dynamic DataFrame, i.e. the exomes DataFrame will load new data as data is written into the delta_stream_output folder. \u00a0\u00a0To view the exomes DataFrame, we can run a DataFrame query to find the count of variants grouped by the sampleId.\n# Read the stream of data \nexomes = spark.readStream.format(\"delta\").load(delta_stream_outpath)\n\n# Display the data via DataFrame query\ndisplay(exomes.groupBy(\"sampleId\").count().withColumnRenamed(\"count\", \"variants\"))\nWhen executing the display statement, the Databricks notebook provides a streaming dashboard to monitor the streaming jobs. \u00a0Immediately below the streaming job are the results of the display statement (i.e. the count of variants by sample_id).\nLet\u2019s continue answering our initial set of questions by running other DataFrame queries based on our exomes DataFrame.\nSingle Nucleotide Variant CountTo continue the example, we can quickly calculate the number of single nucleotide variants (SNVs), as displayed in the following graph.\n%sql\nselect referenceAllele, alternateAllele, count(1) as GroupCount \n  from snvs\n group by referenceAllele, alternateAllele\n order by GroupCount desc\nNote, the display command is part of the Databricks workspace that allows you to view your DataFrame using Databricks visualizations (i.e. no coding required).Variant CountSince we have annotated our variants with functional effects, we can continue our analysis by looking at the spread of variant effects we see. The majority of the variants detected flank regions that code for proteins, these are known as noncoding variants.\ndisplay(exomes.groupBy(\"mutationType\").count())\nAmino Acid Substitution HeatmapContinuing with our exomes DataFrame, let\u2019s calculate the amino acid substitution counts with the following code snippet. \u00a0Similar to the previous DataFrames, we will create another dynamic DataFrame (aa_counts) so that as new data is processed by the exomes DataFrame, it will subsequently be reflected in the amino acid substitution counts as well. \u00a0We are also writing the data into memory (i.e. .format(\u201cmemory\u201d)) and processed batches every 60s (i.e. trigger(processingTime=\u201960 seconds\u2019)) so the downstream Pandas heatmap code can process and visualize the heatmap.\n# Calculate amino acid substitution counts\ncoding = get_coding_mutations(exomes)\naa_substitutions = get_amino_acid_substitutions(coding.select(\"proteinHgvs\"), \"proteinHgvs\")\naa_counts = count_amino_acid_substitution_combinations(aa_substitutions)\naa_counts. \\\n  writeStream. \\\n  format(\"memory\"). \\\n  queryName(\"amino_acid_substitutions\"). \\\n  outputMode(\"complete\"). \\\n  trigger(processingTime='60 seconds'). \\\n  start()\nThe following code snippet reads the preceding amino_acid_substitutions Spark table, determines the max count, creates a new Pandas pivot table from the Spark table, and then plots out the heatmap.\n# Use pandas and matplotlib to build heatmap\namino_acid_substitutions = spark.read.table(\"amino_acid_substitutions\")\nmax_count = amino_acid_substitutions.agg(fx.max(\"substitutions\")).collect()[0][0]\naa_counts_pd = amino_acid_substitutions.toPandas()\naa_counts_pd = pd.pivot_table(aa_counts_pd, values='substitutions', index=['reference'], columns=['alternate'], fill_value=0)\n\nfig, ax = plt.subplots()\nwith sns.axes_style(\"white\"):\n  ax = sns.heatmap(aa_counts_pd, vmax=max_count*0.4, cbar=False, annot=True, annot_kws={\"size\": 7}, fmt=\"d\")\nplt.tight_layout()\ndisplay(fig)\nMigrating to a Continuous PipelineUp to this point, the preceding code snippets and visualizations represent a single run for a single sampleId. \u00a0But because we\u2019re using Structured Streaming and Databricks Delta, this code can be used (without any changes) to construct a production data pipeline that computes quality control statistics continuously as samples roll through our pipeline. To demonstrate this, we can run the following code snippet that will load our entire dataset.\nimport time\nparquets = \"dbfs:\/databricks-datasets\/genomics\/annotations_etl_parquet\/\"\nfiles = dbutils.fs.ls(parquets)\ncounter=0\nfor sample in files:\n  counter+=1\n  annotation_path = sample.path\n  sampleId = annotation_path.split(\"\/\")[4].split(\"=\")[1]\n  variants = spark.read.format(\"parquet\").load(str(annotation_path))\n  print(\"running \" + sampleId)\n  if(sampleId != \"SRS000030_SRR709972\"):\n    variants.write.format(\"delta\"). \\\n             mode(\"append\"). \\\n             save(delta_stream_outpath)\n  time.sleep(10)\nAs described in the earlier code snippets, the source of the exomes DataFrame are the files loaded into the delta_stream_output folder. \u00a0Initially, we had loaded a set of files for a single sampleId (i.e., sampleId = \u201cSRS000030_SRR709972\u201d). \u00a0\u00a0The preceding code snippet now takes all of the generated parquet samples (i.e. parquets) and incrementally loads those files by sampleId into the same delta_stream_output folder. \u00a0\u00a0The following animated GIF shows the abbreviated output of the preceding code snippet.\nhttps:\/\/www.youtube.com\/watch?v=JPngSC5Md-Q\nVisualizing your Genomics PipelineWhen you scroll back to the top of your notebook, you will notice that the exomes DataFrame is now automatically loading the new sampleIds. \u00a0Because the structured streaming component of our genomics pipeline runs continuously, it processes data as soon as new files are loaded into the delta_stream_outputpath folder. \u00a0By using the Databricks Delta format, we can ensure the transactional consistency of the data streaming into the exomes DataFrame.\nhttps:\/\/www.youtube.com\/watch?v=Q7KdPsc5mbY\nAs opposed to the initial creation of our exomes DataFrame, notice how the structured streaming monitoring dashboard is now loading data (i.e., the fluctuating \u201cinput vs. processing rate\u201d, fluctuating \u201cbatch duration\u201d, and an increase of distinct keys in the \u201caggregations state\u201d). \u00a0As the exomes DataFrame is processing, notice the new rows of sampleIds (and variant counts). \u00a0This same action can also be seen for the associated group by mutation type query.\nhttps:\/\/www.youtube.com\/watch?v=sT179SCknGM\nWith Databricks Delta, any new data is transactionally consistent in each and every step of our genomics pipeline. \u00a0This is important because it ensures your pipeline is consistent (maintains consistency of your data, i.e. ensures all of the data is \u201ccorrect\u201d), reliable (either the transaction succeeds or fails completely), and can handle real-time updates (the ability to handle many transactions concurrently and any outage of failure will not impact the data). \u00a0\u00a0Thus even the data in our downstream amino acid substitution map (which had a number of additional ETL steps) is refreshed seamlessly.\nAs the last step of our genomics pipeline, we are also monitoring the distinct mutations by reviewing the Databricks Delta parquet files within DBFS (i.e. increase of distinct mutations over time).\nSummaryUsing the foundation of the Databricks Unified Analytics Platform - with particular focus with Databricks Delta - bioinformaticians and researchers can apply distributed analytics with transactional consistency using Databricks Unified Analytics Platform for Genomics. These abstractions allow data practitioners to simplify genomics pipelines. \u00a0Here we have created a genomic sample quality control pipeline that continuously processes data as new samples are processed, without manual intervention. \u00a0Whether you are performing ETL or performing sophisticated analytics, your data will flow through your genomics pipeline rapidly and without disruption. Try it yourself today by downloading the Simplifying Genomics Pipelines at Scale with Databricks Delta notebook.\nGet Started Analyzing Genomics at Scale:\nRead our Unified Analytics for Genomics solution guideDownload the Simplifying Genomics Pipelines at Scale with Databricks Delta notebookSign-up for a free trial of Databricks Unified Analytics for GenomicsAcknowledgmentsThanks to Yongsheng Huang and Michael Ortega for their contributions.Interested in the open source Delta Lake?Visit the Delta Lake online hub to learn more, download the latest code and join the Delta Lake community.\u00a0Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christina-taylor-0\/#","text":"Christina Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristina TaylorData Engineer at ToptalBack to speakersChristina is passionate about modern data platforms, mutil-cloud architecture, scalable data pipelines, as well as the latest and greatest in the open source community. An intensely curious lifelong learner and effective team leader, she builds data lakes with medallion structure that support advanced analytics, data science models, and customer facing applications. She also has a keen interest in interdisciplinary areas such as Cloud FinOps, DevOps and MLOps.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joanna-gurry","text":"Joanna Gurry - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoanna GurryExecutive, Data Delivery at National Australia Bank (NAB)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=singapore","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-thompson","text":"John Thompson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn ThompsonGlobal Head, Artificial Intelligence at EYBack to speakersJohn is an international technology executive with over 35 years of experience in the fields of data, advanced analytics, and artificial intelligence (AI). He is currently the Global Head of AI at EY.\nJohn has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support, and product development organizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/rd-optimization-with-knowledge-graphs","text":"R&D Optimization With Knowledge Graphs | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorR&D Optimization With Knowledge GraphsPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedUnlocking hidden insights in your data with knowledge graphsKnowledge graphs combine the semantics, scalability and flexibility of a graph database with the performance and governance of a data lakehouse. With the Databricks Lakehouse for Healthcare and Life Sciences, R&D teams can:Store and organize all forms of life sciences data in the lakehouseSynthesize new insights through advanced network analytics and machine learningBuild a knowledge graph with Wisecube to reveal opportunities to improve R&DDownload notebookResourcesUse Case GuideRead nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hitesh-sahni\/#","text":"Hitesh Sahni - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHitesh SahniHead of Cloud Data Platforms and Data Engineering Solutions at Deutsche Post DHLBack to speakersHitesh is head of Cloud Data Platforms and Solutions and Lead architect at DPDHL Group responsible for developing, scaling global cloud data management capabilities, delivering cloud data analytics projects including both data platforms and data engineering solutions.\nHitesh is results oriented Technology Leader with business acumen enabling data driven digital transformation, diverse experience in Big Data Analytics and Cloud Space across various industry verticals (banking, Logistics, etc.).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christopher-locklin\/#","text":"Christopher Locklin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristopher LocklinEngineer Manager, Data Platform at GrammarlyBack to speakersChris Locklin has been leading data infrastructure and engineering teams for the last 9 years (at Grammarly, Dropbox, and Verizon), and initially entered the data space in 2010. He is currently the engineering manager of the Data Platform team at Grammarly. The team is responsible for ingesting, processing, and surfacing over 50 billion events every day.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/modernising-risk-management-financial-services-virtual-workshop","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/usps-oig","text":"Applying advanced analytics for the sanctity and delivery of mail | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYDelivering integrity and efficiency for the U.S. Postal ServiceUSPS OIG supports efficient postal service to millions with Databricks Lakehouse40%Reduction in total cost of ownership (compared to SAS)WeeksTo deliver projects instead of months  INDUSTRY: Federal Government PLATFORM USE CASE: Lakehouse,Machine Learning,Data Warehousing  CLOUD: Azure\u201cWith our move to the cloud and lakehouse architecture, we are well positioned to respond to new data challenges swiftly, enabling us to fulfill the agency\u2019s mission of ensuring efficiency, accountability and integrity in the U.S. Postal Service.\u201d\n\u2013 Ben Joseph, CDO, USPS OIGThe United States Postal Service (USPS) delivers more than 400 million pieces of mail each day. Established to sustain public trust in the mail system, the USPS OIG is critical to ensuring the integrity and accountability of the Postal Service, including its personnel, programs, assets and revenue. The USPS OIG embarked on a data modernization journey to better handle the challenges of today and prepare for those of tomorrow. Using the Lakehouse Architecture, the USPS OIG was able to centralize data analysis in the cloud for easier access and cleared data engineering bottlenecks for large-scale analytics and AI. With the means to use data to facilitate the identification of not only challenges but also new opportunities for innovation, the USPS OIG is better positioned to investigate, audit and research postal operations and programs to protect against fraud, waste and abuse, ensuring the efficiency and integrity of the USPS.Inability to scale analytics with the data perpetuates stagnationAs one of the most trusted government agencies in the country, the U.S. Postal Service (USPS) depends on a network of people and technology to collect, transport, process and deliver nearly 130 billion pieces of mail to over 163 million delivery points per year. The United States Postal Service Office of Inspector General (OIG) was established as an independent oversight agency to help maintain confidence in the postal system and improve the bottom line through audits and investigations. For instance, a key focus of the agency is to detect and prevent postal crimes such as mail dumping, which is when postal employees intentionally discard or delay mail rather than deliver it to its intended recipients. By monitoring various USPS data points, the OIG can identify indicators of employees or routes that are involved with dumped mail.Prior to its use of a data lakehouse architecture, the OIG\u2019s on-premises infrastructure was highly complex to manage and costly to scale. This became increasingly problematic as data volumes increased at such a rate that the office faced challenges extracting insights and developing timely solutions. The agency struggled to handle the influx of customer and delivery-related data, provide a centralized view for all teams, and support reliable and performant data pipelines for downstream analytics and machine learning \u2014 a requirement that became heavily evident during the 2020 election season, which saw a historic spike in voting by mail due to COVID-19.With a data team of more than 100 people who needed to work together or respond to anomalous activities in a timely manner, the OIG looked to the cloud and a new data architecture that would offer all its data teams easy access to any data and unlock new analytical and machine learning capabilities to further its efforts to improve mail delivery efficiency and accountability.Lakehouse solves efficiency challenges and opens new doorsA combination of internal and external factors challenged the OIG to simplify the management of all its data at scale while also facilitating analytics and machine learning. \u201cWe wanted to leverage industry standards for data management and analytics in-house, which prompted our transition to the cloud,\u201d explained Ben Joseph, CDO at USPS OIG. \u201cAs we explored our data infrastructure options, we found that a data lakehouse platform is the only environment that offers a common place to do ETL, analytics and machine learning under the same umbrella.\u201dWith a data lakehouse platform, the OIG has removed the barriers that once blocked its ability to deliver reliable and timely data for analytics and machine learning. With an open lakehouse architecture, all the data the agency pulls from USPS is much clearer and easier to use across teams. It has also unlocked a level of operational efficiency and performance at an unprecedented scale. Data engineers can simplify ETL pipeline development and improve data reliability, data analysts can use SQL to collaboratively query and share insights with the built-in visualizations and dashboards, and data scientists can use AutoML to jump-start new machine learning projects by automating tasks and accelerating workflows.For example, one solution called Informed Delivery provides eligible residential customers with a digital preview of their household\u2019s incoming mail. This allows households to see and track their inbound mail more easily. Behind the scenes, OIG stores images of mail alongside traditional data on things like sender, receiver, package contents, weight and value. By combining this data, it can mitigate fraudulent activity in the shape of mail theft or dumping, while improving the customer experience.As a branch of the federal government and a long-established institution without a reputation for being modern in its approach to workflows, the Postal Service expects to see an incredibly positive effect on customer satisfaction and the agency\u2019s reputation through its adoption of the lakehouse.Delivering insights that matter, with confidenceMigrating to a cloud based data lakehouse architecture not only paid dividends from an innovation standpoint, but it also made an impact on costs. Compared to its previous architecture, the agency experienced a 40% reduction in total cost of ownership. These savings were primarily due to the elimination of legacy data infrastructure, unnecessary storage and licensing costs, and productivity improvements.Simultaneously, the OIG\u2019s ability to harness its data for analytics and machine learning use cases was reduced from months to days, because of the data engineering efficiencies introduced by the lakehouse. In fact, it has been able to scale its data ingestion from 1 production pipeline in its legacy system to over 90 production pipelines in the data lakehouse. This has helped the agency deliver more value to its various auditors and investigators in uncovering anomalous activity, while also giving the data team the satisfaction of being able to create customer-facing solutions in ways that were impossible with the previous system.Joseph explained, \u201cOur society has experienced a lot of change on many levels in the last couple of years, and all we want to do as an organization is to be able to respond to those changes and support the various stakeholders who love our products but need more of them. The data lakehouse platform has enabled us to do that on a level we never dreamed of.\u201dNow that the OIG can operate in a more forward-thinking and agile fashion, the team is taking on several additional use cases. With the lakehouse as its data foundation, the OIG is well positioned to continue leveraging data, analytics and AI to deliver value efficiently and with confidence.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/surya-turaga\/#","text":"Surya Turaga - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSurya TuragaSr. Solutions Architect at DatabricksBack to speakersIn the past I have been responsible for Strategic client development, working with senior client stakeholders to act as a thought leader and evangelist across the Advanced Analytics space. Strong conceptual hands-on experience in Cloud and Big Data environments.\nI have also spoken at multiple large events like +30,000 like AWS re:Invent 2022 and Qubole Data Lake Summit etc., \nI love building analytical solutions that combine Machine Learning & Artificial Intelligence. In my career, I have always had the luxury of working very close to technology and love working on challenges around scaling up analytic methods in distributed computing environments.\nI am passionate about turning ideas into data products. I enjoy developing high-performance teams, mentoring data science enthusiasts and working in cross-functional teams.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/datasentics-quality-inspector","text":"Quality Inspector by DataSentics and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionQuality Inspector by DataSenticsIndustry-specific solution developed by DataSentics and powered by the Databricks Lakehouse Platform\nContact usAutomate your production quality controlQuality control is a crucial aspect of any production process, but traditional methods can be time-consuming and prone to human error. Quality Inspector by DataSentics, an Atos company, offers a solution that is both efficient and reliable. With out-of-the-box models for visual quality inspection, which are tailored to meet your specific requirements, you\u2019ll experience stable, scalable quality control that\u2019s easy to improve over time. DataSentics\u2019 highly precise and efficient tailoring process allows them to quickly adapt models to your business needs. Quality Inspector is an end-to-end solution that can be seamlessly integrated into your existing setup, delivering high performance and reliability.Achieve more than 99.8% accuracyReduce your quality control time by up to 90%Automate even the most challenging use cases such as use of 3D cameras, heat cameras, etc.Contact usDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/company\/awards-and-recognition","text":"\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners","text":"Partner | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPartner di DatabricksDatabricks conta oltre 1200+ partner in tutto il mondo che forniscono soluzioni e servizi per dati, analisi e IA ai nostri clienti utilizzando la Databricks Lakehouse Platform. Questi partner consentono di sfruttare Databricks per unificare tutti i carichi di lavoro di dati e IA per ottenere informazioni pi\u00f9 dettagliate e significative.\u201cDatabricks gestisce il volume di dati, mentre Tableau assicura la rapidit\u00e0 della visualizzazione. Queste soluzioni funzionano in perfetta sintonia al centro della nostra piattaforma, per assicurare ai nostri clienti le prestazioni di cui hanno bisogno per offrire funzionalit\u00e0 di punta sui veicoli a guida autonoma\u201d.\u2014 Patrick McAuliffe, Lead Engineer, IncitePartner cloudDatabricks gira su AWS, Microsoft Azure, Google Cloud e Alibaba Cloud, integrandosi strettamente con i servizi di infrastruttura, dati e IA di ciascun providerPartner tecnologiciI partner tecnologici integrano le loro soluzioni con Databricks per offrire funzionalit\u00e0 complementari per ETL, acquisizione di dati, BI, ML e governancePartner consulenzialiI partner consulenziali sono esperti che forniscono supporto qualificato per definire le strategie, implementare e modulare correttamente le attivit\u00e0 di gestione e analisi dei dati e IA con DatabricksDiventa partnerI nostri partner collaborano con Databricks per sviluppare e fornire soluzioni innovative ai clienti. Unisciti al Databricks Partner Program per avere accesso a un'offerta esclusiva di strumenti, formazione, Solution Accelerator e programmi di commercializzazione.Maggiori informazioniProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leon-eller","text":"Leon Eller - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeon EllerSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shiv-trisal","text":"Shiv Trisal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShiv TrisalGTM Director, Manufacturing & Energy at DatabricksBack to speakersShiv has successfully led diverse product and strategy teams and delivered game-changing data and AI-led innovation across Diversified Manufacturing, Transportation and Logistics and Aerospace industries, with roles at Ernst & Young, Booz & Co.\/Strategy & and Raytheon Technologies. As an industry leader, Shiv regularly connects with executives to cover key trends and help enable data and AI strategies to unlock strategic competitive advantage in Manufacturing and Logistics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks MarketplaceOpen Marketplace para dados, an\u00e1lises e IAComece agoraTo play this video, click here and accept cookiesO que \u00e9 Databricks\nMarketplace?\nO Databricks Marketplace \u00e9 um mercado aberto para todos os seus dados, an\u00e1lises e IA, alimentado pelo padr\u00e3o de c\u00f3digo aberto Delta Sharing. O Databricks Marketplace amplia sua oportunidade de oferecer inova\u00e7\u00e3o e avan\u00e7ar em todas as suas iniciativas de an\u00e1lise e IA.\u00a0\nObtenha conjuntos de dados, bem como ativos de IA e an\u00e1lise \u2014 como modelos de ML, notebooks, aplicativos e pain\u00e9is \u2014 sem depend\u00eancias de plataforma propriet\u00e1ria, ETL complicado ou replica\u00e7\u00e3o cara. Essa abordagem aberta permite que voc\u00ea coloque os dados para trabalhar mais rapidamente em cada nuvem com as ferramentas de sua escolha.Descubra mais do que apenas dadosDesbloqueie inova\u00e7\u00e3o e promova as iniciativas de IA, ML e fun\u00e7\u00f5es anal\u00edticas da sua organiza\u00e7\u00e3o. Acesse mais do que apenas conjuntos de dados, incluindo modelos ML, notebooks, aplicativos e solu\u00e7\u00f5es.Avalie produtos de dados mais rapidamenteNotebooks pr\u00e9-incorporados e dados de amostra ajudam voc\u00ea a avaliar rapidamente e ter muito mais confian\u00e7a de que um produto de dados \u00e9 adequado para suas iniciativas de IA, ML ou an\u00e1lise.Evite a depend\u00eancia do fornecedorReduza substancialmente o tempo para fornecer insights e evite ficar preso a compartilhamento e colabora\u00e7\u00e3o abertos e cont\u00ednuos em nuvens, regi\u00f5es ou plataformas. Integre-se diretamente com as ferramentas de sua escolha e exatamente onde voc\u00ea trabalha.Provedores de dados em destaque no Databricks MarketplaceTorne-se um provedor de dados no marketplace\nRecursoseventoInscreva-se agora para Data + AI Summit 2023Registrare-booksUma nova abordagem para o Data SharingLeia o artigoe-booksData, Analytics and AI governanceLeia o artigoApresenta\u00e7\u00e3oGovernan\u00e7a de dados e compartilhamento no Lakehouse no Data + AI Summit 2022 BlogsAn\u00fancio de pr\u00e9-visualiza\u00e7\u00e3o p\u00fablica do MarketplaceAn\u00fancio do Databricks Marketplace no Data + AI Summit 2022Documenta\u00e7\u00e3oAWSAzureGCPProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/naresh-yegireddi\/#","text":"Naresh Yegireddi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNaresh YegireddiStaff Data Engineer at Indigo AGBack to speakersNaresh was born and raised in India. After finishing masters in Electrical Engineering in the year 2007, joined an MNC as a software engineer. Moved to the United States in 2010. Currently working as a Staff Data Engineer at Indigo AG, prior to that, had opportunities to work for SONY PlayStation, GRUBHUB, COMCAST, DELL and AT&T in data warehousing and business intelligence technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/datin-ts-habsah-binti-nordin\/#","text":"Datin Ts. Habsah Binti Nordin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDatin Ts. Habsah Binti NordinChief Data Officer at PETRONASBack to speakersDatin Habsah Nordin is the Head of Enterprise Data at PETRONAS. She is responsible for orchestrating PETRONAS\u2019 data strategy with the aim to liberate data seamlessly, and institutionalize a center of excellence for Data in PETRONAS and oversees the efforts to build the Enterprise Data Hub (EDH) and scale advanced analytics across the organization.\nDatin Habsah is a PETRONAS scholar and holds a Bachelor of Science (Bsc) in Computer Science from the Case Western Reserve University, USA. She joined PETRONAS in 1995 and has since held various leadership roles in IT, Strategic Planning, Business Development, Marketing, Transformation, Internal Audit, Project Management, Data and Knowledge Management.\nPrior to her current role, Datin Habsah was involved in few successful transformation initiatives that focused on business and operating model design. She is now a Board Member of PTSSB DMCC, a company incorporated in the United Arab Emirates (UAE). Since 2021, she been appointed as the first female President of Kelab Sukan and Rekreasi PETRONAS (KSRP) been formed since 1976, and Chairman of the Board for Twin Towers Fitness Center.\nDatin Habsah has completed the INSEAD Leadership Programme (Duke Program) focusing on Strategic Excellence. She is a certified solution-focused coach accredited by the Canadian Council of Professional Certification (CCPC Global Inc) and Certified Data Management Professional accredited by DAMA. She is Adjunct Lecturer and Industry Advisory Panel for University Teknologi PETRONAS in the area of Computer & Information Science Department for undergraduate and postgraduate program.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/awards-and-recognition","text":"Pr\u00eamios e reconhecimento | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPr\u00eamios e reconhecimentoDescubra todos os motivos pelos quais o Databricks \u00e9 reconhecido pelos l\u00edderes do setor.L\u00edder no Quadrante M\u00e1gico de 2022 para sistemas de gerenciamento de banco de dados na nuvemPr\u00eamio Customer Choice Award de 2022 para sistemas de gerenciamento de banco de dados na nuvemL\u00edder no Quadrante M\u00e1gico de 2021 para sistemas de gerenciamento de banco de dados na nuvemL\u00edder no Quadrante M\u00e1gico de 2021 para data science e machine learningLakehouse \u2014 Hype Cycle para solu\u00e7\u00f5es de gerenciamento de dados, 2022Empresas para ficar de olho em 2023As empresas mais inovadoras em data scienceThe Cloud 100The AI 50Os melhores empregadores de startups dos EUAOs melhores locais de trabalho em tecnologiaOs melhores locais de trabalho na \u00e1rea da ba\u00eda de S\u00e3o FranciscoOs melhores locais de trabalho para a gera\u00e7\u00e3o YCNBC Disruptor 50Os melhores lugares para trabalhar em 2022Pronto para saber mais?Adorar\u00edamos saber seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anfisa-kaydak","text":"Anfisa Kaydak - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnfisa KaydakVP, Data Product & Engineering at HealthverityBack to speakersAnfisa studies applied math in State University, Minsk, Belarus. She started her career in the US as a Web developer and quickly became fascinated with data. The journey from gigabytes quickly progressed to petabytes, from RDMS to distributed systems, from data exploration to complex APLD studies and pipeline engineering. She is SME in healthcare data and analytics, and adept in Data and AI technology transformations in healthcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"\u30d1\u30fc\u30c8\u30ca\u30fc\u30da\u30fc\u30b8\uff1a\u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u3068 SI\uff08C&SI\uff09 \u30d1\u30fc\u30c8\u30ca\u30fc | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/product\/startups?itm_data=Ventures-StartupsPage-ApplyNow","text":"Databricks for Startups | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBuild your startup on DatabricksThe most powerful platform for data and AIBuild on the Databricks Lakehouse to address all your data, analytics and AI on one platform. Accelerate speed to product while Databricks manages your data infrastructure. Prepare your product for growth with cost-efficient scalability and performance. Maintain flexibility with open source and multicloud options.Databricks for Startups helps you get up and running quickly. Build data-driven applications on the lakehouse \u2014 the data platform that scales to all your data needs, from zero to IPO and beyond.Free credits\nGet easy access to the Databricks Lakehouse Platform with up to $21K in free creditsExpert advice\nReceive advice from experts and the community to help build your productGo to market\nReach more customers with access to Databricks marketing, events and customersBuilt on DatabricksReady to build?If you\u2019re a startup building data-driven applications and have raised VC funding, we want to hear from you.\nApply nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-hayes","text":"Matthew Hayes - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew HayesVice President of SAP Business at QlikBack to speakersMatthew Hayes is the Vice President of SAP Business at Qlik. He has been innovating solutions for the SAP market for over 20 years. With a strong technical background in SAP, Matt developed Gold Client for handling SAP Test Data Management. Currently, he works to extend Qlik\u2019s offerings to the SAP market and focuses on enabling those solutions for SAP customers and technology partners. Matt is based in Chicago and in the summer months prefers to work remotely from Wrigley Field.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/atiyah-curmally","text":"Atiyah Curmally - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAtiyah CurmallyPrincipal Environmental Specialist at International Finance CorporationBack to speakersAtiyah Curmally's career centers on a passion for sustainable impact investing in emerging markets. At the International Finance Corporation, she focuses on providing insights, guidance, and practical solutions to investors, enabling them to assess risks and make decisions through the environmental, social, and governance (ESG) lens. Atiyah leads the ESG innovation and data science portfolio, including conception and development of an artificial intelligence (AI) solution called MALENA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/br\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPromo\u00e7\u00e3o de pre\u00e7o do Databricks SQL \u2014 Economize mais de 40%Aproveite nossa promo\u00e7\u00e3o de 15 meses para o SQL serverless e o novo SQL ProSaiba maisDatabricks SQLO Melhor Data Warehouse \u00e9 um LakehouseComece agoraAssista \u00e0 demonstra\u00e7\u00e3o\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowO Databricks SQL (DB SQL) \u00e9 um data warehouse serverless na Plataforma Databricks Lakehouse capaz de executar todas as suas aplica\u00e7\u00f5es SQL e BI em escala, com uma rela\u00e7\u00e3o pre\u00e7o\/desempenho at\u00e9 12 vezes melhor, um modelo de governan\u00e7a unificado, APIs e formatos abertos e as ferramentas de sua escolha, sem estar preso a um fornecedor.Melhor rela\u00e7\u00e3o pre\u00e7o\/desempenhoReduza custos e obtenha a melhor rela\u00e7\u00e3o pre\u00e7o\/desempenho, eliminando a necessidade de gerenciar, configurar ou expandir sua infraestrutura de nuvem com o modelo serverless.Governan\u00e7a integradaCrie uma \u00fanica c\u00f3pia de todos os seus dados usando padr\u00f5es abertos e aplique uma camada de governan\u00e7a unificada em todas as equipes de dados usando SQL padr\u00e3o.Ecossistema ricoUse SQL e ferramentas como Fivetran, dbt, Power BI ou Tableau em conjunto com a Databricks para ingerir, transformar e consultar todos os seus dados no local.Elimine silosCapacite cada analista para obter acesso mais r\u00e1pido aos dados mais recentes para an\u00e1lises em tempo real e transicionar sem esfor\u00e7o do BI para ML.Como funciona?Integra\u00e7\u00f5es perfeitas com o ecossistema\u00a0Facilidade de uso\u00a0Desempenho no mundo real\u00a0Governan\u00e7a centralizada\u00a0Um data lake aberto e confi\u00e1vel como baseIngira, transforme e orquestre dados facilmente de qualquer fonteTrabalhe com seus dados, onde quer que estejam localizados. Os recursos prontos para uso permitem que times de analistas e engenharia anal\u00edtica ingiram facilmente dados de qualquer tipo de fonte, como armazenamento de nuvem, aplicativos corporativos, como Salesforce, Google Analytics ou Marketo, usando o Fivetran. Tudo est\u00e1 dispon\u00edvel em um clique. Para gerenciar depend\u00eancias e transformar dados in-place, voc\u00ea pode usar os recursos ETL integrados do lakehouse ou suas ferramentas favoritas, como dbt no Databricks SQL, para obter o melhor desempenho da categoria.\u00a0\u201cA combina\u00e7\u00e3o de Databricks e Fivetran nos permitiu criar um pipeline de dados robusto e moderno em um curto per\u00edodo de tempo. A Fivetran p\u00f4de contar com todos os conectores e integra\u00e7\u00f5es necess\u00e1rios.\u201d\u2014 Justin Wille, diretor de insights e an\u00e1lises da Kreg ToolSaiba maisEscolha suas ferramentas de an\u00e1lises e BI modernasTrabalhe perfeitamente com ferramentas populares de BI, como Tableau, Power BI\u00a0e Looker. Agora, analistas podem usar suas ferramentas favoritas para descobrir novos insights de neg\u00f3cios com base nos dados mais abrangentes e atualizados. Para maximizar a colabora\u00e7\u00e3o, o Databricks SQL tamb\u00e9m permite que cada analista identifique e compartilhe novos insights com o editor SQL integrado, visualiza\u00e7\u00f5es e dashboards.\u00a0\u201cCom os dados na ponta dos dedos, estamos muito mais confiantes de saber que usamos os dados mais recentes e completos para alimentar nossos dashboards e relat\u00f3rios do Power BI.\u201d\u2014 Jake Stone, gerente s\u00eanior de an\u00e1lise de neg\u00f3cios da ButcherBoxSaiba maisElimine o gerenciamento de recursos com computa\u00e7\u00e3o serverlessCom o Databricks SQL serverless, voc\u00ea n\u00e3o precisa mais gerenciar, configurar ou dimensionar a infraestrutura de nuvem no lakehouse. Isso d\u00e1 \u00e0 sua equipe de dados mais tempo para se concentrar em seus neg\u00f3cios principais. Os warehouses do Databricks SQL fornecem compute SQL instant\u00e2neo e el\u00e1stico \u2014 desacoplado do armazenamento \u2014 redimensionados automaticamente para atender a casos de alta concorr\u00eancia de consultas, sem interrup\u00e7\u00f5es.\u00a0\u201cO Databricks SQL Serverless nos permite usar o poder do Databricks SQL e, ao mesmo tempo, ter muito mais efici\u00eancia com nossa infraestrutura.\u201d\u2014 R. Tyler Croy, diretor de engenharia de plataforma da ScribdSaiba maisTotalmente projetado para o melhor desempenho da categoriaO Databricks SQL foi inteiramente otimizado para oferecer o melhor desempenho para todas as suas ferramentas, tipos de queries e aplica\u00e7\u00f5es do mundo real. Isto inclui o Photon, o mecanismo de query de \u00faltima gera\u00e7\u00e3o, que, combinado com os warehouses SQL, oferece rela\u00e7\u00e3o pre\u00e7o\/desempenho at\u00e9 12 vezes superior a outros data warehouses em nuvem.\u00a0\u201cA Plataforma Databricks Lakehouse nos permitiu executar an\u00e1lises que reduzem o tempo necess\u00e1rio para obter insights de comportamentos do p\u00fablico de semanas para minutos.\u201d\u2014 Stephane Caron, diretora s\u00eanior de business intelligence da CBC\/Radio-CanadaSaiba maisCentralize o armazenamento e a governan\u00e7a de todos os seus dados com SQL padr\u00e3oCrie uma \u00fanica c\u00f3pia de todos os seus dados usando o formato aberto Delta Lake para evitar amarras com fornecedores. Realize an\u00e1lises in-place e opera\u00e7\u00f5es ETL\/ELT em seu lakehouse. Trabalhe sem mover ou copiar dados em diferentes sistemas desconexos. Governan\u00e7a refinada, linhagem de dados e SQL padr\u00e3o: essas ferramentas facilitam a descoberta, prote\u00e7\u00e3o e gerenciamento de todos os seus dados nas nuvens com o Unity Catalog da Databricks.\u00a0\u201cA Databricks \u00e9 fundamental para o nosso neg\u00f3cio porque sua arquitetura lakehouse proporciona uma maneira unificada de acessar, armazenar e compartilhar dados acion\u00e1veis.\u201d\u2014 Jagan Mangalampalli, diretor de big data da PunchhSaiba maisDesenvolvido em uma funda\u00e7\u00e3o de dados comum, com tecnologia da Plataforma LakehouseA Plataforma Databricks Lakehouse fornece a solu\u00e7\u00e3o de data warehouse de ponta a ponta mais abrangente para todas as suas necessidades de an\u00e1lises modernas e muito mais. Obtenha desempenho de n\u00edvel global por um custo muito menor do que os data warehouses na nuvem. Reduza o tempo desde a aquisi\u00e7\u00e3o de dados brutos at\u00e9 dados utiliz\u00e1veis em escala e unifique dados em batch e streaming. Al\u00e9m disso, o lakehouse permite que as equipes de dados passem sem esfor\u00e7o da descri\u00e7\u00e3o para a an\u00e1lise preditiva para descobrir novos insights.\u00a0\u201cA Databricks forneceu uma plataforma para nossas equipes de dados e an\u00e1lises acessarem e compartilharem dados no ABN AMRO. As solu\u00e7\u00f5es baseadas em ML impulsionam a automa\u00e7\u00e3o e o insight em toda a empresa.\u201d\u2014 Stefan Groot, diretor de engenharia anal\u00edtica do ABN AMROSaiba maisMigre para a DatabricksN\u00e3o aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA.Migre para a DatabricksIntegra\u00e7\u00f5esAs integra\u00e7\u00f5es perfeitas com o ecossistema fornecem flexibilidade m\u00e1xima para suas equipes de dados. Integre dados cr\u00edticos de neg\u00f3cios com Fivetran, transforme-os no local com dbt e descubra novos insights com Power BI, Tableau ou Looker, tudo sem mover seus dados para um data warehouse obsoleto.Ingest\u00e3o de dados e ETLGovernan\u00e7a de dadosBI e dashboards+ qualquer outro cliente compat\u00edvel com Apache Spark\u2122\u201cHoje, mais do que nunca, as organiza\u00e7\u00f5es precisam de uma estrat\u00e9gia de dados que ofere\u00e7a velocidade e agilidade para serem adapt\u00e1veis. \u00c0 medida que as empresas migram rapidamente seus dados para a nuvem, observamos um interesse crescente em an\u00e1lises no data lake. O Databricks SQL oferece uma experi\u00eancia totalmente nova para os clientes aproveitarem insights de grandes volumes de dados com o desempenho, a confiabilidade e a escalabilidade de que precisam. Temos orgulho de fazer parceria com a Databricks para tornar esta oportunidade uma realidade.\u201d\u2014 Francois Ajenstat, diretor de produtos, TableauHist\u00f3ria do clienteDescubra maisDelta LakeConex\u00e3o de parceirosUnity CatalogDelta Live TablesConte\u00fado relacionado\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre os benef\u00edcios do lakehouse.\nExplorar recursose-booksBuilding the Data Lakehouse, de Bill Inmon, pai do data warehouseWhy The Data Lakehouse Is Your Next Data WarehouseData, Analytics and AI governancee-book: The Big Book of Data EngineeringLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosTrabalho interno do lakehouse no Data + AI World TourWebinar sobre pr\u00e1ticas recomendadas de ajuste de desempenho no lakehouse \u2014 A vida de uma queryTreinamento gratuito do Databricks SQL \u2013 Sob demandaO Melhor Data Warehouse \u00e9 um LakehouseBlogsDatabricks estabelece recorde oficial de desempenho para armazenamento de dadosAn\u00fancio da disponibilidade geral do Databricks SQLEvolu\u00e7\u00e3o da linguagem SQL na Databricks: Ansi por padr\u00e3o e migra\u00e7\u00f5es mais f\u00e1ceis de data warehousesImplantar dbt na Databricks nunca foi t\u00e3o f\u00e1cilT\u00e9cnicas e implementa\u00e7\u00e3o de modelagem de data warehouse na Databricks Lakehouse PlatformComo criar uma solu\u00e7\u00e3o de an\u00e1lise de marketing com Fivetran e dbt na Databricks LakehouseTudo pronto para come\u00e7ar?Experimente gratuitamenteJunte-se \u00e0 comunidadeProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/delta-lake-the-foundation-of-your-lakehouse?itm_data=lakehouse-link-lakehousefoundation","text":"Delta Lake: The Foundation of Your Lakehouse | DatabricksVirtual Event + Live Q&ADelta Lake: The Foundation of Your LakehouseBring reliability, performance and security to your data lakeAvailable on-demandAs an open format storage layer, Delta Lake delivers reliability, security and performance to data lakes. Customers have seen 48x faster data processing, leading to 50% faster time to insight, after implementing Delta Lake.Watch a live demo and learn how Delta Lake:Solves the challenges of traditional data lakes \u2014 giving you better data reliability, support for advanced analytics and lower total cost of ownershipProvides the perfect foundation for a cost-effective, highly scalable lakehouse architectureOffers auditing and governance features to streamline GDPR complianceHas dramatically simplified data engineering for our customersSpeakersHimanshu RajaProduct ManagementDATABRICKSSam SteinyProduct MarketingDATABRICKSBrenner HeintzProduct MarketingDATABRICKSBarbara EckmanSoftware ArchitectCOMCASTTranscript\nSam Steiny: Hi, and welcome to the Databricks event, Delta Lake, the foundation of your lakehouse. My name is Sam Steiny and I work in product marketing at Databricks, focusing specifically on data engineering and on Delta Lake. I'm excited to be here today. I get to be the MC for today's event, and I will be guiding you through today's sessions. More and more, we've seen the term lakehouse referenced in news at events in tech blogs, and thought leadership. And beyond our work at Databricks, organizations across industries have really increasingly turned to this idea of a lakehouse as the future for unified analytics, data science and machine learning.Sam Steiny: In today's event, we'll see an overview of Delta Lake, which is the secure data storage and management layer for your data lake that really forms the foundation of a lakehouse. We'll see a demo of Delta Lake in action, and we'll actually hear how Comcast has leveraged Delta Lake to bring reliability, performance, and security to their data. We'll finish today's event with a live Q and A. So, come prepared with your questions and we'll do our best to answer as many as possible. So, before we start just some quick housekeeping, today's session is being recorded. So, it'll be available on demand to anyone who has registered.Sam Steiny: And then also, if you have any questions throughout the event, please feel free to add them to the Q and A box. We'll do our best to actually answer them in real time there. But we'll also answer the leftover questions as well as any additional ones in the live Q and A at the end of the session. So, now before we get to our speakers, I wanted to share a quick overview of Delta Lake in a video we recently launched. This'll give you a high level understanding of what Delta Lake is, before Himanshu who is the Delta Lake product manager, will go into more detail about Delta Lake and how it forms the foundation of a lakehouse.Speaker 3: Businesses today have the ability to collect more data than ever before. And that data contains valuable insights into your business and your customers, if you can unlock it. As most organizations have discovered, it's no simple task to turn data into insights. Today's data comes in a variety of formats, video, audio, and text. Data lakes have become the defacto solution because they can store these different formats at a low cost and don't lock businesses into a particular vendor like a data warehouse does. But traditional data lakes have challenges, as data lakes accumulate data in different format, maintaining reliable data is challenging and can often lead to inaccurate query results.Speaker 3: The growing data volume also impacts performance, slowing down analysis and decision-making, and with few auditing and governance features data lakes are very hard to properly secure and govern. With all of these challenges, as much as 73% of company data goes unused for analytics and decision-making and value in it is never realized. Delta Lake solves these challenges. Delta Lake is a data storage and management layer for your data lake that enables you to scale insights throughout your organization with a reliable single source of truth for all data workloads, both batch and streaming, increase productivity by optimizing for speed at scale with performance features like advanced indexing and schema enforcement.Speaker 3: Operate with flexibility in an open source environment stored in Apache parquet format and reduce risk by quickly and accurately updating data in your data lake for compliance and maintain better data governance through audit logging. By unlocking your data with Delta Lake, you can do things like dramatically simplified data engineering by performing ETL processes directly on the data lake. Make new real-time data instantly available for data analysis, data science and machine learning, gain confidence in your ability to reliably meet compliance standards like GDPR and CCPA.Speaker 3: Delta Lake on Databricks brings reliability, performance and security to your data all in an open format, making it the perfect foundation for a cost-effective highly scalable lakehouse architecture. Delta Lake, the open, reliable, performant and secure foundation of your lakehouse.Sam Steiny: Great. So, with that high level view, now you have an understanding of Delta Lake and I'm going to now pass it over to Himanshu Raja, who's the product manager for Delta Lake at Databricks. He's going to do a deeper dive into Delta Lake and explain how it really enables a lakehouse for our customers. Over to you, Himanshu.Himanshu Raja: Thank you, Sam. I'm super excited to be here and talk to you about Delta Lake and why it is the right foundation for lakehouse. In today's session, I will cover the challenges of building data analytics stack while lakehouse is the only future proof solution. What is Delta Lake? And why it is the best foundation for your lakehouse? Brenner, will then jump into the most exciting part of the session and do a demo. After the session, you will have enough context, links to the supporting material to get started and build your first data lake.Himanshu Raja: Every company is feeling the pull to become a data company, because when large amounts of data are applied to even simple models, the improvements on use cases is exponential. And here at Databricks, our entire focus is on helping customers apply data to their toughest problems. I'll dig examples of two such customers, Comcast and Nationwide. Comcast is a great example of a media company that has successfully adopted data and machine learning to create new experiences for their viewers that help improve satisfaction and retention.Himanshu Raja: They have built a voice-activated remote control that allows you to speak into the remote, ask it a question, and it will provide some really relevant results, leveraging things like natural language processing and deep learning. And they've built all of this on top of Databricks platform. Nationwide is one of the largest insurance providers in the U.S. nationwide saw that the explosive growth in data availability and increasing market competition was challenging them to provide better pricing to their customers. With hundreds of millions of insurance records to analyze for downstream ML nationwide realized that their legacy batch analysis process was slow and inaccurate, providing limited insights to predict the frequency and severity of the claims.Himanshu Raja: With Databricks, they have been able to employ deep learning models at scale to provide, more accurate pricing predictions resulting in more revenue from claims. Because of this potential, it's not surprising that, 83% of CEOs say AI is a strategic priority. According to a report published by MIT Sloan management review, or that Gartner predicts AI will generate almost trillion dollars in business value in only a couple of years. But it is very hard to get right. Gartner says 85% of the big data projects will fail. Venture Beat published a report that said 87% of data science projects never make it into production. So, while some companies are having success most still struggle.Himanshu Raja: So, the story starts with data warehouses, which it is hard to believe. Will soon celebrate its 40th birthday. Data warehouses came around in the 80s and were purpose-built for BI and reporting. Overtime they have become essential and today every enterprise on the planet has many of them. However, they weren't built for modern data use cases. They have no support for data like video or audio or text. Datasets that are crucial for modern use cases. It had to be very structured data queriable only with SQL. As a result, there is no viable support for data science or machine learning. In addition, there is no support for real-time streaming. They are great for batch processing, but either do not support streaming or can be cost prohibitive.Himanshu Raja: And because they are closed and proprietary systems, they force you to lock your data in, so you cannot easily move data around. So, today the result of all of that is that most organizations will first store all of their data in data lakes and block stores, and then move subsets of it into the data warehouse. So, then the thinking was that potentially data lakes could be the answer to all our problems. Data lakes came around about 10 years ago and they were great because they could indeed handle all your data. And they were there for good for data science and machine learning use cases. And data lakes serves as a great starting point for a lot of enterprises.Himanshu Raja: However, they aren't able to support that data warehousing or BI use cases. Data lakes are actually more complex to set up than a data warehouse. Our warehouse has a lot of familiar support semantics like asset transactions. With the data lakes, you are just dealing with files. So, those abstractions are not provided, you really have to build them yourself. And they're very complex to set up. And even after you do all of that, the performance is not great. You're just dealing with files, the end. In most cases, customers end up with a lot of small files and even the simplest queries will require you to list all those files. That takes time.Himanshu Raja: And then lastly, when it comes to reliability, they are not that great either. We actually have lot more data in that data lakes, then the warehouse, but is the data reliable? Can I actually guarantee that the schema is going to stay the same? How easy it is for an analyst to merge a bunch of different schemas together. As a result of all of these problems, data lakes have sort of turned into these unreliable data swamps where you have all the data, but it's very difficult to make any sense of it. So, understandably in the absence of a better alternative, what we are seeing with most organizations is a strategy of coexistence.Himanshu Raja: So, this is what a data swamp look like. There are tons of different tools to power each architecture required by a business unit or the organization. It's a whole slew of different open source tools that you have to connect. In the data warehousing stack, on the left side, you are often dealing with proprietary data formats. And if you want to enable advanced use cases, you have to move the data across to other stacks. It ends up being expensive and resource intensive to manage. And what does it result into? Because the systems are siloed, the teams become siloed too. Communication slows down, hindering innovation and speed.Himanshu Raja: Different teams often end up with different versions of the truth. The result is multiple copies of data, no consistent security governance model, closed systems and disconnected, less productive data teams. So, how do we get the best of both worlds? We want some things from the data warehouse, we want some things from the data lakes. We want the performance and reliability of the data warehouses, and we want the flexibility and the scalability of the data lakes. This is what we called the lakehouse paradigm. And the idea here is that the data is in the data lake, but now we are going to add some components so that we can now do all the BI and reporting from the warehouse and all the data science and machine learning from data lakes and also support streaming analytics. So, let's build a lakehouse. What are the things we need to build a lakehouse?Himanshu Raja: We said that we want all our data to be in an really scalable storage layer. And we want a unified platform where we can do multiple use cases. We can achieve multiple use cases. So, we need some kind of transactional layer on top of that data storage layer. So, what do you really need is something like asset compliance, so that when you write data, it either fully succeeds or fully fails and things are consistent. The structure transaction layer is what is data lake. And then the other requirement we talked about was performance. So, to support the different type of use cases, we needed to be really fast. We have lot of data that we want to work with. So, there is the data engine, which is a high-performance query engine that Databricks has created in order to support different types of use cases, whether it is SQL, data science, ETL, BI reporting, streaming, all that stuff on top of the engine to make it really, really fast.Himanshu Raja: So, let's do a deep dive on what is data lake. Data lake is an open, reliable, performant and secure data storage and management layer for your data lakes that enable you to create a true single source of truth. Since it's built upon a budget spot, you are able to build high-performance data pipelines to clean your data from raw injection to business level aggregates. And given the open format, it allows you to avoid unnecessary replication and proprietary lock-in. Ultimately, data lake provides that reliability, performance, and security you need to solve your downstream data use cases. Next, I'm going to talk about each of those benefits of data lake. The first and foremost benefit that you get with data lake is high-quality reliable data in your analytics stack.Himanshu Raja: Let me just talk about three key things here. The first is asset transaction. The second is schema enforcement and schema evolution. And then third is unified batch and streaming. So, on asset transactions, Delta employs an all or nothing asset transaction approach to guarantee that any operation you do on your data lake either fully succeeds or gets aborted so that it can be rerun. On schema enforcement Delta Lake uses schema validation on right, which means that all new rights to our table are checked for compatibility with the target table schema at right time. If the schema is not compatible, Delta Lake cancels the transaction altogether, and no data is written and raises an exception to let the user know about the mismatch.Himanshu Raja: We have very recently introduced capabilities to also do schema evolution, where we can evolve the schema on the fly as the data is coming in especially in the cases where the data is semi structured or unstructured. And you may not know what the data types are, or even in a lot of cases, what the columns that are coming in are. The third thing I would like to talk about is unified batch and streaming. Delta is able to handle both batch and streaming data, including the ability to concurrently, write batch and streaming to the same data table. Delta Lake directly integrates with spark structured streaming for low-latency updates.Himanshu Raja: Not only does this result in a simpler system architecture by not requiring you to build a Lambda architecture anymore. It also results in a shorter time from data ingest to query results. The second key advantage of Delta Lake is performance, lightning, fast performance. There are two aspects to performance in data analytic stack. One is how the data is stored, and then the other is performance during query, during run time. So, let's talk about how their data is stored and how does Delta optimizes the data storage format excel. Delta comes with out-of-box capabilities to store the data optimally for querying. Capabilities such as the ordering where the data is automatically structured along multiple dimensions for fast query performance is one. Delta also has data skipping, where Delta maintains the file statistics so that the data subsets relevant to the queries are used instead of the entire tables.Himanshu Raja: We don't have to go and read all the files. Files can be skipped based on the statistics. And then auto-optimize, optimize is a set of features that automatically compacts small files into fewer larger files so that the query performance is great out of the box. It's paying a small pause during writes to offset and give really great benefit for the tables during the requering. So, that's the part about how the data is stored. Now, let's talk about the Delta engine, which comes into play when you actually query that data. Data engine has three key components to provide super fast performance, photon, the query optimizer and caching. Photon is a native vectorized engine, fully compatible with Apache spark, build to accelerate all structured and semi-structured workloads by more than 20X compared to spark 2.4.Himanshu Raja: Second key component of Delta engine is query optimizer. The query optimizer extends the sparks cost-based optimizer and adaptive query execution with the advanced statistics to provide up to 18 X faster query performance for data warehousing workloads than Spark 3.0. And then the third key component of Delta engine is caching. Delta engine automatically caches IO data, and transcodes it into a more CPU efficient fallback to take advantage of NBMESSTs providing up to 5X faster performance for table scans than Spark 3.O. it also includes a second cache for query results to instantly provide results for any subsequent raps. This improves performance for repeated queries like dashboards, where the underlying tables are not changing frequently.Himanshu Raja: So, let me talk about the third main benefit of Delta Lake, which is to provide security and compliance at scale. Delta Lake reduces risk by enabling you to quickly and accurately update data in your data lake, to comply with regulations like GDPR and maintain better data governance through audit logging. Let me talk about two specific features, time-travel and stable and role-based access controls. With time-travel Delta automatically versions the big data that you store in your data lake and enables you to access any historical version of that data. This temporal data management simplifies your data pipeline by making it easy to audit, rollback data in case of accidentally bad writes or deletes and reproduce experiments and reports.Himanshu Raja: Your organization can finally standardize on a clean centralized version, big data repository in your own cloud storage for your analytics. The second feature I would love to talk about is that table and role based access controls. The data lake, you can programmatically grant and revoke access to your data based on specific workspace or role to ensure that your users can only access the data that you want them to. The Databrick's is extensive ecosystem of partners. Customers can enable a variety of security and governance functionality based on their individual needs.Himanshu Raja: Lastly, but one of the most important benefits of Delta Lake is that, it's open and agile. Delta Lake is an open format that works with other open source technologies, avoiding vendor lock-in and opening up an entire community and ecosystem of tools. All the data in Delta Lake is stored in an open Apache parquet format, allowing data to be read by any compatible reader. Developers can use their Delta Lake with their existing data pipelines with minimum changes, as it is fully compatible with spark. The most commonly used big data processing engine. Delta Lake also supports SQL DML, out-of-box to enable customers to migrate SQL workloads to Delta simply and easily.Himanshu Raja: So, let's talk about how we have seen customers leverage Delta Lake for a number of use cases, primarily among them is improving data pipelines, doing ETL at scale, unifying batch, and streaming with direct integration with Apache spark structured streaming to run both batch and streaming workloads in sort of doing the Lambda architecture, doing BI on your data Lake with our Delta engine, super fast, ready performance. You don't need to choose between a data lake and a data warehouse. As we talked about with the lakehouse, you can do BI directly on your data lake and then meeting regulatory needs with standards like GDPR by keeping a record of historical data changes. And who are these users?Himanshu Raja: The data lake is being used by some of the largest Fortune 100 companies in the world. We have customers like Comcast, Wirecomm, Conde Nast, McAfee, Edmonds. In fact, here Databricks all the data analytics is done using data lake. So, I would love to just deep dive in and would like to talk about the Starbucks use case to just give you an idea as to how our customers have used data lake in their ecosystem. Starbucks today does demand forecasting and personalizes the experiences of their customers on their app. And their architectures are actually struggling to handle petabytes of data adjusted for downstream ML and analytics, and they needed a scalable platform to support multiple use cases across the organization.Himanshu Raja: And with Azure Databricks and Delta Lake, their data engineers are able to build pipelines that support batch and real-time workloads on the same platform. They have enabled their data science teams to blend various data sets, to create new models that improve the customer experiences. And most importantly, data processing performance has improved dramatically allowing them to deploy environments and deliver insights in minutes. So, let me wrap up by summarizing what data lake can do for you, why it is the right foundation for your lakehouse. As we discovered that with Delta Lake, you can improve analytics and data science and machine learning throughout your organization by enabling teams to collaborate and ensure that they are working on reliable data to improve speed with which they make decisions.Himanshu Raja: You can simplify data engineering, reduce infrastructure and maintenance costs with best price performance, and you can enable a multi-cloud secure infrastructure platform with data lake. So, how do you get started on data lake? It's actually really easy, if you have a Databricks deployment already on Azure or AWS, and now GCP if you deploy a cluster with DBR, which is the Databricks right time release version 8.0 or higher, you actually do not need to do anything. Delta is now the default format for all creative tables and the data frame APIs. But we also have plenty of sources for you to try out the product and learn.Himanshu Raja: It's actually a lot of fun to deploy your first data lake and just build a really cool dashboard using a notebooks. If you have not tried Databricks before you can sign up for a free trial account and then you can follow our getting started guide. And Brenner, will do a demo very shortly to just showcase the capabilities that we talked about. So, with that over to you, Sam.Sam Steiny: Awesome. Thank you, Himanshu. That was great. Now, in the past the stage over to Brenner Heintz and Brenner is going to take us through a demo that really brings Delta Lake to life. Now, that you've heard what it is and how powerful it can be, let's see it in action. So, over to you, Brenner.Brenner Heintz: My name is Brenner Heintz. I am a technical PMM at Databricks, and today I'm going to show you how Delta Lake provides the perfect foundation for your lakehouse architecture. We're going to do a demo, and I'm going to show you how it works from a practitioner's perspective. Before we do so, I want to highlight the Delta Lake cheat sheet. I've worked on this with several of my colleagues, and the idea here is be able to provide a resource for practitioners like yourself, to be able to quickly and easily get up to speed with Delta Lake and be able to be productive with it very, very quickly. We've provided most, if not all of the commands in this notebook, it's part of the cheat sheet. So, I highly encourage you to download this notebook and you can click directly on this image, it'll take you directly to the cheat sheet, provide a one pager for Delta Lake with Python and a one pager for Delta Lake with Spark SQL.Brenner Heintz: So, first in order to use Delta Lake, you need to be able to convert your data to Delta Lake format. And the way that we're able to do that is instead of saying parquet as part of your create table or your Spark data frame writer command, all you have to do is place that with the word Delta, to be able to start using Delta Lake right away. So, here's a look at what that looks like. With Python, we can use Spark to read in our data in parquet format. You could also read in your data in CSV or other formats for example. Spark is very flexible in that way. And then we simply write it out in Delta format by indicating Delta here.Brenner Heintz: And we're going to save our data in the loans Delta table. We can do the same thing with SQL. We can use a create table command using Delta to then save our table in Delta format. And finally, the convert to Delta command makes it really easy to convert our data to Delta Lake format in place. So, now that we have shown you how to convert your data to Delta like format, let's take a look at a Delta Lake table and what that looks like. So, I've run the cell already. We have 14,705 batch records in our loans Delta table. Today, we're working with some data from the lending club, and you can see the columns that are currently part of our table here.Brenner Heintz: So, I went ahead and kicked off a couple of right streams to our table. And the idea here was to show you that Delta Lake tables are able to handle batch and streaming data, and they're able to integrate those straight out of the box without any additional configuration or anything else that's needed. You don't need to build a Lambda architecture, for example, to integrate both batch in real-time data. Delta Lake tables can easily manage both at once. So, as you can see, we're writing about 500 records per second, into our existing Delta Lake table. And we're doing so with two different writers, just to show you that you can concurrently both read and write from Delta Lake tables consistently with asset transactions, ensuring that you never deal with a pipeline breakage that corrupts the state of your table, for example.Brenner Heintz: Everything in Delta Lake is a transaction. And so this allows us to create isolation between different readers and writers. And that's really powerful, it saves us a lot of headache and a lot of time undoing mistakes that we may have made if we didn't have acid transactions. So, as I promised as well, those two streaming writes have been coupled. I've also created two streaming reads to show you what's happening in the table in near real time. So, we had those initial 14,705 batch records here. But since then we have about 124,000 streaming records that have entered our table since that time.Brenner Heintz: This is essentially the same chart, but showing you what's happening over each 10-second-window, each of these bars represents a 10-second-window, over which as you can see, since our streams began, we have about 5,000 records per stream that are written to our table at any time. So, all of this is just to say that Delta Lake is a very powerful tool that allows you to easily integrate batch and streaming data straight out of the box. It's very easy to use, and you can get started right away. To put the cherry on top, we added a batch query just for good measure, and we plotted it using Databricks built-in visualization tools, which are very easy and allow you to visualize things very quickly.Brenner Heintz: So, now, that we've showed you how easy it is to integrate batch and streaming data with Delta Lake, let's talk about data quality. You need tools like schema enforcement and schema evolution in order to enforce the quality in your tables. And the reason for that is that what you don't want are upstream data sources, adding additional columns, removing columns, or otherwise changing your schema without you knowing about it. Because what that can cause is a pipeline breakage that then affects all of your downstream data tables. So, to avoid that, we can use schema enforcement first and foremost. So, here I've created this new data, data frame that contains a new column, the credit score column, which is not present in our current table.Brenner Heintz: So, because Delta Lake offers schema enforcement when we run this command, we get an exception because the schema mismatch has been detected by Delta Lake. And that's a good thing. We don't want our data to successfully write to our Delta Lake table because it doesn't match what we expect. However, as long as we're aware and we want to intentionally migrate our schema, we can do so by adding a single command to our write command, we include the merge schema option. And now, that extra column is successfully written to our table, and we're also able to evolve our schema. So, now, when we try and select the records that were in our table, in our new data table, you can see that those records were in fact successfully written to the table and that new credit score column is now present in the schema of our table as well.Brenner Heintz: So, these tools give you, they're very powerful and they allow you to enforce your data quality the way that you need to in order to transition your data from raw unstructured data to high quality structured data, that's ready for downstream apps and users overtime. So, now, that we've talked about schema enforcement and scheme evolution, I want to move on to Delta Lake time travel. Time travel is a really powerful feature of Delta Lake. And because everything in Delta Lake as a transaction, and we're tracking all of the transactions that are made to our Delta Lake tables over time in the transaction log, that allows us to go back in time and recreate the state of our Delta Lake table at any point in time.Brenner Heintz: First, let's look at what that looks like. So, at any point, we can access the transaction log by running this describe history command. And as you can see, each of these versions of our table represent some sort of transaction, some sort of change that was made to our tables. So, our most recent change was that we upended those brand new records with a new column to our Delta Lake table. So, you can see that transaction here, before that we had some streaming updates. All of those rights that were occurring to our table were added as transactions. And basically this allows you to then go back and use the version number or timestamp, and then query historical versions of your Delta Lake tables at any point. That's really powerful because you can even do creative things like compare your current version of a table to a previous version to see what has changed since then, and do other sorts of things along those lines.Brenner Heintz: So, let's go ahead and do that. Let's look, we'll use time travel to view the original version of our table, which was version zero. And this should include just those 14,705 records that we started with because at that point version zero of our table, we hadn't streamed any new records into our table at all. And as you can see, the original version, those 14,705 records are the only records that are present in version as of zero. And there is no credit score column either, because of course, back in version zero, we had not yet evolved Delta Lake table schema.Brenner Heintz: So, compare that 14,705 records to the current number of records in our table, which is over 326,000. Finally, another thing you can do with Delta Lake time-travel is restore a previous version of your tables at any given point in time. So, this is really powerful, if you accidentally delete a column you didn't mean to, or delete some records you didn't mean to, you can always go back and use the restore command to then have the current version of your table restored exactly the way that your data was at that given timestamp or version number. So, as you can see, when we run this command to restore our table to its original state version as of zero, we have been able to do so successfully. Now, when we query it, we only get those 14,705 records as part of the table.Brenner Heintz: Next, one of the features that I think developers, data engineers and other data practitioners are really looking for when they're building their lakehouse is the ability to run simple DML command with just one or two lines of code, be able to do operations like deletes, updates, merges, inserts, et cetera. On a traditional data lake, those simply aren't possible. With Delta Lake, you can run those commands and they simply work and they do so transactionally. And they're very, very simple. So, managing change data becomes much, much easier when you have these simple commands at your disposal.Brenner Heintz: So, let's take a look, we'll choose user ID 4420 as our test case here, we'll use sort of modify their data specifically to show you what Delta Lake can do. As you can see, they are currently present in our table, but if we run this delete command and we specify that specific user, when we run the command and then we select all from our table, we now have no results. The delete has occurred successfully. Next, when we look at the described history command, the transaction log, so you can see the delete that we just carried out is now present in our table. And you can also see the restore that we did to jump back to the original version of our table version zero is also present. We can also do things like insert records directly back into our table if we want to do so.Brenner Heintz: Here, we're going to use time-travel to look at version as of zero, the original version of our table before this user was deleted and then insert that user's data back in. So, now when we run the select all command, the user is again, present in our table. The insert into command works great. Next, there's the update command. Updates are really useful, if you have row level changes that you need to make. Here, we're going to change this users funded amount to 22,000. Actually let's make it 25,000, it looks like it was already 22,000 before.Brenner Heintz: So, we'll update that number and then when we query our table, now, in fact, the user's funded amount has been updated successfully. Finally, in Delta Lake you have the ability to do really, really powerful merges. You can have a table full of change data that for example represents inserts and updates to your Delta Lake table. And with Delta Lake, you can do upsert. In just one single step you can... for each row in your data frame that you want to write to your Delta Lake table, if that row is already present in your table, you can simply update the values that are in that row. Whereas if that row is not present in your table, you can insert it.Brenner Heintz: So, that's what's known as an upsert and those are completely possible and they're very, very easy in Delta Lake. They make managing your Delta Lake very, very simple. So, first we create a quick data frame with just two records in it, we want to add user 4420's data back into our table. And then we also created a user whose user ID rather is one under 1 million. So, it's 999,999. And this user is not currently present in our table. We want to insert them. So, this is what our little data frame looks like. And as you can see, we have these as an update or an insert. And when we run our merge into command, Delta Lake is able to identify the rows that already exist, like user 4420, and those that don't already exist. And when they don't exist, we simply insert them.Brenner Heintz: So, as you can see, these updates, and inserts occurred successfully and Delta Lake has no problem with upserts. Finally, the last thing I want to point out are some specific performance enhancements that are offered as part of Delta Lake. But also as part of Databricks, Delta Lake only. We have a couple of commands that are Databricks, Delta Lake only at the moment. First there's the vacuum command. The vacuum command takes a look at the files that are currently a part of your table, and it removes any files that aren't currently part of your table that have been around for a retention period that you specify. So, this allows you to clean up the old versions of your table that are older than a specific retention period, and sort of save on cloud costs that way.Brenner Heintz: Another thing you can do on Databricks Delta Lake is you can cache the results of specific commands in memory. So, if you have a specific table that your downstream analysts tend to always group by a specific dimension, you can cache that SQL command, and it will always appear much quicker than it, and that way it's able to avoid doing a full read of your data, for example. You also had the ability to use the Z order optimized command, which is really powerful. Z order optimize essentially looks at the layout of your data tables and it figures out the perfect way to locate your data in different files. It essentially lays out your files in an optimized fashion, and that allows you to save on cloud storage costs because the way that it lays them out is typically much more compact than would be when you start. And it also then optimizes those tables for a read and write throughput.Brenner Heintz: So, it's very powerful. It speeds up the results of your queries and saves you on storage and compute costs ultimately. So, that's the demo. I hope you've enjoyed this demo. Again, take a look at the Delta Lake cheat sheet that we will post as part of the description or in the chat that is part of the presentation below. So, thanks so much. I hope you've enjoyed this demonstration. Check out Delta Lake and join us on GitHub, Slack, or as part of our mailing list. Thanks so much.Sam Steiny: Awesome. Thanks, Brenner. That was really, really great. I'm so excited now to be joined by Barbara Eckman. Barbara is a senior principal software architect at Comcast, and she's going to be sharing her experience with Delta Lake and how working with Databricks has really made an impact on her day-to-day and on the Comcast business. So, thanks so much for being here, Barbara. We're super excited to have you.Barbara Eckman: Hi, everybody. Really glad to be here. Hope you're all doing well. I'm here to talk about hybrid cloud access control in a self-service computer environment here at Comcast. I want to just real briefly mentioned that Comcast takes very seriously its commitment to our customers to protect their data. I'm part of the Comcast, what we call data experience big data group. And big data in this case means not only public cloud, but also on-prem data. So, we have a heterogeneous data set, which offers some challenges and challenges are fun, right? Our vision is that data is treated as an enterprise asset. This is not a new idea, but it's an important one.Barbara Eckman: And our mission is to power Comcast enterprise through self-service platforms, data discovery lineage, stewardship governance, engineering services, all those important things that enable people to really use the data in important ways. And we know as many do that powerful business insights, the most powerful insights come from models that integrate data, that span silos. Insights for improving the customer experience as well as business value. So, what this means for the business there are some examples. Basically, this is based on the tons of telemetry data that we capture from sensors and Comcast's network. We capture things like latency, traffic, signal to noise ratio, downstream and upstream, error rates and other things that I don't even know what they mean.Barbara Eckman: But this enables us to do things that improve customer experience like plan the network topology to help if there's a region that has a ton of traffic, we might change the policy to support that. Minimizing truck rolls, truck rolls are what we call it when the Comcast guy cable guy comes or cable female comes to your house. And in this COVID times, we really would like to minimize that even more. And if we can analyze the data ahead of time, we can perhaps make any adjustments or suggest adjustments that the user can make to minimize the need for people to come to their house.Barbara Eckman: We can monitor, predict problems and remedy them often before the user even knows because of this data and this involves both the telemetry data and integrating it with other kinds of data across the enterprise. And then optimizing network performance for region or for the whole household. So, now this is really important stuff and it really helps the customers. And we're working to make this even more prevalent. So, what makes your life hard? This is a professional statement. If you want to talk about personally, what makes your life hard? We can do that later, but what makes your life harder as a data professional?Barbara Eckman: People usually say, \"I need to find the data. So if I'm going to be integrating data across silos, I need to find it. I know where it is in myself silo, but maybe.\" And the way we do that is a metadata search and discovery, which we do through Elasticsearch. Then once I find the data that might be of interest to me, I need to understand what it means. So, what someone calls an account ID might not be the same account ID that you are used to calling an account ID, billing IDs, or back office account IDs need to know what it means in order to be able to join it, to make sense as opposed to Franklin data, monster data that isn't really appropriately joined. We need to know who produced it, that it come from a set-top box. Did it come from a third party who touched it while it was journeying through Comcast, through Tenet, through Kafka or Kinesis and someone aggregated it and then maybe somebody else enriched it with other data.Barbara Eckman: And then it landed in a data lake. The user of the data in the data lake wants to know where the data came from, and who added what piece. And you could see this as both the publisher looks at the data in the data lake and says, \"This looks screwy, what's wrong with this? Who messed up my data?\" He could also say, or they could say, \"Wow, this is enriched really great. I want to thank that person.\" And also someone who's just using the data wants to know who to ask questions. What did you enrich this with? Where did that data come from, that kind of thing? So, and all that really is helpful when you're doing this integration. That's data governance and lineage, which we do in Apache Atlas.Barbara Eckman: That's our metadata and lineage repository. Then once you found data and understood it, you have to be able to access it. And we do that through at Apache Ranger and its extension that's provided by Privacera. Once you have access to it, you need to be able to integrate it and analyze it across the enterprise. So, finally, now we get to the good stuff to be able to actually get our hands on the data. And we do that with self-service compute using Databricks. And Databricks is a really powerful tool for that. And finally we find that we do really need asset compliance for important operations. And we do that with Delta Lake. So, I can talk about this in more detail, as this top goes on or in the question session.Barbara Eckman: I'm an architect. So, I have to have bus and line diagrams. So, this is a high-level view of our hybrid cloud solution. So, income passed on our data centers, we have a Hadoop data lake that involves Hadoop Ranger and Apache Atlas working together. We are, as many companies are kind of phasing that out, but not immediately, it takes a while. We have a Terra data, enterprise data warehouse. Similarly, we are thinking to move that and not necessarily to the cloud entirely, but maybe to another on-prem source, like the object store. We use MinIO and basically that gives us the mix this object so it look like S3. So, when the spark jobs that we like to use on S3 also can run on our on pre data store.Barbara Eckman: And that's a big plus of course. And for that, we have a Ranger data service that helps with access control there. Up in the cloud, we use AWS though Azure also has a big footprint in Comcast. And Databricks compute is kind of the center here. We use it to access Kinesis. Redshift is only, we're just starting with that. We use Delta Lake and S3 object store and we have a Ranger plugin that the Databricks folks worked carefully with Privacera to create so that our self-service Databricks environment can have all the nit script and the configurations that it needs to run the access control that Privacera provides.Barbara Eckman: We also use Presto and for our federated query capability, it also has a Ranger plugin and all the tags that are applied to metadata on which policies are built, or are housed in Apache Atlas and Ranger and Atlas synced together. And that's how Ranger knows what policies to apply to what data. And in the question session, if you want to dig deeper into any of this, I'd be very happy to do it. So, this is very exciting to me, we're just rolling this out and it's so elegant and I didn't create it so I can say that. So, Ranger analysis together provide a declarative policy based access control. And as I said, Privacera extends Ranger, which originally only worked in Hadoop to AWS through plugins and proxies. And one of the key ones that we use, of course, is Databricks on all three of these environments. And basically what I like about this is we really have one ranger to rule them all and Atlas is his little buddy, because he provides or she, provides the tags that really power our access control.Barbara Eckman: So, here's again a diagram. And we have a portal that we built for our self service applications and the user tags, the metadata with tags, like this is PII, this is a video domain, that kind of stuff. That goes into Atlas, the tags and the metadata associations are synced with Ranger, the policies based on that. So, who gets the CPI? Who gets to see video domain data? Those are synced and cashed in the range of plugins. And then when a user calls an application, whether it's a cloud application in Databricks, or even an on-prem application, the application asks Ranger, \"Does this user have the access to do what they're asking to do on this data?\" If the answer is yes, and it's very fast, because these are plugins. If the answer is yes, they get access.Barbara Eckman: If no, then they get an error message and we can also do masking and show the data, if someone has access to many columns, but not all columns, I would say a glue table we can mask out the ones that they don't have access to and still give them what data they are allowed to see. Recently we've really needed acid compliance. So, traditionally big data lakes are write once, read many. We have things streaming in from set top boxes in the cable world, those aren't transactional, that's not transactional data. That's what we're used to, but now increasingly we are finding that we need to delete specific records from our parquet files or whatever. We can do this in Spark, but it is a terribly performant. It certainly it can be done, but it turns out Delta Lake does it much better.Barbara Eckman: The deletes are much more performant and you get to view snapshots of past data lake states, which is really pretty awesome. So, we're really moving toward, I love this word, a lakehouse being able to do, write once, read many and acid all in one place. And that is largely thanks to data lakes. So, this is me. Please reach out to me an email if you wish. And I'll be happy to answer questions in the live session if you have any. So, thank you very much for listening.Sam Steiny: Thank you for joining this event, Barbara. That was so awesome. It's great to hear the Comcast story. So, with that, let's get to some questions. We're going to move over to live Q&A. So, please add your questions to that Q&A.Watch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/deloitte-trellis","text":"Deloitte Trellis | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionTrellis by DeloitteIndustry-specific solution developed by Deloitte and powered by the Databricks Lakehouse Platform\nGet startedSolve complex challenges around forecasting and procurementDeloitte's Trellis provides capabilities designed to help solve retail's complex challenges around demand forecasting, replenishment, procurement, pricing and promotion services. Deloitte has leveraged their deep industry and client experience to build an integrated, secured and multicloud-ready \"as-a-service\" Solution Accelerator on top of Databricks Lakehouse for Retail that can be rapidly customized and tailored as appropriate based on the segments' unique needs. With Deloitte Trellis, you can:Focus on critical shifts occurring both on the demand side and supply side of retail's value chainAssess recommendations, associated impact and insights in real timeAchieve significant improvement to both top-line and bottom-line numbersGet startedProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-conover\/#","text":"Mike Conover - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike ConoverSoftware Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/robin-sutara\/#","text":"Robin Sutara - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRobin SutaraField CTO at DatabricksBack to speakersFrom repairing Apache helicopters near the Korean DMZ to the corporate battlefield, Robin has demonstrated success in navigating the high stress, and sometimes combative, complexities of data-led transformations. She has consulted with hundreds of organisations on data strategy, data culture, and building diverse data teams. Robin has had an eclectic career path in technical and business functions with more than two decades in tech companies, including Microsoft and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/real-time-point-of-sale-analytics","text":"Real-Time Point-of-Sale Analytics | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorReal-Time Point-of-Sale AnalyticsPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedCalculate real-time inventories across multiple store locations to improve retail marginsPoint-of-sale analytics is the process of collecting and analyzing data from the processing of transactions at a retail store. When a customer checks out, the data from that transaction feeds into several categories: inventory, sales, product, customer and staff.With volatility in the market and narrowing margins in retail, POS analytics is critical for retailers to ensure they are running their inventory management program as effectively as possible. If a POS system stores and reports data about inventory, retailers are able to have a better idea of what they're selling, what they're storing and what isn't moving.Get started with our Solution Accelerator for Real-Time Point-of-Sale Analytics to improve in-store operations by:Rapidly ingesting all data sources and types at scaleBuilding highly scalable streaming data pipelines with Delta Live Tables to obtain a real-time view of your operationLeveraging real-time insights to tackle your most pressing in-store information needsDownload notebookResourcesBlogLearn moreWebinarLearn moreHands-On WorkshopWatch nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yang-you","text":"Yang You - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYang YouPresidential Young Professor at National University of SingaporeBack to speakersProf. Yang You is a Presidential Young Professor at the National University of Singapore. His team broke the world record of ImageNet and BERT training speed. He is a winner of the IPDPS Best Paper Award, ICPP Best Paper Award, AAAI Distinguished Paper Award, ACM\/IEEE George Michael HPC Fellowship, Siebel Scholar, Lotfi A. Zadeh Prize, and nominated for the ACM Doctoral Dissertation Award. He also made Forbes 30 Under 30 Asia list (2021) for young leaders and IEEE-CS TCHPC early career award.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/07\/13\/using-your-data-to-stop-credit-card-fraud-capital-one-and-other-best-practices.html","text":"Using Your Data to Stop Credit Card Fraud: Capital One and Other Best Practices - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorUsing Your Data to Stop Credit Card Fraud: Capital One and Other Best Practicesby Fahmid KabirJuly 13, 2021 in Company BlogShare this postFraud is a costly and growing problem \u2013 research estimates that $1 of fraud costs companies 3.36x in chargeback, replacement and operational cost. Adding to the pain, according to experts, there are not enough regulations to protect small businesses from chargebacks and losses from fraud. Despite significant advancements in credit card fraud, risk management techniques have adapted, and fraudsters are still able to find loopholes and exploit the system. For credit card companies, the threat of fraudulent card usage is a constant, which results in the need for accurate credit card fraud detection systems. All organizations are at risk of fraud and fraudulent activities, but that risk is especially burdensome to those in financial services. \u201cThreats can originate from internal or external sources, but the effects can be devastating - including loss of consumer confidence, incarceration for those involved, and even the downfall of corporations,\u201d says Badrish Davay, a Data Engineering and Machine Learning leader at Capital One. CNBC reports that the US is the most credit card fraud prone country in the world.\nFraud detection using machine learning\u00a0\nIt\u2019s not all bad news, though. With modern advancements, businesses are able to stay ahead of threats by leveraging data and machine learning. As part of a tech talk at the recent Data + AI Summit, we were able to get a glimpse into how Capital One is using data and artificial intelligence (AI) to address fraud. Badrish Davay from Capital One shared how we can utilize state-of-the-art ML algorithms to stay ahead of the attackers and, at the same time ,constantly learn new ways a system is being exploited. \u201cIn order to more dynamically detect fraudulent transactions, one can train ML models on a dataset, including credit card transaction data, as well as card and demographic information of the cardholder. Capital One uses Databricks to achieve this goal,\u201d noted Davay.\nTo play this video, click here and accept cookiesCapital One analyzes all the fraudulent activities to understand what to look for in credit card fraud. Davay presented the 6 \u201cW\u201d questions they ask \u2013 \u00a0what, who, when, where, why and what if? \u2013 used to uncover trends in fraudulent activities. Davay highlighted various scenarios in which card information may be compromised and how data can help with anomaly detection and identifying fraud. For example, he shared how geospatial data can detect stolen card information when it is being used away from its actual location, along with temporal data to determine fraud.\nAs Davay also explained, when a customer physically loses a card, but doesn\u2019t notify the organization,\u00a0 contextual information ( e.g. work hours, spending habits, etc.) can help determine if transactions are routine or anomalous. A key takeaway from Davay is that we should be able to combine a multiple of independent signals together to get a wider context around traction and demographics data. With the availability of data and advancements in ML, fraud prevention is a key area in which ML is changing both workflows and outcomes, allowing organizations to stay ahead of increasingly technologically advanced criminals.\nToday\u2019s businesses are facing an increasingly sophisticated enemy that attacks, responds and changes tactics extremely quickly. Due to dynamics of fraud, organizations need AI to constantly adapt to changing behaviours and patterns. AI brings agility that rules do not. With data analytics and ML, companies can get ahead of threats. Below are some key reasons why ML is apt for taking on fraud:\nFraud hides under massive amounts of data: The most effective way to detect fraud is to look at the overall behaviors of end users. Looking at transactions or orders is not enough \u2014 we need to follow the events leading up to and after the transaction. This culminates into a lot of structured and unstructured data, and the best way to detect fraud in such huge volumes is with ML and AI.Fraud happens quickly: When an ML system updates in real time, that knowledge can be used within milliseconds to update fraud detection models and prevent an attack.Fraud is always changing: Fraudsters constantly adapt their tactics, making them difficult for humans to detect\u00a0 \u2013 and impossible for static rules-based systems, which don\u2019t learn. ML, however, can adapt to changing behavior.Fraud looks fine on the surface: To the human eye, fraudulent and normal transactions don\u2019t appear any differently from each other. ML has a deeper and more nuanced way of viewing data, which helps avoid false positives.Davay discussed how MLuses statistical models, such as classifiers, and logistic regression to look at past outcomes and anomalies to predict future outcomes. An ML system can learn, predict and make decisions as data comes in real time. In his presentation, Davay outlined what a good fraud prevention model needs to have:\none-stop shop for users to train the model and orchestrate executionReal-time detectionDeep analytics and\u00a0 modeling by leveraging powerful ML tools, such as deep learning and neural networks, for what if data analysis and testing new hypothesesAdherence to company security policy and compliance requirementsNotification service\u00a0 to inform cardholders immediately of suspicious activitySeamless integration with enterprise systemsMLflow in fraud prevention\u00a0\nDavay highlighted the value of Databricks and MLflow in their fraud prevention efforts. He talked about the platform and how different data and fraud teams collaboratively develop and run experiments with the team using Databricks. \u201cEven though they share experiments and data collaboratively within the team, we can implement stringent security measures in order to respect data privacy, and each experiment can have its own compute environments and requirements,\u201d said Davay.\u00a0 He referred to Databricks as \u201ca one-stop shop for all of [their] data science and models, making it perfect for data science projects.\u201d When the team has identified features for predicting whether a transaction is fraudulent or not, they pass these data points to Databricks\u2019 hosted environment, where they can then perform feature engineering, data pre-processing and split the data into test and training sets. They then use a variety of supervised or unsupervised ML algorithms, such as SVM, decision tree and random forest, to train a model. They identify the best performing model and use the Databricks Lakehouse Platform to solve for fraud directly from within the platform. The lakehouse is a conducive environment for fraud detection and you can learn more from our solution accelerators here.\n\nDavay mentioned how \u201cMLflow within the Databricks ecosystem is a great feature that we can use because it has numerous advantages in developing the ML workflow pipeline seamlessly.\u201d MLflow allows Capital One to track their ML experiments from end-to-end throughout the ML model lifecycle. During the talk, Davay mentioned they can run experiments directly from GitHub without the need to go through the code and can directly deploy and train models by serializing them while utilizing packages such as Python\u2019s pickle module, Apache Spark, and\u00a0 MLflow. They then deploy the serialized model and serve it as an API by harnessing MLflow.\nMLflow and microservices\nDavay also touched on microservices and why they are useful in MLflow. A microservice is a gateway to a specific functional aspect of an application. It helps teams like Capital One\u2019s develop applications in a standardized consistent manner over time. Microservices allow Capital One to deploy functionality of applications independent of each other. It helps abstract the functionality while enabling the team to build in a reusable and uniform way of interacting with an application. Furthermore, it lets teams compose complex behavior by combining a variety of other microservices together. Essentially, it empowers companies to use any tech stack in the backend while maintaining compatibility on the front end.\nWith Capital One\u2019s raw data stored in Amazon S3, they quickly integrate interactions between S3 and their framework through Databricks seamlessly and can massively scale ML\u00a0 model training, validation and deployment pipelines through MLflow. Their team trains and validates models on custom clusters in AWS and deploys them through SageMaker directly by using MLflow APIs. MLflow is not only limited to AI, but can embed any piece of business logic (as mentioned in Databricks Rules + AI accelerator) and, as such, benefits from the E2E governance and delivery principles as microservices.\nPutting it all together\u00a0\nDavay shared how Databricks allows Capital one to query and deploy models and manage and clean up the deployment while using MLflow APIs within the AWS ecosystem. In addition, they can ensure safe security and conditional access via AWS SSO.\nBased on observations from Capital One and many other customers, there are several benefits of using data and AI for fraud prevention, including:\nReduced need for manual review. ML automates processes in which behaviors can be learned at the individual level and\u00a0 detect anomalies.The ability to prevent fraud cases without impeding the user experience. AI brings automation to the process seamlessly and prevents fraud in advance without burdening users.Lower operational costs than other approaches. With less manual work and automation, data and AI require fewer resources and preempts losses associated with fraud.Frees up teams\u2019 time to focus on more strategic tasks. Most companies are not in the business of fraud detection, and an ML fraud prevention process can help them focus on core activities.Adapts quickly. Coupled with human talent and experience, data and AI work together to constantly learn and adjust to new user behaviors and trends.When it comes to operationalizing data and AI to build customer relationships and drive higher returns on equity, fraud should be considered a top priority. Curbing fraudulent or malicious behavior\u00a0 \u2013 from fraudulent card transactions \u2013 is key to mitigating negative revenue impact. To more dynamically detect fraudulent transactions, Capital One uses ML and credit card transaction information, as well as card and demographic information, to get a comprehensive view to identify anomalies. Data-driven innovators such as Capital One\u2019s are paving the way in fraud detection and provide a successful model to follow to protect customers and business.\nGet started with fraud prevention in DatabricksGet a jump start with our our prebuilt code and guides in our Fraud Solution Accelerators\u00a0See all our Financial Services solutionsTry Databricks for freeGet StartedRelated postsUsing Your Data to Stop Credit Card Fraud: Capital One and Other Best PracticesJuly 13, 2021 by Fahmid Kabir in Company Blog\nFraud is a costly and growing problem \u2013 research estimates that $1 of fraud costs companies 3.36x in chargeback, replacement and operational cost. 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{"source":"https:\/\/www.databricks.com\/blog\/2020\/07\/10\/a-data-driven-approach-to-environmental-social-and-governance.html","text":"How to Take a Data-driven Approach to ESG Investing With Apache Spark, Delta Lake, and MLflow - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. 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In order to stay competitive, Financial Services Institutions (FSI)\u00a0are increasingly\u00a0disclosing more information about their environmental, social and governance (ESG) performance. By better understanding and quantifying the sustainability and societal impact of any investment in a company or business, FSIs can mitigate reputation risk and maintain the trust with both their clients and shareholders. At Databricks, we increasingly hear from our customers that ESG has become a C-suite priority. This is not solely driven by altruism but also by economics: Higher ESG ratings are generally positively correlated with valuation and profitability while negatively correlated with volatility. In this blog post, we offer a novel approach to sustainable investing by combining natural language processing (NLP) techniques and graph analytics to extract key strategic ESG initiatives and learn companies' relationships in a global market and their impact to market risk calculations.Using the Databricks Unified Data Analytics Platform, we will demonstrate how Apache SparkTM, Delta Lake and MLflow can enable asset managers to assess the sustainability of their investments and empower their business with a holistic and data-driven view to their environmental, social and corporate governance strategies. Specifically, we will extract the key ESG initiatives as communicated in yearly PDF reports and compare these with the actual media coverage from news analytics data.In the second part of this blog, we will learn the connections between companies and understand the positive or negative ESG consequences these connections may have to your business. While this blog will focus on asset managers to illustrate the modern approach to ESG and socially responsible investing, this framework is broadly applicable across all sectors in the economy from Consumer Staples and Energy to Media and Healthcare.Extracting key ESG initiativesFinancial services organisations are now facing more and more pressure from their shareholders to disclose more information about their environmental, social and governance strategies. Typically released on their websites on a yearly basis as a form of a PDF document, companies communicate their key ESG initiatives across multiple themes such as how they value their employees, clients or customers, how they positively contribute back to society or even how they mitigate climate change by, for example, reducing\u00a0 (or committing to reduce) their carbon emissions. Consumed by third-party agencies (such as msci or csrhub), these reports are usually consolidated and benchmarked across industries to create ESG metrics.Extracting statements from ESG reportsIn this example, we would like to programmatically access 40+ ESG reports from top tier financial services institutions (some are reported in the below table) and learn key initiatives across different topics. However, with no standard schema nor regulatory guidelines, communication in these PDF documents can be varied, making this approach a perfect candidate for the use of machine learning (ML).Barclayshttps:\/\/home.barclays\/content\/dam\/home-barclays\/documents\/citizenship\/ESG\/Barclays-PLC-ESG-Report-2019.pdfJP Morgan Chasehttps:\/\/www.jpmorganchase.com\/content\/dam\/jpmc\/jpmorgan-chase-and-co\/documents\/jpmc-cr-esg-report-2019.pdfMorgan Stanleyhttps:\/\/www.morganstanley.com\/pub\/content\/dam\/msdotcom\/sustainability\/Morgan-Stanley_2019-Sustainability-Report_Final.pdfGoldman Sachshttps:\/\/www.goldmansachs.com\/our-commitments\/sustainability\/sustainable-finance\/documents\/reports\/2019-sustainability-report.pdfAlthough our data set is relatively small, we show how one could distribute the scraping process using a user defined function (UDF), assuming the third-party library `PyPDF2` is available across your Spark environment.\nimport requests\nimport PyPDF2\nimport io\n\n@udf('string')\ndef extract_content(url):\n\n    # retrieve PDF binary stream\n    response = requests.get(url)\n    open_pdf_file = io.BytesIO(response.content)\n    pdf = PyPDF2.PdfFileReader(open_pdf_file)\n\n    # return concatenated content\n    text = [pdf.getPage(i).extractText() for i in range(0, pdf.getNumPages())]\n    return \"\\n\".join(text)\nBeyond regular expressions and fairly complex data cleansing\u00a0 (reported in the attached notebooks), we also want to leverage more advanced NLP capabilities to tokenise content into grammatically valid sentences. Given the time it takes to load trained NLP pipelines in memory (such as the `spacy` library below), we ensure our model is loaded only once per Spark executor using a PandasUDF strategy as follows.\nimport gensim\nimport spacy\nfrom pyspark.sql.functions import pandas_udf, PandasUDFType\n\n@pandas_udf('array', PandasUDFType.SCALAR_ITER)\ndef extract_statements(content_series_iter):\n    \n    # load spacy model for english only once\n    spacy.cli.download(\"en_core_web_sm\")\n    nlp = spacy.load(\"en_core_web_sm\")\n    \n    # provide process_text function with our loaded NLP model\n    # clean and tokenize a batch of PDF content\n    for content_series in content_series_iter:\n\n    yield content_series.map(lambda x: process_text(nlp, x))\nWith this approach, we were able to convert raw PDF documents into well defined sentences (some are reported in the table below) for each of our 40+ ESG reports. As part of this process, we also lemmatised our content - that is, to transform a word into its simpler grammatical form, such as past tenses transformed to present form or plural form converted to singular. This extra process will pay off in the modeling phase by reducing the number of words to learn topics from.Goldman Sachswe established a new policy to only take public those companies in the us and europe with at least one diverse board director (starting next year, we will increase our target to two)Barclaysit is important to us that all of our stakeholders can clearly understand how we manage our business for good.Morgan Stanleyin 2019, two of our financings helped create almost 80 affordable apartment units for low-and moderate-income families in sonoma county, at a time of extreme shortage.Riverstonein the last four years, the fund has conserved over 15,000 acres of bottomland hardwood forests, on track to meeting the 35,000-acre goal established at the start of the fundAlthough it is relatively easy for the human eye to infer the themes around each of these statements (in this case diversity, transparency, social, environmental), doing so programmatically and at scale is of a different complexity and requires advanced use of data science.Classifying ESG statementsIn this section, we want to automatically classify each of our 8,000 sentences we extracted from 40+ ESG reports. Together with non matrix factorisation, Latent Dirichlet Allocation (LDA) is one of the core models in the topic modeling arsenal, using either its distributed version on Spark ML or its in-memory sklearn equivalent as follows. We compute our term frequencies and capture our LDA model and hyperparameters using MLflow experiments tracking.\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.decomposition import LatentDirichletAllocation as LDA\nimport mlflow\n\n# compute word frequencies\n# stop words are common english words + banking related buzzwords\nword_tf_vectorizer = CountVectorizer(stop_words=stop_words, ngram_range=(1,1))\nword_tf = word_tf_vectorizer.fit_transform(esg['lemma'])\n    \n# track experiment on ml-flow\nwith mlflow.start_run(run_name='topic_modeling'):\n    \n    # Train a LDA model with 9 topics\n    lda = LDA(random_state = 42, n_components = 9, learning_decay = .3)\n    lda.fit(word_tf)\n    \n    # Log model \n    mlflow.sklearn.log_model(lda, \"model\")\n    mlflow.log_param('n_components', '9')\n    mlflow.log_param('learning_decay', '.3')\n    mlflow.log_metric('perplexity', lda.perplexity(word_tf)) \nFollowing multiple experiments, we found that 9 topics would summarise our corpus best. By looking deeper at the importance of each keyword learned from our model, we try to describe our 9 topics into 9 specific categories, as reported in the table below.Suggested nameLDA descriptive keywordscompany strategyboard, company, corporate, governance, management, executive, director, shareholder, global, engagement, vote, term, responsibility, business, teamgreen energyenergy, emission, million, renewable, use, project, reduce, carbon, water, billion, power, green, total, gas, sourcecustomer focuscustomer, provide, business, improve, financial, support, investment, service, year, sustainability, nancial, global, include, help, initiativesupport communitycommunity, people, business, support, new, small, income, real, woman, launch, estate, access, customer, uk, includeethical investmentsinvestment, climate, company, change, portfolio, risk, responsible, sector, transition, equity, investor, sustainable, business, opportunity, marketsustainable financesustainable, impact, sustainability, asset, management, environmental, social, investing, company, billion, waste, client, datum, investment, providecode of conductinclude, policy, information, risk, review, management, investment, company, portfolio, process, environmental, governance, scope, conduct, datumstrong governancerisk, business, management, environmental, customer, manage, human, social, climate, approach, conduct, page, client, impact, strategicvalue employeesemployee, work, people, support, value, client, company, help, include, provide, community, program, diverse, customer, serviceWith our 9 machine learned topics, we can easily compare each of our FSI's ESG reports side by side to better understand the key priority focus for each of them.Using seaborn visualisation, we can easily flag key differences across our companies (organisations' names redacted). When some organisations would put more focus on valuing employees and promoting diversity and inclusion (such as ORG-21), some seem to be more focused towards ethical investments (ORG-14). As the output of LDA is a probability distribution across our 9 topics instead of one specific theme, we easily unveil the most descriptive ESG initiative for any given organisation using a simple SQL statement and a partitioning function that captures the highest probability for each theme.\nWITH ranked (\n    SELECT\n        e.topic,\n        e.statement,\n        e.company,\n        dense_rank() OVER (\n            PARTITION BY e.company, e.topic ORDER BY e.probability DESC\n        ) as rank\n    FROM esg_reports e\n)\n    \nSELECT \n    t.topic,\n    t.statement\nFROM ranked t\nWHERE t.company = 'goldman sachs'\nAND t.rank = 1  \nThis SQL statement provides us with a NLP generated executive summary for Goldman Sachs (see original report), summarising a complex 70+ pages long document into 9 ESG initiatives \/ actions.TopicStatementsupport communityCalled the Women Entrepreneurs Opportunity Facility (WEOF), the program aims to address unmet financing needs of women-owned businesses in developing countries, recognizing the significant obstacles that women entrepreneurs face in accessing the capital needed to grow their businesses.strong governanceThe ERM framework employs a comprehensive, integrated approach to risk management, and it is designed to enable robust risk management processes through which we identify, assess, monitor and manage the risks we assume in conducting our business activities.sustainable financeIn addition to the Swedish primary facility, Northvolt also formed a joint venture with the Volkswagen Group to establish a 16 GWh battery cell gigafactory in Germany, which will bring Volkswagens total investment in Northvolt to around $1 billion.green energyBesides reducing JFKs greenhouse gas emissions by approximately 7,000 tons annually (equivalent to taking about 1,400 cars off the road), the project is expected to lower the Port Authority's greenhouse gas emissions at the airport by around 10 percent The GSAM Renewable Power Group will hold the power purchase agreement for the project, while SunPower will develop and construct the infrastructure at JFK.customer focusProgram alumni can also join the 10KW Ambassadors Program, an advanced course launched in 2019 that enables the entrepreneurs to further scale their businesses.10,000 Women Measures Impacts in China In Beijing, 10,000 Women held a 10-year alumni summit at Tsinghua University School of Economics and Management.ethical investmentsWe were one of the first US companies to commit to the White House American Business Act on Climate Pledge in 2015; we signed an open letter alongside 29 other CEOs in 2017 to support the US staying in the Paris Agreement; and more recently, we were part of a group of 80+ CEOs and labour leaders reiterating our support that staying in the Paris Agreement will strengthen US competitiveness in global markets.value employeeOther key initiatives that enhance our diversity of perspectives include: Returnship Initiative, which helps professionals restart their careers after an extended absence from the workforce The strength of our culture, our ability to execute our strategy, and our relevance to clients all depend on a diverse workforce and an inclusive environment that encourages a wide range of perspectives.company strategyUnderscoring our conviction that diverse perspectives can have a strong impact on company performance, we have prioritized board diversity in our stewardship efforts.code of conduct13%Please see page 96 of our 2019 Form 10-K for further of approach to incorporation of environmental, social and governance (ESG) factors in credit analysisDiscussion and AnalysisFN-CB-410a.2Environmental Policy FrameworkAlthough we may observe some misclassification (mainly related to how we have named each topic) and may have to tune our model more, we have demonstrated how NLP techniques can be used to efficiently extract well defined initiatives from complex PDF documents. These, however, may not always reflect companies' core priorities nor does it capture every initiative for each theme. This can be further addressed using techniques borrowed from anomaly detection, grouping corpus into broader clusters and extracting sentences that deviate the most from the norm (i.e. sentences specific to an organisation and not mainstream). This approach, using K-Means, is discussed in our notebooks attached.Create a data-driven ESG scoreAs covered in the previous section, we were able to compare businesses side by side across 9 different ESG initiatives. Although we could attempt to derive an ESG score (the approach many third-party organisations would use), we want our score not to be subjective but truly data-driven. In other terms, we do not want to solely base our assumptions on companies' official disclosures but rather on how companies' reputations are perceived in the media, across all 3 environmental, social and governance variables. For that purpose, we use GDELT, the global database of event location and tones.Data acquisitionGiven the volume of data available in GDELT (100 million records for the last 18 months only), we leverage the lakehouse paradigm by moving data from raw, to filtered and enriched, respectively from Bronze, to Silver and Gold layers, and extend our process to operate in near real time (GDELT files are published every 15mn). For that purpose, we use a Structured Streaming approach that we `trigger` in batch mode with each batch operating on data increment only. By unifying Streaming and Batch, Spark is the de-facto standard for data manipulation and ETL processes in modern data lake infrastructures.\ngdelt_stream_df = spark \\\n    .readStream \\                              \n    .format(\"delta\") \\\n    .table(\"esg_gdelt_bronze\") \\                                        \n    .withColumn(\"themes\", filter_themes(F.col(\"themes\"))) \\\n    .withColumn(\"organisation\", F.explode(F.col(\"organisations\"))) \\\n    .select(\n        F.col(\"publishDate\"),\n        F.col(\"organisation\"),\n        F.col(\"documentIdentifier\").alias(\"url\"),\n        F.col(\"themes\"),\n        F.col(\"tone.tone\")\n    )\n\ngdelt_stream_df \\\n    .writeStream \\\n    .trigger(Trigger.Once) \\\n    .option(\"checkpointLocation\", \"\/tmp\/gdelt_esg\") \\\n    .format(\"delta\") \\\n    .table(\"esg_gdelt_silver\")\nFrom the variety of dimensions available in GDELT, we only focus on sentiment analysis (using the tone variable) for financial news related articles only. We assume financial news articles to be well captured by the GDELT taxonomy starting with ECON_*. Furthermore, we assume all environmental articles to be captured as ENV_* and social articles to be captured by UNGP_* taxonomies (UN guiding principles on human rights).Sentiment analysis as proxy for ESGWithout any industry standard nor existing models to define environmental, social and governance metrics, and without any ground truth available to us at the time of this study, we assume that the overall tone captured from financial news articles is a good proxy for companies' ESG scores. For instance, a series of bad press articles related to maritime disasters and oil spills would strongly affect a company's environmental performance. On the opposite, news articles about [...] financing needs of women-owned businesses in developing countries [source] with a more positive tone would positively contribute to a better ESG score. Our approach is to look at the difference between a company sentiment and its industry average; how much more \"positive\" or \"negative\" a company is perceived across all its financial services news articles, over time.In the example below, we show that difference in sentiment (using a 15 days moving average) between one of our key FSIs and its industry average. Apart from a specific time window around COVID-19 virus outbreak in March 2020, this company has been constantly performing better than the industry average, indicating a good environmental score overall.Generalising this approach to every entity mentioned in our GDELT dataset, we are no longer limited to the few FSIs we have an official ESG report for and are able to create an internal score for each and every single company across their environmental, social and governance dimensions. In other words, we have started to shift our ESG lense from being subjective to being data-driven.Introducing a propagated weighted ESG metricsIn a global market, companies and businesses are inter-connected, and the ESG performance of one (e.g. seller) may affect the reputation of another (e.g. buyer). As an example, if a firm keeps investing in companies directly or indirectly related to environmental issues, this risk should be quantified and must be reflected back on companies' reports as part of their ethical investment strategy. We could cite the example of Barclays' reputation being impacted in late 2018 because of its indirect connections to tar sand projects (source).Identifying influencing factorsDemocratised by Google for web indexing, Page Rank is a common technique used to identify nodes' influence in large networks. In our approach, we use a variant of Page Rank, Personalised Page Rank, to identify influential organisations relative to our key financial services institutions. The more influential these connections are, the more likely they will contribute (positively or negatively) to our ESG score. An illustration of this approach is reported below where indirect connections to tar sand industry may negatively contribute to a company ESG score proportional to its personalised page rank influence.Using Graphframes, we can easily create a network of companies sharing a common media coverage. Our assumption is that the more companies are mentioned together in news articles, the stronger their link will be (edge weight). Although this assumption may also infer wrong connections because of random co-occurrence in news articles (see later), this undirected weighted graph will help us find companies' importance relative to our core FSIs we would like to assess.\nval buildTuples = udf((organisations: Seq[String]) => {\n    \/\/ as undirected, we create both IN and OUT connections\n    organisations.flatMap(x1 => {\n        organisations.map(x2 => {\n        (x1, x2)\n        })\n    }).toSeq.filter({ case (x1, x2) =>\n        x1 != x2 \/\/ remove self edges\n    })\n})\n    \nval edges = spark.read.table(\"esg_gdelt\")\n    .groupBy(\"url\")\n    .agg(collect_list(col(\"organisation\")).as(\"organisations\"))\n    .withColumn(\"tuples\", buildTuples(col(\"organisations\")))\n    .withColumn(\"tuple\", explode(col(\"tuples\")))\n    .withColumn(\"src\", col(\"tuple._1\"))\n    .withColumn(\"dst\", col(\"tuple._2\"))\n    .groupBy(\"src\", \"dst\")\n    .count()\n    \nimport org.graphframes.GraphFrame \nval esgGraph = GraphFrame(nodes, edges)\nBy studying this graph further, we observe a power of law distribution of its edge weights: 90% of the connected businesses share a very few connections. We drastically reduce the graph size from 51,679,930 down to 61,143 connections by filtering edges for a weight of 200 or above (empirically led threshold). Prior to running Page Rank, we also optimise our graph by further reducing the number of connections through a Shortest Path algorithm and compute the maximum number of hops a node needs to follow to reach any of our core FSIs vertices (captured in `landmarks` array). The depth of a graph is the maximum of every shortest path possible, or the number of connections it takes for any random node to reach any others (the smaller the depth is, denser is our network).\nval shortestPaths = esgGraph.shortestPaths.landmarks(landmarks).run()\nval filterDepth = udf((distances: Map[String, Int]) => {\n    distances.values.exists(_ \n\n\nWe filter our graph to have a maximum depth of 4. This process reduces our graph further down to 2,300 businesses and 54,000 connections, allowing us to run Page Rank algorithm more extensively with more iterations in order to better capture industry influence.\n\n\n\nval prNodes = esgDenseGraph .parallelPersonalizedPageRank .maxIter(100) .sourceIds(landmarks) .run() We can directly visualise the top 100 influential nodes to a specific business (in this case Barclays PLC) as per below graph. Without any surprise, Barclays is well connected with most of our core FSIs (such as the institutional investors JP Morgan Chase, Goldman Sachs or Credit Suisse), but also to the Security Exchange Commission, Federal Reserve and International Monetary Fund.Further down this distribution, we find public and private companies such as Chevron, Starbucks or Johnson and Johnson. Strongly or loosely related, directly or indirectly connected, all these businesses (or entities from an NLP standpoint) could theoretically affect Barclays ESG performance, either positively or negatively, and as such impact Barclays' reputation.ESG as a propagated metricBy combining our ESG score captured earlier with the importance of each of these entities, it becomes easy to apply a weighted average on the \"Barclays network\" where each business contributes to Barclays' ESG score proportionally to its relative importance. We call this approach a propagated weighted ESG score (PW-ESG).We observe the negative or positive influence of any company's network using a word cloud visualisation. In the picture below, we show the negative influence (entities contributing negatively to ESG) for a specific organisation (name redacted).Due to the nature of news analytics, it is not surprising to observe news publishing companies (such as Thomson Reuters or Bloomberg) or social networks (Facebook, Twitter) as strongly connected organisations. Not reflecting the true connections of a given business but rather explained by a simple co-occurrence in news articles, we should consider filtering them out prior to our page rank process by removing nodes with a high degree of connections. However, this additional noise seems constant across our FSIs and as such does not seem to disadvantage one organisation over another. An alternative approach would be to build our graph using established connections as extracted from advanced uses of NLP on raw text content. This, however, would drastically increase the complexity of this project and the costs associated with news scraping processes.Finally, we represent the original ESG score as computed in the previous section, and how much of these scores were reduced (or increased) using our PW-ESG approach across its environmental, social and governance dimensions. In the example below, for a given company, the initial scores of 69, 62 and 67 have been reduced to 57, 53 and 60, with the most negative influence of PW-ESG being on its environmental coverage (-20%).Using the agility of Redash coupled with the efficiency of Databricks' runtime, this series of insights can be rapidly packaged up as a BI\/MI report, bringing ESG as-a-service to your organisation for asset managers to better invest in sustainable and responsible finance.It is worth mentioning that this new framework is generic enough to accommodate multiple use cases. Whilst core FSIs may consider their own company as a landmark to Page Rank in order to better evaluate reputational risks, asset managers could consider all their positions as landmarks to better assess the sustainability relative to each of their investment decisions.ESG applied to market riskIn order to validate our initial assumption that [...] higher ESG ratings are generally positively correlated with valuation and profitability while negatively correlated with volatility, we create a synthetic portfolio made of random equities that we run through our PW-ESG framework and combine with actual stock information retrieved from Yahoo Finance. As reported in the graph below, despite an evident lack of data to draw scientific conclusions, it would appear that our highest and lowest ESG rated companies (we report the sentiment analysis as a proxy of ESG in the top graph) are respectively the best or worst profitable instruments in our portfolio over the last 18 months.Interestingly, CSRHub reports the exact opposite, Pearson (media) being 10 points above Prologis (property leasing) in terms of ESG scores, highlighting the subjectivity of ESG scoring and its inconsistency between what is communicated and what is actually observed.Following up on our recent blog post about modernizing risk management, we can use this new information available to us to drive better risk calculations. Splitting our portfolio into 2 distinct books, composed of the best and worst 10% of our ESG rated instruments, we report in the graph below the historical returns and its corresponding 95% value-at-risk (historical VaR).Without any prior knowledge of our instruments beyond the metrics we extracted through our framework, we can observe a risk exposure to be 2 times higher for a portfolio made of poor ESG rated companies, supporting the assumptions found in the literature that \"poor ESG [...] correlates with higher market volatility\", hence to a greater value-at-risk.As covered in our previous blog, the future of risk management lies with agility and interactivity. Risk analysts must augment traditional data with alternative data and alternative insights in order to explore new ways of identifying and quantifying the risks facing their business. Using the flexibility and scale of cloud compute and the level of interactivity in your data enabled through our Databricks runtime, risk analysts can better understand the risks facing their business by slicing and dicing market risk calculations at different industries, countries, segments, and now at different ESG ratings. This data-driven ESG framework enables businesses to ask new questions such as: how much of your risk would be decreased by bringing the environmental rating of this company up 10 points? How much more exposure would you face by investing in these instruments given their low PW-ESG scores?Transforming your ESG strategyIn this blog, we have demonstrated how complex documents can be quickly summarised into key ESG initiatives to better understand the sustainability aspect of each of your investments. Using graph analytics, we introduced a novel approach to ESG by better identifying the influence a global market has to both your organisation strategy and reputational risk. Finally, we showed the economic impact of ESG factors\u00a0 on market risk calculation. As a starting point to a data-driven ESG journey, this approach can be further improved by bringing the internal data you hold about your various investments and the additional metrics you could bring from third-party data, propagating the risks through our PW-ESG framework to keep driving more sustainable finance and profitable investments.Try the following notebooks on Databricks to accelerate your ESG development strategy today and contact us to learn more about how we assist customers with similar use cases.Try Databricks for freeGet StartedRelated postsA Data-driven Approach to Environmental, Social and GovernanceJuly 10, 2020 by Antoine Amend in Engineering Blog\nThe future of finance goes hand in hand with social responsibility, environmental stewardship and corporate ethics. In order to stay competitive, Financial Services...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/uri-may\/#","text":"Uri May - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingUri May HuntersBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/training","text":"Training - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTrainingLevel up your data and AI skills through one of our Summit trainings. Whether you\u2019re new to the Lakehouse architecture or a seasoned pro looking to dive deep, we have a course for you.\nHide search filtersreset filtersSearchSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/federal-government","text":"Analytique de donn\u00e9es et IA pour les agences f\u00e9d\u00e9rales | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWAnalytique de donn\u00e9es et IA pour les agences f\u00e9d\u00e9ralesLib\u00e9rez l'innovation pour offrir de meilleurs services publics gr\u00e2ce aux donn\u00e9es et au machine learningDe la strat\u00e9gie f\u00e9d\u00e9rale sur les donn\u00e9es \u00e0 l'ordonnance ex\u00e9cutive sur l'IA, le gouvernement f\u00e9d\u00e9ral am\u00e9ricain mise sur la modernisation de ses capacit\u00e9s d'analytique de donn\u00e9es et d'entreposage.La plateforme Lakehouse de Databricks permet aux agences f\u00e9d\u00e9rales de lib\u00e9rer tout le potentiel de leurs donn\u00e9es pour atteindre les objectifs de leur mission et mieux servir les citoyens.Donner aux agences f\u00e9d\u00e9rales les moyens d'exploiter la puissance des donn\u00e9es et de l'IA pour remplir sa missionUtilis\u00e9e par les principales agences du secteur public+ tout autre client compatible Apache Spark\u2122D\u00e9couvrez comment les leaders du secteur utilisent Databricks pour am\u00e9liorer l'exp\u00e9rience des citoyens dans l'ensemble des services publicsDerniers articles de blog, webinaires et \u00e9tudes de casLes avantages de Databricks pour le gouvernement f\u00e9d\u00e9ralModernisez votre analytique de donn\u00e9es130 car. Modernisez votre pile technologique pour am\u00e9liorer l'exp\u00e9rience des patients et des m\u00e9decins gr\u00e2ce au pipeline DNASeq le plus rapide \u00e0 grande \u00e9chelle.Obtenez des r\u00e9sultats de mission de mani\u00e8re efficace et effective130 car. Modernisez votre pile technologique pour am\u00e9liorer l'exp\u00e9rience des patients et des m\u00e9decins gr\u00e2ce au pipeline DNASeq le plus rapide \u00e0 grande \u00e9chelle.Cr\u00e9ez de meilleures exp\u00e9riences pour les citoyens130 car. Modernisez votre pile technologique pour am\u00e9liorer l'exp\u00e9rience des patients et des m\u00e9decins gr\u00e2ce au pipeline DNASeq le plus rapide \u00e0 grande \u00e9chelle.En savoir plusConformit\u00e9 \u00e9tendue pour un agr\u00e9ment d'exploitation simple et rapideDatabricks a obtenu des agr\u00e9ments d'exploitation sur les r\u00e9gions, les r\u00e9seaux et les contr\u00f4les de conformit\u00e9 qui soutiennent vos objectifs de missionCloudsC2S\nSC2S\nGovCloud\nCloud public\nR\u00e9seauxPubliques\nNIPR\nSIPR\nJWICS\nContr\u00f4les de conformit\u00e9FedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICD-503\nComment Databricks alimente l'innovation pour le gouvernement f\u00e9d\u00e9ralSant\u00e9Am\u00e9liorez la prestation et la qualit\u00e9 des services de sant\u00e9 pour les citoyens gr\u00e2ce \u00e0 une analytique solide et \u00e0 une vue \u00e0 360\u00b0 des patients.\nVue \u00e0 360\u00b0 du patient\u00a0\nOptimisation de la cha\u00eene d'approvisionnement\u00a0\nGestion des assurances\u00a0G\u00e9nomique\u00a0\nD\u00e9couverte et livraison de m\u00e9dicamentsD\u00e9fenseAppliquez les avantages de l'analytique pr\u00e9dictive aux donn\u00e9es g\u00e9ospatiales, IoT et de surveillance pour am\u00e9liorer les op\u00e9rations et prot\u00e9ger la nation.\u00a0\nLogistique\nMaintenance pr\u00e9dictive\u00a0\nSurveillance et reconnaissance\u00a0\nForces de l'ordre et pr\u00e9parationS\u00e9curit\u00e9 int\u00e9rieureD\u00e9tectez et pr\u00e9venez les activit\u00e9s criminelles et les menaces au niveau national gr\u00e2ce \u00e0 l'analytique en temps r\u00e9el et \u00e0 la prise de d\u00e9cision data-driven.\nDouanes et protection des fronti\u00e8res\u00a0\nImmigration et citoyennet\u00e9\u00a0\nLutte contre le terrorisme\u00a0\nGestion de l'aide d'urgence f\u00e9d\u00e9raleAutorit\u00e9 publique \/ CommerceD\u00e9tectez de mani\u00e8re proactive les anomalies gr\u00e2ce au machine learning afin d'att\u00e9nuer les risques et pr\u00e9venir les activit\u00e9s frauduleuses.\nLutte contre la fraude fiscale et recouvrement\u00a0\nGestion des processus et des op\u00e9rations\u00a0\nGestion des subventions\u00a0\nVue \u00e0 360\u00b0 du client\u00c9nergieAm\u00e9liorez la gestion \u00e9nerg\u00e9tique gr\u00e2ce \u00e0 des insights de donn\u00e9es qui garantissent la r\u00e9silience \u00e9nerg\u00e9tique et la durabilit\u00e9.\nS\u00e9curit\u00e9 des infrastructures \u00e9nerg\u00e9tiques\u00a0\nGestion intelligente de l'\u00e9nergie\u00a0\nExploration \u00e9nerg\u00e9tique\u00a0\nFiabilit\u00e9 du r\u00e9seau \u00e9lectriqueCommunaut\u00e9 du renseignementTirez parti d'insights en temps r\u00e9el pour prendre des d\u00e9cisions \u00e9clair\u00e9es pouvant avoir des cons\u00e9quences sur la s\u00e9curit\u00e9 de nos citoyens et du monde entier.\nD\u00e9tection des menaces\u00a0\nNeutralisation des cyberattaques\u00a0\nRenseignement, surveillance et reconnaissance\u00a0\nAnalytique des r\u00e9seaux sociauxRessourcesT\u00e9moignages de clientsFavoriser la transformation num\u00e9rique pour donner la priorit\u00e9 aux patients dans les CMSBonnes pratiques de gouvernance des donn\u00e9es \u2014 Le\u00e7ons tir\u00e9es des centres de services Medicare et MedicaidLe\u00e7ons tir\u00e9es de la modernisation de la plateforme d'analytique de donn\u00e9es de l'USCISModerniser l'Air Force gr\u00e2ce au Big Data et \u00e0 l'IAWebinairesUne r\u00e9ponse rapide aux activit\u00e9s hospitali\u00e8res \u00e0 l'aide des donn\u00e9es et de l'IA pendant la crise de COVID-19Analyse g\u00e9ospatiale et IA dans le secteur publicArchitecture moderne d'analyse de donn\u00e9es pour le gouvernementAm\u00e9liorer la d\u00e9tection des menaces gr\u00e2ce au big data et \u00e0 l'IAActualit\u00e9sAzure Databricks obtient l'autorisation \u00e9lev\u00e9e de FedRAMP sur Microsoft Azure Government (MAG)S\u00e9curit\u00e9 de niveau gouvernemental dans AWS CloudApporter des analyses unifi\u00e9es aux clients du gouvernementDoter la communaut\u00e9 du renseignement am\u00e9ricain d'outils d'analytique et d'IA de premi\u00e8re importanceLes discussions du sommetAutomatiser l'ingestion et l'analyse de donn\u00e9es SWIM (gestion des informations \u00e0 l'\u00e9chelle du syst\u00e8me) de l'Administration F\u00e9d\u00e9rale de l'Aviation (FAA)Analytique g\u00e9ospatiale \u00e0 grande \u00e9chelle\u00a0: analyse des sch\u00e9mas migratoires au cours d'une pand\u00e9miePr\u00eat \u00e0 vous lancer\u00a0?Nous aimerions beaucoup conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.Essai gratuitNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tianyu-liu\/#","text":"Tianyu Liu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTianyu LiuLead Data Scientist (Analytics) at GrabBack to speakersFrom the Analytics Data Platform and Finance Data + AI Transformation Team at Grab.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nat-friedman\/#","text":"Nat Friedman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNat FriedmanCreator of Copilot; Former CEO at GithubBack to speakersNat Friedman has founded two startups, led GitHub as CEO from 2018 to 2022, and now invests in infrastructure, AI, and developer companies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/why-data-focused-startups-are-building-on-a-lakehouse","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thorsten-jacobs","text":"Thorsten Jacobs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThorsten JacobsSr. Solutions Architect at DatabricksBack to speakersThorsten is a Senior Solutions Architect at Databricks and is based in Stockholm, Sweden. Data was always important during his career, as he holds a PhD in physics and previously worked as a Consultant and Data Scientist.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/sql-pricing-aws","text":"Databricks SQL Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWExtended Time SQL Price Promotion - Save 40%+ Take advantage of our 15-month promotion on Serverless SQL and the brand new SQL ProLearn moreOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorDatabricks SQLRun all SQL and BI applications at scale with up to 12x better price-performance, a unified governance model, open formats and APIs, and your tools of choice \u2014 no lock-in.Select planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudSelect regionSelectLoading...Compare featuresFeature DetailSQL ClassicSQL ProSQL\u00a0ServerlessExtended Time Price PromotionPromo Nov. 1, 2022 to Jan. 31, 2024Promo Nov. 1, 2022 to Jan. 31, 2024Data Exploration and\nConnectivityIntelligent auto complete, ANSI SQL & Rest APIIntelligent auto complete, ANSI SQL & Rest APIIntelligent auto complete, ANSI SQL & Rest APIPerformanceMassively parallel processingMassively parallel processing & Predictive I\/OMassively parallel processing & Predictive I\/OSQL ETL\/ELTQuery federation, materialized views and workflow integrationQuery federation, materialized views and workflow integrationData Science and MLPython UDF, notebooks integration & geospatialPython UDF, notebooks integration & geospatialHigh Concurrency BIFully managed compute, workload management & query result cachingGovernance and ManageabilityQuery profiling, unity catalog integration & platform manageabilityQuery profiling, unity catalog integration & platform manageabilityQuery profiling, unity catalog integration & platform manageabilityEnterprise SecuritySee Platform Capabilities and Add-Ons for details* indicates Public Preview feature\n**No data transfer charges to cloud storage region while feature in Preview. See FAQ for more details\n\u00a0\nPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements\nCalculate priceStart free trialContact usWhat is the difference between SQL Serverless and SQL Classic \/ Pro?For SQL Classic and Pro, Databricks deploys cluster resources into your Cloud provider environment, and you are responsible for paying for the corresponding Compute infrastructure charges. For Serverless compute, Databricks deploys the cluster resources in Databricks\u2019 Cloud provider account and you are not required to separately pay for Compute infrastructure charges. Please see here for more details.What cross-region data transfer charges may be incurred in Serverless offerings?The cross-regions storage access feature is currently in Preview. If your source data is in a different cloud region, Databricks is currently waiving charges for transferring data from the Databricks Serverless environment's region to your cloud storage\u2019s region. We will start charging for this at market-competitive rates in the future when the feature is Generally Available (GA). Please note, the Cloud provider may still charge you directly for transferring data to the region the Databricks serverless environment is running in.Do the promotional discounts for SQL Pro and SQL Serverless stack on top of my negotiated discounts?Yes, the promotional discounts stack on top of any contracted discounts that you may have negotiated.How are the promotional discounts for SQL Pro and SQL Serverless implemented?On AWS, the promotional discounts are implemented through a reduction in the DBU rate that is emitted for SQL Pro and Serverless SQL warehouses during the promotional period.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/data-pipelines","text":"Ingegneria dei dati | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWIngegneria dei datiSu Databricks girano ogni giorno decine di milioni di carichi di lavoro di produzioneCominciaGuarda la demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowAcquisisci e trasforma facilmente dati in batch e in streaming sulla Databricks Lakehouse Platform. Organizza flussi di lavoro in produzione affidabili mentre Databricks gestisce automaticamente l'infrastruttura su larga scala. Aumenta la produttivit\u00e0 dei team con verifiche integrate della qualit\u00e0 dei dati e supporto di best practice per lo sviluppo di software.Unificare batch e streamingElimina i silos operando su una sola piattaforma con un'unica API per acquisire, trasformare ed elaborare progressivamente dati in batch e in streaming su larga scala.Concentrati sull'estrazione di valore dai datiDatabricks gestisce automaticamente l'infrastruttura e i componenti operativi dei flussi di lavoro in produzione, consentendo agli utenti di concentrarsi sul valore invece che sugli strumenti.Connetti i tuoi strumenti preferitiUna piattaforma lakehouse aperta per connettere e utilizzare gli strumenti preferiti di data engineering per acquisizione, ETL\/ELT e orchestrazione dei dati.Costruisci un sistema basato sulla piattaforma lakehouseLa piattaforma lakehouse \u00e8 la base pi\u00f9 idonea per costruire e condividere risorse di dati affidabili, con una gestione centralizzata, massima affidabilit\u00e0 e tempi rapidi.\u201cPer noi, Databricks sta diventando una vera e propria centrale per tutto il nostro lavoro ETL. Pi\u00f9 lavoriamo con la Lakehouse Platform, pi\u00f9 diventa facile sia per gli utenti sia per gli amministratori della piattaforma\u201d.\u2014 Hillevi Crognale, Engineering Manager, YipitDataCome funziona?Acquisizione dati semplificataElaborazione ETL automatizzataOrchestrazione affidabile dei flussi di lavoroOsservabilit\u00e0 e monitoraggio a 360 gradiMotore di elaborazione dati di nuova generazioneFondamenti di governance, affidabilit\u00e0 e prestazioniAcquisizione dati semplificataAcquisisci i dati nella\u00a0Lakehouse Platform\u00a0e alimenta le applicazioni di analisi, AI e streaming da un'unica fonte.\u00a0Auto Loader elabora in modo progressivo e automatico i file che arrivano sullo storage in cloud, senza bisogno di gestire le informazioni di stato, in lavori programmati o continui. Il sistema traccia in modo efficiente i nuovi file (nell'ordine dei miliardi) senza doverli elencare in una directory e, inoltre, pu\u00f2 inferire lo schema dai dati sorgente e adattarlo ai cambiamenti che si verificano nel tempo. Il comando\u00a0COPY INTO\u00a0agevola gli analisti nell'acquisizione di file in batch in\u00a0Delta Lake\u00a0tramite SQL.\u201cAbbiamo registrato un incremento della produttivit\u00e0 del 40% nel data engineering, riducendo il tempo necessario per sviluppare nuove idee da alcuni giorni a pochi minuti e aumentando la disponibilit\u00e0 e l'accuratezza dei nostri dati\u201d.\u2014 Shaun Pearce, Chief Technology Officer,\u00a0GoustoMaggiori informazioniElaborazione ETL automatizzataUna volta acquisiti, i dati grezzi devono essere trasformati in modo che siano pronti per analisi e AI. Databricks offre potenti funzionalit\u00e0 ETL per ingegneri dei dati, data scientist e analisti con\u00a0Delta Live Tables\u00a0(DLT). DLT \u00e8 il primo framework che adotta un semplice approccio dichiarativo per costruire pipeline ETL e ML su dati in batch o in streaming, automatizzando al tempo stesso attivit\u00e0 complesse come la gestione dell'infrastruttura, l'orchestrazione dei compiti, la gestione e il ripristino di errori e l'ottimizzazione delle prestazioni. Con DLT gli ingegneri possono trattare i dati come codice e applicare best practice moderne di ingegneria software come test, gestione, monitoraggio e documentazione degli errori, per implementare pipeline affidabili su larga scala.Maggiori informazioniOrchestrazione affidabile dei flussi di lavoroDatabricks Workflows \u00e8 il servizio completamente gestito per l'orchestrazione di tutti i dati, le analisi e l'AI, nativo sulla Lakehouse Platform. Si possono orchestrare diversi carichi di lavoro per l'intero ciclo di vita, inclusi Delta Live Tables e Jobs per SQL, Spark, notebook, dbt, modelli di ML e altro ancora. La stretta integrazione con la Lakehouse Platform sottostante consente di creare ed eseguire carichi di lavoro in produzione affidabili su qualsiasi cloud, offrendo al tempo stesso un monitoraggio accurato e centralizzato, con la massima semplicit\u00e0 per gli utilizzatori finali.\"La nostra missione \u00e8 trasformare il modo in cui alimentiamo il pianeta. I nostri clienti del settore energetico hanno bisogno di dati, servizi di consulenza e ricerca per realizzare questa trasformazione. Databricks Workflows ci offre la velocit\u00e0 e la flessibilit\u00e0 necessarie per fornire gli approfondimenti di cui i nostri clienti hanno bisogno\".\u2014 Yanyan Wu, Vice President of Data,\u00a0Wood MackenzieMaggiori informazioniOsservabilit\u00e0 e monitoraggio a 360 gradiLa piattaforma lakehouse offre visibilit\u00e0 su tutto il ciclo di vita di dati e AI, consentendo agli ingegneri dei dati e ai team operativi di visualizzare lo stato di salute dei loro flussi di lavoro in produzione in tempo reale, gestire la qualit\u00e0 dei dati e osservare l'andamento storico. Databricks Workflows offre l'accesso a grafici e dashboard dei flussi di dati che tracciano la salute e le prestazioni dei lavori in produzione e delle pipeline Delta Live Tables. Anche i registri di eventi vengono mostrati come tabelle di Delta Lake, consentendo di monitorare e visualizzare prestazioni, qualit\u00e0 dei dati e metriche affidabili da diverse angolazioni.Motore di elaborazione dati di nuova generazioneL'ingegneria dei dati di Databricks si basa su\u00a0Photon, un motore di nuova generazione compatibile con le API di Apache Spark che offre un rapporto prezzo\/prestazioni\u00a0da record\u00a0e scalabilit\u00e0 automatica a migliaia di nodi.\u00a0Spark Structured Streaming offre un'unica API per elaborazione in batch e in streaming, agevolando l'adozione dello streaming sul lakehouse senza modificare il codice o acquisire nuove competenze.Maggiori informazioniGovernance dei dati, affidabilit\u00e0 e prestazioni all'avanguardiaIl data engineering su Databricks permette di beneficiare dei componenti che costituiscono le fondamenta della\u00a0Lakehouse Platform\u00a0: Unity Catalog e Delta Lake. I dati grezzi vengono ottimizzati con Delta Lake, un formato di storage open-source che garantisce affidabilit\u00e0 attraverso transazioni ACID e una gestione scalabile dei metadati con prestazioni ad altissima velocit\u00e0. Delta Lake insieme a Unity Catalog offre una governance granulare per tutte le risorse di dati e AI, semplificando le modalit\u00e0 di governance con un unico modello omogeneo per scoprire, accedere e condividere i dati su diversi cloud. Unity Catalog offre inoltre supporto nativo per Delta Sharing, il primo protocollo aperto del settore per la condivisione semplice e sicura dei dati con altre organizzazioni.Migrazione a DatabricksStanco dei silos di dati, della lentezza e dei costi esorbitanti di sistemi obsoleti come Hadoop e i data warehouse aziendali? Migra a Databricks Lakehouse, la piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI.Migrazione a DatabricksIntegrazioniAssicura la massima flessibilit\u00e0 ai team di gestione dei dati, utilizzando Partner Connect e un ecosistema di partner tecnologici per realizzare un'integrazione diretta con gli strumenti di ingegneria dei dati pi\u00f9 diffusi. Ad esempio, si possono acquisire dati critici con Fivetran, trasformarli in loco con dbt e orchestrare le pipeline con Apache Airflow.Acquisizione ed ETL di dati+ Qualsiasi altro client compatibile con Apache Spark\u2122\ufe0fReferenzeScopri di pi\u00f9Delta LakeFlussi di lavoroDelta Live TablesDelta SharingContenuti associati\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video sui vantaggi del data engineering con Databricks.\nEsplora risorseeBookCostruire il Data Lakehouse, di Bill Inmon, padre del data warehouseGovernance di dati, analisi e intelligenza artificialeTutto sulla gestione dei datiThe Big Book of Data EngineeringScopri la nuova soluzione Delta SharingMigrazione da data warehouse a data lakehouse per principiantiEventiGestire la trasformazione dei dati con Delta Live TablesSerie di webinar sull'acquisizione di dati senza problemiDATA+AI SUMMIT 2022Modernizzare il data warehouseBlogAnnuncio della disponibilit\u00e0 di Databricks Delta Live Tables (DLT)Presentazione di Databricks WorkflowsPanoramica di tutte le nuove funzionalit\u00e0 di streaming strutturato sviluppate nel 2021 per Databricks e Apache Spark10 funzionalit\u00e0 avanzate per semplificare la gestione di dati semi-strutturati nel lakehouse di DatabricksPronto per cominciare?Prova gratuitaEntra nella communityawsazureGCPProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/life-sciences-industry-solutions","text":"Life Sciences Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for the Life Sciences IndustryBringing new treatments to patients in need with data analytics and AIData analytics and AI are critical for improving the success of drug discovery and ensuring the efficient delivery of new treatments to market.Databricks helps life science organizations consolidate massive volumes of data and apply powerful analytics so they can realize benefits across the entire drug lifecycle \u2014 to achieve lowered costs and better patient outcomes.Learn how to accelerate R&D with big data. Read the ebook.Leading healthcare organizations use Databricks to drive innovation in patient careLatest blog posts, webinars, and case studiesWhy Databricks for healthcareUnlock health data and break data silosConnect structured and unstructured data from EHRs, wearables, imaging platforms, genome sequencers and more to deliver a complete view into patient health.Patient insights at population scaleBetter predict health risks with analytics and AI that scale for millions of patient records in the cloud.Deliver reproducibility and complianceCollaborative analytics workspaces that bring data teams together while streamlining the machine learning lifecycle and providing regulatory-grade MLOps.Use casesAcross the healthcare landscape, data and AI is providing insights and predictive capabilities to personalize care, automate claims and payment processing, and improve patient engagement.Supply ChainCreate more resilient supply chains by improving accuracy in inventory prediction, understanding customer demand, reducing excess inventory, and avoiding lost sales\nSupply chain control tower \nDemand forecasting \nSafety stock \nSupply chain \nESG safetyIoT and RoboticsOptimize productivity, increase inventory accuracy, and build a more agile warehouse experience\nPredictive maintenance \nAutomated quality control \nWarehouse roboticsCost OptimizationLower costs of manufacturing processes by boosting operational efficiencies and ensuring fast time-to-market of outputs\nPicking and delivery pathing\nCommodity usage optimization \nWorker safety and health monitoringLearn More About our life sciences SolutionsResourcesCase StudiesAstraZenecaRegeneronBiogenCVS HealthLivongoWebinarsImproving Patient Insights With a Health LakehouseEnabling a Scalable Data Science Pipeline With MLflow at Thermo Fisher ScientificHow Regeneron Accelerates Genomic Discovery at Biobank-ScaleeBooksDatabricks for Life Sciences Solution SheetGuide to Healthcare & Life Sciences Guidebook at Data + AI Summit 2021Analyzing Real-World Evidence at ScaleTop Databricks Life Sciences ResourcesReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.\u00a0Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chang-she","text":"Chang She - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChang SheCEO at LanceDBBack to speakersChang She is the CEO and cofounder of LanceDB, the developer-friendly, serverless vector database for AI applications. Previously Chang was VP of Eng at Tubi TV where he led all data and ML efforts. In a past life Chang was one of the original co-authors of the Pandas library.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/category\/company","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/craig-wiley\/#","text":"Craig Wiley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCraig WileySr. Director of Product, Lakehouse AI at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Databricks by Avanade\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcIntelligent Manufacturing\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcLegacy System Migration by Avanade\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcRisk Management by Avanade\u8a73\u3057\u304f\u898b\u308b\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30fb\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2Migrate Legacy Cards and Core Banking Portfolios by Capgemini and Databricks\u8a73\u3057\u304f\u898b\u308b\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30fb\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2Migrate to Cloud and Databricks by Capgemini and Databricks\u8a73\u3057\u304f\u898b\u308b\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30fb\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2Capgemini Revenue Growth Management\u8a73\u3057\u304f\u898b\u308b\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30fb\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2Migrate to Databricks by Celebal Technologies and Databricks\u8a73\u3057\u304f\u898b\u308b\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30fb\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2Cognizant Video Quality of Experience\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcPersona 360 by DataSentics and Databricks\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcSAP Migration Accelerator by DataSentics - Databricks\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcPrecisionView\u2122 by Deloitte\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcTrellis by Deloitte\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcSmart Migration to Databricks by EPAM\u8a73\u3057\u304f\u898b\u308b\u5e83\u544a\u30fb\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30c6\u30af\u30ce\u30ed\u30b8\u30fcLeapLogic Migration Solution by Impetus\u8a73\u3057\u304f\u898b\u308b\u3082\u3063\u3068\u898b\u308b\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/azure-databricks-achieves-fedramp-high-authorization-on-microsoft-azure-government-mag","text":"Azure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)Databricks' Unified Data Analytics Platform Enables Global Enterprises to Process Highly Sensitive Data \nNovember 25, 2020Share this postSAN FRANCISCO, CA \u2013 November 25, 2020 \u2013 Databricks, the Data and AI Company, today announced that Microsoft Azure Databricks has received a Federal Risk and Authorization Management Program (FedRAMP) High Authority to Operate (ATO). This authorization validates Azure Databricks security and compliance for high-impact data analytics and AI across a wide range of public sector, industry, and enterprise use cases.\nFedRAMP is a standardized approach to security assessment, authorization, and continuous monitoring for cloud services as defined by the National Institute of Standards and Technology (NIST). The ATO was granted by the FedRAMP Joint Authorization Board (JAB) which consists of representatives from the Department of Defense (DoD), Department of Homeland Security (DHS), and the General Services Administration (GSA).\n\u201cAt Veterans Affairs, we included Azure Databricks as part of our Microsoft Azure Authority to Operate (ATO),\" said Joseph Fourcade, Lead Cyber Security Analyst, U.S. Department of Veterans Affairs Enterprise Cloud Solutions Office (ECSO). \u201cWhen Databricks received FedRAMP High approval, we were able to move quickly to inherit that same Azure ATO and approve Azure Databricks for production workloads. Timing couldn't have been better, as we have been working with a number of VA customers implementing Databricks for critical programs.\"\n\u201cNumerous federal agencies are looking to build cloud data lakes and leverage Delta Lake for a complete and consistent view of all their data,\u201d said Kevin Davis, VP, Public Sector at Databricks. \u201cThe power of data and AI are being used to dramatically enhance public services, lower costs and improve quality of life for citizens. Using Azure Databricks, government agencies have aggregated hundreds of data sources to improve citizen outreach, automated processing of hourly utility infrastructure IoT data for enabled predictive maintenance, deployed machine learning models to predict patient needs, and built dashboards to predict transportation needs and optimize logistics. FedRAMP High authorization for Azure Databricks further enables federal agencies to analyze all of their data for improved decision making and more accurate predictions.\u201d\n\"We are pleased to add Azure Databricks to our portfolio of services approved for FedRAMP at the high impact level in Microsoft Azure Government,\" said Lily Kim, General Manager of Azure Government at Microsoft. \"Azure Government provides the most trusted cloud for mission-critical government workloads. FedRAMP High approval for Azure Databricks enables government customers to build fast and reliable data lakes for innovative new use cases, such as risk management and predictive analytics.\"\nWith this certification, customers can now use Azure Databricks to process the U.S. government\u2019s most sensitive, unclassified data in cloud computing environments, including data that involves the protection of life and financial assets. From personalized healthcare and education to space exploration and energy research, Azure Databricks enables organizations to accelerate new innovation while minimizing risk when working with highly sensitive, private and public sector data.\nWith FedRAMP, organizations have a consistent way to evaluate the security of cloud solutions using NIST and FISMA defined standards. FedRAMP offers several levels of assurance and Azure Databricks has met all of the requirements for authorization for the highest degree of assurance. Azure Databricks joins many other Azure services with the FedRAMP High authorization, enabling public sector, enterprise and industry vertical customers to create and deploy cloud-based applications with confidence.\nSee the list of Azure services by FedRAMP and DoD CC SRG audit scope. Learn more about FedRAMP by reading Microsoft Documentation.\nAbout Databricks\nDatabricks is the data and AI company. Thousands of organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, Nationwide and H&M \u2014 rely on Databricks\u2019 open and unified platform for data engineering, machine learning and analytics. Databricks is venture-backed and headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\nMedia Contact:\nKeyana Corliss\nHead of Global Communications\n[email\u00a0protected]\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/awards-and-recognition","text":"Awards and Recognition | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAwards and RecognitionTake a look at the ways Databricks has been recognized by industry leaders.Leader in the 2022 Magic Quadrant for Cloud Database Management Systems2022 Customer Choice Award for Cloud Database Management SystemsLeader in the 2021 Magic Quadrant for Cloud Database Management SystemsLeader in the 2021 Magic Quadrant for Data Science and Machine LearningLakehouse \u2014 Hype Cycle for Data Management, 2022Hot Companies to Watch in 2023Most Innovative Companies in Data ScienceThe Cloud 100The AI 50America\u2019s Best Startup EmployersBest Workplaces in TechnologyBest Workplaces in the Bay AreaBest Workplaces for MillennialsCNBC Disruptor 50Best Places to Work 2022Ready to learn more?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-johnson","text":"Ryan Johnson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan JohnsonSenior Staff Engineer at DatabricksBack to speakersRyan Johnson is a Senior Staff Software Engineer and tech lead at Databricks, working with the Delta Lake table format at the boundary between the storage system and the query layer. Before joining Databricks, he worked on the storage layer at Amazon Redshift and previously did database systems research as a professor at the University of Toronto. He loves writing code and solving low-level systems problems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/careers","text":"Carreiras na Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Carreiras em DatabricksNossa miss\u00e3o: ajudar as equipes de dados a resolver os problemas mais complexos do mundo. Voc\u00ea quer se juntar a n\u00f3s?Ver vagas abertas OverviewCultureBenefitsDiversityStudents & new gradsLeve sua carreira ao pr\u00f3ximo n\u00edvel. Invista no futuro.Databricks lidera a revolu\u00e7\u00e3o de dados e IA. Criamos uma categoria chamada lakehouse. Atualmente, milhares de empresas est\u00e3o usando esse recurso para resolver problemas como mudan\u00e7as clim\u00e1ticas, fraudes, rotatividade de clientes e muito mais. Se voc\u00ea est\u00e1 procurando uma oportunidade que possa realmente marcar sua carreira, encontrou.Descubra por que lakehouse \u00e9 o futuroPor que escolher Databricks?Estamos crescendo r\u00e1pido e recrutando os melhores talentos do mundo. Somos os Bricksters: uma combina\u00e7\u00e3o especial de pensadores inteligentes, curiosos e animados. Pergunte a um Brickster o que ele gosta em seu trabalho e provavelmente ouvir\u00e1 sobre nossa cultura.Veja os princ\u00edpios da nossa culturaEncontre sua equipeAdministra\u00e7\u00e3oDesenvolvimento comercialCaso de sucessoEngenhariaEngenharia de campoFinan\u00e7asTIInforma\u00e7\u00f5es legaisMarketingOpera\u00e7\u00f5esPessoas e RHProdutoServi\u00e7os profissionaisRecrutamentoVendasSeguran\u00e7aEst\u00e1gios e in\u00edcio de carreiraBenef\u00edcios, vantagens e trabalho h\u00edbridoPara ter o melhor desempenho no trabalho, sua sa\u00fade e bem-estar s\u00e3o essenciais. \u00c9 por isso que oferecemos excelentes benef\u00edcios e vantagens, incluindo formas flex\u00edveis de trabalhar. O importante \u00e9 que voc\u00ea encontre o que funciona melhor para voc\u00ea e sua equipe.Confira nossos benef\u00edciosDiversidade, Equidade e Inclus\u00e3oAcreditamos que a diversidade de origens, perspectivas e habilidades \u00e9 o que impulsiona nosso sucesso. Por esse motivo, nos esfor\u00e7amos para criar e nutrir um ambiente inclusivo e de suporte. Descubra como estamos reduzindo as desigualdades salariais, combatendo vieses inconscientes no recrutamento e muito mais.Ver a inclus\u00e3o em a\u00e7\u00e3oLocaliza\u00e7\u00f5esNossa sede est\u00e1 em S\u00e3o Francisco, na Calif\u00f3rnia, e temos mais de 20 escrit\u00f3rios em 12 pa\u00edses. Com mais de 4.500 Bricksters em todo o mundo e uma estrat\u00e9gia de desenvolvimento ambiciosa, somos uma das empresas do setor de nuvem corporativa que mais cresce.Conhe\u00e7a nossos escrit\u00f3rios ao redor do mundoAm\u00e9ricas\n\u00a0S\u00e3o FranciscoSeattleWashington, D.C.Cidade de Nova YorkVer maisEuropa\n\u00a0LondresAmsterd\u00e3BerlimMuniqueVer mais\u00c1sia-Pac\u00edfico\n\u00a0T\u00f3quioSingapuraSeulHangzhouVer maisOportunidades para estudantes e rec\u00e9m-formadosTemos o compromisso de desenvolver a pr\u00f3xima gera\u00e7\u00e3o de l\u00edderes da Databricks. \u00c9 por isso que queremos que nossos estagi\u00e1rios e rec\u00e9m-formados na universidade tenham um papel essencial no desenvolvimento da nossa plataforma.Nosso Programa de Treinamento foi desenvolvido para voc\u00ea aproveitar ao m\u00e1ximo sua experi\u00eancia: hackathons de engenharia, Olimp\u00edadas de Estagi\u00e1rios, noites de jogos de tabuleiro e happy hours.Explore est\u00e1gios e oportunidades Transpar\u00eancia da cobertura do plano de sa\u00fade (somente nos EUA)ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/behzad-bordbar\/#","text":"Behzad Bordbar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBehzad BordbarLead Data Scientist at Marks & SpencerBack to speakersBehzad started working at M&S in Jan 2021 as Lead Data Scientist. As part of the Data Science Retails team, he is involved in the digital transformation of Retail operations utilizing Machine Learning and Artificial Intelligence. He has a PhD in mathematics and over 20 years of experience solving challenging and complex business problems using innovative data solutions. He has published over 120 technical and scientific papers and contributed to several open-source projects.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/william-zanine","text":"William Zanine - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWilliam ZanineHead of Data Management, Channel and Specialty North America at IQVIABack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/built-on-partner-program","text":"Skip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPrograma de parceria Built on DatabricksCrie, comercialize e expanda seus neg\u00f3cios com a DatabricksInscreva-se agoraO programa de parceria Built on Databricks fornece recursos t\u00e9cnicos e de entrada ao mercado para acelerar o desenvolvimento do seu aplicativo SaaS moderno e expandir seus neg\u00f3cios. Desenvolvido na Plataforma Databricks Lakehouse, ele oferece uma experi\u00eancia unificada e econ\u00f4mica para criar aplicativos, produtos e servi\u00e7os de dados e compartilhar dados em escala com um ecossistema aberto global.As empresas que usam o Built on Databricks geram valor comercial em escalaBlogLeia o artigoWebinarVerBlogLeia o artigoBenef\u00edcios da parceria Built on DatabricksAcesso a especialistas da Databricks\nConecte-se \u00e0 equipe de produto, engenharia e suporte da DatabricksDesenvolva em uma plataforma moderna\nA plataforma lakehouse l\u00edder de mercado para dados unificados, an\u00e1lises e IAAlcance mais clientes\nCobertura expandida para mais clientes de dados a partir de uma plataforma aberta e seguraSuporte de marketing\nAcesse investimentos de marketing para ajudar a aumentar a exposi\u00e7\u00e3o e expandir seu alcanceColabora\u00e7\u00e3o em vendas\nDesenvolva mais oportunidades por meio de capacita\u00e7\u00e3o e colabora\u00e7\u00e3o com a equipe de vendas da DatabricksComece hoje mesmo!Inscreva-se agoraProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/why-the-data-lakehouse-is-your-next-data-warehouse","text":"\n\n\n\n\n\n\n\nWhy the Data Lakehouse is your next Data Warehouse - 2nd Edition\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/hassle-free-data-ingestion-webinar-series?itm_data=DataIngestionRelatedContent-DataIngestWebinarSeries","text":"Hassle-Free Data Ingestion | DatabricksOn DemandHassle-Free Data IngestionWebinar SeriesIngesting data from hundreds of different data sources is a critical step before organizations can execute advanced analytics, data science and machine learning. But ingesting and unifying this data to create a reliable single source of truth is extremely time consuming and costly.In this webinar series, discover how Databricks simplifies data ingestion into Delta Lake for all data types. Each webinar includes an overview and demo to introduce you to the newly released features and tools that make structured, semi-structured and unstructured data ingestion even easier on the Databricks Lakehouse Platform.Webinars in the series:Intro to Data Ingestion on Databricks \u2014 Learn how Databricks enables you to easily and quickly ingest data continuously or at low latency and empowers more users with SQL-only ingestion capabilitiesSemi-Structured Data Ingestion \u2014 Deep dive into how Databricks simplifies JSON data ingestion into Delta Lake at scaleUnstructured Data Ingestion \u2013 Discover how Databricks makes it easy to ingest unstructured data at scale with Auto Loader and see how partners, like Labelbox, can help you label your unstructured data.Download the seriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/danica-fine\/#","text":"Danica Fine - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDanica FineSenior Developer Advocate at ConfluentBack to speakersDanica Fine is a Senior Developer Advocate at Confluent where she helps others get the most out of their event-driven pipelines. In her previous role as a software engineer on a streaming infrastructure team, she predominantly worked on Kafka Streams- and Kafka Connect-based projects. She can be found on Twitter, tweeting about tech, plants, and baking @TheDanicaFine.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/board-of-directors","text":"Conselho de Administra\u00e7\u00e3o da Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLideran\u00e7aCom uma vis\u00e3o de longo prazo, nossa equipe de lideran\u00e7a conta com d\u00e9cadas de experi\u00eancia para tra\u00e7ar um novo curso para dados e IAConhe\u00e7a nossa equipeEquipe executivaEquipe fundadoraConselho de Administra\u00e7\u00e3oIon StoicaCofundador e presidente-executivoBen HorowitzCofundador da Andreessen HorowitzElena DonioMembro do conselhoAli GhodsiCofundador e diretor executivoPete SonsiniParceiro geral na New Enterprise AssociatesJonathan ChadwickMembro do conselhoMatei ZahariaCofundador e tecn\u00f3logo-chefeScott ShenkerProfessor de Ci\u00eancia da Computa\u00e7\u00e3o na UC BerkeleyProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
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{"source":"https:\/\/www.databricks.com\/it\/dataaisummit\/?itm_data=menu-learn-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sarah-pollitt\/#","text":"Sarah Pollitt - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSarah PollittGroup Product Manager at MatillionBack to speakersSarah has over 10 years experience in data management and software delivery in a wide variety of major industries. \nSarah is passionate about supporting people make their lives easier with data, supporting women in tech and ensuring equity in the Product and Technology spaceLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/blog\/category\/company","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sai-ravuru","text":"Sai Ravuru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSai RavuruSenior Manager of Data Science & Analytics at JetBlueBack to speakersSai Ravuru is the Senior Manager of Data Science & Analytics at JetBlue architecting the AI & ML strategy for all of JetBlue. He manages a portfolio of Operations Data Science, Commercial Data Science, AI & ML engineering and Business Intelligence teams & products.\nSai Ravuru is a seasoned Data Scientist and aviation executive with over a decade of experience in empowering efficiencies in aviation using AI & ML. He started his career simulating hypersonic missiles on supercomputing clusters.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tanmay-kumar","text":"Tanmay Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTanmay KumarSenior Manager at Deloitte Consulting LLPBack to speakersImpact-driven leader with experience in engaging and maintaining C-level relationships and delivering large business transformation programs with focus on enterprise data\/cloud strategy, data management and modernization for Banking, Technology and Media clients.\nSenior program executive with extensive experience in leading cross-discipline functional and data engineering\/science teams for project scoping, requirements and delivery, defining technology roadmap, developing success strategy, fostering vendor partnerships, driving process improvement, executive communication, agile\/scrum techniques, implementing project governance and staff recruitment.\nTechnical expertise in designing cloud-based data architectures, implementing data warehouses, data lakes, integration pipelines, business intelligence, visualization & data science platforms across functions like Sales, Marketing, Risk and Finance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/session_eu20\/scaling-security-for-agile-organizations-with-data-analytics-by-bp","text":"AboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLCDatabricks - YouTube"}
{"source":"https:\/\/www.databricks.com\/br\/product\/open-source","text":"C\u00f3digo aberto | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWC\u00f3digo abertoOs engenheiros da Databricks est\u00e3o por tr\u00e1s de v\u00e1rias das tecnologias de dados de c\u00f3digo aberto mais populares do mundoParticipe de um MeetupNossos projetos de c\u00f3digo aberto mais popularesApache Spark\u2122O Apache Spark \u00e9 um mecanismo unificado para executar workloads de data engineering, data science e ML.\nO que \u00e9 o Apache Spark?\nCompara\u00e7\u00e3o entre Spark e Databricks\nAcesse spark.apache.org\nDelta LakeO Delta Lake permite que voc\u00ea crie uma arquitetura de lakehouse em sistemas de armazenamento como AWS S3, ADLS, GCS e HDFS.\nSaiba mais sobre o Delta Lake\nAcesse delta.io\nTech Talks: Introdu\u00e7\u00e3o ao Delta Lake\nMLflowO MLflow gerencia o ciclo de vida do ML, incluindo experimenta\u00e7\u00e3o, reprodutibilidade, deployment e um registro de modelo central.\nMLflow gerenciado na Databricks\nAcesse mlflow.org\nTech Talks: Gerenciar o ciclo de vida do ML\nRedashO Redash permite que qualquer pessoa aproveite o SQL para explorar, consultar, visualizar e compartilhar dados de fontes de small e big data.\nAcesse o Redash no GitHub\nDelta SharingO Delta Sharing \u00e9 o primeiro protocolo aberto para compartilhamento seguro de dados, que facilita a troca de dados com outras organiza\u00e7\u00f5es.\nAcesse o Delta Sharing\nDatabricks \u00e9 compat\u00edvel com estas tecnologias de c\u00f3digo aberto populares adicionaisTensorFlowADatabricks \u00e9 compat\u00edvel com o TensorFlow, uma biblioteca de refer\u00eancia para deep learning e computa\u00e7\u00e3o geral de clusters\nTensorFlow na Databricks\nPyTorch\u2122O Facebook, o criador do PyTorch, e a Databricks colaboraram em integra\u00e7\u00f5es conjuntas\nPyTorch na Databricks\nKeras\u2122Uma API de deep learning escrita em Python, executada sobre o TensorFlow. Est\u00e1 dispon\u00edvel no Databricks Runtime para ML\nKeras no Databricks\nRStudioUm conjunto de ferramentas de c\u00f3digo aberto para data science colaborativa usando R \u200b\nPrograma\u00e7\u00e3o R para big data\nscikit-learnPacote Python amplamente usado em machine learning baseado em NumPy, SciPy e Matplotlib\u200b\u200b\nScikit-learn na Databricks\nXGBoostUma biblioteca de aumento de gradiente distribu\u00edda vinculada a linguagens como Python, R e C++XGBoost no DatabricksTerraformO HashiCorp Terraform \u00e9 uma ferramenta popular de c\u00f3digo aberto para criar uma infraestrutura de nuvem segura e previs\u00edvel que abrange v\u00e1rios provedores de servi\u00e7os de nuvem. O provedor do Databricks Terraform fornece aos clientes uma ferramenta flex\u00edvel e poderosa para gerenciar todos os seus workspaces Databricks e o restante de sua infraestrutura. O uso do Terraform tamb\u00e9m incentiva os clientes a adotarem as pr\u00e1ticas recomendadas com infraestrutura como c\u00f3digo (IaC)Terraform na DatabricksTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brooke-wenig","text":"Brooke Wenig - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrooke WenigDirector, Machine Learning Practice at DatabricksBack to speakersBrooke Wenig is a Machine Learning Practice Lead at Databricks. She leads a team of data scientists who develop large-scale machine learning pipelines for customers, as well as teach courses on distributed machine learning best practices. She is a co-author of Learning Spark, 2nd Edition, co-instructor of the Distributed Computing with Spark SQL Coursera course, and co-host of the Data Brew podcast. She received an MS in Computer Science from UCLA with a focus on distributed machine learning and a BA in Chinese. She enjoys cycling and taking her dog, Bingo, to the beach.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kieran-taylor\/#","text":"Kieran Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKieran TaylorSenior Software Engineer II at InstacartBack to speakersKieran Taylor is a senior software engineer with Instacart. He works on the Data Platform team to build the data infrastructure used by data analysts, scientists and pipeline engineers that powers Instacart. Kieran is passionate about functional programming, data intensive applications and the unbounded use cases that are still to be unlocked in the space. Outside of work you can find Kieran travelling, playing tennis or beach volleyball in Santa Monica.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=MachineLearning-FooterCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/srinivasa-kanamatha\/#","text":"Srinivasa Kanamatha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSrinivasa KanamathaSenior Manager at BlackBerryBack to speakersSrinivasa have worked in the cybersecurity industry for over 13 years. His primary focus have always been in Data Engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators?industry=Manufacturing","text":"Databricks Solution Accelerators - Deliver Data & AI Value Faster - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIndustry SolutionsDeliver the data and AI-driven outcomes that matter most \u2014 fasterStart your free trialDatabricks Solution AcceleratorsSave hours of discovery, design, development and testing with Databricks Solution Accelerators. Our purpose-built guides \u2014 fully functional notebooks and best practices \u2014 speed up results across your most common and high-impact use cases. Go from idea to proof of concept (PoC) in as little as two weeks.\n\u00a0\nStart using Solution Accelerators with your free Databricks trial or your existing account.\n\u00a0\nStart your free trial todayBrowse AcceleratorssearchHide filtersIndustrySortDatabricksToxicity Detection in GamingfeaturedDatabricksOn-Shelf AvailabilityfeaturedDatabricksFine-Grained Demand Forecastingfeatured\ud83d\udd25DatabricksAutomated PHI RemovalfeaturednewDatabricksAbstracting Real-World Data for OncologyDatabricksAnti-Money LaunderingDatabricksCohort Building with Knowledge GraphsDatabricksComputer Vision FoundationsDatabricksCustomer Entity ResolutionDatabricksCustomer Lifetime Value\ud83d\udd25DatabricksCustomer SegmentationSplunkCyber Analytics (Splunk Connector)DatabricksDetecting Adverse Drug EventsnewDatabricksDigital Pathology Image AnalysisDatabricksDigital TwinsDatabricksESG Performance Analytics\ud83d\udd25DatabricksFHIR Interoperability with dbigniteDatabricksFuzzy Item MatchingDatabricksGenome-Wide Association StudiesDatabricksGeospatial Analytics to Identify FraudDatabricksHL7v2 Interoperability With SmolderDatabricksMedia Mix Modeling (MMM)DatabricksMedicare Risk AdjustmentDatabricksMerchant ClassificationDatabricksModern Investment PlatformDatabricksMulti-Touch AttributionDatabricksOptimized Order PickingDatabricksOverall Equipment EffectivenessDatabricksPredictive Maintenance (IoT)DatabricksPrice TransparencynewDatabricksProduct Quality InspectionDatabricksPropensity ScoringnewDatabricksR&D Optimization with Knowledge GraphsnewDatabricksReal-Time Bidding OptimizationDatabricksReal-Time Financial Fraud PreventionDatabricksReal-Time Point-of-Sale AnalyticsnewDatabricksReal-world EvidenceDatabricksRecommendation EngineDatabricksRegulatory ReportingDatabricksReputation RiskDatabricksRetention ManagementDatabricksRisk ManagementDatabricksSafety StockDatabricksSales Forecasting & Ad Attribution\ud83d\udd25DatabricksScalable Route GenerationDatabricksSocial Determinants of HealthDatabricksSubscriber Churn PredictionDatabricksSupply Chain Distribution OptimizationDatabricksSurvival Analysis & Lifetime ValueDatabricksThreat Detection with DNSDatabricksVideo Quality of ExperienceFAQHow much do Solution Accelerators cost?Solution Accelerators are available to any Databricks customer free of charge.Do I need to be a Databricks customer to use a Solution Accelerator?You can implement Solution Accelerators with a free Databricks trial or with your existing Databricks account.What can I expect from a Solution Accelerator?Solution Accelerators are designed to help you save hours of discovery, design, development and testing. Our goal is to jump-start your data and AI use cases by providing the right resources (notebooks, proven patterns and best practices). You can expect to go from idea to proof of concept (PoC) in as little as two weeks.See how actual customers use DatabricksExplore Customer StoriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/technology-partner-program","text":"Databricks \uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\u0000\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\uc81c\ud488\uc744 \uc0ac\uc6a9\ud560 \uc900\ube44\uac00 \ub41c\n\uc218\ucc9c \uba85\uc758 Databricks \uace0\uac1d\uacfc \uc5f0\uacb0\uc9c0\uae08 \uc2e0\uccad\ud558\uae30Databricks\ub294 \uc5c5\uacc4 \ucd5c\uace0\uc758 \ub370\uc774\ud130 \ubc0f AI \uc81c\ud488\uacfc \ud1b5\ud569\ub418\uace0, \uc774\ub97c \uac15\ud654\ud569\ub2c8\ub2e4. \ud30c\ud2b8\ub108\uc5d0\uac8c\ub294 \uc0c8\ub85c\uc6b4 \uace0\uac1d\uc744 \ud655\ubcf4\ud558\uace0 \ube44\uc988\ub2c8\uc2a4\ub97c \uc131\uc7a5\uc2dc\ud0a4\ub294 \ub370 \ud544\uc694\ud55c \uae30\uc220 \ubc0f \uc2dc\uc7a5 \uc9c4\ucd9c \uc9c0\uc6d0\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\uae30\uc220 \ud30c\ud2b8\ub108 \ud61c\ud0dd\ud310\ub9e4 \uc778\uc13c\ud2f0\ube0c\uc81c\ud488 \ud310\ub9e4\ub97c \ub3d5\uae30 \uc704\ud55c Databricks \ud544\ub4dc \uc870\uc9c1\uc758 \uc778\uc13c\ud2f0\ube0c\uace0\uac1d \uc561\uc138\uc2a4Databricks Partner Connect\ub97c \ud1b5\ud574 \uc0c8\ub85c\uc6b4 \uace0\uac1d \uc9c1\uc811 \ud655\ubcf4\uc790\uc138\ud788\ub9c8\ucf00\ud305 \uc9c0\uc6d0\ub9c8\ucf00\ud305 \ud22c\uc790\uc5d0 \uc561\uc138\uc2a4\ud558\uc5ec \ub3c4\ub2ec \ubc94\uc704 \ud655\ub300\uc81c\ud488 \ubc0f R&D \ud300 \uc561\uc138\uc2a4Databricks \uc81c\ud488, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubc0f \uc9c0\uc6d0 \uc9c1\uc6d0 \uc561\uc138\uc2a4\ubb34\ub8cc \uc0cc\ub4dc\ubc15\uc2a4 \ud658\uacbd\ubb34\ub8cc \uc0cc\ub4dc\ubc15\uc2a4 \ud658\uacbd\uc5d0\uc11c \uad6c\ucd95 \ubc0f \ud14c\uc2a4\ud2b8\uacf5\ub3d9 \ub9c8\ucf00\ud305 \ud504\ub85c\uadf8\ub7a8Databricks\uc640\uc758 \uacf5\ub3d9 \ub9c8\ucf00\ud305 \ud504\ub85c\uadf8\ub7a8\uc5d0 \ucc38\uc5ec\uc5f0\uacb0\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uc9c0\uae08 \uc2e0\uccad\ud558\uae30\ud30c\ud2b8\ub108 \ucc3e\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \u0000\uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andria-fuquen\/#","text":"Andria Fuquen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndria FuquenTechnical Program Manager at ImmutaBack to speakersAndria Fuquen is a Technical Program Manager at Immuta, a data security focused company. She has over 7 years of experience across engineering, data systems, governance and security. At Immuta, her role is to help customers achieve success through their onboarding phase and become empowered to further streamline their data security practices. Ms. Fuquen is a strong advocate for diversity and supporting women in tech, proudly representing the Latina community. When not working, Andria enjoys spinning vinyl records and perfecting her salsa moves.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/balaji-ramanujam\/#","text":"Balaji Ramanujam - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBalaji RamanujamAVP - Senior Principal Technology Architect at InfosysBack to speakersBalaji is Head of Industry Architecture - Data and AI North America (USA & Canada), with 23 years of experience in Information Technology and experience in Healthcare \/ Life sciences , Banking & Retail industry. He is a Data Technologist with flair and passion for solving complex data problems, helping business build connections and eco-systems (Next generation data trend). He is architecture Leader for North America on Cloud and Data Management , Data engineering and ML engineering technologies with focus on creating Business Platforms and creating industry solutions.\nHe has strong skills in Cloud Data Architecture, Enterprise ML, Data Modeling, design, development and implementation of ETL & BI Analytics solutions. Worked on large programs involving complex business requirements and different business teams. He has played key roles in initiating and enabling new projects. Technical Architect \/Consultant \/ advisor to multiple BI Projects - providing inputs from solution architecture to data model to reporting layer - to enhance the efficiency of a solution.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Clientes da\u2028 Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWClientes da DatabricksDescubra como empresas inovadoras em todos os setores usam a Databricks Lakehouse PlatformHist\u00f3rias em destaque\n\n\nHist\u00f3ria de cliente\n\nCria\u00e7\u00e3o de um neg\u00f3cio omnicanal eficiente do ponto de vista operacional\nOs clientes brasileiros contam com a Via (antiga Via Varejo) para uma ampla sele\u00e7\u00e3o de produtos e servi\u00e7os, como eletr\u00f4nicos de consumo, eletrodom\u00e9sticos, m\u00f3veis e cart\u00f5es de cr\u00e9dito.\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nTransformando pagamentos m\u00f3veis em um superaplicativo financeiro\nO PicPay tem a miss\u00e3o de se tornar o primeiro superaplicativo de tecnologia financeira do Brasil, oferecendo uma variedade de servi\u00e7os, como cart\u00f5es de cr\u00e9dito, carteira digital, pagamentos P2P, com\u00e9rcio eletr\u00f4nico e rede social.\n\nLeia mais\n\n\nHist\u00f3ria de cliente\n\nShell inova com solu\u00e7\u00f5es de energia para um mundo mais limpo\nA Databricks Lakehouse ajuda a democratizar os dados e modernizar as opera\u00e7\u00f5es globalmente\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nReinventando o mobile banking com ML\nComo um dos maiores bancos internacionais, o HSBC apresenta uma nova forma de gerenciar pagamentos digitais em dispositivos m\u00f3veis.\n\nLeia mais\n\n\nHist\u00f3ria de cliente\n\nABN AMRO transforma o setor banc\u00e1rio em escala global\nABN AMRO coloca os dados e Al em a\u00e7\u00e3o com a Databricks Lakehouse\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nExperi\u00eancias de jogo avan\u00e7adas que chamam a aten\u00e7\u00e3o dos jogadores\nA SEGA Europe encanta gamers no mundo todo h\u00e1 d\u00e9cadas com jogos ic\u00f4nicos, como Sonic the Hedgehog, e novos favoritos, como Warhammer.\u00a0\n\nLeia maisExplorar todos os clientesO efeito da equipe de dadosAs equipes de dados s\u00e3o as for\u00e7as unidas que resolvem os problemas mais dif\u00edceis do mundo.Veja como \u2192A pr\u00f3xima hist\u00f3ria de sucesso pode ser suaEntre em contatoRecursosHist\u00f3ria de clienteDescubra como a Databricks permite que a Cond\u00e9 Nast ofere\u00e7a conte\u00fado personalizado aos seus clientes.Saiba maisHist\u00f3ria de clienteSaiba como a Apple e o Disney+ obtiveram sucesso unindo an\u00e1lises e IASaiba maisHist\u00f3ria de clienteSlawek Kierner, vice-presidente s\u00eanior e diretor de dados e an\u00e1lises da Humana, fala sobre o papel dos dados e da IA na equidade da sa\u00fadeAssistirTudo pronto para come\u00e7ar?Experimente gratuitamenteEntre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/product\/managed-mlflow?itm_data=product-link-managedMLFlow","text":"Managed MLflow | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWManaged MLflowManaging the complete machine learning lifecycleTry for freeSchedule a demoWhat is Managed MLflow?Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete machine learning lifecycle with enterprise reliability, security and scale. The latest update to MLflow is packed with innovative features that broaden its ability to manage and deploy large language models (LLMs). This enhanced LLM support is delivered through three new model flavors: Hugging Face Transformers, OpenAI functions and LangChain.BenefitsModel developmentAccelerate and simplify machine learning lifecycle management with a standardized framework for developing production-ready ML models. With managed MLflow Recipes, you can bootstrap ML projects, perform rapid iteration with ease and ship high-quality models to production at scale.Experiment trackingRun experiments with any ML library, framework or language, and automatically keep track of parameters, metrics, code and models from each experiment. By using MLflow on Databricks, you can securely share, manage and compare experiment results along with corresponding artifacts and code versions \u2014 thanks to built-in integrations with the Databricks Workspace and notebooks.Model managementUse one central place to discover and share ML models, collaborate on moving them from experimentation to online testing and production, integrate with approval and governance workflows and CI\/CD pipelines, and monitor ML deployments and their performance. The MLflow Model Registry facilitates sharing of expertise and knowledge, and helps you stay in control.Model deploymentQuickly deploy production models for batch inference on Apache Spark\u2122 or as REST APIs using built-in integration with Docker containers, Azure ML or Amazon SageMaker. With Managed MLflow on Databricks, you can operationalize and monitor production models using Databricks Jobs Scheduler and auto-managed Clusters to scale based on the business needs.FeaturesMLflow Model Registry\nCENTRAL REPOSITORY: Register MLflow models with the MLflow Model Registry. A registered model has a unique name, version, stage, and other metadata.\nMODEL VERSIONING: Automatically keep track of versions for registered models when updated.\nMODEL STAGE: Assign preset or custom stages to each model version, like \u201cStaging\u201d and \u201cProduction\u201d to represent the lifecycle of a model.\nCI\/CD WORKFLOW INTEGRATION: Record stage transitions, request, review and approve changes as part of CI\/CD pipelines for better control and governance.\nMODEL STAGE TRANSITIONS: Record new registration events or changes as activities that automatically log users, changes, and additional metadata such as comments.\nMLflow Models\nMLFLOW MODELS: A standard format for packaging machine learning models that can be used in a variety of downstream tools \u2014 for example, real-time serving through a REST API or batch inference on Apache Spark.\nMODEL CUSTOMIZATION: Use Custom Python Models and Custom Flavors for models from an ML library that is not explicitly supported by MLflow\u2019s built-in flavors.\nBUILT-IN MODEL FLAVORS: MLflow provides several standard flavors that might be useful in your applications, like Python and R functions, Hugging Face, OpenAI and LangChain, PyTorch, Spark MLlib, TensorFlow, and ONNX.\nBUILT-IN DEPLOYMENT TOOLS: Quickly deploy on Databricks via Apache Spark UDF for a local machine, or several other production environments such as Microsoft Azure ML, Amazon SageMaker, and building Docker Images for Deployment.\nMLflow Recipes\nSIMPLIFIED PROJECT STARTUP: MLflow Recipes provides out-of-box connected components for building and deploying ML models.\nACCELERATED MODEL ITERATION: MLflow Recipes creates standardized, reusable steps for model iteration \u2014 making the process faster and less expensive.\nAUTOMATED TEAM HANDOFFS: Opinionated structure provides modularized production-ready code, enabling automatic handoff from experimentation to production.\nMLflow Projects\nMLFLOW PROJECTS: MLflow projects allow you to specify the software environment that is used to execute your code. MLflow currently supports the following project environments: Conda environment, Docker container environment, and system environment. Any Git repo or local directory can be treated as an MLflow project.\nREMOTE EXECUTION MODE: Run MLflow Projects from Git or local sources remotely on Databricks clusters using the Databricks CLI to quickly scale your code.\nMLflow Tracking\nMLFLOW TRACKING: Automatically log parameters, code versions, metrics, and artifacts for each run using Python, REST, R API, and Java API\nMLFLOW TRACKING SERVER: Get started quickly with a built-in tracking server to log all runs and experiments in one place. No configuration needed on Databricks.\nEXPERIMENT MANAGEMENT: Create, secure, organize, search, and visualize experiments from within the Workspace with access control and search queries.\nMLFLOW RUN SIDEBAR: Automatically track runs from within notebooks and capture a snapshot of your notebook for each run, so that you can always go back to previous versions of your code.\nLOGGING DATA WITH RUNS: Log parameters, data sets, metrics, artifacts and more as runs to local files, to a SQLAlchemy compatible database, or remotely to a tracking server.\nDELTA LAKE INTEGRATION: Track large-scale data sets that fed your models with Delta Lake snapshots.\nARTIFACT STORE: Store large files such as S3 buckets, shared NFS file system, and models in Amazon S3, Azure Blob Storage, Google Cloud Storage, SFTP server, NFS, and local file paths.\nSee our Product News from Azure Databricks and AWS to learn more about our latest features.Comparing MLflow offeringsHow it worksMLflow is a lightweight set of APIs and user interfaces that can be used with any ML framework throughout the Machine Learning workflow. It includes four components: MLflow Tracking, MLflow Projects, MLflow Models and MLflow Model RegistryMore about MLflowMLflow TrackingRecord and query experiments: code, data, config, and results.\nLearn moreMLflow ProjectsPackaging format for reproducible runs on any platform.\nLearn moreMLflow ModelsGeneral format for sending models to diverse deployment tools.\nLearn moreMLflow Model RegistryCentralized repository to collaboratively manage MLflow models throughout the full lifecycle.\nLearn moreManaged MLflow on DatabricksManaged MLflow on Databricks is a fully managed version of MLflow providing practitioners with reproducibility and experiment management across Databricks Notebooks, Jobs, and data stores, with the reliability, security, and scalability of the Databricks Lakehouse Platform.Read the docsLog your first run as an experimentExecute runs remotely as Databricks jobsDeploy a model for a batch interfaceResourcesBlogsDatabricks Extends MLflow Model Registry With Enterprise FeaturesHow to Display Model Metrics in Dashboards Using the MLflow Search APIAutomate Deployment and Testing With Databricks Notebook + MLflowIntroducing the MLflow Model RegistryA Guide to MLflow Talks at Spark + AI Summit 2019 EuropeProductionizing Machine Learning: From Deployment to Drift DetectionDetecting Bias With SHAPHyperparameter Tuning With MLflow, Apache Spark MLlib and HyperoptA Guide to MLflow Talks at Spark + AI Summit 2019MLflow On-Demand Webinar and FAQ Now AvailableIntroducing MLflow: An Open Source Machine Learning PlatformVideosComcast: How to Utilize MLflow and Kubernetes to Build an Enterprise ML PlatformGojek: Scaling Ride-Hailing With Machine Learning on MLflowShowtime: Data-Driven Transformation: Leveraging Big Data at Showtime With Apache SparkBest Practices for Hyperparameter Tuning With MLflowAdvanced Hyperparameter Optimization for Deep Learning With MLflowRStudio: Managing the Machine Learning Lifecycle With MLflow and RSplice Machine\u2019s Use of Apache Spark and MLflowKount: Moving a Fraud-Fighting Random Forest From scikit-learn to Spark With MLlibTutorialsDetecting Financial Fraud at Scale With Decision Trees and MLflow on DatabricksUsing Dynamic Time Warping and MLflow to Detect Sales Trends (Part 1)Using Dynamic Time Warping and MLflow to Detect Sales Trends (Part 2)How to Use MLflow to Experiment a Keras Network Model: Binary Classification for Movie ReviewsHow to Use MLflow, TensorFlow and Keras With PyCharmHow to Use MLflow to Reproduce Results and Retrain Saved Keras ML ModelsWebinarsAutoML Rapid, Simplified Machine Learning EveryoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningAutomated Hyperparameter Tuning, Scaling and Tracking on DatabricksWhat\u2019s New With MLflow? On-Demand Webinar and FAQs Now AvailableManaging the Complete Machine Learning Lifecycle: On-Demand Webinar Now AvailableUnderstanding MLflow: Ask the ExpertsMLOps Virtual EventeBooksStandardizing the Machine Learning LifecycleFour Real-Life Machine Learning Use CasesThe Big Book of Machine Learning Use CasesNotebooksMLflow Quick Start in PythonMLflow Quick Start in RMLflow Quick Start in ScalaFinancial Fraud Detection Using Decision Tree Machine Learning ModelsUsing Dynamic Time Warping and MLflow to Detect Sales Trends (dbc format)DocumentationTracking Training RunsSaving and Deploying ModelsReproducible RunsManaging ModelsReady to get started?Try Databricks for freeQuick Start GuideProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/data-pipelines","text":"Data Engineering | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWData EngineeringDezenas de milh\u00f5es de cargas de trabalho produtivas s\u00e3o executadas diariamente no DatabricksIntrodu\u00e7\u00e3oAssista \u00e0 demonstra\u00e7\u00e3o\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowIngira e transforme facilmente dados em batch e streaming na Plataforma Databricks Lakehouse. Orquestre fluxos de trabalho de produ\u00e7\u00e3o confi\u00e1veis enquanto a Databricks gerencia automaticamente sua infraestrutura em escala. Aumente a produtividade de suas equipes com testes de qualidade de dados integrados e suporte \u00e0s melhores pr\u00e1ticas de desenvolvimento de software.Unifique batch e streamingElimine silos em uma plataforma com uma API unificada para ingerir, transformar e processar dados em batch e streaming de forma incremental em escala.Foque em extrair valor dos dadosA Databricks gerencia automaticamente sua infraestrutura e os componentes operacionais de seus fluxos de trabalho de produ\u00e7\u00e3o para que voc\u00ea possa se concentrar no valor, n\u00e3o nas ferramentas.Conecte suas ferramentas de escolhaUma Plataforma Lakehouse aberta para se conectar e usar suas ferramentas preferidas de engenharia de dados para ingest\u00e3o de dados, ETL\/ELT e orquestra\u00e7\u00e3o.Conte com a Plataforma LakehouseA Plataforma Lakehouse fornece a melhor funda\u00e7\u00e3o para construir e compartilhar ativos de dados confi\u00e1veis que s\u00e3o governados centralmente, confi\u00e1veis e extremamente r\u00e1pidos.\"A Databricks est\u00e1 se tornando o recurso completo para todo o nosso trabalho de ETL. Quanto mais trabalhamos com a Plataforma Lakehouse, mais f\u00e1cil \u00e9 para os usu\u00e1rios e administradores.\"\u2014 Hillevi Crognale, gerente de engenharia da YipitDataComo funciona?Ingest\u00e3o simplificada de dadosProcessamento automatizado de ETLOrquestra\u00e7\u00e3o confi\u00e1vel de fluxos de trabalhoMonitoramento e observabilidade de ponta a pontaMotor de processamento de dados de \u00faltima gera\u00e7\u00e3oFunda\u00e7\u00e3o de governan\u00e7a, confiabilidade e desempenhoIngest\u00e3o simplificada de dadosConsuma dados em sua Plataforma Lakehouse e potencialize suas an\u00e1lises, IA e aplica\u00e7\u00f5es de streaming de um s\u00f3 lugar.\u00a0O Auto Loader processa de forma incremental e autom\u00e1tica os arquivos que chegam ao armazenamento de nuvem, sem a necessidade de gerenciar informa\u00e7\u00f5es de estado, em jobs programados ou cont\u00ednuos. Ele rastreia com efici\u00eancia novos arquivos (escalando para bilh\u00f5es) sem ter que list\u00e1-los em um diret\u00f3rio e tamb\u00e9m pode inferir automaticamente o esquema dos dados de origem e evolu\u00ed-lo conforme as mudan\u00e7as ao longo do tempo. O comando COPY INTO facilita para analistas operarem a ingest\u00e3o de arquivos em batch para o Delta Lake com SQL.\"Vimos um aumento de 40% na produtividade da engenharia de dados - reduzindo o tempo que leva para desenvolver novas id\u00e9ias de dias para minutos e aumentando a disponibilidade e a precis\u00e3o de nossos dados.\"\u2014 Shaun Pearce, diretor de tecnologia,\u00a0GoustoSaiba maisProcessamento automatizado de ETLUma vez ingeridos, os dados brutos precisam ser transformados para que fiquem prontos para an\u00e1lise e IA. A Databricks fornece poderosos recursos ETL para times de engenharia, ci\u00eancia e an\u00e1lise de dados com Delta Live Tables (DLT). DLT \u00e9 a primeira estrutura que utiliza uma abordagem declarativa simples para construir pipelines ETL e ML em batch ou streaming de dados, enquanto automatiza complexidades operacionais tais como gerenciamento de infraestrutura, orquestra\u00e7\u00e3o de tarefas, tratamento e recupera\u00e7\u00e3o de erros, e otimiza\u00e7\u00e3o de desempenho. Com as DLTs, a equipe de engenharia tamb\u00e9m pode tratar seus dados como c\u00f3digo e aplicar as melhores pr\u00e1ticas de engenharia de software como testes, monitoramento e documenta\u00e7\u00e3o para criar pipelines confi\u00e1veis em escala.Saiba maisOrquestra\u00e7\u00e3o de fluxos de trabalho confi\u00e1velOs fluxos de trabalho Databricks s\u00e3o o servi\u00e7o de orquestra\u00e7\u00e3o totalmente gerenciado para todos os seus dados, an\u00e1lises e IA nativos da sua Plataforma Lakehouse. Organize cargas de trabalho diversas em todo o ciclo de vida, incluindo Delta Live Tables e Jobs para SQL, Spark, notebooks, dbt, modelos de ML e muito mais. A integra\u00e7\u00e3o profunda com a Plataforma Lakehouse garante que voc\u00ea crie e execute cargas de trabalho de produ\u00e7\u00e3o confi\u00e1veis em qualquer nuvem e, ao mesmo tempo, forne\u00e7a monitoramento profundo e centralizado com simplicidade para usu\u00e1rios finais.\u201cNossa miss\u00e3o \u00e9 transformar a forma como alimentamos o planeta. Nossos clientes do setor de energia precisam de dados, consultoria e pesquisas para alcan\u00e7ar essa transforma\u00e7\u00e3o. O Databricks Workflows nos d\u00e1 a velocidade e a flexibilidade para fornecer os insights de que nossos clientes precisam.\u201d\u2014 Yanyan Wu, vice-presidente de dados,\u00a0Wood MackenzieSaiba maisMonitoramento e observabilidade de ponta a pontaA Plataforma Lakehouse oferece visibilidade em todo o ciclo de vida de dados e IA para que equipes de engenharia de dados e de opera\u00e7\u00f5es possam ver a integridade de seus fluxos de trabalho de produ\u00e7\u00e3o em tempo real, gerenciar a qualidade dos dados e entender tend\u00eancias hist\u00f3ricas. Nos Fluxos de trabalho da Databricks, voc\u00ea pode acessar gr\u00e1ficos de fluxo de dados e pain\u00e9is que rastreiam a integridade e o desempenho de seus jobs produ\u00e7\u00e3o e pipelines de Delta Live Tables. Os logs de eventos tamb\u00e9m s\u00e3o expostos como tabelas do Delta Lake para que voc\u00ea possa monitorar e visualizar m\u00e9tricas de desempenho, qualidade dos dados e confiabilidade de qualquer \u00e2ngulo.Motor de processamento de dados de \u00faltima gera\u00e7\u00e3oA engenharia de dados da Databricks \u00e9 alimentada pelo Photon, o motor de \u00faltima gera\u00e7\u00e3o compat\u00edvel com as APIs do Apache Spark, oferecendo pre\u00e7o\/desempenho recordes enquanto escala automaticamente para milhares de n\u00f3s.\u00a0O Spark Structured Streaming oferece uma API unificada para processamento em batch e stream, facilitando a ado\u00e7\u00e3o do streaming no lakehouse sem alterar o c\u00f3digo ou aprender novas habilidades.Saiba maisGovernan\u00e7a, confiabilidade e desempenho de dados de \u00faltima gera\u00e7\u00e3oA engenharia de dados na Databricks significa que voc\u00ea se beneficia dos componentes fundamentais da\u00a0Plataforma Lakehouse\u00a0\u2014 Unity Catalog e Delta Lake. Seus dados brutos s\u00e3o otimizados com o\u00a0Delta Lake, um formato de armazenamento de c\u00f3digo aberto que fornece confiabilidade por meio de transa\u00e7\u00f5es ACID e tratamento escal\u00e1vel de metadados com desempenho extremamente r\u00e1pido. Isso se combina com o\u00a0Unity Catalog\u00a0para oferecer uma governan\u00e7a granular para todos os seus dados e ativos de IA, simplificando a forma como voc\u00ea governa, com um modelo consistente para descobrir, acessar e compartilhar dados entre as nuvens. O Unity Catalog tamb\u00e9m fornece suporte nativo para\u00a0Delta Sharing, o primeiro protocolo aberto da ind\u00fastria para compartilhamento de dados f\u00e1cil e seguro com outras organiza\u00e7\u00f5es.Migre para a DatabricksN\u00e3o aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA.Migre para a DatabricksIntegra\u00e7\u00f5esOfere\u00e7a o m\u00e1ximo de flexibilidade \u00e0s suas equipes de dados \u2014 aproveite o Partner Connect e um ecossistema de parceiros de tecnologia para se integrar perfeitamente a ferramentas populares de engenharia de dados. Por exemplo, voc\u00ea pode ingerir dados cr\u00edticos de neg\u00f3cios com o Fivetran, transform\u00e1-los no lugar com dbt e orquestrar seus pipelines com o Apache Airflow.Ingest\u00e3o de dados e ETL+ qualquer outro cliente compat\u00edvel com Apache Spark\u2122Hist\u00f3ria de clienteDescubra maisDelta LakeFluxos de trabalhoDelta Live TablesDelta SharingConte\u00fado relacionado\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre os benef\u00edcios da data engineering no Databricks.\nExplorar recursose-booksBuilding the Data Lakehouse, de Bill Inmon, pai do data warehouseData, Analytics and AI governanceGerenciamento de dados 101e-book: The Big Book of Data EngineeringExplore a nova solu\u00e7\u00e3o de Delta SharingLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosGerencie a transforma\u00e7\u00e3o de dados com Delta Live TablesS\u00e9rie de webinars sobre ingest\u00e3o de dados sem complica\u00e7\u00f5esData + AI Summit 2022Modernize seu data warehouseBlogsAnunciando disponibilidade geral de Delta Live Tables (DLT) da DatabricksApresentando os fluxos de trabalho da DatabricksUma vis\u00e3o geral de todos os novos recursos estruturados de streaming desenvolvidos em 2021 para Databricks e Apache Spark10 recursos poderosos para simplificar o gerenciamento de dados semiestruturados no Databricks LakehouseTudo pronto para come\u00e7ar?Experimente gratuitamenteJunte-se \u00e0 comunidadeAWSAzureGCPProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leena-dalvi","text":"Leena Dalvi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeena DalviAssistant Vice President, Enterprise Data & Analytics at Navy Federal Credit UnionBack to speakersLeena is an exceptionally energetic and passionate Data Transformation and Governance leader with over 20 years of strategic and hands-on Leadership and Data Management experience in the Financial Services industry. She is a results-oriented leader and visionary with a passion for data governance who can think strategically and act as a change agent to transform an organization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ricardo-portilla\/#","text":"Ricardo Portilla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRicardo PortillaPrincipal Solution Architect at DatabricksBack to speakersRicardo has 12+ years of experience with Financial Services customers bringing use cases to production. He has designed and consulted on solutions architecture with dozens of customers from Capital Markets to Banking and Wealth Management. His previous work was at FINRA where he moved FINRA mission-critical workloads from on-prem warehouses to the cloud and established a machine learning practice for financial fraudLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/diversity-and-inclusion","text":"Diversity and Inclusion | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe future of data is open to allDiversity, Equity and Inclusion at DatabricksDriven by data. Powered by people.We\u2019re on a mission to diversify big data \u2014 starting with our team. We believe different backgrounds, experiences, perspectives, insights and skills fuel innovation and deepen our connection to one another and our customers. We strive to cultivate a culture of belonging where everyone is empowered to do the best work of their careers. From ensuring equal pay for equal work to building programming that celebrates, educates and uplifts our team, Diversity, Equity and Inclusion (DEI) is woven into everything we do.Fair Pay Workplace Certified\nWe\u2019re proud to be one of the first six organizations certified by\u00a0Fair Pay Workplace. As part of our efforts to achieve pay parity, Databricks underwent a rigorous evaluation of our pay data and practices and committed to staying accountable through ongoing pay equity analyses.\nGaingels and Flucas Ventures\nOur commitment to diversity, equity and inclusion encompasses our entire team \u2014\u00a0from the people who work with us to the people who invest in us. That\u2019s why we\u2019re proud to partner with an array of world-class investors, including\u00a0Gaingels\u00a0and\u00a0Flucas Ventures, which focus on funding companies that demonstrate a deep commitment to DEI.\n\u201cWe know that the more data we have, the better our insights. The same is true of diversity and inclusion \u2014 Databricks thrives by including the widest possible diversity of backgrounds, experiences and viewpoints.\u201d\u2014 Ali Ghodsi, Co-founder and CEO, DatabricksOur communitiesWe believe empowering our employees is the key to unlocking our full potential. Our vibrant Employee Resource Groups (ERGs) are employee-led collectives that play a critical role in creating an inclusive and supportive environment at Databricks. These diverse communities of employees and allies create space for connection and celebration and bring awareness to meaningful issues.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\nOur experiences\u201cAt Databricks, I build teams that I would want to belong to. That means having the safety to be my authentic self and providing that same comfort zone to everyone around me. The impact of that care we show for one another and our dedication to inclusion is huge for our entire community.\u201d\u2014 Stacy Kerkela, Director of EngineeringRead more\u201cHaving a LatinX Network at Databricks makes me feel a stronger sense of community \u2013 an open community \u2013 because at Databricks, our Employee Resource Groups welcome and educate all people, regardless of their background.\u201d\u2014 Miguel Peralvo, Senior Solutions ArchitectRead more\u201cMany companies are focused on increasing gender diversity, but it\u2019s great to be part of a company that is visibly taking action to help move the needle.\u201d\u2014 Allie Emrich, Program Management, ProductRead moreInclusion in actionReportPartnerships With ColorStack and Rewriting the CodeOur University Recruiting team partners with\u00a0ColorStack\u00a0and\u00a0Rewriting the Code\u00a0to help more women as well as Black and LatinX students pursue a career in technology.\nRead moreReportWomen in Tech Mentorship ProgramAt Databricks, we recognize the importance of offering professional growth and advancement opportunities for historically underrepresented communities.Read moreReport2021 InHerSight AwardWe\u2019re excited to be featured among the best computer software workplaces for women, according to women. Learn more by visiting our InHerSight profile.Read moreLet\u2019s build the future of data, togetherWe\u2019re on a mission to simplify and democratize data and AI \u2014 and we can\u2019t do it without you.Explore opportunitiesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/culture","text":"How we work | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHow we workOur culture principles unite us and guide everything we doSee open jobs OverviewCultureBenefitsDiversityStudents & new gradsWe are customer obsessedThe customer is at the center of everything we do. What\u2019s best for the customer is best for Databricks.We raise the barEvery day is an opportunity for us to do even better \u2014 as team members and as a company.We are truth seekingWe make our decisions based on data, and we adapt as it changes.We operate from first principlesFirst principles thinking drives our innovation and leadership. To build lasting impact, we start with why.We bias for actionSpeed is critical. We debate, plan, execute \u2014 and iterate \u2014 with urgency.We put the company firstWe do what\u2019s best for the company, which ultimately incorporates all our culture principles.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maggie-davis","text":"Maggie Davis - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaggie DavisPrincipal, Data Engineering at SlalomBack to speakersMaggie Davis brings 10+ years of strong experience in distributed data engineering, cloud architecture, and devops practices. She most recently worked with clients on developing a large-scale lakehouse to master customer data using ML as well as an automated package destruction tracking solution to identify covid-19 vaccine distribution issues on Databricks. Maggie currently is a Principal of Data Engineering at Slalom Consulting.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-powell\/#","text":"Michael Powell - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious Diseases at California Department of Public Health (CDPH)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/industries\/retail-industry-solutions","text":"\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u696d\u754c\u5411\u3051\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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|\u5348\u524d8\u6642(\u592a\u5e73\u6d0b\u6a19\u6e96\u6642)\n\u00a0\n\u88fd\u9020\u696d\u306e\u305f\u3081\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u767a\u898b\u3059\u308b\n\u30b3\u30fc\u30cb\u30f3\u30b0\u304c\u3001\u624b\u4f5c\u696d\u306b\u3088\u308b\u691c\u67fb\u3092\u6700\u5c0f\u9650\u306b\u6291\u3048\u3001\u8f38\u9001\u30b3\u30b9\u30c8\u3092\u524a\u6e1b\u3057\u3001\u9867\u5ba2\u6e80\u8db3\u5ea6\u3092\u9ad8\u3081\u308b\u91cd\u8981\u306a\u610f\u601d\u6c7a\u5b9a\u3092\u3069\u306e\u3088\u3046\u306b\u884c\u3063\u3066\u3044\u308b\u304b\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u4eca\u3059\u3050\u767b\u9332\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeacons2023\u5e746\u670826\u65e5\uff5e29\u65e5\n\n\u76f4\u63a5\u53c2\u52a0\u3059\u308b\u304b\u3001\u57fa\u8abf\u8b1b\u6f14\u306e\u30e9\u30a4\u30d6\u30b9\u30c8\u30ea\u30fc\u30e0\u306b\u53c2\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3054\u767b\u9332\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29REGISTER NOW\u300c\u30ea\u30c6\u30fc\u30eb\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u300d\u306e\u6d3b\u7528\u30ab\u30b9\u30bf\u30de\u30fc\u30b8\u30e3\u30fc\u30cb\u30fc\u306e\u3042\u3089\u3086\u308b\u6bb5\u968e\u306b\u304a\u3051\u308b\u6210\u679c\u3092\u6700\u5927\u5316\u3059\u308b\u5c0f\u58f2\u696d\u5411\u3051\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306e\u7d71\u5408\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3054\u767b\u9332\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u9ad8\u6027\u80fd\u3001\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3001\u4f4e\u30b3\u30b9\u30c8\u30ea\u30c6\u30fc\u30eb\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30b7\u30a7\u30a2\u30ea\u30f3\u30b0\u3068\u30ac\u30d0\u30ca\u30f3\u30b9\u6a5f\u80fd\u3092\u7d44\u307f\u8fbc\u3093\u3067\u30c7\u30fc\u30bf\u3068 AI 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\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u306f\u3001\u6210\u679c\u5275\u51fa\u3092\u52a0\u901f\u3059\u308b\u30d5\u30eb\u6a5f\u80fd\u306e Notebook 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POS \u5206\u6790\u8907\u6570\u5e97\u8217\u306e\u5728\u5eab\u3092\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u8a08\u7b97\u3057\u3001\u5c0f\u58f2\u5e97\u306e\u30de\u30fc\u30b8\u30f3\u3092\u6539\u5584\n\u3042\u3089\u3086\u308b\u7a2e\u985e\u306e POS \u30c7\u30fc\u30bf\u3092\u8fc5\u901f\u306b\u5927\u898f\u6a21\u306b\u53d6\u308a\u8fbc\u307f\u3001\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306e\u30a4\u30f3\u30b5\u30a4\u30c8\u3092\u5c0e\u304d\u51fa\u3059\u3053\u3068\u3067\u3001\u5e97\u8217\u306b\u304a\u3051\u308b\u7dca\u6025\u306e\u60c5\u5831\u30cb\u30fc\u30ba\u306b\u5bfe\u5fdc\u3057\u307e\u3059\u3002\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u5c0f\u58f2\u696d\u5411\u3051\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30fc\u3092\u898b\u308bDatabricks 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\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u9700\u8981\u4e88\u6e2c\u3001\u88dc\u5145\u3001\u8abf\u9054\u3001\u4fa1\u683c\u3001\u30d7\u30ed\u30e2\u30fc\u30b7\u30e7\u30f3\u30b5\u30fc\u30d3\u30b9\u306b\u95a2\u3059\u308b\u8ab2\u984c\u3092\u89e3\u6c7a\u3059\u308b\u3002\u8a73\u3057\u304f\u898b\u308bBrickbuilder \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u898b\u308b\u300c\u4ee5\u524d\u306f\u975e\u5e38\u306b\u56f0\u96e3\u3060\u3063\u305f\u3001\u30aa\u30f3\u30e9\u30a4\u30f3\u3068\u30aa\u30d5\u30e9\u30a4\u30f3\u306e\u8cfc\u8cb7\u60c5\u5831\u3092\u304a\u5ba2\u3055\u307e\u30ec\u30d9\u30eb\u3067\u7d44\u307f\u5408\u308f\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u3053\u306e\u30aa\u30e0\u30cb\u30c1\u30e3\u30cd\u30eb\u30d3\u30e5\u30fc\u306b\u3088\u308a\u3001\u3088\u308a\u5305\u62ec\u7684\u306a\u63a8\u85a6\u30a8\u30f3\u30b8\u30f3\u3092\u30aa\u30f3\u30e9\u30a4\u30f3\u3067\u69cb\u7bc9\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u3001\u975e\u5e38\u306b\u591a\u304f\u306e\u30a8\u30f3\u30b2\u30fc\u30b8\u30e1\u30f3\u30c8\u3092\u7372\u5f97\u3057\u3066\u3044\u307e\u3059\u3002\u300d\nJumbo \u793e \u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u30fb\u5206\u6790\u30de\u30cd\u30fc\u30b8\u30e3\u30fc Wendell Kuling \u6c0f\n\u300cDatabricks 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\u6c0f\n\u300c\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3092\u8907\u6570\u306e\u4e8b\u696d\u90e8\u304c\u30bb\u30eb\u30d5\u30b5\u30fc\u30d3\u30b9\u3067\u5229\u7528\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u306f\u4ee5\u524d\u306b\u306f\u8003\u3048\u3089\u308c\u306a\u3044\u3053\u3068\u3067\u3057\u305f\u3002\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u5c0e\u5165\u52b9\u679c\u306f\u975e\u5e38\u306b\u5927\u304d\u3044\u3068\u611f\u3058\u3066\u3044\u307e\u3059\u3002\u300d\n\u30b3\u30ed\u30f3\u30d3\u30a2\u30b9\u30dd\u30fc\u30c4\u30a6\u30a7\u30a2\u793e \u30b7\u30cb\u30a2\u30a8\u30f3\u30bf\u30fc\u30d7\u30e9\u30a4\u30ba\u30c7\u30fc\u30bf\u30de\u30cd\u30fc\u30b8\u30e3\u30fc\n\u30e9\u30e9\u30fb\u30de\u30a4\u30ca\u30fc\u6c0f\n\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30bb\u30eb\u30d5\u30ac\u30a4\u30c9\u30c4\u30a2\u30fc\u30ea\u30c6\u30fc\u30eb\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u63a2\u7d22\u306b\u5fc5\u8981\u306a\u5168\u3066\u306e\u30ea\u30bd\u30fc\u30b9Web \u30bb\u30df\u30ca\u30fc\u5c0f\u58f2\u696d\u306b\u304a\u3051\u308b\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306a\u610f\u601d\u6c7a\u5b9a\u306e\u4fc3\u9032eBook\u5c0f\u58f2\u696d\u306b\u304a\u3051\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30af\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u0000\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sachin-balgonda-patil","text":"Sachin Balgonda Patil - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSachin Balgonda PatilSolutions Architect at DatabricksBack to speakersSachin is a Solutions Architect at Databricks and is based out of London, UK. He has spent around 20 years Architecting, Designing and Implementing complex production grade applications for various customers across the globe. In his prior role, he has implemented streaming applications for the financial services and has deep interest in real time streaming workloads. Before joining Databricks, he worked for a global system integration company.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-are-transformations","text":"What are Transformations?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTransformationsAll>TransformationsTry Databricks for freeGet StartedWhat Are Transformations?In Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d a DataFrame you will have to instruct Spark how you would like to modify the DataFrame you have into the one that you want. These instructions are called transformations. Transformations are the core of how you will be expressing your business logic using Spark. There are two types of transformations, those that specify narrow dependencies and those that specify wide dependencies.What Are Narrow Dependencies?Transformations consisting of narrow dependencies [we\u2019ll call them narrow transformations] are those where each input partition will contribute to only one output partition. What Are Wide Dependencies?A wide dependency [or wide transformation] style transformation will have input partitions contributing to many output partitions. You will often hear this referred to as a shuffle where Spark will exchange partitions across the cluster. With narrow transformations, Spark will automatically perform an operation called pipelining on narrow dependencies, this means that if we specify multiple filters on DataFrames they\u2019ll all be performed in-memory. The same cannot be said for shuffles. When we perform a shuffle, Spark will write the results to disk. You\u2019ll see lots of talks about shuffle optimization across the web because it\u2019s an important topic but for now all you need to understand are that there are two kinds of transformations. Additional ResourcesOptimized Data Transformation DocumentationWhich Data Broke My Code? Inspecting Spark TransformationsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/analyst-paper\/databricks-named-leader-by-gartner","text":"Databricks Named a Leader | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks Named a LeaderCloud Database Management SystemsDatabricks named a Leader in 2022 Gartner\u00ae Magic Quadrant\u2122 CDBMSDatabricks is proud to announce that Gartner has named us a Leader in the 2022 Magic Quadrant for Cloud Database Management Systems for the second consecutive year.We believe this recognition validates our vision for the lakehouse as a single, unified platform for data management and engineering \u2014 as well as, analytics and AI.Download the report to learn why Gartner named Databricks a Leader and gain additional insight into the benefits that a lakehouse platform can bring to your organization.Access the Report Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/eric-schmidt","text":"Eric Schmidt - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEric SchmidtFormer CEO and Chairman, Google; Co-Founder at Schmidt FuturesBack to speakersEric Schmidt is an accomplished technologist, entrepreneur and philanthropist. He joined Google in 2001 and helped grow the company from a Silicon Valley startup to a global leader in technology alongside founders Sergey Brin and Larry Page. Eric served as Google\u2019s Chief Executive Officer and Chairman from 2001\u20132011, as well as Executive Chairman and Technical Advisor. Under his leadership, Google dramatically scaled its infrastructure and diversified its product offerings while maintaining a strong culture of innovation. In 2017, he co-founded Schmidt Futures, a philanthropic initiative that bets early on exceptional people making the world better. Eric founded the Special Competitive Studies Project in 2021, a nonprofit initiative focused on strengthening America\u2019s long-term AI and technological competitiveness in national security, the economy and society.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christian-hamilton","text":"Christian Hamilton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristian HamiltonDirector, Data Science Technology at 84.51Back to speakersChristian Hamilton is a Director of Data Science Technology at 84.51\u00b0. He has spent 22 years in Kroger companies, holding diverse titles in Data Science, Retail Operations, and Finance. His work in emerging technology includes developing the first recommender sciences for Kroger\u2019s digital channels & implementing spark streaming. He\u2019s currently focused on democratizing data across the enterprise, establishing single sources of truth, empowering collaboration, and championing observability and governance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-partners-with-google-cloud-to-deliver-its-platform-to-global-businesses","text":"Databricks Partners with Google Cloud to Deliver its Platform to Global BusinessesPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Partners with Google Cloud to Deliver its Platform to Global BusinessesDatabricks launches on Google Cloud with integrations to Google BigQuery and AI Platform that unify data engineering, data science, machine learning, and analytics across both companies\u2019 services\nFebruary 17, 2021Share this postSunnyvale and San Francisco, Calif., February 17, 2021 \u2013 Today, Google Cloud and Databricks announced a new partnership to deliver Databricks at global scale on Google Cloud. Under the partnership, organizations can now use Databricks to create a lakehouse capable of data engineering, data science, machine learning, and analytics on Google Cloud\u2019s global, scalable, and elastic network. Databricks on Google Cloud will deeply integrate with Google BigQuery's open platform and will leverage Google Kubernetes Engine (GKE), enabling customers to deploy Databricks in a fully containerized cloud environment for the first time. With this integrated solution, organizations can unlock AI-driven insights, enable intelligent decision-making, and ultimately accelerate their digital transformations through data-driven applications.\n\u201cBusinesses with a strong foundation of data and analytics are well-positioned to grow and thrive in the next decade,\u201d said Thomas Kurian, CEO at Google Cloud. \u201cWe\u2019re delighted to deliver Databricks\u2019 lakehouse for AI and ML-driven analytics on Google Cloud. By combining Databricks\u2019 capabilities in data engineering and analytics with Google Cloud\u2019s global, secure network\u2014and our expertise in analytics and delivering containerized applications\u2014we can help companies transform their businesses through the power of data.\u201d\n\u201cThis is a pivotal milestone that underscores our commitment to enable customer flexibility and choice with a seamless experience across cloud platforms,\u201d said Ali Ghodsi, CEO and co-founder of Databricks. \u201cWe are thrilled to partner with Google Cloud and deliver on our shared vision of a simplified, open, and unified data platform that supports all analytics and AI use-cases that will empower our customers to innovate even faster.\u201d\n\u201cFor Cond\u00e9 Nast, finding valuable insights from massive amounts of data is essential for creating world class content experiences that delight our global customers. Databricks on Google Cloud provides a lakehouse for our data engineers, data scientists and analysts to consolidate, collaborate, analyze, and use all of our global data to experiment and innovate quickly. We\u2019re excited to see leaders like Google Cloud and Databricks come together to streamline and simplify getting value from data,\u201d said Nana Essuman, Director of Data Engineering at Cond\u00e9 Nast.\nDeploying Databricks rapidly and securely at global scale\nGlobal businesses need the ability to quickly deploy applications at any scale, and the elasticity to scale them up or down depending on their needs. Delivering Databricks on Google Cloud enables customers to rapidly provision Databricks on Google Cloud\u2019s global network, with advanced security and data protection controls required for highly-regulated industries, and with the flexibility to quickly adjust usage based on the needs of the business.\nAdditionally, customers will soon be able to deploy Databricks from the Google Cloud Marketplace, enabling simplified procurement and user provisioning, Single Sign-On, and unified billing.\nAdvancing analytics with Databricks, BigQuery, and Google Cloud AI Platform\nDatabricks on Google Cloud is tightly integrated with Google BigQuery, giving customers the freedom of choice and access to their choice of data analytics services. With this integration, businesses can extend their existing Databricks lakehouse capabilities, now running on Google Cloud, and can cross-leverage Google BigQuery for analytics, ultimately simplifying their data investments, increasing usage, and creating new, data-driven business models and opportunities.\nUnique integrations between Databricks and Google Cloud include:\n\nTight integration of Databricks with Google Cloud\u2019s analytics solutions, giving customers the ability to easily extend AI-driven insights across data lakes, data warehouses, and multiple business intelligence tools.\nPre-built connectors to seamlessly and quickly integrate Databricks with BigQuery, Google Cloud Storage, Looker and Pub\/Sub.\nFast and scalable model training with AI Platform using the data workflows created in Databricks, and simplified deployment of models built in Databricks using AI Platform Prediction.\n\nDelivering containerized Databricks deployments for the first time\nDatabricks on Google Cloud represents the first container-based deployments of Databricks, on any cloud.\nIncreasingly, Kubernetes and containers are the de facto orchestration system for enterprise workloads and applications running in the cloud. Databricks on Google Cloud is built on GKE, Google Cloud\u2019s secure, managed Kubernetes service, to support containerized deployments of Databricks in the cloud. By adopting GKE as an operating environment, Databricks is able to leverage managed services for security, network policy, and compute and as a result, provide customers with increasing business value through Databricks analytics, AI, and ML capabilities. Additionally, with GKE, Databricks increases its agility and the ability to accelerate the release of new features, quickly, at scale, and at lower cost.\nSupporting open source innovation and partner collaboration\nDatabricks and Google Cloud share a commitment to open innovation and open source software. Under this new partnership, the two companies will continue to support the open source community, encourage open innovation and collaboration, making it easier for joint customers to build on open-source technologies.\nAdditionally,\u00a0 members of our joint ecosystem of partners have committed to ensure seamless integrations and expertise with Databricks on Google Cloud, including Accenture, Cognizant, Collibra, Confluent, Deloitte, Fishtown Analytics, Fivetran, Immuta, Informatica, Infoworks, Insight, MongoDB, Privacera, Qlik, SoftServe, Slalom, Tableau, TCS and Trifacta among others.\nOn April 6, join Databricks CEO, Ali Ghodsi, and Google Cloud CEO, Thomas Kurian as they share more about the partnership and vision of an open, unified data analytics platform during a discussion hosted by TechCrunch; visit the event page for more information.\nTo learn more about Databricks on Google Cloud, visit: https:\/\/www.databricks.com\/product\/google-cloud\nAbout Google Cloud\nGoogle Cloud provides organizations with leading infrastructure, platform capabilities and industry solutions. We deliver enterprise-grade cloud solutions that leverage Google\u2019s cutting-edge technology to help companies operate more efficiently and adapt to changing needs, giving customers a foundation for the future. Customers in more than 150 countries turn to Google Cloud as their trusted partner to solve their most critical business problems.\nAbout Databricks\nDatabricks is the data and AI company. Thousands of organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, Nationwide, and H&M \u2014 rely on Databricks\u2019 open and unified platform for data engineering, data science, machine learning, and analytics. Databricks is venture-backed and headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake, and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.\nMedia contacts\n[email\u00a0protected]\n[email\u00a0protected]\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#b6c6c4dfc0d7d5cff6d2d7c2d7d4c4dfd5ddc598d5d9db","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c2dbe9d5539b6\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/jp\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-keller","text":"Jonathan Keller - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan KellerSr. Director, Product Management at DatabricksBack to speakersJonathan leads Product Management for data governance at Databricks, including Unity Catalog and Delta Sharing. He was previously Director of Product Management for Google Cloud\u2019s BigQuery team, after almost 20 years at Microsoft in various roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/28\/project-lightspeed-faster-and-simpler-stream-processing-with-apache-spark.html","text":"Project Lightspeed: Faster and Simpler Stream Processing With Apache SparkSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorProject Lightspeed: Faster and Simpler Stream Processing With Apache Sparkby Karthik Ramasamy, Matei Zaharia, Reynold Xin, Michael Armbrust, Awez Syed, Ray Zhu, Alexander Balikov, Jerry Peng, Shrikanth Shankar and Sameer ParanjpyeJune 28, 2022 in Engineering BlogShare this postStreaming data is a critical area of computing today. It is the basis for making quick decisions on the enormous amounts of incoming data that systems generate, whether web postings, sales feeds, or sensor data, etc. Processing streaming data is also technically challenging, and it has needs far different from and more complicated to meet than those of event-driven applications and batch processing.To meet the stream processing needs, Structured Streaming was introduced in Apache Spark\u2122 2.0. Structured Streaming is a scalable and fault-tolerant stream processing engine built on the Spark SQL engine. The user can express the logic using SQL or Dataset\/DataFrame API. The engine will take care of running the pipeline incrementally and continuously and update the final result as streaming data continues to arrive. Structured Streaming has been the mainstay for several years and is widely adopted across 1000s of organizations, processing more than 1 PB of data (compressed) per day on the Databricks platform alone.As the adoption accelerated and the diversity of applications moving into streaming increased, new requirements emerged. We are starting a new initiative codenamed Project Lightspeed to meet these requirements, which will take Spark Structured Streaming to the next generation. The requirements addressed by Lightspeed are bucketed into four distinct categories:Improving the latency and ensuring it is predictableEnhancing functionality for processing data with new operators and APIsImproving ecosystem support for connectorsSimplifying deployment, operations, monitoring and troubleshootingIn this blog, we will discuss the growth of Spark Structured Streaming and its key benefits. Then we will outline an overview of the proposed new features and functionality in Project Lightspeed.Growth of Spark Structured StreamingSpark Structured Streaming has been widely adopted since the early days of streaming because of its ease of use, performance, large ecosystem, and developer communities. The majority of streaming workloads we saw were customers migrating their batch workloads to take advantage of the lower latency, fault tolerance, and support for incremental processing that streaming offers. We have seen tremendous adoption from streaming customers for both open source Spark and Databricks. The graph below shows the weekly number of streaming jobs on Databricks over the past three years, which has grown from thousands to 4+ millions and is still accelerating.Advantages of Spark Structured StreamingSeveral properties of Structured Streaming have made it popular for thousands of streaming applications today.Unification - The foremost advantage of Structured Streaming is that it uses the same API as batch processing in Spark DataFrames, making the transition to real-time processing from batch much simpler. Users can simply write a DataFrame computation using Python, SQL, or Spark\u2019s other supported languages and ask the engine to run it as an incremental streaming application. The computation will then run incrementally as new data arrives, and recover automatically from failures with exactly-once semantics, while running through the same engine implementation as a batch computation and thus giving consistent results. Such sharing reduces complexity, eliminates the possibility of divergence between batch and streaming workloads, and lowers the cost of operations (consolidation of infrastructure is a key benefit of Lakehouse). Additionally, many of Spark\u2019s other built-in libraries can be called in a streaming context, including ML libraries.Fault Tolerance & Recovery - Structured Streaming checkpoints state automatically during processing. When a failure occurs, it automatically recovers from the previous state. The failure recovery is very fast since it is restricted to failed tasks as opposed to restarting the entire streaming pipeline in other systems. Furthermore, fault tolerance using replayable sources and idempotent sinks enables end-to-end exactly-once semantics.Performance - Structured Streaming provides very high throughput with seconds of latency at a lower cost, taking full advantage of the performance optimizations in the Spark SQL engine. The system can also adjust itself based on the resources provided thereby trading off cost, throughput and latency and supporting dynamic scaling of a running cluster. This is in contrast to systems that require upfront commitment of resources.Flexible Operations - The ability to apply arbitrary logic and operations on the output of a streaming query using foreachBatch, enabling the ability to perform operations like upserts, writes to multiple sinks, and interact with external data sources. Over 40% of our users on Databricks take advantage of this feature.Stateful Processing - Support for stateful aggregations and joins along with watermarks for bounded state and late order processing. In addition, arbitrary stateful operations with [flat]mapGroupsWithState backed by a RocksDB state store are provided for efficient and fault-tolerant state management (as of Spark 3.2).Project LightspeedWith the significant growing interest in streaming in enterprises and making Spark Structured Streaming the de facto standard across a wide variety of applications, Project Lightspeed will be heavily investing in improving the following areas:Predictable Low LatencyApache Spark Structured Streaming provides a balanced performance across multiple dimensions - throughput, latency and cost. As Structured Streaming grew and is used in new applications, we are profiling our customer workloads to guide improvements in tail latency by up to 2x. Towards meeting this goal, some of the initiatives we will be undertaking are as follows:Offset Management - Our customer workload profiling and performance experiments indicate that offset management operations consume upto 30-50% of the time for pipelines. This can be improved by making these operations asynchronous and configurable cadence, thereby reducing the latency.Asynchronous Checkpointing - Current checkpointing mechanism synchronously writes into object storage after processing a group of records. This contributes substantially to latency. This could be improved by as much as 25% by overlapping the execution of the next group of records with writing of the checkpointing for the previous group of records.State Checkpointing Frequency - Spark Structured Streaming checkpoints the state after a group of records have been processed that adds to end-to-end latency. Instead, if we make it tunable to checkpoint every Nth group, the latency can be further reduced depending on the choice for N.Enhanced Functionality for Processing Data \/ EventsSpark Structured Streaming already has rich functionality for expressing predominant sets of use cases. As enterprises extend streaming into new use cases, additional functionality is needed to express them concisely. Project Lightspeed is advancing the functionality in the following areas:Multiple Stateful Operators - Currently, Structured Streaming supports only one stateful operator per streaming job. However, some use cases require multiple state operators in a job such as:\n\u00a0Chained time window aggregation (e.g. 5 mins tumble window aggregation followed by 1 hour tumble window aggregation)Chained stream-stream outer equality join (e.g. A left outer join B left outer join C)Stream-stream time interval join followed by time window aggregationProject Lightspeed will add support for this capability with consistent semantics.Advanced Windowing - Spark Structured Streaming provides basic windowing that addresses most use cases. Advanced windowing will augment this functionality with simple, easy to use, and intuitive API to support arbitrary groups of window elements, define generic processing logic over the window, ability to describe when to trigger the processing logic and the option to evict window elements before or after the processing logic is applied.State Management - Stateful support is provided through predefined aggregators and joins. In addition, specialized APIs are provided for direct access to state and manipulating it. New functionality, in Lightspeed, will incorporate the evolution of the state schema as the processing logic changes and the ability to query the state externally.Asynchronous I\/O - Often, in ETL, there is a need to join a stream with external databases and microservices. Project Lightspeed will introduce a new API that manages connections to external systems, batch requests for efficiency and handles them asynchronously.Python API Parity - While Python API is popular, it still lacks the primitives for stateful processing. Lightspeed will add a powerful yet simple API for storing and manipulating state. Furthermore, Lightspeed will provide tighter integrations with popular Python data processing packages like Pandas - to make it easy for the developers.Connectors and EcosystemConnectors make it easier to use the Spark Structured Streaming engine to process data from and write processed data into various messaging buses like Apache Kafka and storage systems like Delta lake. As part of Project Lightspeed, we will work on the following:New Connectors - We will add new connectors working with partners (for example, Google Pub\/Sub, Amazon DynamoDB) to enable developers to easily use the Spark Structured Streaming engine with additional messaging buses and storage systems they prefer.Connector Enhancement - We will enable new functionalities and improve performance on existing connectors. Some examples include AWS IAM auth support in the Apache Kafka connector and enhanced fan-out support in the Amazon Kinesis connector.Operations and TroubleshootingStructured Streaming jobs are continuously running until explicitly terminated. Because of the always-on nature, it is necessary to have the appropriate tools and metrics to monitor, debug and alert when certain thresholds are exceeded. Towards satisfying these goals, Project Lightspeed will improve the following:Observability - Currently, the metrics generated from structured streaming pipelines for monitoring require coding to collect and visualize. We will unify the metric collection mechanism and provide capabilities to export to different systems and formats. Furthermore, based on customer input, we will add additional metrics for troubleshooting.Debuggability - We will provide capabilities to visualize pipelines and how its operators are grouped and mapped into tasks and the executors the tasks are running. Furthermore, we will implement the ability to drill down to specific executors, browse their logs and various metrics.What\u2019s NextIn this blog, we discussed the advantages of Spark Structured Streaming and how it contributed to its widespread growth and adoption. We introduced Project Lightspeed which advances Spark Structured Streaming into the real-time era as more and more new use cases and workloads migrate into streaming.In subsequent blogs, we will expand on the individual categories of improving Spark Structured Streaming performance across multiple dimensions, enhanced functionality, operations and ecosystem support.Project Lightspeed will roll out incrementally by collaborating and closely working with community. We are expecting most of the features to be delivered by early next year.Try Databricks for freeGet StartedRelated postsStructured Streaming: A Year in ReviewFebruary 7, 2022 by Steven Yu and Ray Zhu in Data Engineering\nAs we enter 2022, we want to take a moment to reflect on the great strides made on the streaming front in Databricks...\nHow to Monitor Streaming Queries in PySparkMay 27, 2022 by Hyukjin Kwon, Karthik Ramasamy and Alexander Balikov in Open Source\nStreaming is one of the most important data processing techniques for ingestion and analysis. It provides users and developers with low latency and...\nWhat\u2019s New in Apache Spark\u2122 3.1 Release for Structured StreamingApril 27, 2021 by Yuanjian Li, Shixiong Zhu and Bo Zhang in Engineering Blog\nAlong with providing the ability for streaming processing based on Spark Core and SQL API, Structured Streaming is one of the most important...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/retention-management","text":"Solution Accelerator - How to build: Profit-driven retention management | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: Profit-driven retention managementEffectively manage retention and reduce churn\nDevelop an understanding of how a customer lifetime should progress and examine where in that lifetime journey customers are likely to churn so you can effectively manage retention and reduce your churn rate.\nRead the full write-up\nDownload notebooksBenefits and business valueStop the bleedingIdentify which customers are most likely to leave your service\nMassive speed improvementScan through large volumes of data easily, and quickly generate useful customer analysis records\nIncrease customer lifetime valueIdentify the value of retaining the customer\nReference ArchitectureDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/francisco-rius\/#","text":"Francisco Rius - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFrancisco RiusHead of Data Science and Data Engineering at Minecraft at MicrosoftBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/junta-nakai","text":"Junta Nakai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJunta NakaiRVP, Industry Solutions, Financial Services and Sustainability at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christopher-locklin","text":"Christopher Locklin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristopher LocklinEngineer Manager, Data Platform at GrammarlyBack to speakersChris Locklin has been leading data infrastructure and engineering teams for the last 9 years (at Grammarly, Dropbox, and Verizon), and initially entered the data space in 2010. He is currently the engineering manager of the Data Platform team at Grammarly. The team is responsible for ingesting, processing, and surfacing over 50 billion events every day.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#a2d2d0cbd4c3c1dbe2c6c3d6c3c0d0cbc1c9d18cc1cdcf","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c2df2b83982c0\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/delta-live-tables-demo","text":"Delta Live Tables Demo: Reliable Data Pipelines | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta Live Tables DemosGet started for freeDelta Live Tables Overview\nIn this demo, we give you a first look at Delta Live Tables, a cloud service that makes reliable ETL \u2013 extract, transform and load capabilities \u2013 easy on Delta Lake. It helps data engineering teams streamline ETL development with a simple UI and declarative tooling, improve data reliability through defined data quality rules and bad data monitoring, and scale operations with deep visibility through an event log.\nStreaming Data With Delta Live Tables\nLet's analyze tweets from Data + AI Summit 2022! Modern data engineering requires a more advanced data lifecycle for data ingestion, transformation and processing. In this session, you can learn how the Databricks Lakehouse Platform provides an end-to-end data engineering solution that automates the complexity of building and maintaining data pipelines. Enjoy a fun, live, streaming data example with a Twitter data stream, Databricks Auto Loader and Delta Live Tables as well as Hugging Face sentiment analysis.\nHow to Create Low Latency Streaming Data Pipelines With Apache Kafka or Amazon Kinesis and Delta Live Tables\nAs shown at the Current.io 2022 conference in Austin (the next generation of Kafka Summit), this live demo elaborates on how the Databricks Lakehouse Platform simplifies data streaming to deliver streaming analytics and applications on one platform. Learn how to build low latency streaming data pipelines that ingest from a message bus like Confluent Cloud, Apache Kafka or any other Kafka-compatible cloud service such as Amazon MSK. The same principles can be used to ingest data from Amazon Kinesis. Frank's full conference session spans Spark on Databricks, Spark Structured Streaming with Delta Lake, and Delta Live Tables. Slides, code and a blog posting are available.\nSee full list of demosDive deeper into Delta LakeLearn moreLearn moreLearn moreCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet Started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/oreilly-definitive-guide","text":"\n\n\n\n\n\n\n\nO\u2019Reilly Definitive Guide\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/data-management-the-good-the-bad-the-ugly?itm_data=product-page-resource-data-mamagemet-big-rock","text":"Data Management The Good The Bad The Ugly - DatabricksOn-Demand WebinarData ManagementThe good, the bad, the uglyCould this be the end of the 2 AM page? Learn how Databricks helps data engineers sleep at night.Maintaining data infrastructure isn\u2019t easy, but it\u2019s the foundation that makes ML, AI and data science possible. Discover how Databricks simplifies data management \u2014 from data processing with ETL to data governance \u2014 and why that makes the lakehouse architecture a reality.You\u2019ll also learn about newly released features and tools that extend the power of the Databricks Lakehouse Platform. Here\u2019s what we\u2019ll cover:How to automatically and reliably ingest and prepare structured and unstructured data at scale for data lakesHow to simplify your architecture and enable data scientists and analysts to query the freshest and most complete data using their SQL and BI tools of choiceHow to centrally share and govern data within and across organizations using open source Delta Sharing and a unified data catalogThis presentation will come to life with an end-to-end demo of Databricks\u2019 most recent capabilities for end-to-end data management and a live Q&A throughout the event.The notebooks will be provided so you can follow along and practice at your own pace.Watch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#c9b9a8bbbda7acbbba89ada8bda8abbba0aaa2bae7aaa6a4","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c2dfb783c3adc\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deepa-paranjpe","text":"Deepa Paranjpe - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeepa ParanjpeDirector of Engineering at DiscoveryBack to speakersDeepa Paranjpe is director of engineering in WBD.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/himanshu-arora\/#","text":"Himanshu Arora - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHimanshu AroraResident Solutions Architect at DatabricksBack to speakersHimanshu is a Resident Solutions Architect at Databricks. He has been using Spark, Big Data, and Reactive systems for a few years now in production to help enterprises in their data and digital transformation journey. Prior to that, he was a Java\/Scala developer. Himanshu joined Databricks in 2020 and since then he has been helping Databricks customers on numerous projects around Data Architecture & Design, Optimization & Best Practices, Lakehouse implementation, Migration to Databricks, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/glossary\/sparklyr","text":"What is Sparklyr?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSparklyrAll>SparklyrTry Databricks for freeGet StartedWhat is Sparklyr?Sparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little latency. Sparklyr is an effective tool for interfacing with large datasets in an interactive environment. This way you can benefit from the familiar tools in R in order to analyze data in Spark., giving you the best of both worlds.  Through Sparklyr you can use Spark as the backend for dplyr, a popular data manipulation package. Sparklyr provides a range of functions that allow us to access the Spark tools for transforming\/pre-processing data, On top of that, it also provides interfaces to Spark\u2019s distributed machine learning algorithms and much more. Sparklyr is also extensible. R packages that depend on Sparklyr to call the full Spark API can be created. One such extension is H2O\u2019s Rsparkling, an R package compatible with H2O\u2019s machine learning algorithm.Main highlights of Sparklyr:Users can interactively manipulate Spark data using dplyr as well as SQL (via DBI).Spark datasets can be filtered and aggregated and afterward brought into R to be analyzed.You will be able to orchestrate distributed machine learning from R using either Spark MLlib or H2O SparkingWater.Sparklyr users are able to generate extensions that call the full Spark API and provide interfaces to Spark packages.Sparklyr tool offers an exhaustive dplyr backend useful in case of data manipulation, analysis, and visualizationLoads data into Spark DataFrames from various locations such as local R data frames, Hive tables, CSV, JSON, and Parquet files.Sparklyr is able to connect to both local instances of Spark as well as to remote Spark clustersAdditional ResourcesSparklyr DocumentationR and Spark: How to Analyze Data Using RStudio\u2019s Sparklyr and H2O\u2019s Rsparkling PackagesIntroducing Apache Spark 3.0: Now available in Databricks Runtime 7.0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/media-entertainment-resources\/explore-lakehouse-for-media","text":"\n\n\n\n\n\n\n\nExplore the Lakehouse for Media & Entertainment\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/glossary\/artificial-neural-network","text":"What is an Artificial Neural Network?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWArtificial Neural NetworkAll>Artificial Neural NetworkTry Databricks for freeGet StartedWhat is an Artificial Neural Network?An artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.How Do Artificial Neural Networks Work?Artificial Neural Networks can be best viewed as weighted directed graphs, that are commonly organized in layers. These layers feature many nodes which imitate biological neurons of the human brain. that are interconnected and contain an activation function. The first layer receives the raw input signal from the external world-- analogous to optic nerves in human visual processing. Each successive layer gets the output from the layer preceding it, similar to the way neurons that are situated further from the optic nerve receive signals from those closest to them. The output at each node is called its activation or node value. The last tier produces the output of the system. ANNs are actually mathematical models that are capable of learning; by using ANNs we have been able to enhance existing data analysis technologies. They are one of the reasons we have seen an important progress in artificial intelligence (AI), machine learning (ML), and deep learning.Perceptron Artificial Neural NetworkPerceptron is the simplest type of artificial neural network. This type of network is typically used for making binary predictions. A Perceptron can only work if the data can be linearly separable. Multi-layer Artificial Neural NetworkA fully connected multi-layer neural network is also known as a Multilayer Perceptron (MLP). This type of artificial neural network is made of more than one layer of artificial neurons or nodes, ( for example the Convolutional Neural Network, Recurrent Neural Network etc \u2026) A multi-layer ANN is used to solve more complex classification and regression tasks. The most common model is the 3-layer fully-connected backpropagation model. The first layer consists of input neurons, that send data on to the second layer, which in turn sends the output neurons to the third layer.  Furthermore, there are two Artificial Neural Network topologies: FeedForward and Feedback.FeedForward Artificial Neural NetworkIn this ANN, the information flow is unidirectional. The information travels only in one direction; forward; without making any feedback loops. \u00a0It first goes through the input nodes, then through the hidden nodes (in case there are any), and in the end, it goes through the output nodes.FeedBack Artificial Neural NetworkIn this case, there are inherent feedback connections between the neurons of the networks. Here, feedback loops are allowed. \u00a0Additional ResourcesIntroduction to Neural Networks WebinarTraining your Neural Network WebinarApplying your Convolutional Neural Network WebinarBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ricardo-portilla","text":"Ricardo Portilla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRicardo PortillaPrincipal Solution Architect at DatabricksBack to speakersRicardo has 12+ years of experience with Financial Services customers bringing use cases to production. He has designed and consulted on solutions architecture with dozens of customers from Capital Markets to Banking and Wealth Management. His previous work was at FINRA where he moved FINRA mission-critical workloads from on-prem warehouses to the cloud and established a machine learning practice for financial fraudLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/kr\/company\/diversity","text":"\ub2e4\uc591\uc131\uacfc \ud3ec\uc6a9\uc131 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \u0000\u0000\uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 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\ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ubbf8\ub798\uc758 \ub370\uc774\ud130\ub294 \ubaa8\ub450\uc5d0\uac8c \uc5f4\ub824 \uc788\uc2b5\ub2c8\ub2e4Databricks\uc758 \ub2e4\uc591\uc131, \ud3c9\ub4f1 \ubc0f \ud3ec\uc6a9\uc131\ub370\uc774\ud130\ub85c \uc6c0\uc9c1\uc774\uace0, \uc0ac\ub78c\uc774 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\uc800\ud76c\ub294 \ube45\ub370\uc774\ud130\ub97c \ub2e4\uc591\ud654\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud569\ub2c8\ub2e4. \uadf8 \ub178\ub825\uc740 \uc6b0\ub9ac \ud300\ubd80\ud130 \uc194\uc120\uc218\ubc94\ud569\ub2c8\ub2e4. \ub2e4\uc591\ud55c \ubc30\uacbd, \uacbd\ud5d8, \uad00\uc810, \uc778\uc0ac\uc774\ud2b8, \uae30\uc220\uc740 \ud601\uc2e0\uc744 \ucd09\uc9c4\ud558\uace0, \uc11c\ub85c \uac04\uc758 \uc720\ub300\uc640 \uace0\uac1d\uacfc\uc758 \uc720\ub300\ub97c \ub354\uc6b1 \uae4a\uc5b4\uc9c0\uac8c \ud569\ub2c8\ub2e4. \uc800\ud76c\ub294 \ubaa8\ub4e0 \uc0ac\ub78c\uc774 \uc790\uc2e0\uc758 \ucee4\ub9ac\uc5b4\uc5d0\uc11c \ucd5c\uace0\uc758 \uc131\uacfc\ub97c \ub0bc \uc218 \uc788\ub294 \uc18c\uc18d\uac10\uc744 \ud0a4\uc6b0\ub294 \ubb38\ud654\ub97c \uc870\uc131\ud558\uace0\uc790 \ud569\ub2c8\ub2e4. \ub3d9\uc77c \ub178\ub3d9 \ub3d9\uc77c \uc784\uae08 \uc6d0\uce59\uc744 \uc900\uc218\ud558\ub294 \uac83\uc5d0\uc11c\ubd80\ud130 \uc6b0\ub9ac \ud300\uc758 \ub178\uace0\ub97c \ucd95\ud558\ud558\uace0, \ud300\uc6d0\ub4e4\uc744 \uad50\uc721\ud558\uace0 \uc0ac\uae30\ub97c \ub192\uc774\ub294 \ud504\ub85c\uadf8\ub7a8\uc744 \ub9cc\ub4dc\ub294 \uac83\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0, DEI(Diversity, Equity and Inclusion)\ub294 \uc800\ud76c\uac00 \ud558\ub294 \ubaa8\ub4e0 \uc77c\uc5d0 \ubc14\ud0d5\uc774 \ub429\ub2c8\ub2e4.Fair Pay Workplace \uc778\uc99d\nFair Pay Workplace\uc5d0\uc11c \ucc98\uc74c\uc73c\ub85c \uc778\uc99d\uc744 \ubc1b\uc740 6\uac1c \uae30\uad00 \uc911 \ud558\ub098\uc778 \uac83\uc5d0 \uc790\ubd80\uc2ec\uc744 \ub290\ub07c\ube48\ub2e4. Databricks\uc5d0\uc11c\ub294 \uacf5\ud3c9\ud55c \uae09\uc5ec\u0000\ub97c \uc81c\uacf5\ud558\uae30 \uc704\ud55c \ub178\ub825\uc758 \uc77c\ud658\uc73c\ub85c, \uae09\uc5ec \ub370\uc774\ud130\uc640 \uc81c\ub3c4\ub97c \uc5c4\uaca9\ud788 \ud3c9\uac00\ud558\uba70 \uc9c0\uc18d\uc801\uc778 \uae09\uc5ec \ud3c9\ub4f1\uc131 \ubd84\uc11d\uc744 \ud1b5\ud574 \ub05d\uae4c\uc9c0 \ucc45\uc784\uc744 \uc9c0\uace0\uc790 \ud569\ub2c8\ub2e4.Gaingels \ubc0f Flucas Ventures\n\ub2e4\uc591\uc131, \u0000\u0000\ud3c9\ub4f1, \ud3ec\uc6a9\uc131\uc5d0 \ub300\ud55c \ub178\ub825\uc740 \uc800\ud76c\uc640 \ud568\uaed8 \uc77c\ud558\ub294 \uc0ac\ub78c\ub4e4\uc5d0\uc11c\ubd80\ud130 \uc800\ud76c\uc5d0\uac8c \ud22c\uc790\ud558\ub294 \uc0ac\ub78c\ub4e4\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0 \uc6b0\ub9ac \ud300\uc5d0 \ucc38\uc5ec\ud558\ub294 \ubaa8\ub4e0 \uc0ac\ub78c\uc744 \uc544\uc6b0\ub985\ub2c8\ub2e4. \uadf8\ub798\uc11c DEI\uc5d0 \ub300\ud55c \uae4a\uc740 \ud5cc\uc2e0\uc744 \ubcf4\uc774\ub294 \uae30\uc5c5\uc5d0 \ud22c\uc790\ud558\ub294 Gaingels, Flucas Ventures \ub4f1\uc758 \uc138\uacc4\uc801 \uc218\uc900\uc758 \uc5ec\ub7ec \ud22c\uc790\uc790\uc640\ub3c4 \ud30c\ud2b8\ub108\ub97c \ub9fa\uc740 \uac83\uc744 \uc790\ub791\uc2a4\ub7fd\uac8c \uc0dd\uac01\ud569\ub2c8\ub2e4.\u201c\ub370\uc774\ud130\uac00 \ub9ce\uc744\uc218\ub85d \ub354 \uc88b\uc740 \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc2b5\ub2c8\ub2e4. \ub2e4\uc591\uc131\uacfc \ud3ec\uc6a9\uc131\ub3c4 \ub9c8\ucc2c\uac00\uc9c0\uc785\ub2c8\ub2e4. Databricks\ub294 \ubc30\uacbd, \uacbd\ud5d8, \uad00\uc810\uc744 \ucd5c\ub300\ud55c \ub2e4\uc591\ud558\uac8c \ud3ec\uc6a9\ud568\uc73c\ub85c\uc368 \ubc88\ucc3d\ud569\ub2c8\ub2e4.\u201d\u2014 Ali Ghodsi, \uacf5\ub3d9 \ucc3d\uc5c5\uc790 \uacb8 CEO, Databricks\uc6b0\ub9ac \ucee4\ubba4\ub2c8\ud2f0\uc9c1\uc6d0\uc744 \uc9c0\uc6d0\ud558\ub294 \uac83\uc774\uc57c\ub9d0\ub85c \uc6b0\ub9ac \ud68c\uc0ac\uc758 \ubaa8\ub4e0 \uc7a0\uc7ac\ub825\uc744 \uc2e4\ud604\ud560 \uc218 \uc788\ub294 \uc5f4\uc1e0\ub77c\uace0 \uc0dd\uac01\ud569\ub2c8\ub2e4. \ud65c\uae30 \ub118\uce58\ub294 \uc9c1\uc6d0 \ub9ac\uc18c\uc2a4 \uadf8\ub8f9(ERG)\ub294 \uc9c1\uc6d0\uc774 \uc8fc\ub3c4\ud558\ub294 \uacf5\ub3d9\uccb4\ub85c, Databricks\uc5d0\uc11c \ud3ec\uc6a9\uc801\uc774\uace0 \ud798\uc774 \ub418\ub294 \ud658\uacbd\uc744 \uc870\uc131\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \uc9c1\uc6d0\uacfc \ud611\ub825\uc790\ub85c \uad6c\uc131\ub41c \uc774\ub7f0 \ub2e4\uc591\ud55c \ucee4\ubba4\ub2c8\ud2f0\ub294 \uc720\ub300\ub97c \ud0a4\uc6b0\uace0 \uc11c\ub85c \ucd95\ud558\ud558\uae30 \uc704\ud55c \uacf5\uac04\uc744 \ub9c8\ub828\ud574\uc8fc\uba70, \uc758\ubbf8 \uc788\ub294 \ubb38\uc81c\uc5d0 \ub300\ud55c \uc758\uc2dd\uc744 \uc81c\uace0\ud569\ub2c8\ub2e4.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\n\uc9c1\uc6d0 \uacbd\ud5d8\u201c\uc800\ub294 Databricks\uc5d0\uc11c \uc81c\uac00 \uc18d\ud558\uace0 \uc2f6\uc740 \ud300\uc744 \uad6c\ucd95\ud569\ub2c8\ub2e4. \uc989, \uc9c4\uc815\ud55c \uc81c \uc790\uc2e0\uc744 \uc548\uc804\ud558\uac8c \uacf5\uac1c\ud560 \uc218 \uc788\uace0 \uc8fc\ubcc0\uc758 \ubaa8\ub4e0 \uc0ac\ub78c\ub4e4\uc5d0\uac8c\ub3c4 \ub611\uac19\uc774 \ud3b8\uc548\ud55c \uacf5\uac04\uc744 \uc81c\uacf5\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc6b0\ub9ac\uac00 \uc11c\ub85c\uc5d0\uac8c \ubcf4\uc5ec\uc8fc\ub294 \ubc30\ub824\uc640 \ud3ec\uc6a9\uc5d0 \ub300\ud55c \ud5cc\uc2e0\uc740 \uc6b0\ub9ac \ucee4\ubba4\ub2c8\ud2f0 \uc804\uccb4\uc5d0 \uc5c4\uccad\ub09c \uc601\ud5a5\uc744 \ubbf8\uce69\ub2c8\ub2e4.\u201d\u2014 Stacy Kerkela, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uc774\uc0ac\uc790\uc138\ud788 \uc77d\uae30\u201cDatabricks\uc758 LatinX Network\uc5d0\uc11c \uac1c\ubc29\uc801 \ucee4\ubba4\ub2c8\ud2f0\uc5d0 \ub300\ud55c \uac15\ud55c \uc18c\uc18d\uac10\uc744 \ub290\ub08d\ub2c8\ub2e4. Databricks\uc758 \uc9c1\uc6d0 \ub9ac\uc18c\uc2a4 \uadf8\ub8f9\uc5d0\uc11c\ub294 \ubc30\uacbd\uacfc \uad00\uacc4\uc5c6\uc774 \ubaa8\ub4e0 \uc0ac\ub78c\uc744 \ud658\uc601\ud558\uace0 \uad50\uc721\ud558\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4.\u201d\u2014 Miguel Peralvo, \uc120\uc784 \uc194\ub8e8\uc158 \uc544\ud0a4\ud14d\ud2b8\uc790\uc138\ud788 \uc77d\uae30\u201c\ub9ce\uc740 \uae30\uc5c5\uc774 \uc131 \ub2e4\uc591\uc131\uc744 \ub298\ub9ac\ub294 \ub370 \uc9d1\uc911\ud558\uc9c0\ub9cc, \ud070 \ubcc0\ud654\ub97c \uc77c\uc73c\ud0a4\uae30 \uc704\ud574 \uac00\uc2dc\uc801\uc778 \uc870\uce58\ub97c \ucde8\ud558\ub294 \ud68c\uc0ac\uc5d0 \uc18c\uc18d\ub418\uc5b4 \uc788\ub294 \uac83\uc744 \uae30\uc058\uac8c \uc0dd\uac01\ud569\ub2c8\ub2e4.\u201d\u2014 Allie Emrich, \uc81c\ud488 \ud504\ub85c\uadf8\u0000\ub7a8 \uad00\ub9ac\uc790\uc790\uc138\ud788 \uc77d\uae30\ud3ec\uc6a9 \ud65c\ub3d9\ubcf4\uace0\uc11cColorStack \ubc0f Rewriting the Code\uc640\uc758 \ud30c\ud2b8\ub108\uc2ed\uc6b0\ub9ac \ub300\ud559 \ubaa8\uc9d1 \ud300\uc740\u00a0ColorStack\u00a0\ubc0f\u00a0Rewriting the Code\u00a0\uc640 \ud611\ub825\ud558\uc5ec \ub354 \ub9ce\uc740 \uc5ec\uc131\uacfc \ud751\uc778 \ubc0f \ub77c\ud2f4\uacc4 \ud559\uc0dd\ub4e4\uc774 \uae30\uc220 \ubd84\uc57c\uc5d0\uc11c \uacbd\ub825\uc744 \uc313\uc744 \uc218 \uc788\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788 \uc77d\uae30\ubcf4\uace0\uc11cWomen in Tech Mentorship \ud504\ub85c\uadf8\ub7a8Databricks\uc5d0\uc11c\ub294 \uc5ed\uc0ac\uc801\uc73c\ub85c \uc18c\uc678\ubc1b\uc740 \ucee4\ubba4\ub2c8\ud2f0\uc5d0 \ub300\ud55c \uc9c1\uc5c5\uc801 \uc11c\uc7a5\uacfc \ubc1c\uc804 \uae30\ud68c\ub97c \uc81c\uacf5\ud558\ub294 \uac83\uc774 \uc911\uc694\ud558\ub2e4\uace0 \uc0dd\uac01\ud569\ub2c8\ub2e4.\uc790\uc138\ud788 \uc77d\uae30\ubcf4\uace0\uc11c2021 InHerSight Award\uc5ec\uc131\ub4e4\uc774 \ud3c9\uac00\ud558\ub294, \uc5ec\uc131\uc744 \uc704\ud55c \ucd5c\uace0\uc758 \ucef4\ud4e8\ud130 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc9c1\uc7a5\uc5d0 \uc120\uc815\ub41c \uac83\uc744 \uae30\uc058\uac8c \uc0dd\uac01\ud569\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 InHerSight \ud504\ub85c\ud544\uc5d0\uc11c \ud655\uc778\ud574 \uc8fc\uc138\uc694.\uc790\uc138\ud788 \uc77d\uae30\ub370\uc774\ud130\uc758 \ubbf8\ub798\ub97c \ud568\uaed8 \ub9cc\ub4e4\uc5b4 \ubcf4\uc138\uc694\uc800\ud76c\ub294 \ub370\uc774\ud130\uc640 AI\ub97c \ub2e8\uc21c\ud654\ud558\uace0 \ubbfc\uc8fc\ud654\ud558\ub294 \uac83\uc744 \ubaa9\ud45c\ub85c \ud558\uba70, \uc774 \ubbf8\uc158\uc5d0\ub294 \uc5ec\ub7ec\ubd84\uc774 \uaf2d \ud544\uc694\ud569\ub2c8\ub2e4.\uae30\ud68c \uc54c\uc544\ubcf4\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-doxey\/#","text":"Matthew Doxey - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew DoxeySenior Epidemiologist at Washington State Department of HealthBack to speakersMatt Doxey is a public health data scientist with the Washington State Department of Health's Center for Data Science, where he leads data science and disease modeling initiatives. An epidemiologist by training with experience in global health initiatives and improving health outcomes in under-served communities, Matt is passionate about using innovative, data-driven methods and technologies to protect and enhance community and population health through better data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maria-vechtomova","text":"Maria Vechtomova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaria VechtomovaML Engineer at Ahold DelhaizeBack to speakersMaria is a Senior Machine Learning Engineer at Ahold Delhaize. Maria is bridging the gap between data scientists infra and IT teams at different brands and focuses on standardization of machine learning operations across all the brands within Ahold Delhaize. During more than nine years in Data and Analytics, Maria tried herself in different roles, from data scientist to a machine learning engineer, was part of teams in various domains, and have built broad knowledge. Maria believes that a model only starts living when it is in production. For this reason, last seven years, her focus was on the automation and standardization of processes related to machine learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ashwin-gangadhar","text":"Ashwin Gangadhar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAshwin GangadharSenior Solutions Architect at MongoDBBack to speakersAshwin is a Senior Solutions architect with MongoDB based in Bangalore India. He has 7+ years of experience in building data driven applications, involving complex architectural and scalability requirements in diverse industries. He has worked extensively in providing solutions for Search relevancy building and delivering solutions in ML \/ NLP modeling, data processing\/data mining pipelines.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/spark\/comparing-databricks-to-apache-spark","text":"Comparing Databricks to Apache Spark | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWComparing Apache Spark\u2122 and DatabricksApache Spark capabilities provide speed, ease of use and breadth of use benefits and include APIs supporting a range of use cases:Data integration and ETLInteractive analyticsMachine learning and advanced analyticsReal-time data processingDatabricks builds on top of Spark and adds:Highly reliable and performant data pipelinesProductive data science at scaleWant to learn more? Visit our\u00a0platform page.Feature ComparisonExpand all | Collapse all\u00a0column1column2column3\n\nDatabricks RuntimeBuilt on Apache Spark and optimized for performance\u00a0Learn moreNOYESManaged Delta LakeReliable and Performant Data LakesNO\nYES\nIntegrated WorkspaceInteractive Data Science and CollaborationNO\nYES\nProduction Jobs And WorkflowsData Pipelines and Workflow AutomationNO\nYES\nEnterprise SecurityEnd-to-End Data Security and Compliance Learn moreNO\nYES\nIntegrationsCompatible with Common Tools in the EcosystemNO\nYES\nExpert SupportUnparalled Support by the Leading Committers of Apache SparkNO\nYES\nAdditional ResourcesBlogBenchmarking Big Data SQL Platforms in the CloudCustomer StoryHow Hotels.com increased data analyzed by 20x without performance issuesDemoManaged Delta Lake: The best of data lakes, warehouses, and streaming systems.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adi-polak\/#","text":"Adi Polak - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdi PolakData & AI Technologist at TechnologistBack to speakersAdi is a world-leading specialist in the field of Data & AI. In her role as Vice President of DevEx at Treeverse, Adi contributes to lakeFS, Git for data project loved by Data & AI practitioners. In her work, she brings her vast industry research and engineering experience to bear in educating and helping teams design, architect, and build cost-effective data systems and machine learning pipelines that emphasize scalability, expertise, and business goals. Adi is a proud Databricks beacon, frequent worldwide presenter and the author of O\u2019Reilly\u2019s book, \u201cScaling Machine Learning with Spark.\u201dLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sanjeev-kumar\/#","text":"Sanjeev Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSanjeev KumarVice President, Data Analytics and AI at Gainwell TechnologiesBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/deep-dive-into-lakehouse-with-delta-lake-complimentary-training","text":"Lakehouse: Take a deep dive | DatabricksFree TrainingLakehouse: Take a deep diveWhat to know about Delta LakeGet an overview of data architecture concepts, an introduction to the Lakehouse paradigm and an in-depth look at Delta Lake features and functionality. You\u2019ll learn about applying software engineering principles with Databricks and discover how to serve data to end users through aggregate tables and Databricks SQL.Find out how to:Use Delta Lake to support your Lakehouse architectureBuild an end-to-end batch and streaming OLAP data pipeline using Delta LakeMake data available for consumption by downstream stakeholdersFollow Databricks best practices as you engineer a Delta design patternWe recommend this course to anyone who\u2019s familiar with data engineering concepts and has a basic knowledge of Delta Lake core features and use cases.Free On-Demand TrainingProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pulkit-chadha","text":"Pulkit Chadha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPulkit ChadhaSr. Solutions Architect at DatabricksBack to speakersPulkit Chadha is a Sr. Solutions Architect at Databricks. He has over 12 years of experience working in Data Engineering with expertise in building and optimizing data pipelines using various tools and technologies. Pulkit has worked with enterprises in various industries like Healthcare, Media and Entertainment, Hi-Tech, and Manufacturing providing data engineering solutions to meet enterprises' unique business needs. His work history includes the likes of Dell Services, Adobe, and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/12\/06\/deploying-dbt-on-databricks-just-got-even-simpler.html","text":"Deploying dbt on Databricks Just Got Even Simpler - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDeploying dbt on Databricks Just Got Even Simplerby Dave Eyler, Takuya Ueshin, Bilal Aslam and Shant HovsepianDecember 6, 2021 in Platform BlogShare this postAt Databricks, nothing makes us happier than making our users more productive, which is why we are delighted to announce a native adapter for dbt. It\u2019s now easier than ever to develop robust data pipelines on Databricks using SQL.dbt is a popular open source tool that lets a new breed of \u2018analytics engineer\u2019 build data pipelines using simple SQL. Everything is organized within directories, as plain text, making version control, deployment, and testability simple.With the new dedicated dbt-databricks adapter available in public preview today, dbt developers can get started by simply running pip install dbt-databricks. This package is open source, and built on the brilliant work led by dbt Labs and the other contributors who made dbt-spark possible. Not only did we streamline the installation by removing any dependency on ODBC drivers, we embraced dbt\u2019s \u201cconvention over configuration\u201d for maximum performance:dbt models use the Delta format by defaultIncremental models always leverage Delta Lake\u2019s MERGE statementExpensive queries like unique key generation are now accelerated with PhotonMore improvements to this adapter are coming as we continue to improve the overall integration between dbt and the Databricks Lakehouse Platform. With record-breaking performance and full support for standard SQL, it is the best place to run data warehousing workloads, including data pipelines built with dbt.We are also excited about the upcoming addition of dbt Cloud to Partner Connect, Databricks\u2019 one-stop shop for its customers to discover and integrate the best data and AI tools on the market. dbt Cloud is a hosted service made by dbt Labs, which helps data analysts and data engineers collaboratively build and productionize dbt projects. Coming in January, any Databricks customer will be able to start a free trial of dbt Cloud from Partner Connect and automatically integrate the two products. That said, the two products already work great together, and we encourage you to connect dbt Cloud to Databricks today.Speaking of dbt Labs, we hope to see you at their conference, Coalesce, which begins today! Reynold Xin will be having a fireside chat with Drew Banin, CPO for dbt Labs and Ricardo Portillo will be speaking about building data pipelines for Financial Services leveraging dbt and Databricks. You should definitely check it out and join the conversation on the dbt Community Slack in #coalesce-databricks. We look forward to your feedback!Stay tuned for more exciting updates on how Databricks works with dbt and watch our Github repository for new releases.Try Databricks for freeGet StartedRelated postsDeploying dbt on Databricks Just Got Even SimplerDecember 6, 2021 by Dave Eyler, Takuya Ueshin, Bilal Aslam and Shant Hovsepian in Platform Blog\nAt Databricks, nothing makes us happier than making our users more productive, which is why we are delighted to announce a native adapter...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks - Re\u00fana todas as suas an\u00e1lises e workloads de IA | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWAzure DatabricksDados e servi\u00e7o de IA da Databricks dispon\u00edveis por meio do Microsoft Azure para armazenar todos os seus dados em um lakehouse aberto e simples e consolidar todas as suas an\u00e1lises e workloads de IA.Introdu\u00e7\u00e3oAgendar uma demonstra\u00e7\u00e3oO Azure Databricks \u00e9 otimizado para o Azure e totalmente integrado ao Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI e outros servi\u00e7os do Azure para armazenar todos os seus dados em um lakehouse \u00fanico e aberto, reunindo todas as suas an\u00e1lises e workloads de IA.Simples\nRe\u00fana seus dados, an\u00e1lises e IA\nem uma plataforma comum para todos os casos de uso de dadosAberta\nUnifique seu ecossistema de dados\ncom c\u00f3digo aberto, padr\u00f5es e formatosColaborativo\nUnifique suas equipes de dados\npara colaborar em todos os workflows de dados e IAPor que o Azure Databricks?Workloads do Apache Spark\u2122 com desempenho 50 vezes melhor\nImplante clusters de compute que escalam automaticamente com o Spark altamente otimizado e que s\u00e3o executados at\u00e9 50 vezes mais r\u00e1pido.Saiba maisMilh\u00f5es de horas de servidor a cada dia\nO Azure Databricks \u00e9 usado por milhares de clientes que executam milh\u00f5es de horas de servidor todos os dias em mais de 34\u00a0regi\u00f5es do Azure.Saiba maisFacilidade de uso\nComece com um \u00fanico clique no Azure Portal, integre nativamente os servi\u00e7os de dados e os servi\u00e7os de seguran\u00e7a do Azure e aumente sua produtividade em 25% com data engineering e data science colaborativas.Saiba maisCasos de uso de cada setorServi\u00e7os financeirosSwiss Re\nAn\u00e1lise de dados unificada\u00a0para data engineering, data science e analistas.HSBC\nCriou uma\u00a0plataforma de pagamento digital\u00a0usando Azure Databricks.ABN AMROMelhorou os workflows de an\u00e1lise\u00a0ao facilitar a colabora\u00e7\u00e3o e a produ\u00e7\u00e3o de insights de IA enquanto aproveita os recursos avan\u00e7ados e automatizados de machine learning.Saiba maisVarejoSa\u00fade e ci\u00eancias da vidaParticipe de um evento do Azure DatabricksDatabricks, Microsoft e nossos parceiros t\u00eam o prazer de organizar esses eventos dedicados ao Azure Databricks. Sinta-se \u00e0 vontade para nos visitar em um evento perto de voc\u00ea para saber mais sobre o servi\u00e7o de dados e IA que mais cresce no Azure. A agenda e o formato variam de tempos em tempos. Portanto, verifique a p\u00e1gina espec\u00edfica do evento para obter mais detalhes.\u00a0Saiba maisOtimizado para AzureIntegra\u00e7\u00e3o perfeita com servi\u00e7os e armazenamentos de dados do Azure por meio de conectores especializados para acesso r\u00e1pido a dados e\u00a0gerenciamento simplificado\u00a0em seu ambiente. Isso facilita a configura\u00e7\u00e3o de\u00a0controles de seguran\u00e7a,\u00a0gerenciamento de ambientes e\u00a0processamento\u00a0de todos os seus dados do Azure.Saiba maisIntegra\u00e7\u00f5es em destaqueAzure Active DirectoryO Single Sign On\u00a0com o Azure Active Directory \u00e9 a melhor maneira de se conectar ao Azure Databricks. O Azure Databricks tamb\u00e9m \u00e9 compat\u00edvel com o\u00a0provisionamento automatizado de usu\u00e1rios\u00a0com o Azure AD para criar novos usu\u00e1rios, fornecer a eles o n\u00edvel certo de acesso e remover usu\u00e1rios para desprovisionar o acesso.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultRecursosArtigos t\u00e9cnicosAzure Databricks para data engineeringAzure Databricks: a melhor plataforma para executar ML e IATr\u00eas casos de uso no Azure DatabricksIntrodu\u00e7\u00e3o ao Apache Spark no Azure DatabricksV\u00eddeosAli Ghodsi e Rohan Kumar (CVP, Microsoft) em uma conversa no Keynote Data + AI Summit NA 2021Integra\u00e7\u00e3o demo com a nuvem do Azure DatabricksIngest\u00e3o de dados no Delta Lake no Azure DatabricksExplore seus dados usando o Databricks SQLe-booksQuadrante M\u00e1gico da Gartner de 2021 para Plataformas de Data Science e Machine LearningModern Cloud Data Platform for DummiesOito etapas para um desenvolvedor aprender Apache Spark\u2122 com Delta LakeApache Spark\u2122 Under the Hood: Introdu\u00e7\u00e3o \u00e0 arquitetura central e conceitos b\u00e1sicosTudo pronto para come\u00e7ar?Introdu\u00e7\u00e3oAgendar uma demonstra\u00e7\u00e3oProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pascal-van-bellen","text":"Pascal van Bellen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPascal van BellenSenior Consultant at ORAYLIS GmbHBack to speakersPascal van Bellen has been working in BI & BigData for more than 7 years. \nHaving already worked in this area for several years, he is involved in building solutions with Azure Databricks.\nPascal is a Senior Consultant at Oraylis GmbH in Germany and is responsible for implementation of large scale modern data platforms in various Azure cloud scenarios.\nAs a certified Databricks champion he is particularly interested in the development of large scale BigData use cases using Databricks and Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/krishti-bikal\/#","text":"Krishti Bikal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKrishti BikalSenior Executive - Director BI & Analytics at EmeraldBack to speakersKrishti is a Senior technical Executive at EmeraldX, where he is currently leading various Data Analytics projects. One of them is implementation of ThoughtSpot Everywhere for Emerald's Customer Hub. He has over 15 years of industry experience in Data Engineering and Analytics.\nHe holds B. Tech in Mechanical Engineering from NIT Patna, India and Masters in MIS from University of Illinois, USA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/darth-vader\/#","text":"Darth Vader - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDarth VaderSith Lord at The Galactic EmpireBack to speakersOnce the heroic Jedi Knight named Anakin Skywalker, Darth Vader was seduced by the dark side of the Force. Forever scarred by his defeat on Mustafar, Vader was transformed into a cybernetically-enhanced Sith Lord. At the dawn of the Empire, Vader led the Empire\u2019s eradication of the Jedi Order and the search for survivors. He remained in service of the Emperor -- the evil Darth Sidious -- for decades, enforcing his Master\u2019s will and seeking to crush the Rebel Alliance and other detractors.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leo-duncan","text":"Leo Duncan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeo DuncanSr. Solutions Architect at Kyvos Insights Inc.Back to speakersLeo Duncan is a Senior Solutions Architect at Kyvos Insights Inc. With over 18 years of analytics experience, he has designed and developed game-changing BI solutions for some of the world's most recognized brands. Leo's innovative approach and strategic vision have earned him a reputation as an analytics genius, empowering organizations to make informed, data-driven decisions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/behzad-bordbar","text":"Behzad Bordbar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBehzad BordbarLead Data Scientist at Marks & SpencerBack to speakersBehzad started working at M&S in Jan 2021 as Lead Data Scientist. As part of the Data Science Retails team, he is involved in the digital transformation of Retail operations utilizing Machine Learning and Artificial Intelligence. He has a PhD in mathematics and over 20 years of experience solving challenging and complex business problems using innovative data solutions. He has published over 120 technical and scientific papers and contributed to several open-source projects.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-roome\/#","text":"Paul Roome - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul RoomeStaff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Databricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30 | DatabricksDatabricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30AWS, Microsoft Azure \ub610\ub294 Google Cloud \uc911 \uc6d0\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4\uc5d0\uc11c 14\uc77c \ub3d9\uc548 Databricks \ud50c\ub7ab\ud3fc \uc804\uccb4\ub97c \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud574 \ubcf4\uc138\uc694.\ub370\uc774\ud130 \uc218\uc9d1 \ub2e8\uc21c\ud654 \ubc0f ETL \uc790\ub3d9\ud654\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uc218\ubc31 \uac1c\uc758 \uc18c\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574 \ubcf4\uc138\uc694. \uac04\ub2e8\ud55c \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \uc5b8\uc5b4\ub85c \ud611\uc5c5\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uacf5\ub3d9 \uc800\uc791, \uc790\ub3d9 \ubc84\uc804 \uad00\ub9ac, Git \ud1b5\ud569, RBAC\ub97c \ud65c\uc6a9\ud558\uc5ec Python, R, Scala \ubc0f SQL\ub85c \ucf54\ub529\ud558\uc138\uc694.\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 12\ubc30 \ub354 \uc6b0\uc218\ud55c \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc804 \uc138\uacc4 7,000\uac1c \uace0\uac1d\uc0ac\uac00 BI\ubd80\ud130 AI\uc5d0 \uc774\ub974\ub294 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc704\ud574\uc11c Databricks \ub97c \uc120\ud0dd\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.Databricks \uacc4\uc815 \uc0dd\uc131\ud558\uae301\/2\uc774\ub984\uc131\ud68c\uc0ac \uc774\uba54\uc77c\ud68c\uc0ac\uc9c1\ud568\uc804\ud654\ubc88\ud638(\uc120\ud0dd\uc0ac\ud56d)\ubcf4\uae30 \uc911\uc5d0\uc11c \uc120\ud0dd\ud558\uc138\uc694\uad6d\uac00\uacc4\uc18d\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0(\uc5c5\ub370\uc774\ud2b8\ub428)\uc774\uc6a9\uc57d\uad00\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/innovate-speed-data?itm_data=home-navmenu-solution-innovatespeeddata","text":"Innovate at the speed of data | DatabricksOn DemandInnovate at the speed of dataExplore the Databricks Lakehouse for ManufacturingAvailable on demandLegacy tools and data silos hinder the analytics that help you optimize your supply chain. They also prevent the single view of the customer that drives innovation. That\u2019s why many manufacturers are migrating to the Databricks Lakehouse for Manufacturing. With this platform, they\u2019re delivering precise service outcomes in the field, optimizing supply chain operations, boosting productivity and innovating at the speed of data.Watch to learn more about the lakehouse and how Corning is using the lakehouse to make critical decisions that minimize manual inspections, lower shipping costs and increase customer satisfaction.You\u2019ll learn how the lakehouse can help you achieve:90% lower cost for new manufacturing lines50x faster time to insight5%-10% reduction in unplanned downtime and costStreaming IoT data from millions of assetsSpeakersDenis KamotskyPrincipal Software EngineerCorningShiv TrisalGlobal Industry Director - Manufacturing & LogisticsDatabricksSam SteinyPrincipal Industry Marketing Manager - Retail & ManufacturingDatabricksJoin usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/10\/20\/detecting-at-risk-patients-with-real-world-data.html","text":"How to Detect At-risk Patients with Real World Data - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDetecting At-risk Patients with Real World DataHow to use the Machine Learning Runtime and MLflow on top of a health Delta Lake to predict patient diseaseby Amir Kermany and Frank Austin NothaftOctober 20, 2020 in Engineering BlogShare this postWith the rise of low cost genome sequencing and AI-enabled medical imaging, there has been substantial interest in precision medicine. In precision medicine, we aim to use data and AI to come up with the best treatment for a disease. While precision medicine has improved outcomes for patients diagnosed with rare diseases and cancers, precision medicine is reactive: the patient has to be sick for precision medicine to be deployed.When we look at healthcare spending and outcomes, there is a tremendous opportunity to improve cost-of-care and quality of living by preventing chronic conditions such as diabetes, heart disease, or substance use disorders. In the United States, 7 out of 10 deaths and 85% of healthcare spending is driven by chronic conditions, and similar trends are found in Europe and Southeast Asia. Noncommunicable diseases are generally preventable through patient education and by addressing underlying issues that drive the chronic condition. These issues can include underlying biological risk factors such as known genetic risks that drive neurological conditions, socioeconomic factors like environmental pollution or lack of access to healthy food\/preventative care, and behavioral risks such as smoking status, alcohol consumption, or having a sedentary lifestyle.Precision prevention is focused on using data to identify patient populations at risk of developing a disease, and then providing interventions that reduce disease risk. An intervention might include a digital app that remotely monitors at-risk patients and provides lifestyle and treatment recommendations, increased monitoring of disease status, or offering supplemental preventative care. However, deploying these interventions first depends on identifying the patients at risk.One of the most powerful tools for identifying patients at risk is the use of real world data (RWD), a term that collectively refers to data generated by the healthcare ecosystem, such as electronic medical records (EMR) and health records (EHR) from hospitalizations, clinical practices, pharmacies, healthcare providers, and increasingly data collected from other sources such as genomics, social media, and wearables. In our last blog we demonstrated how to build a clinical data lake from EHR data. In this blog, we build on that by using the Databricks Unified Data Analytics Platform to track a patient\u2019s journey and create a machine learning model. Using this model, given a patient\u2019s encounter history and demographics information, we can assess the risk of a patient for a given condition within a given window of time. In this example, we will look at drug overuse, an important topic given the broad range of poor health outcomes driven by substance use disorders. By tracking our models using MLflow, we make it easy to track how models have changed over time, adding confidence to the process of deploying a model into patient care.Disease prediction using machine learning on DatabricksData preparationTo train a model to predict risk at a given time, we need a dataset that captures relevant demographic information about the patient (such as age at time of encounter, ethnicity etc) as well as time series data about the patient\u2019s diagnostic history. We can then use this data to train a model that learns the diagnoses and demographic risks that influence the patient\u2019s likelihood of being diagnosed with a disease in the upcoming time period.\nFigure 1: Data schemas and relationships between tables extracted from the EHRTo train this model, we can leverage the patient's encounter records and demographic information, as would be available in an electronic health record (EHR). Figure 1 depicts the tables we will use in our workflow. These tables were prepared using the notebooks from our previous blog. We will proceed to load encounters, organizations and patient data (with obfuscated PII information) from Delta Lake and create a dataframe of all patient encounters along with patient demographic information.\npatient_encounters = (\n    encounters\n    .join(patients, ['PATIENT'])\n    .join(organizations, ['ORGANIZATION'])\n)\ndisplay(patient_encounters.filter('REASONDESCRIPTION IS NOT NULL').limit(10))\nBased on the target condition, we also select a set of patients that qualify to be included in the training data. Namely, we include cases, patients that have been diagnosed with the disease at least once through their encounter history, and an equal number of controls, patients without any history of the disease.\npositive_patients = (\n    patient_encounters\n    .select('PATIENT')\n    .where(lower(\"REASONDESCRIPTION\").like(\"%{}%\".format(condition)))\n    .dropDuplicates()\n    .withColumn('is_positive',lit(True))\n)\nnegative_patients = (\n    all_patients\n    .join(positive_patients,on=['PATIENT'],how='left_anti')\n    .limit(positive_patients.count())\n    .withColumn('is_positive',lit(False))\n)\npatients_to_study = positive_patients.union(negative_patients)\nNow we limit our set of encounters to patients included in the study.\nqualified_patient_encounters_df = (\n    patient_encounters\n    .join(patients_to_study,on=['PATIENT'])\n    .filter(\"DESCRIPTION is not NUll\")\n)    \nNow that we have the records of interest, our next step is to add features. For this forecasting task, in addition to demographic information, we choose the total number of times having been diagnosed with the condition or any known coexisting conditions (comorbidities) and the number of previous encounters as historical context for a given encounter.Although for most diseases there is extensive literature on comorbid conditions, we can also leverage the data in our real world dataset to identify comorbidities associated with the target condition.\ncomorbid_conditions = (\n    positive_patients.join(patient_encounters, ['PATIENT'])\n    .where(col('REASONDESCRIPTION').isNotNull())\n    .dropDuplicates(['PATIENT', 'REASONDESCRIPTION'])\n    .groupBy('REASONDESCRIPTION').count()\n    .orderBy('count', ascending=False)\n    .limit(num_conditions)\n    )\nIn our code, we use notebook widgets to specify the number of comorbidities to include, as well as the length of time (in days) to look across encounters. These parameters are logged using MLflow\u2019s tracking API.Now we need to add comorbidity features to each encounter. Corresponding to each comorbidity we add a column that indicates how many times the condition of interest has been observed in the past, i.e.whereWe add these features in two steps. First, we define a function that adds comorbidity indicator functions (i.e. xi,c):\ndef add_comorbidities(qualified_patient_encounters_df,comorbidity_list):\noutput_df = qualified_patient_encounters_df\nidx = 0\nfor comorbidity in comorbidity_list:\n    output_df = (\n        output_df\n        .withColumn(\"comorbidity_%d\" % idx, (output_df['REASONDESCRIPTION'].like('%' + comorbidity['REASONDESCRIPTION'] + '%')).cast('int'))\n        .withColumn(\"comorbidity_%d\"  % idx,coalesce(col(\"comorbidity_%d\" % idx),lit(0))) # replacing null values with 0\n        .cache()\n    )\n    idx += 1\nreturn(output_df)\nAnd then we sum these indicator functions over a contiguous range of days using Spark SQL\u2019s powerful support for window functions:\ndef add_recent_encounters(encounter_features):\n  lowest_date = (\n    encounter_features\n    .select('START_TIME')\n    .orderBy('START_TIME')\n    .limit(1)\n    .withColumnRenamed('START_TIME', 'EARLIEST_TIME')\n    )\n  output_df = (\n    encounter_features\n    .crossJoin(lowest_date)\n    .withColumn(\"day\", datediff(col('START_TIME'), col('EARLIEST_TIME')))\n    .withColumn(\"patient_age\", datediff(col('START_TIME'), col('BIRTHDATE')))\n    )\n  w = (\n    Window.orderBy(output_df['day'])\n    .partitionBy(output_df['PATIENT'])\n    .rangeBetween(-int(num_days), -1)\n  )\n  for comorbidity_idx in range(num_conditions):\n    col_name = \"recent_%d\" % comorbidity_idx\n    \n    output_df = (\n        output_df\n        .withColumn(col_name, sum(col(\"comorbidity_%d\" % comorbidity_idx)).over(w))\n        .withColumn(col_name,coalesce(col(col_name),lit(0)))\n    )\n  return(output_df)\nAfter adding comorbidity features, we need to add the target variable, which indicates whether the patient is diagnosed with the target condition in a given window of time in the future (for example a month after the current encounter). The logic of this operation is very similar to the previous step, with the difference that the window of time covers future events. We only use a binary label, indicating whether the diagnosis we are interested in will occur in the future or not.\ndef add_label(encounter_features,num_days_future):\n  w = (\n    Window.orderBy(encounter_features['day'])\n    .partitionBy(encounter_features['PATIENT'])\n    .rangeBetween(0,num_days_future)\n  )\n  output_df = (\n    encounter_features\n    .withColumn('label', max(col(\"comorbidity_0\")).over(w))\n    .withColumn('label',coalesce(col('label'),lit(0)))\n  )\n    return(output_df)\nNow we write these features into a feature store within Delta Lake. To ensure reproducibility, we add the mlflow experiment ID and the run ID as a column to the feature store. The advantage of this approach is that we receive more data, we can add new features to the featurestore that can be re-used to refer to in the future.Controlling for quality issues in our dataBefore we move ahead with the training task, we take a look at the data to see how different labels are distributed among classes. In many applications of binary classification, one class can be rare, for example in disease prediction. This class imbalance will have a negative impact on the learning process. During the estimation process, the model tends to focus on the majority class at the expense of rare events. Moreover, the evaluation process is also compromised. For example, in an imbalance dataset with 0\/1 labels distributed as 95% and %5 respectively,\u00a0 a model that always predicts 0, would have an accuracy of 95%. If the labels are imbalanced, then we need to apply one of the common techniques for correcting for imbalanced data.Looking at our training data, we see (Figure 2) that this is a very imbalanced dataset: over 95% of the observed time windows do not show evidence of a diagnosis. To adjust for imbalance, we can either downsample the control class or generate synthetic samples. This choice depends on the dataset size and the number of features. In this example, we downsample the majority class to obtain a balanced dataset. Note that in practice, you can choose a combination of methods, for example downsample the majority class and also assign class weights in your training algorithm.\ndf1 = dataset_df.filter('label==1')\nn_df1=df1.count()\ndf2 = dataset_df.filter('label==0').sample(False,0.9).limit(n_df1)\ntraining_dataset_df = df1.union(df2).sample(False,1.0)\ndisplay(training_dataset_df.groupBy('label').count())\nModel trainingTo train the model, we augment our conditions with a subset of demographic and comorbidity features, apply labels to each observation, and pass this data to a model for training downstream. For example, here we augment our recent diagnosed comorbidities with Encounter Class (e.g., was this appointment for preventative care or was it an ER visit?, ), and the cost of the visits, and for demographic information, we choose Race, Gender, Zip and the patient's age at the time of the encounter.Most often, although the original clinical data can add up to terabytes, after performing filtering and limiting records based on inclusion\/exclusion criteria, we end up with a dataset that can be trained on a single machine. We can easily transform spark dataframes to pandas dataframes and train a model based on any algorithm of choice. When using the Databricks ML runtime, we have access to a wide range of open ML libraries readily available.Any machine learning algorithm takes a set of parameters (hyper parameters), and depending on the input parameters the score can change. In addition, in some cases wrong parameters or algorithms can result in overfitting. To ensure that the model performs well,\u00a0 we use hyperparameter tuning to choose the best model architecture and then we will train the final model by specifying the parameters that were obtained from this step.To perform model tuning, we first need to pre-process the data. In this dataset, in addition to numeric features (counts of recent comorbidities for example), we also have the categorical demographic data that we would like to use. For categorical data, the best approach is to use one-hot-encoding. There are two main reasons for this: first, most classifiers (logistic regression in this case), operate on numeric features. Second, if we simply convert categorical variables to numeric indices, it would introduce ordinality in our data which can mislead the classifier: for example, if we convert states names to indices, e.g. California to 5 and New York to 23, then New York becomes \u201cbigger\u201d than California. While this reflects the index of each state name in an alphabetized list, in the context of our model, this ordering does not mean anything. One-hot-encoding eliminates this effect.The pre-processing step in this case does not take any input parameters and\u00a0 hyperparameters only affect the classifier and not the preprocessing part. Hence, we separately perform pre-processing and then use the resulting dataset for model tuning:\nfrom sklearn.preprocessing import OneHotEncoder\nimport numpy as np\ndef pre_process(training_dataset_pdf):\n    X_pdf=training_dataset_pdf.drop('label',axis=1)\n    y_pdf=training_dataset_pdf['label']\n    onehotencoder = OneHotEncoder(handle_unknown='ignore')\n    one_hot_model = onehotencoder.fit(X_pdf.values)\n    X=one_hot_model.transform(X_pdf)\n    y=y_pdf.values\n    return(X,y)\nNext, we would like to choose the best parameters to the model. For this classification, we use LogisticRegression with elastic net penalization. Note that after applying one-hot-encoding, depending on the cardinality of the categorical variable in question, we can end up with many features which can surpass the number of samples. To avoid overfitting for such problems, a penalty is applied to the objective function. The advanaget of elastic net regularization is that it combines two penalization techniques (LASSO and Ridge Regression) and the degree of the mixture can be controlled by a single variable, during hyperparameter tuning.To improve on the model, we search a grid of hyperparameters using hyperopt to find the best parameters. In addition, we use the SparkTrials mode of hyperopt to perform the hyperparameter search in parallel.This process leverages Databricks\u2019 managed MLflow to automatically log parameters and metrics corresponding to each hyperparameter run. To validate each set of parameters, we use a k-fold cross validation skim using F1 score as the metric to assess the model. Note that since k-fold cross validation generates multiple values, we choose the minimum of the scores (the worst case scenario) and try to maximize that when we use hyperopt.\nfrom math import exp\ndef params_to_lr(params):\n    return {\n    'penalty':          'elasticnet',\n    'multi_class':      'ovr',\n    'random_state':     43,\n    'n_jobs':           -1,\n    'solver':           'saga',\n    'tol':              exp(params['tol']), # exp() here because hyperparams are in log space\n    'C':                exp(params['C']),\n    'l1_ratio':         exp(params['l1_ratio'])\n    }\ndef tune_model(params):\n    with mlflow.start_run(run_name='tunning-logistic-regression',nested=True) as run:\n    clf = LogisticRegression(**params_to_lr(params)).fit(X, y)\n    loss = - cross_val_score(clf, X, y,n_jobs=-1, scoring='f1').min()\n    return {'status': STATUS_OK, 'loss': loss}\nTo improve our search over the space, we choose the grid of parameters in logspace and define a transformation function to convert the suggested parameters by hyperopt. For a great overview of the approach and why we chose to define the hyperparameter space like this, look at this talk that covers how you can manage the end-to-end ML life cycle on Databricks.\nfrom hyperopt import fmin, hp, tpe, SparkTrials, STATUS_OK\nsearch_space = {\n    # use uniform over loguniform here simply to make metrics show up better in mlflow comparison, in logspace\n    'tol':                  hp.uniform('tol', -3, 0),\n    'C':                    hp.uniform('C', -2, 0),\n    'l1_ratio':             hp.uniform('l1_ratio', -3, -1),\n}\nspark_trials = SparkTrials(parallelism=2)\nbest_params = fmin(fn=tune_model, space=search_space, algo=tpe.suggest, max_evals=32, rstate=np.random.RandomState(43), trials=spark_trials)\nThe outcome of this run is the best parameters, assessed based on the F1-score from our cross validation.\nparams_to_lr(best_params)\nOut[46]: {'penalty': 'elasticnet',\n    'multi_class': 'ovr',\n    'random_state': 43,\n    'n_jobs': -1,\n    'solver': 'saga',\n    'tol': 0.06555920596441883,\n    'C': 0.17868321158011416,\n    'l1_ratio': 0.27598949120226646}\nNow let\u2019s take a look at the MLflow dashboard. MLflow automatically groups all runs of the hyperopt together and we can use a variety of plots to inspect the impact of each hyperparameter on the loss function, as shown in Figure 3. This is particularly important for getting a better understanding of the behavior of our model and the effect of the hyperparameters. For example, we noted that lower values for C, the inverse of regularization strength, result in higher values for F1.\nFig 3. Parallel coordinates plots for our models in MLflow.After finding the optimal parameter combinations, we train a binary classifier with the optimal hyperparameters and log the model using MLflow. MLflow\u2019s model api makes it easy to store a model, regardless of the underlying library that was used for training, as a python function that can later be called during model scoring. To help with model discoverability, we log the model with a name associated with the target condition (for example in this case, \u201cdrug-overdose\u201d).\nimport mlflow.sklearn\nimport matplotlib.pyplot as plt\nfrom sklearn.pipeline import Pipeline\nfrom mlflow.models.signature import infer_signature\n## since we want the model to output probabilities (risk) rather than predicted labels, we overwrite\n## mlflow.pyfun's predict method:\nclass SklearnModelWrapper(mlflow.pyfunc.PythonModel):\n    def __init__(self, model):\n    self.model = model\n    \n    def predict(self, context, model_input):\n    return self.model.predict_proba(model_input)[:,1]\ndef train(params):\n    with mlflow.start_run(run_name='training-logistic-regression',nested=True) as run:\n    mlflow.log_params(params_to_lr(params))\n    \n    X_arr=training_dataset_pdf.drop('label',axis=1).values\n    y_arr=training_dataset_pdf['label'].values\n    \n    ohe = OneHotEncoder(handle_unknown='ignore')\n    clf = LogisticRegression(**params_to_lr(params)).fit(X, y)\n    \n    pipe = Pipeline([('one-hot', ohe), ('clf', clf)])\n    \n    lr_model = pipe.fit(X_arr, y_arr)\n    \n    score=cross_val_score(clf, ohe.transform(X_arr), y_arr,n_jobs=-1, scoring='accuracy').mean()\n    wrapped_lr_model = SklearnModelWrapper(lr_model)\n    \n    model_name= '-'.join(condition.split())   \n    mlflow.log_metric('accuracy',score)\n    mlflow.pyfunc.log_model(model_name, python_model=wrapped_lr_model)\n    displayHTML('The model accuracy is: <b style=\"color: tomato;\"> %s <\/b>'%(score))\n    return(mlflow.active_run().info)\nNow, we can train the model by passing the best params obtained from the previous step.Note that for model training, we have included preprocessing (one hot encoding) as part of the sklearn pipeline and log the encoder and classifier as one model. In the next step, we can simply call the model on patient data and assess their risk.Model deployment and productionalizationAfter training the model and logging it to MLflow, the next step is to use the model for scoring new data. One of the features of MLflow is that you can search through experiments based on different tags. For example, in this case we use the run name that was specified during model training to retrieve the artifact URI of the trained models. We can then order the retrieved experiments based on key metrics.\nimport mlflow\nbest_run=mlflow.search_runs(filter_string=\"tags.mlflow.runName = 'training-logistic-regression'\",order_by=['metrics.accuracy DESC']).iloc[0]\nmodel_name='drug-overdose'\nclf=mlflow.pyfunc.load_model(model_uri=\"%s\/%s\"%(best_run.artifact_uri,model_name))\nclf_udf=mlflow.pyfunc.spark_udf(spark, model_uri=\"%s\/%s\"%(best_run.artifact_uri,model_name))   \nOnce we have chosen a specific model, we can then load the model by specifying the model URI and name:We can also use Databricks\u2019s model registry to manage model versions, production lifecycle and also easy model serving.Translating disease prediction into precision preventionIn this blog, we walked through the need for a precision prevention system that identifies clinical and demographic covariates that drive the onset of chronic conditions. We then looked at an end-to-end machine learning workflow that used simulated data from an EHR to identify patients who were at risk of drug overdose. At the end of this workflow, we were able to export the ML model we trained from MLflow, and we applied it to a new stream of patient data.While this model is informative, it doesn\u2019t have impact until translated into practice. In real world practice, we have worked with a number of customers to deploy these and similar systems into production. For instance, at the Medical University of South Carolina, they were able to deploy live-streaming pipelines that processed EHR data to identify patients at risk of sepsis. This led to detection of sepsis-related patient decline 8 hours in advance. In a similar system at INTEGRIS Health, EHR data was monitored for emerging signs of pressure ulcer development. In both settings, whenever a patient was identified, a care team was alerted to their condition. In the health insurance setting, we have worked with Optum to deploy a similar model. They were able to develop a disease prediction engine that used recurrent neural networks in a long-term short-term architecture to identify disease progression with good generalization across nine different disease areas. This model was used to align patients with preventative care pathways, leading to improved outcomes and cost-of-care for chronic disease patients.While most of our blog has focused on the use of disease prediction algorithms in healthcare settings, there is also a strong opportunity to build and deploy these models in a pharmaceutical setting. Disease prediction models can provide insights into how drugs are being used in a postmarket setting, and even detect previously undetected protective effects that can inform label expansion efforts. Additionally, disease prediction models can be useful when looking at clinical trial enrollment for rare\u2014or otherwise underdiagnosed\u2014diseases. By creating a model that looks at patients who were misdiagnosed prior to receiving a rare disease diagnosis, we can create educational material that educates clinicians about common misdiagnosis patterns and hopefully create trial inclusion criteria that leads to increased trial enrollment and higher efficacy.Get started With precision prevention on a health Delta LakeIn this blog, we demonstrated how to use machine learning on real-world data to identify patients at risk of developing a chronic disease. To learn more about using Delta Lake to store and process clinical datasets, download our free eBook on working with real world clinical datasets. You can also start a free trial today using the patient risk scoring notebooks from this blog.Try Databricks for freeGet StartedRelated postsDetecting At-risk Patients with Real World DataOctober 20, 2020 by Amir Kermany and Frank Austin Nothaft in Engineering Blog\nWith the rise of low cost genome sequencing and AI-enabled medical imaging, there has been substantial interest in precision medicine. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mitch-ertle","text":"Mitch Ertle - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMitch ErtlePartner Solutions Engineer at Sigma ComputingBack to speakersMitch Ertle is an experienced data practitioner with over a decade of experience in Data Analytics. Prior to joining Sigma, Mitch spent three years leading data teams on Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/product\/data-lakehouse","text":"\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\uff5c\u30c7\u30e2\u306e\u3054\u4f9d\u983c\u3092\u627f\u3063\u3066\u304a\u308a\u307e\u3059 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister now\u30b7\u30f3\u30d7\u30eb\u3001\u30aa\u30fc\u30d7\u30f3\u3001\u30de\u30eb\u30c1\u30af\u30e9\u30a6\u30c9Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/br\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDelta SharingUm padr\u00e3o aberto para compartilhamento seguro de ativos de dadosCome\u00e7arAssista \u00e0 demonstra\u00e7\u00e3oO Delta Sharing da Databricks \u00e9 uma solu\u00e7\u00e3o aberta para compartilhar com seguran\u00e7a dados em tempo real de seu lakehouse para qualquer plataforma de computa\u00e7\u00e3o.Principais benef\u00edciosCompartilhamento aberto entre plataformasEvite amarras de fornecedores e compartilhe facilmente dados existentes nos formatos Delta Lake e Apache Parquet para qualquer plataforma de dados.Compartilhamento de dados em tempo real sem replica\u00e7\u00e3oCompartilhe dados em tempo real entre plataformas, nuvens ou regi\u00f5es sem precisar replic\u00e1-los ou copi\u00e1-los para outro sistema.Governan\u00e7a centralizadaCentralize o gerenciamento, controle, auditoria e rastreamento do uso de dados compartilhados em uma \u00fanica plataforma.Marketplace para produtos de dadosCrie e entregue produtos de dados, incluindo conjuntos de dados, modelos de ML e notebooks uma vez e distribua livremente em um marketplace central.Salas limpas de dados que protegem a privacidadeColabore facilmente com seus clientes e parceiros em qualquer nuvem por meio de um ambiente seguro, protegendo a privacidade dos dados.Como funcionaIntegra\u00e7\u00e3o nativa com a plataforma da DatabricksA integra\u00e7\u00e3o nativa com o Unity Catalog\u00a0permite gerenciar e auditar centralmente os dados compartilhados entre as organiza\u00e7\u00f5es. Ela tamb\u00e9m permite que voc\u00ea compartilhe com confian\u00e7a ativos de dados com fornecedores e parceiros para uma melhor coordena\u00e7\u00e3o dos seus neg\u00f3cios, atendendo aos crit\u00e9rios de seguran\u00e7a e conformidade.Gerencie compartilhamentos facilmenteCrie e gerencie provedores, destinat\u00e1rios e compartilhamentos com uma interface de usu\u00e1rio f\u00e1cil de usar, comandos SQL ou APIs REST com suporte completo para CLI e Terraform.Descubra e acesse produtos de dados por meio de um marketplace abertoDescubra, avalie e acesse com facilidade produtos de dados, incluindo conjuntos de dados, modelos de machine learning, dashboards e notebooks, de qualquer lugar, sem precisar estar na plataforma da Databricks.Salas limpas de dados que protegem a privacidadeColabore com seus clientes e parceiros em qualquer nuvem em um ambiente seguro. Compartilhe dados de seus data lakes com seguran\u00e7a, sem replica\u00e7\u00e3o. Encontre colaboradores na nuvem de sua prefer\u00eancia e ofere\u00e7a a flexibilidade de executar c\u00e1lculos complexos e cargas de trabalho em qualquer linguagem: SQL, R, Scala, Java e Python. Guie colaboradores em casos de uso comuns utilizando modelos pr\u00e9 definidos, notebooks e dashboards para acelerar o tempo at\u00e9 insights.Casos de usoCompartilhamento entre diferentes divis\u00f5es internasCrie um Data Mesh com Delta Sharing para compartilhar dados com seguran\u00e7a entre diferentes unidades de neg\u00f3cios e subsidi\u00e1rias em nuvens ou regi\u00f5es sem copiar ou replicar os dados.Compartilhamento B2BMonetiza\u00e7\u00e3o de dadosClientes\u201cO Delta Sharing nos ajudou a simplificar nosso processo de entrega para grandes conjuntos de dados. Assim, nossos clientes podem usar seu pr\u00f3prio ambiente de computa\u00e7\u00e3o para consultar dados recentes, classificados e selecionados com pouco ou nenhum esfor\u00e7o de integra\u00e7\u00e3o. Quanto a n\u00f3s, podemos continuar expandindo nosso cat\u00e1logo de produtos de dados \u00fanicos e de alta qualidade.\u201d\u2014 William Dague, Head de dados alternativos\u201cComo uma empresa orientada por dados, devemos garantir que nossos clientes tenham acesso aos nossos conjuntos de dados. A Plataforma Databricks Lakehouse com o Delta Sharing se alinha perfeitamente a esse processo para nos permitir alcan\u00e7ar com seguran\u00e7a uma base de usu\u00e1rios muito maior, independentemente da nuvem ou plataforma utilizada.\u201d\u2014 Felix Cheung, vice-presidente de engenharia\u201cCom os poderosos recursos do Delta Sharing da Databricks, a Pumpjack Dataworks tem uma experi\u00eancia de onboarding mais suave. N\u00e3o precisamos mais exportar, importar e remodelar os dados: para nossos clientes, isso \u00e9 um valor agregado imediato. De fato, a acelera\u00e7\u00e3o dos resultados gera mais oportunidades de neg\u00f3cios para nossos clientes e seus parceiros.\u201d\u2014 Corey Zwart, diretor de engenharia\u201cCom o Delta Sharing, nossos clientes t\u00eam acesso a conjuntos de dados selecionados quase instantaneamente e podem integr\u00e1-los \u00e0s ferramentas anal\u00edticas de sua escolha. As conversas com nossos clientes est\u00e3o ficando mais ricas: discuss\u00f5es de alto n\u00edvel sobre an\u00e1lises substituem as sess\u00f5es t\u00e9cnicas de perguntas e respostas sobre a ingest\u00e3o de dados e nos permitem criar experi\u00eancias bem-sucedidas para os clientes. Nosso relacionamento com os clientes est\u00e1 mudando. Estamos nos esfor\u00e7ando para fornecer novos conjuntos de dados e atualizar os existentes por meio do Delta Sharing para manter os clientes a par das principais tend\u00eancias em seus setores.\u201d\u2014 Anup Segu, tech lead de engenharia de dadosUm ecossistema abertoAcesse a vers\u00e3o publicada mais recente diretamente do provedor, em ferramentas f\u00e1ceis de usar com SQL, Python ou BI.RecursosApresenta\u00e7\u00f5es e webinars[Apresenta\u00e7\u00e3o] Governan\u00e7a de dados e compartilhamento de lakehouse no Data + AI Summit 2022[Webinar sob demanda] Acelere o valor comercial com o Delta SharingBlogsAn\u00fancio da disponibilidade geral do Delta SharingDelta Sharing: Um protocolo aberto para o compartilhamento seguro de dadosTr\u00eas principais casos de uso para compartilhar dados com o Delta SharingVis\u00e3o geral da solu\u00e7\u00e3o e e-books[e-book] Explore a nova solu\u00e7\u00e3o de Delta SharingDelta Sharing: Um padr\u00e3o aberto para o compartilhamento seguro de dadosAscens\u00e3o do Data Lakehouse por Bill Inmon, pai do data warehouseTudo pronto para come\u00e7ar a usar a Databricks?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/de\/trust?itm_data=menu-item-securitytrustcenter","text":"Security & Trust Center \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueWir wissen, dass Daten zu Ihren wertvollsten G\u00fctern geh\u00f6ren und jederzeit gesch\u00fctzt werden m\u00fcssen. Deshalb ist Sicherheit in jeden Layer der Lakehouse-Plattform von Databricks integriert. Dank unserer Transparenz k\u00f6nnen Sie Ihre rechtlichen Anforderungen erf\u00fcllen und gleichzeitig die Vorteile unserer Plattform nutzen.Wir wissen, dass Daten zu Ihren wertvollsten G\u00fctern geh\u00f6ren und jederzeit gesch\u00fctzt werden m\u00fcssen. Deshalb ist Sicherheit in jeden Layer der Lakehouse-Plattform von Databricks integriert. Dank unserer Transparenz k\u00f6nnen Sie Ihre rechtlichen Anforderungen erf\u00fcllen und gleichzeitig die Vorteile unserer Plattform nutzen.Vertrauensw\u00fcrdige PlattformVertrauen entsteht durch Transparenz. Finden Sie heraus, wie wir mithilfe branchenweit f\u00fchrender Praktiken (z.\u00a0B. Penetrationstests, Sicherheitsl\u00fcckenmanagement und sichere Softwareentwicklung) die Databricks Lakehouse-Plattform zuverl\u00e4ssig absichern.Mehr InformationenSicherheitsmerkmaleWir implementieren umfassende Sicherheitsfunktionen zum Schutz Ihrer Daten und Workloads, beispielsweise Verschl\u00fcsselung, Netzwerkkontrollen, Audits, Identit\u00e4tsintegration, Zugriffssteuerung und Data Governance.Mehr InformationenComplianceBranchen\u00fcbergreifend vertrauen Kunden auf der ganzen Welt auf die Lakehouse-Plattform von Databricks. Wir verf\u00fcgen \u00fcber alle erforderlichen Zertifizierungen und Bescheinigungen, um auch die speziellen Anforderungen stark regulierter Branchen zu erf\u00fcllen.Mehr InformationenDatenschutzWir w\u00fcrdigen den Schutz Ihrer Daten und wissen, dass er f\u00fcr Ihr Unternehmen und Ihre Kunden gleicherma\u00dfen zwingend notwendig ist. Databricks unterst\u00fctzt Sie bei der Einhaltung von Datenschutzgesetzen und der Erf\u00fcllung beh\u00f6rdlicher Anforderungen.Mehr InformationenMit unserem Due-Diligence-Paket, das Dokumentations- und Compliance-Materialien enth\u00e4lt, f\u00fchren Sie Sicherheits\u00fcberpr\u00fcfungen von Databricks selbst durch.Due-Diligence-PaketProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shawn-benjamin","text":"Shawn Benjamin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShawn BenjaminData and Business Intelligence Chief at U.S. Department of Homeland Security - USCISBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maria-daibert","text":"Maria Daibert - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaria DaibertData Platform Product Manager at AB InbevBack to speakersData Platform Product Manager at Anheuser-Busch InBev (Brazil), with 5+ years of expertise in product management, business development and agile frameworks. Passionate about Big Data, strategy and agility. A Data Mesh enthusiast.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gilad-asulin","text":"Gilad Asulin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGilad AsulinBig Data Engineer Team Leader at Akamai Technologies, IncBack to speakersGilad Asulin is a Senior Big Data Team Leader at Akamai.\nHe has over 20 years of experience in development and software architecture. \nGilad specialties are Big Data, cloud security and cloud technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/demand-forecasting","text":"Demand Forecasting at Scale | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorBuild Demand Forecasts at ScalePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedDemand forecasting is the process of leveraging historical data and other analytical information to build models that help predict future estimates of customer demand for specific products over a specific period. It helps shape product road map, inventory production and inventory allocation, among other things.According to\u00a0McKinsey, a 10% to 20% improvement in supply chain forecasting accuracy is likely to produce a 5% reduction in inventory costs and a 2% to 3% increase in revenues. In a world where margins are increasingly narrow and critical, this percentage can be make or break. But traditional supply chain forecasting tools have failed to deliver the desired results, limiting success of retailers and manufacturers.Generate fine-grained forecasts at the retail store level in less timePerform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform. This accelerator helps retailers overcome the technical limitations of legacy data analytics solutions that undermine forecasting accuracy. Instead, perform full forecasts on atomic-level data within tight service windows to do things like:Construct a forecast for each store-item combinationProject demand for each product across storesAs new sales data arrives, efficiently generate new forecasts and append existing forecastsWork in either Python or RDownload notebookIntermittent demand forecasting with NixtlaFine-grained forecasting often exposes patterns of intermittent demand. These patterns require specialized techniques to produce forecasts for goods that do not move at a regular, easily predictable cadence.In this accelerator, built with our partners at Nixtla, we demonstrate how these techniques can be employed to produce:Scalable, accurate forecasts across large numbers of store-item combinations experiencing intermittent demandAutomated model selection, aka model bake-offs, to ensure the best model is selected for each store-item combinationMetrics that help us identify the optimal frequency with which to generate new predictionsDownload notebookForecast demand at the part level for streamlined manufacturingPerform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Leverage this accelerator to:Build fine-grained demand forecasting that can be scalably performed on a more frequent basisManage material shortages and predict overplanningDownload notebookResources\nAll the resources you need. All in one place.\nExplore the resource library to learn how to forecast demand at scale.\nExplore resourceseBooks & VideosLearn moreExplainer VideoLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/accenture-unified-view-demand","text":"Accenture Unified View of Demand | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionUnified View of Demand by AccentureIndustry-specific solution developed by Accenture and powered by the Databricks Lakehouse PlatformGet startedGenerate more accurate forecasts in less timeTo drive growth and innovation, leading retail and CPG companies are pivoting their supply chain to become more customer-centric. Accenture Unified View of Demand is an open, glass box approach to demand planning. Maximize accuracy, granularity and timeliness with a single-source-of-truth demand plan while also enabling better explainability and alignment across various functions. With Accenture Unified View of Demand, you can:Increase forecast accuracy, speed and granularityShift from debating forecasts to input alignmentScale patterns for consumption-led forecastingGet startedProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks VenturesInvesting in the future of data, analytics and AI\nDatabricks Ventures invests in innovative companies that share our view of the future for data, analytics and AI. Our inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.Portfolio company benefitsExclusive insight into the product roadmap and support for building deep technical integrationsGuidance and best practices from the network of Databricks mentorsBroader reach by partnering with Databricks go-to-market programsLakehouse Fund investment\nfocusA shared vision to build the future of data, analytics and AI on the lakehouse architectureInvestments in early to growth-stage companies in partnership with a lead investorProjects and entrepreneurs that share Databricks\u2019 commitment to open source and building on open platforms, much like the Databricks LakehouseOur PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\nLearn moreArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\nLearn moredbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\nLearn moreHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.Learn moreThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.Learn moreThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.Learn moreLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.Learn moreMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.Learn morePerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.Learn moreRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.Learn moreTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.Learn moreFAQsWhy partner with Databricks Ventures?\nDepending on the size and stage of the investment, Databricks will provide unique access to product roadmap direction, technical integration support, and go-to-market support; access to Databricks mentors for guidance and best practices; and exposure in Databricks\u2019 global go-to-market programs, including our Data + AI Summit series.What are Databricks Ventures\u2019 investment criteria?\nWe are investing in innovative founders of private companies who share our view of the future for data and AI and are committed to extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.What stages does Databricks invest in?\nWe invest in early through growth-stage private companies within the data, analytics and AI ecosystem.Does Databricks Ventures lead investment rounds?\nNo, we do not lead rounds. Our strategy is to invest alongside a lead institutional investor.What is Databricks Ventures\u2019 typical investment size?\nDatabricks Ventures takes minority positions in rounds led by institutional VCs; typical check size varies based on stage of company and size of funding round.Does Databricks take board seats?No, Databricks does not plan to take board seats in portfolio companies.Build your startup on DatabricksDatabricks for Startups offers free credits, expert advice and go-to-market support.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/varun-sharma","text":"Varun Sharma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVarun SharmaPrincipal Data Engineer at Visa Inc.Back to speakersVarun Sharma is a Principal Data Engineer at Visa's Data and AI platform, with over a decade of Big Data experience in the finance domain. At Visa, Varun has been instrumental in building a high-performance data engineering platform to power the company's analytics and machine learning applications. Varun has a deep understanding of distributed computing like frameworks like Apache Spark and Hadoop. He's very passionate about making data accessible to everyone.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/elasticsearch","text":"What is Spark Elasticsearch?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark ElasticsearchAll>Spark ElasticsearchTry Databricks for freeGet StartedWhat is Spark Elasticsearch?Spark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and released under the terms of the Apache License.\nElasticsearch is Java-based, thus available for many platforms that can search and index document files in diverse formats. The data stored in Elasticsearch is in the form of schema-less JSON documents; similar to NoSQL databases. The history of and an introduction to ElasticsearchAn integral aspect of a larger set of open-source tools known as the Elastic Stack, Elasticsearch is a popular full-text search engine, originally designed and developed by engineers at the Google Brain Team. It's widely used in a number of commercial applications, from Reddit, to YouTube to eBay. For many companies, text-based search has become an essential component of their business processes. In this way, Elasticsearch is similar to other search engines.\nOne key difference between Elasticsearch and other search engines is that Elasticsearch can store and manage distributed data. In other words, it's designed to deal with data that has a constantly varying size. This provides the capability for very complex queries, no matter how large a data set is. However, the potential impact of making a single database server handle data from multiple users can increase significantly.Who uses Elasticsearch?Thousands of top companies use Elasticsearch for both their online and offline data, including tech giants like Google, Oracle, Microsoft and many other household names.\nBut you don't have to be a tech giant to want an easy way to index structured data. You just have to know it exists and understand how it works.But what is Elasticsearch used for, exactly?Elasticsearch can serve a broad range of use cases, such as:Logging and Log Analysis:\u00a0 The ecosystem of complementary open source software and platforms built up around Elasticsearch has made it one of the easiest to implement and scale logging solutions.Scraping and Combining Public Data: Elasticsearch is flexible enough to take in multiple different sources of data and keep it all manageable and searchable.Full-Text Search: ElasticSearch is document-oriented. It stores and indexes documents. Indexing creates or updates documents. Once the indexing is finished, you can search, sort, and filter complete documents\u2014not rows of columnar data.Event Data and Metrics: Elasticsearch is also known for working great well on time-series data such as metrics and application events. No matter the technology you are using, Elasticsearch probably has the needed components to easily grab data for common applications; and in the rare case that it doesn't, adding that capability is quite easy.Elasticsearch architecture: key componentsTo understand how Spark Elasticsearch works, when to use it and when not to use it, you have to first understand the infrastructure behind the Elasticsearch architecture. These key components include everything from the Elasticsearch cluster, ports 9200 and 9300, and Elasticsearch shards to Elasticsearch replicas, analyzers and documents.Elasticsearch clusterAn elasticsearch cluster is a group of interconnected computing nodes, all of which store different pieces of cluster data. As a user, you can adjust the number of nodes each cluster is assigned to run by altering the \"elasticsearch.yml\" file found in the configurations folder. While it's possible to run as many clusters as you'd like, most users typically find one node is all it takes to achieve their desired results.Elasticsearch nodeAn Elasticsearch node is a computing resource that is specifically tuned for searching, indexing and scaling the database. Since Elasticsearch is a distributed database, it uses a single source of truth, which is the Elasticsearch data node that holds all of your data. Each node in a cluster uses a different name. Typically, Elasticsearch nodes have about 10 to 50 million documents in each index.Ports 9200 and 9300There are two types of ports available on Elasticsearch shard. The first of the two shard ports is always open, and the second shard port is opened only when an Elasticsearch index is created and a cluster is initialized. 9200 is the default port to use for the primary shard and 9300 is the default port to use for its replica.Elasticsearch shardsElasticsearch shards are simply a collection of Kibana indexes inside one index. There are two types of index in Elasticsearch, Elasticsearch documents (doc) and Elasticsearch indexes. Documents are bound with identifiers and indexes with a unique name.Elasticsearch replicasA replica is a copy of a shard with all changes being reflected on the secondary replica but remaining transparent to the client. The primary replica is updated automatically when new data is added or when deleted, updated or modified.Elasticsearch analyzersAn analyzer is a part of an Elasticsearch cluster that fetches data from the database and performs analysis with it. This makes it possible to filter and sort the data that's been returned to the user.Elasticsearch documentThe Elasticsearch documents are the primary index type in Elasticsearch. Each document is created as an ID in the data set and has a single column per document type. A simple example of a document ID for Elasticsearch is {doc id}. In general, each document in an Elasticsearch cluster has a shard ID, name and an array of indexes with all the fields having their own shard-wide identifiers.How does Elasticsearch work?In short, Elasticsearch works by taking data and publishing it on to every node in the cluster, and then scaling data up and down based on the current amount of data being stored. Elasticsearch benefits from being able to store all of your data in one database, with an elastic index container.\nBecause Elasticsearch is a document-oriented, RESTful search engine, it has a variety of useful tools and can work with large, and otherwise intimidating, data sets. Additionally, this software can be used as a complementary tool in addition to another. For instance, Elasticsearch + Spark.An Elasticsearch query exampleLet's say you wanted to search for the word \"Telecommunications\". The following simple search syntax will do the trick:\n$\"Telecommunications\"\nSince Elasticsearch works from documents, you can't simply search through a list of documents. You need to query a \"document type\". We'll use the phrase \"type:Telecommunications\" to ensure we only get documents that meet the search criteria.\nTo make this query, we pass the document ID number as a query parameter:\n$\"type:telecommunications\"\nTo test this further, you could also create a simple example document by running the following:\ncreate index:type:telecommunications create partition:type:telecommunications --data-urlencode \/tasks --data-urlencode tasks\/What type of database does Elasticsearch use?By combining the Lucene indexing build with a robust distribution database model, the Elasticsearch tool is able to fragment data sets into small components known as shards and distribute them across various nodes.But where does Elasticsearch store data?The data stored in Elasticsearch is either in JSON format or CSV format. Every index has its own template for documents stored in the index. The index is fully-replicated using a message bus to communicate with the secondary replication. Log files are written as Elasticsearch indexes.\nThese documents are stored as an array of key-value pairs in a data structure known as a \"memcached set\". A memcached set is a lightweight, low-memory, scalable data structure and has the ability to hold and process data with a large memory volume.\nElasticsearch's storage is optimized for ingest, indexing and search operations with files being written to the disk at regular intervals. In fact, the only way to change the index's size is to delete the last inserted document and replace it with a new one. This task is called \"data migration\" and refers to a new document being created from the new index, updated and then re-inserted.What is Elasticsearch aggregation?Elasticsearch aggregation, or allocating the same cluster to multiple endpoints, is a powerful feature that allows you to use the same Elasticsearch cluster for additional data and functionality without affecting the performance of your production cluster.\nWhen aggregating clusters, each node is assigned one of three different workload types. The workload types are:Non-relationalOnline transaction processing (OLTP)Online analytical processing (OLAP)Non-relationalAll of the network requests generated by Elasticsearch are generated by queries that are being run against the Elasticsearch cluster.\nWhen an Elasticsearch node is idle, it is the responsibility of the operating system to run queries on a background thread and continuously report on the results. When an Elasticsearch node is being used, it will participate in a failover mechanism (in the event of a node failure) or (in the case of node overload) it will pass the query requests through to a number of other nodes, waiting until one of the other nodes is free.\nWhile the network traffic generated by Elasticsearch is most commonly querying related data, there are many other situations that can also take advantage of Elasticsearch.OLTPAll of the network requests generated by Elasticsearch are still generated by queries that are running against the Elasticsearch cluster.\nWhile this can be a full Elasticsearch cluster for a large system (and certainly a good start), there are times when it's desirable to combine Elasticsearch with a relational data source. In those cases, Elasticsearch will be running against a secondary relational data source for processing and will only keep track of some of the queries it has run. In this scenario, each node is assigned only one secondary source, with the other remaining idle.OLAPA key distinction between Elasticsearch aggregation and regular aggregation is that, while other aggregations can use the same Elasticsearch cluster for multiple purposes, Elasticsearch aggregation uses a secondary data source to store and process the aggregated data. This allows for Elasticsearch aggregation to store more data without creating additional queries on a primary dataset, such as SQL or NoSQL data sets.How to install Elasticsearch and use itInstallation is fairly straightforward. It's possible to use default repositories for Elasticsearch and set a default environment for Elasticsearch, too.\nElasticsearch uses a configuration file called Kibana.yml as the basis for its configuration. You can modify the file to suit your needs. You can also use any of the more popular Elasticsearch plugin providers such as InfluxDB, Logstash, etc.The steps to installing Elasticsearch:Install the Elasticsearch Development version as well as the server and install dependenciesInstall the BOSH Extension for Java. The BOSH extension helps you write HTML templates for your Elasticsearch to make data more accessible and readable for humans as well as data manipulation tools. The BOSH extension requires a Java runtime. You can use default repositories for Java on your operating system to install it.Launch ElasticsearchInstall the Java plugin for BOSHThat's it. Elasticsearch is up and running on your machine and you now have access to all of the data in an easy to read way.Elasticsearch data visualizationElasticsearch allows you to search and filter through all sorts of data via a simple API. The API is RESTful, so users can not only use it for data-analysis but can also use it in production for web-based applications. Currently, Elasticsearch includes faceted search, a functionality that allows you to compute aggregations of your data. Here are some of the most relevant features:It provides a scalable search solution.Performs near-real-time searches.Provides support for multi-tenancy.Streamlines backup processes and ensures data integrity.An index can be recovered in case of a server crash.Uses Javascript Object Notation (JSON) as well as Java application program interfaces (APIs).Automatically indexes JSON documents.Indexing uses unique type-level identifiers.Each index can have its own settings.Searches can be done with Lucene-based query strings.Why use Elasticsearch instead of SQL?The Elasticsearch service is by far the most widely adopted, powerful and useful search technology because when it comes to processing large amounts of data quickly and efficiently, it's notably better than most of its SQL counterparts.\nElasticsearch is purpose-built for enterprise search use, providing powerful features and ease of use tools to businesses that rely on data analytics. Thus offering them a more practical and flexible way to store, search and analyze batches of data in a less resource-intensive way.How to check Elasticsearch versionThere are two quick ways to check the version of Elasticsearch you're running. The first is to launch and login to your ElasticSearch console and view your software version. The second is to check your Elasticsearch official documentation.Top three Elasticsearch alternatives on the marketWhen considering which software to use, there are three top Elasticsearch alternatives to take into account before making your decision:AWSAmazon Web Services (AWS) has become the top computing platform for startups, cutting-edge research and the biggest enterprises looking to enhance their computing infrastructure. With technology that allows customers to use and build their own virtual servers, along with the industry's widest set of cloud-computing services, AWS powers the so-called \"cloud wars\" between Microsoft's Azure and Google's GCP.SolrApache Solr is an open source (BSD licensed) search analytics engine daemon written in Java and is one of the most popular open-source search engines. In fact, Solr powers the search functionality of many of the world's largest e-commerce sites and social media platforms including Twitter, Yahoo, Amazon, eBay and eBay Enterprise.\nSolr uses a distributed architecture to provide rapid search, and features a unique unified Storage API that enables the search engine to integrate seamlessly with virtually any storage mechanism used by the enterprise.ArangoDBArangoDB is a distributed, NoSQL document-oriented database and has become a popular choice due to its powerful data analytical processing and ease-of-use. It's an SQL-like language that operates over the ArangoDB key-value store, allowing users to create tables, joins and queries the same way they would in relational databases.\nArangoDB does a good job of keeping all of its code up to date, and the support pages are well designed. As the project matures and more people contribute, you can expect these pages to stay up to date and easy to navigate. Not to mention, it's compatible with all the major programming languages like Python and Javascript.The three best Elasticsearch toolsTo make the most of your data, we recommend using Elasticsearch in tandem with other tools and software\u2014most notably Hevo Data, Logstash, and Apache Nifi.Hevo DataHevo Data Elasticsearch is a free, open-source distributed search engine designed to ingest Elasticsearch data, parse it into queries and run them as event logs on the cluster nodes. The software lets you run analytics queries in real time on real-time data as well as backups of that data.LogstashSimply put, Logstash is an Elasticsearch tool that allows you to define rules that help manage incoming data as soon as it's extracted by Elasticsearch. By taking the data and instantly processing it, Logstash provides analytical and visualization tools perfect for making the most out of your data.Apache NiFiApache Nifi is a set of libraries that enables \"deep linking\" between multiple data sources, including but not limited to popular Open Source APIs such as Facebook's Core Location API, Twitter's REST APIs, and even Yelp's In-App Feature API. With Apache NiFi, users are able to link their own APIs and make all of a dataset's information available to various other software.Is Elasticsearch right for you?With everything you know now about Elasticsearch, from its capabilities to its infrastructure and architecture, all that's left is deciding whether it's an ideal tool for your business.Additional ResourcesElasticSearch DatasetsScalable Time Series Forecasting and Monitoring using Apache Spark and ElasticSearch at AdyenBuilding a Dataset Search Engine with Spark and ElasticsearchBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/04\/11\/data-att-modernization-lakehouse.html","text":"Unlocking the Power of Data: AT&T\u2019s Modernization Journey to the Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorUnlocking the Power of Data: AT&T\u2019s Modernization Journey to the Lakehouseby Kate HopkinsApril 11, 2022 in Company BlogShare this postThis is a guest post from Kate Hopkins, Vice President of Data Platforms at AT&T.The beginning: Moving and managing petabytes of data with careAT&T started its data transformation journey in late 2020 with a sizable mission: to move from our core on-premises Hadoop data lake to a modernized cloud architecture. Our strategy was to empower data teams by democratizing data, as well as scale AI efforts without overburdening our DevOps team. We saw enormous potential in increasing our use of insights for improving the AT&T customer experience, growing the AT&T business and operating more efficiently.While some businesses might accomplish smaller migrations more readily, we at AT&T had a lot to consider. Our data platform ecosystem of technologies ingests over 10 petabytes of data per day, and we manage over 100 million petabytes of data across the network. It was extremely important for us to take our time selecting the right tool for the job. Not only because of the large data volumes but also because we have 182 million wireless subscribers and 15 million broadband households to support who are using data. In addition, we have important systems that protect our customers against breaches and fraud. Essentially, we needed to democratize our data in order to use it to its full potential but balance that democratization with privacy, security, and data governance.Our legacy architecture, which includes over six different data management platforms, enabled data teams to work closely with data and act on it quickly. But at the same time, it locked those efforts in silos. These distributed pockets of work led to challenges accessing and acquiring data, as well as data duplication and latency issues. Without a single truth from which to draw information, metrics were created out of different versions of data that reflected different points in time and levels of quality.Ultimately, to realize the data-driven innovations we desired, we needed to modernize our infrastructure by moving to the cloud and adopting a data architecture built on the premise of open formats, simplicity, and cross-team collaboration. We chose Databricks Lakehouse as a critical component for this monumental initiative.Accessible data leads to better insights and a center of excellence2021 was all about getting AT&T\u2019s on-premises data into the Databricks Lakehouse Platform. I\u2019m excited to say that with Lakehouse as our unified platform, we\u2019ve successfully moved all our core data lake data to the cloud.Our data science team, who were the first adopters, adjusted to this change with ease. They have since been able to move their machine learning (ML) workloads to the cloud. This has enabled faster data retrieval, more data (if you can believe it), and accessibility to modernized technologies that have brought fraud down to the lowest level in years. For example, we\u2019ve been able to train and deploy models that detect fraudulent phone purchase attempts and then communicate that fraud across all channels to stop it completely. We\u2019ve also seen a significant increase in operational efficiency, a reduction in customer churn, and an increase of customer LTV.Within CDO, we\u2019ve been onboarding a large data engineering and data science community. We\u2019re ingesting both structured customer data into Delta Lake, as well as a large amount of raw, unstructured, real-time data to help continue powering these important use cases.But the value doesn\u2019t stop at our ability to scale data science. Our business users have also been able to extract data insights through integrations that run Power BI and Tableau dashboards off the data in Delta Lake. The sales organization uses data-driven insights fed through Tableau to uncover new upsell opportunities. They are also able to generate recommendations on ideal responses based on the questions customers are asking.Most importantly, moving to Databricks Lakehouse has enabled AT&T to move to the analytics center of excellence (COE) model. As we decentralize our technology team to support businesses more closely, we\u2019re ultimately aiming to empower each business unit to serve themselves. This includes knowing who to reach out to if they have a question, where to find training, how to get a deeper understanding of how much they\u2019re spending, and more. And for all of those reasons, the center of excellence has been key. It\u2019s led to greater product adoption, and so much meaningful trust and appreciation from our partners.Retiring on-prem entirely, making cost-saving gains, and accelerating success in 2022In 2020, we succeeded in making the case and proving the benefits of moving to the cloud. The ability to rapidly execute our transformation plan helped us exceed our savings targets for 2021, and I'm expecting to do the same in 2022. The real win, however, is going to be the increased business benefits we expect to see this year as we continue moving our data over to Delta Lake so we can retire our on-prem system entirely.This move will enable us to do really exciting things, like standardize our artificial intelligence (AI) tooling, scale data science and AI adoption across the business, support business agility through federation, and leverage more capabilities as our roadmap evolves.I\u2019m certain that the Databricks Lakehouse architecture will enable our future here at AT&T. It\u2019s the target architecture for our AI use cases, and we are confident it will increase our business agility because in less than a year we have already seen the results of the federation and business value it enables. Critically, it also supports required data security and the governance for a single version of truth across our complex data ecosystem.Related Content: AI Modernization at AT&T and the Application to Fraud with DatabricksTry Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nicolas-pelaez\/#","text":"Nicolas Pelaez - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNicolas PelaezTechnical Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/migration\/hadoop","text":"Migrate from Hadoop to Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMigrate from HadoopMove your legacy Hadoop platform to the Databricks Lakehouse\nTry Databricks freeContact DatabricksHadoop has proven unscalable, overly complex and unable to deliver on innovative use cases. Migrating from Hadoop to Databricks will help you scale effectively, simplify your data platform and accelerate innovation with support for analytics, machine learning and AI.The challenge with HadoopOn-premises Hadoop deployments have significant limitations, including wasted hardware capacity, high DevOps burden, increased power costs and software version upgrades.Even if you migrate legacy on-premises Hadoop workloads to cloud-based managed services like EMR, HDInsight or Dataproc, you\u2019ll still run into the same reliability and scalability issues. This leads to a lot of time being wasted on troubleshooting, infrastructure, resource management overhead and stitching different managed services on the cloud to maintain an end-to-end pipeline.To learn more about the challenges organizations face with on-premises as well as cloud deployments of Hadoop, check out these blogs:BlogIt\u2019s Time to Re-evaluate Your Relationship With Hadoop\nRead moreBlog7 Reasons to Migrate From Your Cloud-Based Hadoop\nRead moreWhy migrate from Hadoop to the Databricks Lakehouse?Simplify your data platform\nGet a single modern platform for all your data, analytics and AI use cases. Unify governance and the user experience across clouds and data teams.\nScale cost-effectively\nStop managing servers, and scale on demand with serverless. Run data warehousing at scale with up to 12x better price\/performance.\nAccelerate innovation\nBuild AI, ML and real-time analytics capabilities faster with collaborative, self-service tools and open source technologies such as MLflow and Apache Spark\u2122.\nMigrate with confidence\nAutomated tools, technical guidance, partner solutions and professional services help you eliminate risk and accelerate your migration journey.\nReady to take your first step?Contact DatabricksMigration resourcesWebinarStep-by-Step Guide to Hadoop Migration\nWatch noweBookMigrating From Hadoop to Data Lakehouse for Dummies\nDownload nowTechnical GuideMigration Guide: Hadoop to Databricks\nDownload nowBrickbuilder SolutionsLeverage Brickbuilder Solutions from leading consulting partners \u2014 built for migrating from Hadoop to the Databricks LakehouseLegacy System Migration by AvanadeMove your data to unlock its full value\nGet startedMigrate to Cloud and Databricks by CapgeminiStreamline data migration to the Databricks Lakehouse Platform\nGet startedMigrate to Databricks by Celebal TechnologiesQuicker migration from on-premises at lower cost\nGet startedLeapLogic Migration Solution by ImpetusAuto-transform ETL, data warehouse, analytics and Hadoop workloads to Databricks\nGet startedData Wizard for Hadoop\/EDW Migrations by InfosysConfidently move your data to Databricks\nGet startedData Intelligence Suite by WiproMigrate with confidence to Databricks\nGet startedCustomers who have successfully migrated from cloud-based Hadoop to DatabricksCustomers who have successfully migrated from on-premises Hadoop to DatabricksMigrating from a data warehouse?Learn moreResourceseBooksMigrating From Hadoop to Data Lakehouse for DummiesMigration Guide: Hadoop to DatabricksThe Hidden Value of Hadoop Migration to a Cloud Data LakeThe Hidden Value of Hadoop Migration \u2014 AWSEventsStep-by-Step Guide to Hadoop MigrationHow to Break Up With Hadoop \u2014 Build a Future With a Data Platform Made for AI and BILife After HadoopData Lake Modernization \u2014 10 Habits of Highly Effective Hadoop Migrations to Azure DatabricksBlogsIt\u2019s Time to Re-evaluate Your Relationship With HadoopTop Considerations When Migrating Off of Hadoop5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architecture7 Reasons to Migrate From Your Cloud-Based Hadoop to the Databricks Lakehouse PlatformThe Hidden Value of Hadoop MigrationGet startedMigration doesn\u2019t have to be a headache. Contact us today to talk about what it could look like for you.Try Databricks freeContact DatabricksProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/aws","text":"Databricks on AWS Data Platform - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks on AWSThe simple, unified data platform seamlessly integrated with AWS\n\u00a0Get startedSchedule a demoDatabricks on AWS allows you to store and manage all your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all your analytics and AI workloads.Reliable data engineeringSQL analytics on all your dataCollaborative data scienceProduction machine learningWhy Databricks on AWS?Simple\nDatabricks enables a single, unified data architecture on S3 for SQL analytics, data science and machine learning12x better price\/performance\nGet data warehouse performance at data lake economics through SQL-optimized compute clustersProven\nThousands of customers have implemented Databricks on AWS to provide a game-changing analytics platform that addresses all analytics and AI use casesDollar Shave Club: Personalizing customer experiences with Databricks\nDownload eBookHotels.com: Optimizing the customer experience with machine learning\nDownload case studyHP: From data prep to deep learning \u2014 how HP unifies analytics with Databricks\nWatch on-demand webinarFeatured integrationsAWS GravitonAWS GravitonDatabricks clusters support\u00a0AWS Graviton\u00a0instances. These instances use AWS-designed Graviton processors that are built on top of the Arm64 instruction set architecture. AWS claims that instance types with these processors have the best price\/performance ratio of any instance type on Amazon EC2.\u00a0Read moreAWS SecurityAmazon RedshiftAWS GlueEnterprise RolloutUse CasesPersonalized recommendation engines\nProcess all your data in real time to provide the most relevant product and service recommendations.Genomic sequencing\nModernize your technology stack to improve the experience for patients and physicians with the fastest DNASeq pipeline at scale.Fraud detection and\nprevention\nLeverage complete historical data together with real-time data streams to quickly identify anomalous and suspicious financial transactions.ResourcesWhitepapersMining Your Data Lake for Analytics InsightsUnifying Big Data and AI in the Financial Services IndustryThe Hidden Value of Hadoop MigrationWebinarsModernize Data and Analytics Platforms with Confidence with Databricks and AWSWhy Data-Focused Startups Are Building on the LakehouseHarness the Power of Real-Time Analytics for Rapid Decision-Making at QubyLoyaltyOne Simplifies and Scales Data Analytics Pipelines With Delta LakeUnlock the Potential Inside Your Data LakeBuilding a Data Lakehouse at DoorDash and GrammarlyIndustriesLeveraging AI\/ML to Extract Real-World Insights From Population-Scale Clinical Lab Data at PrognosHow Machine Learning Is Changing Data Analytics in GovernmentReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alain-briancon\/#","text":"Alain Briancon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlain BrianconVP Data Science Profiles by Kantar at Kantar GroupBack to speakersAlain is Vice President of Data Science at Kantar Profiles decision. Alain is a serial entrepreneur and inventor with 77 patents. Over the last ten years, through various startups, Alain has applied data science to IoT, predicting appliance failures, political campaigns, food and diet management, customer engagement, upsell\/cross-sells, and now surveys. Alain graduated from the Massachusetts Institute of Technology with a Ph.D. in Electrical Engineering and Computer Science. Outside work, he enjoys writing movie scripts, collecting fountain pens, and enjoying family and dogs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/agenda\/#","text":"Agenda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAgenda at a glanceExplore sessionsSTARTING AT $1,795In Person EventFREEVirtual EventMonday, June 26, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALTuesday, June 27, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALBreakout Sessions30010Partner SummitLightning Talks, AMA\u2019s, & Meetups on topics such as Apache Spark \u2122, Delta Lake, MLflow, and moreWednesday, June 28, 2023KeynotesIN PERSONVIRTUALBreakout Sessions30010100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsClosing PartyThursday, June 29, 2023KeynotesIN PERSONVIRTUALBreakout Sessions100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsOn Demand Library HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sumesh-nair\/#","text":"Sumesh Nair - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSumesh NairDirector of Engineering, Data and Cloud Strategy at Optum, United HealthGroupBack to speakersExperienced and Accomplished senior IT leader with a 20-year track record of excellence. An Agile enthusiast with a history of transforming organizations to optimize product engineering & delivery. A servant-leader known for building high-performing teams to discover new solutions, challenge norms, and gain competitive advantages in the market. An experienced leader with P&L Oversight background, multi-channel product leadership, and driving organizational change by exceeding expectations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=amsterdam%2C%20netherlands","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/binwei-yang\/#","text":"Binwei Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBinwei Yangsoftware engineer at intelBack to speakersBinwei Yang is a big data analytics architect at Intel, focusing on performance optimization of big data software, accelerator design and utilization in big data framework, as well as the big data and HPC framework integration. Prior to the big data role, Binwei worked in intel micro architecture team and focusing on performance simulation and analysis.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/learn","text":"Apprendre | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWApprendrePlongez dans l'univers de Databricks et explorez les ressources qui s'offrent \u00e0 vous. Vous y trouverez des formations, des certifications, des \u00e9v\u00e9nements \u00e0 venir, de la documentation utile et bien plus encore.D\u00e9marrer avec DatabricksApprenez les fondamentauxLa plateforme Lakehouse de Databricks permet de construire et d'ex\u00e9cuter facilement des pipelines de donn\u00e9es, de collaborer \u00e0 des projets de Data Science et d'analytique, tout en construisant et d\u00e9ployant des mod\u00e8les de Machine Learning. Consultez nos guides de prise en main ci-dessous.Vous d\u00e9butez avec Databricks ? D\u00e9marrez votre parcours Databricks avec les conseils d'un ing\u00e9nieur de la r\u00e9ussite client exp\u00e9riment\u00e9.Onboarding Databricks\nLakehouse Fundamentals Training\nWatch 4 short videos, take the quiz and get your badge\nto share on LinkedIn or your r\u00e9sum\u00e9\nGet startedData Science et Data EngineeringAdministrateurs DatabricksAnalyses SQLMachine learningFormationOptez pour la formation de la Databricks Academy. D\u00e9couvrez comment ma\u00eetriser l'analytique des donn\u00e9es avec l'\u00e9quipe \u00e0 l'origine du projet de recherche Apache Spark\u2122 \u00e0 l'universit\u00e9 de Californie \u00e0 Berkeley.Databricks AcademyCertificationLes examens de certification \u00e9valuent votre ma\u00eetrise de la plateforme Databricks Lakehouse et des m\u00e9thodes indispensables \u00e0 la mise en \u0153uvre de projets de qualit\u00e9. Ils vous aident \u00e0 obtenir la reconnaissance de votre secteur, \u00e0 vous d\u00e9tacher de la concurrence et \u00e0 am\u00e9liorer votre productivit\u00e9 et vos r\u00e9sultats. Ils offrent aussi une preuve tangible de votre investissement dans la formation.Certification DatabricksObtenez des r\u00e9ponses \u00e0 vos questionsDiff\u00e9rentes options s'offrent \u00e0 vous pour obtenir des r\u00e9ponses aux questions que vous pourriez vous poser \u00e0 vos d\u00e9buts\u00a0:Interrogez un expert technique Databricks en directCommunaut\u00e9 en ligneExplorez des sujets populaires au sein de la communaut\u00e9 Databricks.Interagissez avec la communaut\u00e9Sujets populaires du forumDatabricksDelta LakeSparkSQLpysparkAzureAWSGCPBesoin d'un coup de main\u00a0?Si vous b\u00e9n\u00e9ficiez d'un contrat d'assistance ou que vous souhaitez en contracter un, consultez nos options ci-dessous. Pour obtenir des conseils strat\u00e9giques (avec un ing\u00e9nieur Customer success ou un contrat de Services professionnels), adressez-vous \u00e0 l\u2019administrateur de votre workspace pour contacter votre charg\u00e9 de compte Databricks.Consultez nos options de soutienGalerie NotebookCette galerie pr\u00e9sente certaines des possibilit\u00e9s offertes par les notebooks ax\u00e9s sur les technologies et les cas d'usage pouvant facilement \u00eatre import\u00e9s dans votre propre environnement Databricks, ou dans l'\u00e9dition gratuite de la communaut\u00e9.Galerie Notebook DatabricksDocumentationLe site d\u00e9di\u00e9 \u00e0 la documentation technique de Databricks fournit des conseils pratiques et des informations de r\u00e9f\u00e9rence pour la Data Science, la Data Engineering et le Machine Learning de Databricks, ainsi que pour les environnements adapt\u00e9s \u00e0 diff\u00e9rents profils de Databricks SQL.Documentation AWSDocumentation AzureDocumentation Google\u00c9v\u00e9nements et communaut\u00e9 DatabricksSommet Data + IARejoignez nos conf\u00e9rences, annonces de produits et plus de 200 sessions techniques, avec un \u00e9ventail d'experts du secteur, du monde universitaire et de la recherche.En savoir plus\u00c9v\u00e9nements mondiauxR\u00e9servez votre place \u00e0 l'une de nos conf\u00e9rences mondiales ou r\u00e9gionales, d\u00e9monstrations de produits en direct, ou \u00e0 l'un de nos webinars, \u00e9v\u00e9nements parrain\u00e9s par des partenaires ou meetups.En savoir plusMeetups en ligne sur les donn\u00e9es et l'IAD\u00e9couvrez ce qu'il se passe dans les groupes Databricks Meetup du monde entier et rejoignez-en un, virtuellement, pr\u00e8s de chez vous.En savoir plusBeaconsD\u00e9couvrez les Databricks Beacons, un groupe de membres de la communaut\u00e9 qui font tout leur possible pour am\u00e9liorer la communaut\u00e9 des donn\u00e9es et de l'IA.En savoir plusUniversity AllianceRejoignez la Databricks University Alliance pour acc\u00e9der \u00e0 des ressources gratuites destin\u00e9es aux \u00e9ducateurs souhaitant enseigner \u00e0 l'aide de Databricks.En savoir plusDiffusion vid\u00e9o Data BrewExploration des donn\u00e9es + IA avec des expertsBrooke Wenig et Denny LeeS\u00e9rie de vid\u00e9osConf\u00e9rences et meetups en ligne sur les technologiesBrooke Wenig et Denny LeeEntretiens techniquesG\u00e9rer le cycle de vie du Machine Learning de bout en bout en utilisant MLflowJules DamjiEntretiens techniquesD\u00e9marrer avec Delta LakeDenny LeeEntretiens techniquesSe plonger dans Delta Lake (avanc\u00e9)Denny LeeDatabricks Demo Hub (d\u00e9monstrations de produits)Recherche sur les donn\u00e9es et l'IAMatei ZahariaCofondateur et technologiste en chef deDatabricksReynold XinCofondateur et Chief ArchitectDatabricksSue Ann HongIng\u00e9nieur logicielDatabricksLisez les articles r\u00e9cents des fondateurs, des collaborateurs et des chercheurs de Databricks sur les syst\u00e8mes distribu\u00e9s, l'IA et l'analytique des donn\u00e9es, en collaboration avec des universit\u00e9s de premier plan comme celle de Californie \u00e0 Berkeley ou de Stanford.Acc\u00e9der \u00e0 la rechercheProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/onik-kurktchian","text":"Onik Kurktchian - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOnik KurktchianHead of S&P Global Marketplace Workbench at S&P GLOBALBack to speakersOnik Kurktchian is a Product Manager and\u202fleads the Analytical Platforms and Services in S&P Global Market Intelligence. He is part of the\u202fteam\u202fthat is responsible for creating products and services that enable data exploration and workflow solutions across all client segments. Previously, he has worked as a Product Specialist across multiple S&P products between Desktop, Excel and Feed Solutions. Onik holds an MSc from LSE in Economic History and a BSc from Queen Mary in Economics & Finance. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/rivian","text":"Customer Story: Rivian | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYDriving into the future of electric transportation250 platform usersA 50x increase from a year ago INDUSTRY: Manufacturing SOLUTION: Predictive maintenance,scaling ML models for IoT,data-driven ESG PLATFORM: Lakehouse,Delta Lake,Unity Catalog CLOUD: AWS\u201cDatabricks Lakehouse empowers us to lower the barrier of entry for data access across our organization so we can build the most innovative and reliable electric vehicles in the world.\u201d\n\u2014 Wassym Bensaid, Vice President of Software Development, RivianRivian is preserving the natural world for future generations with revolutionary Electric Adventure Vehicles (EAVs). With over 25,000 EAVs on the road generating multiple terabytes of IoT data per day, the company is using data insights and machine learning to improve vehicle health and performance. However, with legacy cloud tooling, it struggled to scale pipelines cost-effectively and spent significant resources on maintenance \u2014 slowing its ability to be truly data driven. Since moving to the Databricks Lakehouse Platform, Rivian can now understand how a vehicle is performing and how this impacts the driver using it. Equipped with these insights, Rivian is innovating faster, reducing costs, and ultimately, delivering a better driving experience to customers.Struggling to democratize data on a legacy platformBuilding a world that will continue to be enjoyed by future generations requires a shift in the way we operate. At the forefront of this movement is Rivian \u2014 an electric vehicle manufacturer focused on shifting our planet\u2019s energy and transportation systems entirely away from fossil fuel. Today, Rivian\u2019s fleet includes personal vehicles and involves a partnership with Amazon to deliver 100,000 commercial vans. Each vehicle uses IoT sensors and cameras to capture petabytes of data ranging from how the vehicle drives to how various parts function. With all this data at its fingertips, Rivian is using machine learning to improve the overall customer experience with predictive maintenance so that potential issues are addressed before they impact the driver.Before Rivian even shipped its first EAV, it was already up against data visibility and tooling limitations that decreased output, prevented collaboration and increased operational costs. It had 30 to 50 large and operationally complicated compute clusters at any given time, which was costly. Not only was the system difficult to manage, but the company experienced frequent cluster outages as well, forcing teams to dedicate more time to troubleshooting than to data analysis. Additionally, data silos created by disjointed systems slowed the sharing of data, which further contributed to productivity issues. Required data languages and specific expertise of toolsets created a barrier to entry that limited developers from making full use of the data available. Jason Shiverick, Principal Data Scientist at Rivian, said the biggest issue was the data access. \u201cI wanted to open our data to a broader audience of less technical users so they could also leverage data more easily.\u201dRivian knew that once its EAVs hit the market, the amount of data ingested would explode. In order to deliver the reliability and performance it promised, Rivian needed an architecture that would not only democratize data access, but also provide a common platform to build innovative solutions that can help ensure a reliable and enjoyable driving experience.Predicting maintenance issues with Databricks LakehouseRivian chose to modernize its data infrastructure on the Databricks Lakehouse Platform, giving it the ability to unify all of its data into a common view for downstream analytics and machine learning. Now, unique data teams have a range of accessible tools to deliver actionable insights for different use cases, from predictive maintenance to smarter product development. Venkat Sivasubramanian, Senior Director of Big Data at Rivian, says, \u201cWe were able to build a culture around an open data platform that provided a system for really democratizing data and analysis in an efficient way.\u201d Databricks\u2019 flexible support of all programming languages and seamless integration with a variety of toolsets eliminated access roadblocks and unlocked new opportunities. Wassym Bensaid, Vice President of Software Development at Rivian, explains, \u201cToday we have various teams, both technical and business, using Databricks Lakehouse to explore our data, build performant data pipelines, and extract actionable business and product insights via visual dashboards.\u201dRivian\u2019s ADAS (advanced driver-assistance systems) Team can now easily prepare telemetric accelerometer data to understand all EAV motions. This core recording data includes information about pitch, roll, speed, suspension and airbag activity, to help Rivian understand vehicle performance, driving patterns and connected car system predictability. Based on these key performance metrics, Rivian can improve the accuracy of smart features and the control that drivers have over them. Designed to take the stress out of long drives and driving in heavy traffic, features like adaptive cruise control, lane change assist, automatic emergency driving, and forward collision warning can be honed over time to continuously optimize the driving experience for customers.Secure data sharing and collaboration was also facilitated with the Databricks Unity Catalog. Shiverick describes how unified governance for the lakehouse benefits Rivian productivity. \u201cUnity Catalog gives us a truly centralized data catalog across all of our different teams,\u201d he said. \u201cNow we have proper access management and controls.\u201d Venkat adds, \"With Unity Catalog, we are centralizing data catalog and access management across various teams and workspaces, which has simplified governance.\u201d End-to-end version controlled governance and auditability of sensitive data sources, like the ones used for autonomous driving systems, produces a simple but secure solution for feature engineering. This gives Rivian a competitive advantage in the race to capture the autonomous driving grid.Accelerating into an electrified and sustainable worldBy scaling its capacity to deliver valuable data insights with speed, efficiency and cost-effectiveness, Rivian is primed to leverage more data to improve operations and the performance of its vehicles to enhance the customer experience. Venkat says, \u201cThe flexibility that lakehouse offers saves us a lot of money from a cloud perspective, and that\u2019s a huge win for us.\u201d With Databricks Lakehouse providing a unified and open source approach to data and analytics, the Vehicle Reliability Team is able to better understand how people are using their vehicles, and that helps to inform the design of future generations of vehicles. By leveraging the Databricks Lakehouse Platform, they have seen a 30%\u201350% increase in runtime performance, which has led to faster insights and model performance.Shiverick explains, \u201cFrom a reliability standpoint, we can make sure that components will withstand appropriate lifecycles. It can be as simple as making sure door handles are beefy enough to endure constant usage, or as complicated as predictive and preventative maintenance to eliminate the chance of failure in the field. Generally speaking, we\u2019re improving software quality based on key vehicle metrics for a better customer experience.\u201dFrom a design optimization perspective, Rivian\u2019s unobstructed data view is also producing new diagnostic insights that can improve fleet health, safety, stability and security. Venkat says, \u201cWe can perform remote diagnostics to triage a problem quickly, or have a mobile service come in, or potentially send an OTA to fix the problem with the software. All of this needs so much visibility into the data, and that\u2019s been possible with our partnership and integration on the platform itself.\u201d With developers actively building vehicle software to improve issues along the way.Moving forward, Rivian is seeing rapid adoption of Databricks Lakehouse across different teams \u2014 increasing the number of platform users from 5 to 250 in only one year. This has unlocked new use cases including using machine learning to optimize battery efficiency in colder temperatures, increasing the accuracy of autonomous driving systems, and serving commercial depots with vehicle health dashboards for early and ongoing maintenance. As more EAVs ship, and its fleet of commercial vans expands, Rivian will continue to leverage the troves of data generated by its EAVs to deliver new innovations and driving experiences that revolutionize sustainable transportation.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/cognizant-video-quality-experience","text":"Cognizant Video Quality of Experience | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionVideo Quality of Experience by CognizantIndustry-specific solution developed by Cognizant and powered by the Databricks Lakehouse Platform\nGet startedIdentify and remediate video quality of experience issuesWhether it\u2019s a delayed time-to-first-frame, a playback failure or a rebuffing event, it only takes one poor video experience for viewers to churn. Cognizant\u2019s Video Quality of Experience (QoE) solution limits the occurrence of such events by pairing fine-grained telemetry with ML and AI to identify and remediate video QoE issues in near real-time.Optimize the video viewing experience for your fansIncrease user engagementReduce churnGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dillon-bostwick\/#","text":"Dillon Bostwick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDillon BostwickSolutions Architect at DatabricksBack to speakersDillon Bostwick has spent the last 5 years as a Solutions Architect at Databricks, where he has an extensive background in working with data engineers, data scientists, and business stakeholders to productionize data and machine learning projects. He is also active in developing new field projects intended to accelerate the management of data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/percy-liang","text":"Percy Liang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPercy LiangProfessor of Computer Science at StanfordBack to speakersPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/platform-addons","text":"Databricks Platform and Add-OnsSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPlatform Tiers and Add-OnsOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorSelect cloudAWSAzureGoogle CloudPlatform TiersFeature DetailStandardPremiumEnterpriseDatabricks WorkspaceWorkspace for production jobs, analytics and MLWorkspace for production jobs, analytics and MLWorkspace for production jobs, analytics and MLPerformanceUp to 50x faster than Apache Spark\u2122Optimized Runtime EngineGovernance and ManageabilityDatabricks Workspace administrationAudit logs and automated policy controlsAudit logs and automated policy controlsEnterprise SecuritySecured cloud and network architecture with authentications like single sign-onExtend your cloud-native security for company-wide adoptionAdvanced compliance and security for mission-critical dataPlatform Add-OnsStandardPremiumEnterpriseEnhanced Security and Compliance \nProvides enhanced security and controls for your compliance needs15% of Product SpendPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements\nCalculate priceStart free trialContact usFAQHow is Product Spend calculated when used for add-on charges?Product Spend is calculated based on AWS product spend at list, before the application of any discounts, usage credits, add-on uplifts, or support fees.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/manufacturing-industry-solutions","text":"Soluzioni per l'industria manifatturiera - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWScopri Lakehouse for ManufacturingRiduci i costi, aumenta la produttivit\u00e0 e unifica il tuo ecosistema di dati sull'unica piattaforma pensata per il modo in cui le aziende manifatturiere usano i datiRegistratiContattiRiduci i costi di gestione (TCO). Migliora le prestazioni. Aumenta la scalabilit\u00e0.Lakehouse for ManufacturingUnifica tutti i carichi di lavoro di dati, analisi e AI, con condivisione e governance integrate, in modo che i team interni ed esterni abbiano accesso ai dati di cui hanno bisogno, quando ne hanno bisogno.Impatto su tutta la catena del valoreCoinvolgimento del clienteRisultati precisi ed esperienze fluide per i clientiCon una vista a 360 gradi di clienti, attivit\u00e0 operative e risorse, potrai ottenere il massimo in termini di disponibilit\u00e0 (uptime), qualit\u00e0 del servizio e valore economico lungo tutto il ciclo di vita del prodotto, con esiti personalizzati per ciascun cliente, servizi proattivi di assistenza sul campo e soluzioni mission-critical differenziate.Efficienza operativaProduttivit\u00e0 dei dipendentiInnovazione di prodottoSoluzioni e partner per l'industria manifatturieraSoluzioni di analisi dei dati e AI senza compromessi realizzate appositamente per le aziende manifatturiereGli Acceleratori Databricks sono guide specifiche \u2014 notebook con funzionalit\u00e0 complete e best practice \u2014 che velocizzano il raggiungimento di risultati nel settore manifatturiero. Risparmia tempo nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo per casi d'uso come gemelli digitali, efficienza delle apparecchiature (OEE), previsioni e altro ancora.Monitoraggio dell'efficacia totale dell'impianto (OEE) e dei KPIPrestazioni e scalabilit\u00e0 elevate nel monitoraggio di apparecchiature a 360 gradi\nAcquisisci ed elabora progressivamente dati da sensori\/dispositivi IoT in diversi formati, elaborando ed estrapolando KPI e metriche per ottenere informazioni approfondite preziose.CominciaPrevisioni a livello di singola partePrevedere la domanda di singole parti per snellire la produzione\nPrevedi la domanda di parti a livello singolo invece che aggregato, per ridurre al minimo le interruzioni della supply chain e aumentare le vendite.CominciaGemelli digitaliAumentare l'efficienza operativa e migliorare i processi decisionali\nElabora dati concreti in tempo reale, ricava informazioni approfondite su larga scala da trasferire a svariate applicazioni a valle, e ottimizza l'operativit\u00e0 degli impianti con decisioni guidate dai dati.CominciaScopri gli acceleratori per l'industria manifatturieraAbbiamo collaborato con le principali societ\u00e0 di consulenza per fornire soluzioni innovative per settori specifici. Le soluzioni Databricks Brickbuilder aiutano a ridurre i costi e aumentare il valore generato dai dati. Con decenni di competenze settoriali alle spalle \u2014 e specificamente costruite per la Databricks Lakehouse Platform \u2014 le soluzioni Brickbuilder sono ritagliate su misura per le tue esigenze.Manifattura intelligente Sfrutta i dati, aumenta l'interoperabilit\u00e0 e fornisci informazioni avanzate su larga scala sfruttando analisi e AI.Maggiori informazioniIspezione di qualit\u00e0Automatizza il controllo di qualit\u00e0 con la visione artificiale per individuare difetti, corpi estranei, anomalie o configurazioni errate.Maggiori informazioniGestione predittiva del rischio di fornituraAumenta all'ennesima potenza la visibilit\u00e0 sui flussi di ordini e sulle prestazioni dei fornitori, per massimizzare l'efficienza, gestire le eccezioni e migliorare la resilienza.Maggiori informazioniScopri tutte le soluzioni dei partner\u201cDatabricks Lakehouse ci consente di eliminare le barriere di accesso ai dati in tutta la nostra organizzazione, aiutandoci a realizzare i veicoli elettrici pi\u00f9 innovativi e affidabili al mondo\u201d.\n\u2013 Wassym Bensaid, Vice President of Software Development, Rivian\n\u201cL'uso di Databricks nel corso degli anni \u00e8 aumentato notevolmente. Abbiamo cominciato a usare Databricks come piattaforma di Big Data e AI e il suo impiego si \u00e8 progressivamente ampliato. Abbiamo un gruppo completamente diverso di citizen engineer e data scientist che usano Databricks come strumento moderno di business intelligence per prendere decisioni pi\u00f9 efficaci.\"\n\u2014Daniel Jeavons, General Manager, Advanced Analytics CoE, Shell\n\u201cLa piattaforma Databricks ci ha aiutato a ridurre al minimo i rischi di indisponibilit\u00e0 del motore, ad accorciare i tempi di consegna dei ricambi e ad aumentare l'efficienza nelle rotazioni di magazzino: tutto questo ci consente di proporre TotalCare, il nostro programma di manutenzione Power-by-the-Hour (PBH) leader nel settore dell'aviazione\u201d.\n\u2014 Stuart Hughes, Chief Information and Digital Officer, Rolls-Royce Civil Aerospace\nRisorseeBookMetti a frutto i dati dell'ERPWebinarMigliorare la manutenzione predittiva per le aziende manifatturiere con dati e AIeBookQuattro forze che guidano la manifattura intelligentePronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amine-benhamza","text":"Amine Benhamza - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmine BenhamzaLead Solutions Architect at DatabricksBack to speakersAmine is a Sr. Solutions Architect specializing in Cloud, Data & AI, Migrations, and Enterprise Architecture. He has a significant experience and skills in: \n- Designing Cloud-Native Enterprise Architecture for SMBs and Fortune 500 Companies\n- Building & Lead Cross-Functional SME teams\n- Collaborating with Marketing and GTM teams to evangelize cloud-native technology to customers & partnersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions","text":"Acc\u00e9l\u00e9rateurs de solutions Databricks \u2013 Cas d'usage DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks pour l'industrieDes solutions d\u2019analytique et d\u2019IA sans compromis sp\u00e9cialement pens\u00e9es pour votre secteur d\u2019activit\u00e9D\u00e9marrerPlanifier une d\u00e9moD\u00e9couvrez le Lakehouse d\u00e9di\u00e9 \u00e0 votre secteur d'activit\u00e9Communications, m\u00e9dias et divertissementSuscitez l'attention, captivez les imaginationsEn savoir plusServices financiersRenforcez la confiance, assurez la s\u00e9r\u00e9nit\u00e9En savoir plusSant\u00e9 et sciences du vivantD\u00e9couvrez et offrez des soins de meilleure qualit\u00e9En savoir plusVente au d\u00e9tail et biens de consommationGuidez vos clients dans leur parcours et affirmez votre marqueEn savoir plusTous les secteurs d'activit\u00e9searchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listSolutions pour l'industrieDe l\u2019id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulementLes acc\u00e9l\u00e9rateurs de solutions Databricks sont des guides sp\u00e9cialis\u00e9s con\u00e7us pour acc\u00e9l\u00e9rer les r\u00e9sultats \u00e0 l'aide de notebooks enti\u00e8rement fonctionnels et de bonnes pratiques. Les clients Databricks gagnent du temps dans leurs op\u00e9rations de d\u00e9couverte, de conception, de d\u00e9veloppement et de test. Beaucoup d'entre eux passent de l'id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulement.Explorez les Acc\u00e9l\u00e9rateursPr\u00eat \u00e0 commencer?D\u00e9couvrez ce que Databricks peut faire pour vous avec un essai gratuit.D\u00e9marrez votre essai gratuitProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=finance","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/wejo","text":"Customer Story: wejo \u2013 DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYEnabling the connected car with AI50xFaster time-to-insight due to Improved IT operations20xFaster data processing of vehicle and road data90%Decrease in time-to-market of new innovationsWatch video INDUSTRY: Automotive SOLUTION: Scaling ML models for IoT PLATFORM USE CASE: Delta Lake,data science,machine learning,ETL CLOUD: AWS\"Before Databricks, the time to market would\u2019ve been weeks, if not months to meet the analysis requirements for some of our customers. Now, it takes hours.\u201d\n\u2013 Steve Pimblett, Chief Information Officer and Data Officer, wejowejo was founded with the global ambition to be the world\u2019s largest connected car company. To date, wejo has curated over 140 billion miles of data and expects to have 17 million cars on its platform by the end of the year. With more than 15 billion data points every day and counting, wejo trusts Databricks to deliver ML-powered innovations to the automotive industry, and deliver better driving experiences.Pipelines stretched to ingest 3 trillion monthly data pointsIn order to drive value to the customer, wejo ingests streaming data across 50 million connected vehicles, processing data from OEMs and satellite navigation systems every three seconds. This data provides insights into improving traffic flow, reducing accidents, safety alerts and emergency services, right through to new innovations in optimizing parking. With various data streams coming in from multiple disjointed sources, harnessing the insights from the data through data science is very difficult and resource-intensive.Massive data volumes: They are processing over three trillion data points per month, all in a streaming environment from car to marketplace in less than 40 seconds \u2014 requires significant scale within a low latency environment.Challenges to scale: With so much data to ingest, wejo struggled with relying on Mapreduce clusters which were rigid in size and limited in the libraries that were available. This would result in days of delay waiting for the right Python modules to be installed, which slowed innovation.Slow performance: Long-running jobs could take hours if not days to process.Reliable, performant data pipelines at scale with Delta LakeDatabricks provides wejo with a unified data analytics platform that has fostered a scalable and collaborative environment across data science and engineering, allowing data teams to more quickly innovate and deliver ML-powered innovations to the automotive industry.Managed platform in the cloud simplifies the provisioning of compute clusters to any size.Support for multiple languages (SQL, Scala, Python, R) improves collaboration across data engineering, data science, and analysts.Native support for Delta Lake allows their data engineering team to reliably run and scale both batch and streaming pipelines on the same data.Making the roads safer with ML innovationsWith Databricks, wejo is now able to do large-scale data processing and machine learning faster and cheaper. But most importantly, they are now able to easily share the output across the team and the organization \u2014 enabling others to drive innovation into the market.Improved operational efficiency:\u00a0Features such as auto-scaling clusters has improved data engineering operations, accelerating pipelines for downstream analytics from weeks to minutes.Better cross-team collaboration:\u00a0Shared notebook environment with support for multiple languages has improved team productivity.Faster time-to-insight:\u00a0We now get in over a 20x performance benefit over open-source Spark with Databricks and 90% decrease in time to market.\u00a0Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-boyd\/#","text":"Ryan Boyd - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan BoydCo-founder at MotherDuckBack to speakersRyan Boyd (LinkedIn) is a Boulder-based software engineer, data + authNZ geek and technology executive. He's currently a co-founder at MotherDuck, where they're making data analytics fun, frictionless and ducking awesome. He previously led developer relations teams at Databricks, Neo4j and Google Cloud. He's the author of O'Reilly's Getting Started with OAuth 2.0.Ryan advises B2B SaaS startups on growth marketing and developer relations as a Partner at Hypergrowth Partners. Prior to leading the Google Cloud Developer Relations team, he spent 7 years at Google working on 20+ different developer products and was the co-founder of Google Code Labs which aimed to improve quality and stability of Google's developer products.Ryan graduated with a degree in Computer Science from Rochester Institute of Technology (RIT) where he later worked full-time building web applications + APIs and architecting the central web hosting platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sneh-kakileti","text":"Sneh Kakileti - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSneh KakiletiVice President, Product Management at ZoomInfoBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anfisa-kaydak\/#","text":"Anfisa Kaydak - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnfisa KaydakVP, Data Product & Engineering at HealthverityBack to speakersAnfisa studies applied math in State University, Minsk, Belarus. She started her career in the US as a Web developer and quickly became fascinated with data. The journey from gigabytes quickly progressed to petabytes, from RDMS to distributed systems, from data exploration to complex APLD studies and pipeline engineering. She is SME in healthcare data and analytics, and adept in Data and AI technology transformations in healthcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/03\/09\/introducing-lakehouse-for-healthcare-and-life-sciences.html","text":"Introducing Lakehouse for Healthcare and Life Sciences - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Lakehouse for Healthcare and Life SciencesDelivering better patient outcomes with data and AIby Michael Sanky and Michael OrtegaMarch 9, 2022 in NewsShare this postEach of us will likely generate millions of gigabytes of health data in our lifetimes: medical and pharmacy claims, electronic medical records with extensive clinical documentation, medical images; perhaps streaming data from wearable devices, blood biopsy data that can detect cancer, and genomic sequencing. These data sets have enormous potential to uncover new, life-saving treatments, predict disease before it happens, and fundamentally change the way that care is delivered.\nFor healthcare and life sciences organizations seeking to deliver better patient outcomes, legacy technology is most often the rate-limiting factor. Common challenges include:\nData silos and limited support for semi-structured data (like provider notes) and unstructured data (like images) prevent organizations from gaining a holistic view of a patientRapid growth in data is outpacing the scale of existing infrastructure, preventing population-level researchBatch processing and disjointed analytic tools prevent real-time response to challenges such as supply chain constraints and ICU bed capacityTraditional data architectures that don\u2019t support advanced analytics and AI use casesSadly, for these reasons, the opportunity to tap into AI-driven innovation is simply out of reach for most organizations on the front lines of developing new drugs and treating patients in need.\nMeet Lakehouse for Healthcare and Life SciencesWell, that\u2019s changing! Today, we\u2019re thrilled to introduce the Lakehouse for Healthcare and Life Sciences \u2014 a platform designed to help organizations collaborate with data and AI in service of a unified goal: improving health outcomes. The Lakehouse eliminates the need for legacy data architectures, which have inhibited innovation, by providing a simple, open and multi-cloud platform for all your data, analytics and AI workloads. Building on this foundation are solution accelerators developed by Databricks and our ecosystem of partners for high-value analytics and AI use cases such as disease prediction, medical image classification, and biomarker discovery.\nTo play this video, click here and accept cookiesWe know that healthcare organizations face a unique, and often painful, set of challenges that can significantly hinder innovation. We\u2019ve designed the Lakehouse to address these challenges and provide the following benefits:\nBuild a 360 degree view of the patient: It\u2019s widely accepted that a vast majority of medical data is unstructured, which makes gaining a holistic patient view that much harder with siloed systems. This problem gets exponential as healthcare becomes increasingly interconnected between healthcare providers, payers and pharma manufacturers. Lakehouse is open by design and supports all data types, enabling organizations to create a 360 degree view of patient health. Couple this with the pre-built data ingestion and curation solution accelerators to bring health data to your lakehouse, and it\u2019s even easier.Scale analytics for population-level insights: Scale is critical for initiatives like population health analytics and drug discovery, but for years legacy technology has failed to keep up with ballooning health data like genomics and imaging. Built in the cloud and designed for performance, the Lakehouse supports the largest of data jobs at lightning-fast speeds. For example, Regeneron reduced data processing from 3 weeks to 5 hours, and genotype- phenotype queries from 30 minutes to 3 seconds for workloads that scaled to 1.5M exomes. With the Lakeouse, organizations can quickly and reliably analyze data for millions of patients.Deliver real-time care and operations: Healthcare happens in real-time and requires real-time insights for critical use cases from managing ICU capacity to monitoring the distribution of temperature-sensitive vaccines. Unfortunately, traditional data warehouses aren\u2019t designed to operate in real-time. The Lakehouse enables real-time analysis on streaming data so organizations can deliver care when it's needed, not after the fact.Leverage predictive health insights: The future of healthcare is predictive, not descriptive. The Lakehouse provides a robust set of analytics and AI tools directly connected to your data so organizations can innovate drug discovery and patient care with machine learning. Additionally, our network of partners has built accelerators for high-value analytics and AI use cases, including drug targeting and repurposing, drug safety monitoring, disease prediction and digital pathology analysis for cancer detection.With these capabilities, Databricks is empowering a new breed of data and AI innovators in healthcare:\nUsing AI to develop diagnostic and therapeutic products that help children living with behavioral conditionsApplied machine learning to 17M+ electronic health records to identify new treatment indications for approved therapies.Delivering recommendations to patients using streaming data from connected health wearables for diabetes management.Tailor-made Solutions for Healthcare & Life SciencesTo help organizations realize value from their Lakehouse projects faster, Databricks and our ecosystem of partners have developed solution accelerators and open-source libraries\u2014like Glow for genomics and Smolder for HL7v2 messages\u2014to address common industry use cases.\nData Ingestion and Curation Tools - easily ingest structured and unstructured health data (e.g. FHIR\/HL7v2, imaging, genomics) into your Lakehouse for analytics at scale with our templates for data ingestion and curation.Analytics and AI Templates - packaged solutions for high-value analytics and AI use cases such as drug target identification, drug repurposing, disease risk prediction, medical image analytics (e.g. detecting cancer in pathology images) and more.Featured partner solutionsIntelligent Drug RepurposingInteroperabilityNatural Language Processing for HealthcareBiomedical Research Intelligent Data ManagementIdentify new therapeutic uses for existing drugs with the power of data and machine learning.Automate the ingestion of streaming FHIR bundles into your lakehouse and standardize with OMOP for patient analytics at scale.Extract insights from unstructured medical text for use cases such as automated PHI removal, adverse event detection, and oncology research.Improve biomarker discovery for precision medicine with a highly scalable and extensible whole-genome processing solution.Check out our full set of solutions on our Lakehouse for Healthcare and Life Sciences page.\nGet started building your LakehouseYou have the data. Now you have the platform. Join the hundreds of healthcare and life sciences organizations innovating on the Lakehouse. Here are some resources to help you get started:\nJoin us at HIMSS to meet with our technical experts and participate in live use case demosCheck out our new ebook Improving Health Outcomes with Data + AITry Databricks for freeGet StartedSee all News postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-are-ml-pipelines","text":"What are ML Pipelines?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWML PipelinesAll>ML PipelinesTypically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and cleaning, extracting features, and training a classification model with cross-validation. Though there are many libraries we can use for each stage, connecting the dots is not as easy as it may look, especially with large-scale datasets. Most ML libraries are not designed for distributed computation or they do not provide native support for pipeline creation and tuning.The ML Pipelines is a High-Level API for MLlib that lives under the \"spark.ml\" package. A pipeline consists of a sequence of stages. There are two basic types of pipeline stages: Transformer and Estimator. A Transformer takes a dataset as input and produces an augmented dataset as output. E.g., a tokenizer is a Transformer that transforms a dataset with text into an dataset with tokenized words. An Estimator must be first fit on the input dataset to produce a model, which is a Transformer that transforms the input dataset. E.g., logistic regression is an Estimator that trains on a dataset with labels and features and produces a logistic regression model.Additional ResourcesManaged MLflow ProductMemory Optimization and Reliable Metrics in ML Pipelines at NetflixProductionizing Spark ML Pipelines with the Portable Format for AnalyticsPractical ML | Virtual EventFree Training: Building and Deploying Machine Learning ModelsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/taylor-hosbach\/#","text":"Taylor Hosbach - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTaylor HosbachData Scientist at DIRECTVBack to speakersTaylor Hosbach is a Data Scientist at DIRECTV. He joins DIRECTV from Hopper and Epic where he utilized machine learning and advanced analytics to deliver actionable insights that improve business operations. He also has experience managing teams and working cross-functionally with the business to drive impact and opportunities for implementing Data Science solutions. Taylor holds an M.S. in Data Science from The University of Texas at Austin and a B.S. from Lehigh University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/01\/29\/strategies-for-modernizing-investment-data-platforms.html","text":"Strategies for Modernizing Investment Data Platforms - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorStrategies for Modernizing Investment Data Platformsby Ricardo PortillaJanuary 29, 2021 in Engineering BlogShare this postThe appetite for investment was at a historic high in 2020 for both individual and institutional investors. One study showed that \u201cretail traders make up nearly 25% of the stock market following COVID-driven volatility\u201d. Moreover, institutional investors have piled on investments in cryptocurrency, with 36% invested in cryptocurrency, as outlined in Business Insider . As investors gain access to and trade alternative assets such as cryptocurrency, trading volumes have skyrocketed and created new data challenges. Moreover, cutting edge research is no longer restricted to institutional investors on Wall Street -- today\u2019s world of investing extends to digital exchanges in Silicon Valley, data-centric market makers, and retail brokers that are investing increasingly in AI-powered tools for investors. Data lakes have become standard for building financial data products and research, but they come with a unique set of challenges:\nLack of blueprints for how to build an enterprise data lake in the cloudOrganizations are still struggling to guarantee both reliability and timeliness of their data, leading to sub-optimal processes and diluted insightsAs a result, scalable AI (such as volatility forecasting) is difficult to achieve due to high maintenance costs and the lack of a blueprint for scale and hence trading profitability. As part of our suggested blueprint, we recommend standardization on Delta Lake, which is an open-source storage layer that brings ACID transactions to Apache Spark\u2122 and big data workloads. A table in Delta Lake is both a batch table, as well as a streaming source and sink. Streaming data ingest, batch historic backfill, and interactive queries all just work out of the box. In particular, since raw market data is delivered in real-time and must be used in near real-time to support trading decisions, Delta Lake is critical to support trading use cases.\nThis blog has 2 main sections. The first covers detailed options for landing financial market data into Delta Lake. The second section covers a blueprint for productionalizing use cases such as financial product volatility forecasting as well as market surveillance on Delta Lake. Notably, as part of the use cases, we introduce an open-source time-series package developed as part of Databricks Labs, which helps build the foundation for the use cases above.\nHow to build a market Delta LakeIn this blog, through a series of design patterns and real-world examples, we will address the data challenges from the previous section. As a visual guide, the reference architecture below will be the basis for how to build out data lake sources and curate datasets for end reporting, trading summaries, and market surveillance alerts.\nFundamental data source ingestionFundamental data, (positioned at the top left in Figure 1) loosely defined as economic and financial factors used to measure a company\u2019s intrinsic value, is available today from most financial data vendors. Two of the most common sources include Factset and S&P Market Intelligence Platform. Both of these sources make data available via FTP, API, and a SQL Server database. Since data is available via a database for factor analysis, there are three easy options for ingestion into Delta Lake:\nOption 1 - Partner ingestion networkDatabricks has partnered with six companies which make up the \u201cData Ingestion Network of Partners.\u201d Our partners have capabilities to ingest data from a variety of sources, including FTP, CRMs, marketing sources, and database sources. Since financial vendors allow financial clients to host databases, our partner tools can be used to pull out data to store directly in Delta Lake. Full documentation on how to ingest using this network and a listing of partners is located at Databricks\u2019 documentation, Partner data integrations.\nOption 2 - Use native cloud-based ingestion toolsCloud service providers also have existing tools for database replication into Delta Lake. Below are two options for ingesting from databases (on-prem or cloud) into Delta Lake.\nAWSAWS offers a solution, Database Migration Services, which allows organizations to set up a Change Data Capture (CDC) process to replicate database changes to cloud data lakes. We\u00a0 outlined a specific method for replicating database changes to Delta Lake in our blog, \u201cMigrating Transactional Data to a Delta Lake using AWS DMS.\u201d Since Xpressfeed S&P data, for example, has hundreds of sources, ranging from ESG risk scores and alternative data to fundamental earnings and news sentiment datasets, an automated way to replicate these to Delta Lake is critical. The AWS solution mentioned above provides a simple way to set this up.\nAzureOne of Azure\u2019s most popular services is Azure Data Factory (ADF) and with good reason. ADF allows copying from many different data sources, including databases, FTP and even cross-cloud sources such as BigQuery. In particular, there are two methods of writing data to Delta Lake from a SQL database:\nADF offers a simple \u2018Copy To\u2019 factory that simply copies database tables to blob storage (Blob or ADLS Gen2), and Delta Lake is a valid target table for this copy functionality.For a more customized transformation from a database to Delta Lake, ADF is flexible enough to read all tables from a database using an information schema as shown here. From here, one can simply configure a Databricks notebook which uses the input table name from the information schema and copies each table by executing a Databricks notebook which reads from the database using JDBC. Examples are here.API-based data source ingestionBloomberg is one of the industry standards for market data, reference data, and hundreds of other feeds. In order to show an example of API-based ingestion (middle left in Figure 1) from a Bloomberg data subscription, the B-PIPE (Bloomberg data API for accessing market data sources) emulator will be used. The Java market data subscription client code in the original emulator has been modified in the code below to publish events into a Kinesis real-time stream using the AWS SDK.\nWrite B-PIPE market data to streaming service\/\/ Open Market Data Subscription service\nsession.openServiceAsync(\"\/\/blp\/mktdata\", new CorrelationID(-9999));\n\n\/\/ Create list of securities to ingest continuously into Delta Lake\nSubscriptionList slist = new SubscriptionList();\nslist.add(new Subscription(\"SPY US EQUITY\", RunMarketDataSubscription._fields));\nslist.add(new Subscription(\"AAPL 150117C00600000 EQUITY\", RunMarketDataSubscription._fields));\nslist.add(new Subscription(\"AMD US EQUITY\", RunMarketDataSubscription._fields));\nsession.subscribe(slist)\n\n\/\/ Inside loop through continuous stream of messages from B-PIPE market data subscription \n\/\/ Use Kinesis client to write records retrieved from API to Kinesis stream\nAmazonKinesisClient kinesisClient = new AmazonKinesisClient(new BasicAWSCredentials(, ));\nString kinesisEndpointUrl = \"https:\/\/kinesis.us-east-1.amazonaws.com\";\nString regionName = \"us-east-1\";\nkinesisClient.setEndpoint(kinesisEndpointUrl);\n\n\/\/ Create PutRecordRegust with bytes from API request (output) and include sequence number\nPutRecordRequest putRecordRequest = new PutRecordRequest();\nputRecordRequest.setStreamName( \"databricks-bpipe\" );\nputRecordRequest.setData(ByteBuffer.wrap( output.getBytes() ));\nputRecordRequest.setPartitionKey( \"mkt-data-partitionKey\" );\nputRecordRequest.setSequenceNumberForOrdering( sequenceNumberOfPreviousRecord );\nPutRecordResult putRecordResult = kinesisClient.putRecord( putRecordRequest );\nsequenceNumberOfPreviousRecord = putRecordResult.getSequenceNumber();Write data from Kinesis stream to Delta Lakeval kinesis = spark.readStream\n .format(\"kinesis\")\n .option(\"streamName\", \"databricks-bpipe\")\n .option(\"region\", \"us-east-1\")\n .option(\"initialPosition\", \"latest\")\n .load()\n\nval df = kinesis\n  .withColumn(\"mktdata\", col(\"data\").cast(\"string\"))\n  .withColumn(\"event_ts\", split(col(\"mktdata\"), \",\")(0))\n  .withColumn(\"ticker\", split(split(col(\"mktdata\"), \",\")(1), \" \")(1))\n  .withColumn(\"quote_pr\", translate(split(col(\"mktdata\"), \",\")(2), \"$\", \"\"))\n  .withColumn(\"event_dt\", col(\"event_ts\").cast(\"timestamp\").cast(\"date\"))\n\ndf\n .writeStream\n .partitionBy(\"event_dt\")\n .format(\"delta\")\n .option(\"path\", \"\/tmp\/databricks\/bpipe\")\n .option(\"checkpointLocation\", \"\/tmp\/databricks\/bpipe_cp\")\n .start()Transform and read recordsdisplay(spark.read.format(\"delta\").load(\"\/tmp\/databricks\/bpipe\"))\nTick data source ingestionTick data (positioned in bottom left of Figure 1), which is the general term for high resolution intraday market data, typically comes from data vendors as batch sources in CSV, JSON or binary formats. Types of tick data include trade, quote, and contracts data, and an example of delivery\u00a0 is the tick data history service offered by Thomson Reuters. The easiest way to continuously land data into Delta Lake from these sources is to set up the Databricks autoloader to read from a bucket and redirect data into a separate Delta Lake table. From here, various ETL processes might curate each message type into refined or aggregated Delta tables. The benefits of autoloader are twofold:\nReliability and Performance inherited from Delta LakeLower costs due to underlying use of SQS (AWS ) or AQS (Azure) to avoid re-listing input files as well as a managed checkpoint to avoid manual selection of the most current unread files.From Delta Lake to financial services use case productionizationBeyond the data collection challenges that surface when building any data platform, investment management firms increasingly need to address the incorporation of AI into product suites, as well as managing costs for feature engineering. In particular:\nBoth retail and institutional investment firms need to also be able to query and run ETL on data lakes in a cost-effective manner and minimize the amount of maintenance costs associated with enriching and querying data lakes.Retail investors expect AI-powered offerings and insights in subscriptions. The optimal solution will host the AI infrastructure in such a way that users can create AI-powered applications and dashboards where time spent on the setup of libraries and elastic compute infrastructure is minimized, and the underlying processing can be scaled to billions of data points that come in daily from transactional data sources (customer transactions and tick quotes alike).Now that we\u2019ve presented reliable, efficient approaches for landing financial datasets into a cloud data lake, we want to address some of the existing gaps between financial datasets in the cloud and AI-powered products.\nThe image above shows how datasets and siloed infrastructure are not enough to deliver investment analysis products in production. Most FSIs have adopted nearly all of the AI use case enablers on the right-hand side but have failed to maximize the volume-weighted overlap of these with core datasets. The Databricks Unified Data Analytics Platform subsumes the first four AI use case enablers out of the box. To make productionization more concrete, we\u2019ll show how to use a new Databricks open-sourced package tempo for manipulating time series at scale. Then we\u2019ll dive into the following use case feature creation templates which use tempo and show how to get the best of both worlds in the Venn diagram above.\nRetail investing details using fundamental data to inform daily volatility predictions.Market surveillance details a process for summarizing price improvement and detecting spoofing.Tempo - Time Series PackageIn financial services, time series are ubiquitous, and we find that our customers struggle with manipulating time series at scale. In the past, we have outlined a few approaches to scaling time-series queries. Now, Databricks Labs has released a simple common set of time-series utilities to make time-series processing simpler in an open-source package called tempo. This package contains utilities to do the following:\nAS OF joins to merge up to millions of irregular time series togetherFeature creation with rolling aggregations of existing metricsOptimized writes to Delta Lake ideal for ad-hoc time-series queriesVolume-weighted average price (VWAP) calculationsResamplingExponential Moving Average calculationsBy combining the versatile nature of tick data, reliable data pipelines and open source software like tempo, organizations can unlock exponential value from a variety of use cases at minimal costs and fast execution cycles. The next section walks through two recurring themes in capital markets which utilize tempo: volatility forecasting and market surveillance.\nVolatility forecasting methodology with fundamental and technical dataS&P Global Market Intelligence provides fundamental data that can be ingested using a mechanism called Xpressfeed (covered earlier in this guide). Some important points about this feed are that:\nIt covers thousands of fundamental data metricsIt covers hundreds of thousands of globally listed and unlisted equitiesReporting frequency is daily \u2013 there is a filing date that can be used for point-in-time analysesAlthough we do not cover the curation process for the tick ETL (contact Databricks sales for more information on this use case), we outline the processing from standard tick formats to a final forecasting object using the tempo library; our implementation is in the links reported in the bottom of this blog. The high-level details are as follows:\nCreate Point-in-time Calendar - Merge the latest fundamental data onto the latest calendar date using the filing date (fundamental data point filing date as of trade date). Commonly referred to as AS-OF join, this operation is usually expensive and subject to technical bottlenecks in a highly imbalanced dataset. tempo will guarantee this operation to be evenly distributed to leverage at best the cloud elasticity (and its associated costs).Create peer groups - using meaningful fundamental data items such as EPS, return on equity, float % (to represent stakeholder holdings), form peer groups based on each metric. Note that the data item values need to be pivoted to perform meaningful feature engineering here.Resample tick data to the hour (or whatever granularity desired). Hourly is chosen due to the fact that daily aggregation does not provide enough granularity for a good forecast on volatility.Forecast market volatility on Databricks using the runtime for machine learning.Aggregate forecasting results to find max \/ min volatility companies based on securities being evaluated.\nOne of the noteworthy aspects of this data architecture is the last transitions when creating gold forecasting tables. In particular,\nWe have incorporated ML as part of the feature engineering processing. This means we should apply full rigor for CI\/CD as part of ML governance. Here is a template for accomplishing this in full rigor.We have chosen to highlight the importance of GPUs for forecasting volatility. In the notebook example at the end of this blog, we have chosen to use xgboost and simple range statistics on various quote metrics as part of our features. By leveraging the gpu_hist tree method and fully-managed GPU clusters and runtime, we can save 2.65X on costs (and 2.27X on runtime), both exhibiting the hard cost reduction and productivity savings for data teams.\u00a0 These metrics were obtained on 6 months of tick data from a major US exchange.Ultimately, with the help of tempo and Databricks Runtime for Machine Learning, retail brokerages can service their clients with dashboards unifying fundamental and technical analysis using AI techniques. Below is the result of our peer group forecasts.\nMarket surveillance methodology with tick dataMarket surveillance is an important part of the financial services ecosystem, which aims to reduce market manipulation, increase transparency, and enforce baseline rules for various assets classes. Some examples of organizations, both governmental and private, that have broad surveillance programs in place include NASDAQ, FINRA, CFTC, and CME Group. As the retail investing industry gets larger with newer and inexperienced investors (source), especially in the digital currency space, it is important to understand how to build a basic surveillance program that reduces financial fraud and increases transparency in areas such as market volatility, risk, and best execution. In the section below, we show how to build basic price improvement summaries, as well as putting a basic spoofing implementation together.\nPrice improvementPrice improvement refers to the amount of improvement on the bid (in the case of a sell order) or the ask (in the case of a buy order) that brokers provide clients. This is important for a retail broker because it often contributes to perceived quality of a broker if it consistently saves clients money on a set of trades over time. The basic concept of price improvement is:\nMaria places a market order at 10:00 AM for stock XYZ for 100 shares at which the best bid\/ask is $10\/$11Broker A routes the order to an exchange to get an execution price of $10.95 per shareThe savings is $0.05 * 100 = $5.00 on this execution, representing some modest price improvementEven though the improvement is small, over time, these savings can add up over hundreds of trades. Some brokers display this information in-app also for transparency and to showcase the ability to route to appropriate market centers or market makers to get good prices.\nCalculating price improvementPrice improvement is really a special case of slippage (how much the execution price shifts from the best bid\/ask at order arrival time). It affects digital currency as much as traditional equities, arguably more so since there is a high amount of volatility and order-volume fluctuation. For example, here are some insights on finance market depth and slippage. Below is a basic blueprint for how to calculate slippage using tempo (detailed code is available in the attached notebook):\nIngest market order messages (orders placed)Ingest execution messagesPerform AS OF join to order arrival time using tempoPerform AS OF join to execution time using tempoMeasure the difference in the execution price and the bid\/ask available at order arrival timeSummarize by firm and serve up in SQL analytics and\/or BI dashboardsIngestion of order book data to get orders and executions is typically available in JSON or other flat file formats from internal systems or OMS (order management systems). Once this data is available, the AS OF join operates on a pair of data frames as described in the official tempo documentation here:\nBelow we display the code which performs the join.\nfrom tempo.tsdf import TSDF\n\ntrades = spark.table(\"exchange_trades\")\ntrades_tsdf = TSDF(trades, ts_col = 'event_ts', partition_cols = [\"DATE\", \"TICKER\"])\nquotes_tsdf = TSDF(spark.table(\"tempo.delta_tick_quotes_6mo\"), ts_col='event_ts', partition_cols = [\"DATE\", \"TICKER\"])\nex_asof = trades_tsdf.asofJoin(quotes_tsdf, right_prefix = \"asof_ex_time\")\norders_tsdf = TSDF(ex_asof.df, ts_col = 'order_arrival_ts', partition_cols = [\"DATE\", \"TICKER\"])\norder_asof = ex_asof.asofJoin(quotes_tsdf, right_prefix = \"asof_ord_time\")\n\norder_asof \\\n  .df \\\n  .write \\\n  .format(\"delta\") \\\n  .mode('overwrite') \\\n  .saveAsTable(\"tempo.silver_trade_slippage\")\nOnce this data is available in Delta Lake, it can be sliced in various ways to get a summary of those securities that have prominent slippage. See the example below, which summarizes the log of the aggregate slippage for a slice of time on a trading day.\nSpoofingSpoofing refers to a market manipulation pattern which involves entry of artificial interest (via fake order placement) followed by execution on the opposite side to take advantage of best bid\/ask changes, which were falsely influenced by the original artificial interest. The spoofing order of events typically involves cancellation of orders as well - we outline a simple example below.\nSpoofing is one of the hundreds of different market manipulation techniques and occurs in many different asset classes. In particular, it has been part of most market surveillance programs for equities, but due to increased demand in digital currencies such as bitcoin and Ether, it is of increased importance. In fact, since the volatility of cryptocurrencies is so variable, it is critical to protect clients from potential spoofing activities to secure trust in crypto platforms, whether they be exchanges or DeFi frameworks.\nSample patternThe sequence of steps to detect spoofing applies to other manipulation patterns (e.g. front-running, layering, etc), so we\u2019ve outlined a simple approach to highlight some underlying techniques.\nSave order placement information - key on ORDER ID and sequence numberSave cancellation information for all orders (comes equipped with ORDER ID)Record NBBO at order arrival time (order_rcvd_ts in data below) as well as the NBBO prior to order arrivalJoin orders and cancellations (look for full cancellations) and record sequences of the following form:\nNBBO change at limit order placement from seconds prior to order placement (for a sell order, decrease in best ask)Cancellation at order placement (we refer to a fake order as a non-bonafide order)Execution on the opposite side of the order placement aboveWash trade (self-trade) activity by the same market participant (or as a nuance, this could represent different MPIDs under the same CRD)Sample pattern for capturing the NBBO (quote as a proxy here) information using the tempo AS OF join:\nfrom tempo.tsdf import TSDF\n\norders_and_cncls_tsdf = TSDF(orders_and_cncls, ts_col = 'prior_order_rcvd_ts', partition_cols = [\"DATE\", \"TICKER\"])\nprior_quotes_tsdf = TSDF(prior_quotes, ts_col='event_ts', partition_cols = [\"DATE\", \"TICKER\"])\nprior_order_asof = orders_and_cncls_tsdf.asofJoin(prior_quotes_tsdf, right_prefix = \"asof_prior_order\")\nprior_order_asof = TSDF(prior_order_asof.df, ts_col = 'order_rcvd_ts', partition_cols = [\"DATE\", \"TICKER\"])\norder_asof = prior_order_asof.asofJoin(prior_quotes_tsdf, right_prefix = \"asof_order\")\n\nnbbo_deltas = order_asof.df \\\n  .withColumn(\"nbbo_ask_delta_direction\", signum(col(\"asof_prior_order_ASK_PRICE\") - col(\"asof_order_ASK_PRICE\"))) \\\n  .withColumn(\"nbbo_bid_delta_direction\", signum(col(\"asof_order_BID_PRICE\") - col(\"asof_prior_order_BID_PRICE\"))) \\\n  .withColumn(\"nbbo_ask_delta\", abs(col(\"asof_prior_order_ASK_PRICE\") - col(\"asof_order_ASK_PRICE\"))) \\\n  .withColumn(\"nbbo_bid_delta\", abs(col(\"asof_order_BID_PRICE\") - col(\"asof_prior_order_BID_PRICE\")))\nBelow, we visualize the downward motion of the NBBO for a few sample orders, which validates the pattern we are looking for in the NBBO change.\nFinally, we save off the report of firms with non-bonafide executions that happen to coincide with some wash trading activity.\nConclusionsIn this blueprint, we\u2019ve focused on the ingestion of common datasets into Delta Lake as well as strategies for productionizing pipelines on Delta Lake objects. Utilizing Delta Lake enables FSIs to focus on product delivery for customers, ultimately resulting in increased AUM, decreased financial fraud, and increased subscriptions as the world of investing expands to more and more retail investors. From a technical perspective, all the use cases above are made possible by core tenets of a modern data architecture with help from the newly released tempo library:\nSupport for open-source packages and integration with industry-accepted frameworksInfrastructure support for AI use casesFeature creation templatesTime-series analyses supportWe have documented these approaches and provided feature creation templates for a few popular use cases in the notebook links below. In addition, we\u2019ve\u00a0 introduced tempo and its applications within these templates as a foundation for investment data platforms.\nTry the below notebooks on Databricks to accelerate your investment platforms today and contact us to learn more about how we assist customers with similar use cases.\nBloomberg API Ingestion NotebookVolatility Forecasting from Fundamental & Technical DataExecution Quality and SpoofingTry Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hao-zhu","text":"Hao Zhu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHao ZhuSenior Manager at NVIDIABack to speakersHao Zhu is senior manager, accelerated Spark applications at NVIDIA. Hao and his team mainly cover customer engagement and application development for RAPIDS Accelerator for Apache Spark. Hao is experienced in Hadoop, database, massively parallel processing query engines, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/performance-tuning-best-practices-on-the-lakehouse","text":"Performance-Tuning Best Practices on the Lakehouse | DatabricksWebinarPerformance-Tuning Best Practices on the LakehouseInside the life of a queryHave you heard all the buzz about the lakehouse, and are you wondering what happens under the hood? How does data come in, how do you lay out and refine it for best query performance, how do you run queries, what happens during query execution and how do you optimize for world-class performance and results?Join this webinar to discover the life of a query on Databricks SQL. This webinar includes demos, live Q&As and lessons learned in the field so you can dive in and find out how to harness all the power of the Lakehouse Platform.In this webinar, you\u2019ll learn how to:Quickly and easily ingest business-critical data into your lakehouse and continuously refine data with optimized Delta tables for best performance \u2014 no tuning requiredWrite, share and reuse queries with a native first-class SQL development experience on Databricks SQL \u2014 and unlock maximum productivityGet full transparency and visibility into query execution with an in-depth breakdown of operation-level details so you can dive inSpeakersFranco PatanoSr. Solutions ArchitectDatabricksLucas CerdanSr. Product ManagerDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/digital-twins","text":"Digital Twins | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorDigital TwinsPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedIncrease operational efficiency and improve decision-makingMarket dynamics and volatility are requiring manufacturers to bring products to market quicker, optimize production processes and build agile supply chains at scale at a lower price. To do so, many manufacturers have turned to building digital twins, which are virtual representations of objects, products, pieces of equipment, people, processes, or even complete manufacturing ecosystems.Digital twins are created using data derived from sensors (often IoT or IIoT) that are attached to or embedded in the original object. This data provides both structural and operational views of what happens to the object in real time, allowing engineers to monitor systems and model systems dynamics.Get started with our Solution Accelerator for Digital Twins to build performant and scalable end-to-end digital twins that:Process real-world data in real timeCompute insights at scale and deliver to multiple downstream applicationsOptimize plant operations with data-driven decisionsDownload notebooksResourcesBlogRead noweBookDownload nowWebinarLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/deliver-real-time-retail-insights","text":"Deliver Real-Time Retail Insights | DatabricksOn-DemandDeliver Real-Time Retail InsightsJoin us to learn how to remove common barriers to profitabilityAvailable on-demandRetailers get into trouble when they make decisions ahead of the information. But business is moving faster than ever, and traditional data platforms \u2014 such as data warehouses \u2014 weren\u2019t designed to operate in real time.Join us to learn how the Databricks Lakehouse for Retail is helping customers like Reckitt address these architectural challenges. You\u2019ll find out how to modernize your data and AI capabilities in ways that drive real-time decisions and enhance customer experiences.You\u2019ll discover:Why retailers are under so much pressure to make faster decisionsHow these pressures may dictate your choice of data architectureHow Reckitt standardized on the Lakehouse for Retail to deliver insights at scaleWhat useful real-time analytics look like in actionSpeakersBryan SmithIndustry Solutions DirectorDatabricksSergiy TkachukData Science ManagerReckittSaurabh ShuklaSpecialist Solutions ArchitectDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/partnerconnect","text":"Conex\u00e3o de parceiros | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWConex\u00e3o de parceirosDescubra e integre facilmente dados, an\u00e1lises e solu\u00e7\u00f5es de IA com seu lakehouseAssista \u00e0s demonstra\u00e7\u00f5esO Partner Connect facilita a descoberta de dados, an\u00e1lises e ferramentas de IA diretamente dentro da plataforma Databricks, e integra rapidamente as ferramentas que voc\u00ea j\u00e1 utiliza hoje. Com o Partner Connect, voc\u00ea pode simplificar a integra\u00e7\u00e3o de ferramentas em alguns cliques e estender rapidamente as capacidades do seu lakehouse.Conecte seus dados e ferramentas de IA ao lakehouseConecte facilmente seus dados preferidos e ferramentas de IA ao lakehouse e potencialize qualquer caso de uso de an\u00e1liseDescubra dados validados e solu\u00e7\u00f5es de IA para novos casos de usoUm portal \u00fanico para solu\u00e7\u00f5es de parceiros validadas para voc\u00ea criar seu pr\u00f3ximo aplicativo de dados mais rapidamenteConfigure em poucos cliques com integra\u00e7\u00f5es pr\u00e9-constru\u00eddasO Partner Connect simplifica suas integra\u00e7\u00f5es configurando automaticamente recursos, incluindo clusters, tokens e arquivos de conex\u00e3o, para se conectar com solu\u00e7\u00f5es de parceirosComece como um parceiroOs parceiros de banco de dados est\u00e3o posicionados de forma \u00fanica para oferecer aos clientes insights anal\u00edticos mais r\u00e1pidos. Aproveite o desenvolvimento da Databricks e recursos de parceiros para crescer ao lado de nossa plataforma aberta, baseada nas nuvens.Comece uma parceria\"Com base em nossa parceria de longa data, o Partner Connect nos permite projetar uma experi\u00eancia integrada entre nossas empresas e nossos clientes. Com o Partner Connect, oferecemos uma experi\u00eancia simplificada que torna mais f\u00e1cil do que nunca para que os milhares de clientes da Databricks, sejam usu\u00e1rios atuais do Fivetran ou os que nos encontrem por meio do Partner Connect, possam desbloquear insights em seus dados, descobrir mais casos de uso de an\u00e1lises e obter valor do seu lakehouse mais rapidamente, conectando facilmente centenas de fontes de dados ao seu lakehouse.\"\u2014 George Fraser, CEO da FivetranDemosFivetranConecte dados de mais de 180 aplicativos populares, incluindo aplicativos SaaS (Salesforce, Google Analytics etc.), no lakehousedbtComece com dbt Cloud e Databricks para construir transforma\u00e7\u00f5es de dadosPower BITraga as vantagens do desempenho e da tecnologia do Databricks Lakehouse para todos os seus usu\u00e1riosTableauCapacite todos os usu\u00e1rios com um data lakehouse para an\u00e1lises modernas conectando o Tableau Desktop ao Databricks SQLRiverySimplifique a jornada dos dados de a ingest\u00e3o at\u00e9 a transforma\u00e7\u00e3o e entrega no Delta LakeLabelboxPrepare facilmente dados n\u00e3o estruturados para IA e an\u00e1lises no LakehouseProphecyCrie e implemente pipelines Spark e Delta usando uma interface visual de arrastar e soltarArcionConecte fontes de dados ao lakehouse com uma plataforma de replica\u00e7\u00e3o distribu\u00edda baseada em CDCExperimente gratuitamenteRecursosBlogFevereiro de 2023 \u2013 An\u00fancio de novas integra\u00e7\u00f5es de parceiros no Partner ConnectSetembro de 2022 \u2013 Introdu\u00e7\u00e3o a novas integra\u00e7\u00f5es de parceiros no Partner ConnectJunho de 2022 \u2013 An\u00fancio de novas integra\u00e7\u00f5es de parceiros no Partner ConnectDesenvolva seus neg\u00f3cios na Databricks com o Partner ConnectDocumenta\u00e7\u00e3oGuia do Databricks Partner ConnectPronto para saber mais?Aproveite o desenvolvimento da Databricks e recursos de parceiros para crescer ao lado de nossa plataforma aberta, baseada nas nuvens.Comece uma parceriaEntre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=deltasharing-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erni-durdevic\/#","text":"Erni Durdevic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErni DurdevicSpecialist Solutions Architect (Geospatial) at DatabricksBack to speakersErni is a Big Data specialist helping Databricks customers to develop breakthrough applications at scale.\nHe is specialised in Data Engineering, focusing on geospatial and time series data workloads. He is the co-creator of DiscoverX, an active contributor to the open-source geospatial library Mosaic, and an enthusiastic member of the Geospatial SME group at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/driving-innovation-and-transformation-in-the-federal-government-with-data-ai","text":"Driving Innovation and Transformation in the Federal Government With Data + AI | DatabrickseBookDrive innovation in government with Data + AIThe opportunity for the federal government to leverage data analytics and AI cannot be overstated. With access to some of the largest current and historical data sets available for the United States \u2014 and with vast personnel resources and some of the best private sector use cases and applications of AI available in the world \u2014 the U.S. federal government has the ability to transform the efficiency and effectiveness of many of its agencies.In this eBook, you will learn:What opportunities are available for data and machine learning within the public sectorWhy a lakehouse approach can help with some of the biggest challenges facing federal agenciesHow the U.S. Citizenship and Immigration Services achieved a 24x performance gain in data processingGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amir-skovronik\/#","text":"Amir Skovronik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmir SkovronikDistinguished Software Engineer at AkamaiBack to speakersAmir is a distinguished engineer at Akamai with more than 10 years of experience in big data systems, and today functions as the technical leader of Asgard, the Akamai cloud base data warehouseLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/02\/17\/announcing-the-launch-of-databricks-on-google-cloud.html","text":"Announcing the Launch of Databricks on Google Cloud - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing the Launch of Databricks on Google Cloudby Hiral JasaniFebruary 17, 2021 in AnnouncementsShare this postToday, we are proud to announce the availability of Databricks on Google Cloud. This jointly developed service provides a simple, open lakehouse platform for data engineering, data science, analytics, and machine learning. It brings together the Databricks capabilities customers love with the data analytics solutions and global scale available from Google Cloud.\nOpen data platform meets open cloudDatabricks and Google Cloud share a common vision for an open data platform built on open standards, open APIs, and open infrastructure. With this partnership, organizations get the choice and flexibility to manage infrastructure and access data with the tools they need across cloud and on-premises environments. By adopting open frameworks and APIs, customers get the benefits of open source combined with managed cloud analytics and AI products.\nWhat does our new partnership mean for customers? Enterprises can now implement the Databricks Lakehouse Platform on Google Cloud \u2014 made possible by Delta Lake on Databricks. Delta Lake adds data reliability to data lakes with ACID transactions and versioning and better data governance and query performance to data in Google Cloud Storage. This announcement helps enterprises unify their analytics infrastructure on Google Cloud so they can simplify management for all data applications, including real-time streaming, SQL workloads, business intelligence, data science, machine learning, and graph analytics.\nThe open cloud approach also improves interoperability and portability for enterprises that want to use multiple public clouds for analytics applications. A recent Gartner study concluded that at least 80% of enterprises had adopted a multi-cloud strategy across multiple geographies. The multi-cloud capability of Databricks allows customers to increase the efficiency and productivity of data processes, improve customer experiences, and create new revenue opportunities even when data is distributed across more than one cloud. For example, one leading global fast-food company (and Google Cloud customer) wants to build and deploy marketing solutions, such as churn reduction, behavioral segmentation, and lifetime value for about a dozen global markets by year-end 2021. By architecting a global data platform with Databricks, they will provide each regional business with a choice for their public cloud platform.\nStreamlined integrationsDatabricks is tightly integrated with Google Cloud compute, storage, analytics, and management products to give customers a simple, unified experience with high performance and enterprise security.\nCompute and Storage: Built on Google Kubernetes Engine (GKE), Databricks on Google Cloud is the first fully container-based Databricks runtime on any cloud. It takes advantage of GKE\u2019s managed services for the portability, security, and scalability developers know and love. Read\/write access to GCS from Databricks allows customers to execute workloads faster and at lower costs.\nAnalytics: Databricks has an optimized connector with Google BigQuery that allows easy access to data in BigQuery directly via its Storage API for high-performance queries. The connector has support for additional predicate pushdown, querying named tables and views, and for directly running SQL on BigQuery and loading the results in an Apache Spark\u2122 DataFrame. Also, Looker\u2019s integration with Databricks and support for SQL Analytics, along with an open API environment on Google Cloud, complements the open, multi-cloud architecture. This integration gives Looker users the ability to directly query the data lake, providing an entirely new visualization experience.\nSecurity and Administration: Experience a simplified deployment from the Google Cloud Marketplace with unified billing and one-click setup inside the Google Cloud console. Databricks\u2019 integration with Google Cloud Identity allows customers to simply use their Google Cloud credentials for single sign-on and user provisioning on Databricks.\nPut Databricks to work on Google CloudSome of the most innovative use cases for Databricks on Google Cloud are in retail, telco, media and entertainment, manufacturing, and financial services. Across every industry, data is driving digital transformation initiatives. With the lakehouse architecture, Databricks and Google Cloud customers are finding new ways to accelerate data-driven innovation.\nHere are some of the most popular workloads customers are using Databricks for today. To learn more about industry-specific use cases, visit the Industry Solutions page.\nData lake modernizationDelta Lake on Databricks provides a modern foundation to transition from expensive, hard-to-scale on-premises systems to well-architected Google Cloud Storage\u2013based data lakes. In fact, companies that have migrated to Databricks from a cloud-based Hadoop service realize up to 50% performance improvement in data processing and 40% lower monthly infrastructure cost. Moving to Databricks on Google Cloud helps customers reduce administrative overhead, quickly scale up or down compute resources and reduce operational costs with autoscaling and job termination.\nScalable data processing to prepare data for analyticsDatabricks simplifies your ETL architecture and lowers costs to ingest and process data using a high-performance runtime on clusters optimized for data processing at scale. With Delta Lake, you can reliably store all data (structured, semi-structured, and unstructured) in raw format and incrementally move it through the transformation stages to an aggregated, BI-ready tier with ACID guarantees.\nReliable analytics on the data lakeCustomers use Delta Lake on top of data lakes based on Google Cloud Storage file-store to bring reliability, performance, and lifecycle management. Delta Lake helps prevent data corruption, run faster queries, improve data freshness, and reproduce ML models, allowing customers to always trust their data for analytical insights. In addition, Databricks provides Delta Engine to significantly accelerate query performance on data lakes, especially those enabled by Delta Lake.\nData science and machine learningManaged MLflow on Databricks allows data teams to track all experiments and models in one place, publish dashboards, and facilitate handoffs with peers and stakeholders across the entire workflow \u2014 from raw data to insights. Databricks\u2019 collaborative workspace allows data teams to explore data, share insights, run experiments, and build ML models faster to be more productive.\nGetting startedThe launch of Databricks on Google Cloud is a win-win for customers. The tight integration of Databricks with Google Cloud\u2018s analytics and AI products delivers a broad range of capabilities \u2014 with more to come. Together, we will continue to innovate and support customers in building intelligent applications that solve tough data problems.\nIf you are interested in Databricks on Google Cloud, request access via the product page. To learn more, visit us at the launch event hosted by TechCrunch where Ali Ghodsi and Thomas Kurian share their vision from this partnership and the benefits to customers.\nSIGN UP FOR FREE TRIALTry Databricks for freeGet StartedSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/saad-ansari\/#","text":"Saad Ansari - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSaad AnsariSenior Staff Product Manager at DatabricksBack to speakersSaad is a product manager at Databricks working on the Developer Ecosystem. Prior to this he was CTO and co-founder at Connecterra using Artificial Intelligence to improve sustainability, productivity and animal welfare in the Dairy Industry (think Fitbit for cows!). Saad has also worked as a PM and Developer at Microsoft. He holds a masters in computer science from Stanford.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Stop Credit Card Fraud: Capital One and Other Best Practices\u6295\u8cc7\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3092\u30e2\u30c0\u30ca\u30a4\u30ba\u3059\u308b\u6226\u7565 \u2192\u30c8\u30e9\u30f3\u30b6\u30af\u30b7\u30e7\u30f3\u30a8\u30f3\u30ea\u30c3\u30c1\u30e1\u30f3\u30c8\u306b\u3088\u308b\u9867\u5ba2\u4f53\u9a13\u306e\u6539\u5584 Data + AI Summit 2022\u306b\u304a\u3051\u308b\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u5411\u3051\u306e\u4e3b\u306a\u30dd\u30a4\u30f3\u30c8\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059\u304a\u5ba2\u69d8\u306e\u30d3\u30b8\u30cd\u30b9\u30b4\u30fc\u30eb\u3092\u304a\u805e\u304b\u305b\u304f\u3060\u3055\u3044\u3002Databricks \u306e\u30b5\u30fc\u30d3\u30b9\u30c1\u30fc\u30e0\u304c\u304a\u5f79\u306b\u7acb\u3061\u307e\u3059\u3002Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alexander-vanadio","text":"Alexander Vanadio - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlexander VanadioPrincipal Consultant at OptivBack to speakersAlex has studied Computer Science at the University of Maryland, College Park. He has been doing some combination of software engineering, data engineering, and ML engineering for over 15 years. Most recently, he has been working on PB scale streaming workloads for a Fortune 500 company.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/product\/unity-catalog","text":"Governan\u00e7a unificada para dados, an\u00e1lises e IA | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWUnity CatalogGovernan\u00e7a unificada para dados, an\u00e1lises e IA\n\u00a0Come\u00e7arAssista \u00e0 demonstra\u00e7\u00e3o\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowO Unity Catalog \u00e9 uma solu\u00e7\u00e3o de governan\u00e7a unificada para todos os dados e ativos de IA em seu lakehouse, incluindo arquivos, tabelas, modelos de machine learning e dashboards, independentemente da nuvem usada.Governan\u00e7a centralizada para dados e IACom um modelo baseado em ANSI SQL, centralize a governan\u00e7a comum de arquivos, tabelas, dashboards e modelos de ML, independentemente da nuvem.Busca e descoberta de dados integradasEncontre, entenda e consulte rapidamente dados em todo o seu conjunto de dados para m\u00e1xima produtividade.Desempenho e escalaObtenha melhor desempenho para suas queries com servi\u00e7o de metadados de baixa lat\u00eancia e otimiza\u00e7\u00e3o autom\u00e1tica de tabelas.Linhagem automatizada para todas as cargas de trabalhoCrie uma vis\u00e3o unificada e transparente de todo o seu ecossistema de dados, enriquecido por uma linhagem automatizada e precisa de todas as cargas de trabalho em SQL, R, Python, Scala, em todos os tipos de ativos: tabelas, notebooks, fluxos de trabalho e dashboards.Integra\u00e7\u00e3o com suas ferramentas existentesAproveite seus cat\u00e1logos de dados e solu\u00e7\u00f5es de governan\u00e7a existentes para preparar seus dados e estrat\u00e9gia de governan\u00e7a de IA para o futuro.Como funcionaGerencie e controle centralmente todos os ativos de dadosCom o modelo de governan\u00e7a comum baseado no padr\u00e3o aberto ANSI SQL, simplifique a governan\u00e7a de arquivos, tabelas, dashboards e modelos de ML, independentemente da nuvem. Defina as pol\u00edticas de acesso no n\u00edvel da conta uma vez e aplique-as a todas as cargas de trabalho e workspaces. O Unity Catalog mant\u00e9m um log das opera\u00e7\u00f5es realizadas nos dados, fornecendo auditoria centralizada e precisa dos seus dados. Voc\u00ea pode cumprir os requisitos de conformidade e auditoria com total tranquilidade.\u00a0Gerenciar controles de acesso refinadosUse fun\u00e7\u00f5es SQL padr\u00e3o para definir filtros de linha e m\u00e1scaras de coluna e habilitar controles de acesso espec\u00edficos. \u00c0 medida que a Databricks continua desenvolvendo recursos para melhorar a escalabilidade e a integra\u00e7\u00e3o, os pr\u00f3ximos controles de acesso baseados em atributos permitir\u00e3o definir pol\u00edticas de acesso com base em tags personalizadas (atributos).Experi\u00eancia de busca de dados unificada e seguraEncontre, entenda e consulte rapidamente dados relevantes em todo o seu acervo de dados com uma experi\u00eancia de busca unificada criada para analistas de dados, engenheiros de dados e data scientists. No Unity Catalog, a busca de dados \u00e9 segura por padr\u00e3o: o acesso aos resultados \u00e9 limitado com base nos privil\u00e9gios dos usu\u00e1rios. Assim, voc\u00ea obt\u00e9m uma camada extra de seguran\u00e7a para prote\u00e7\u00e3o da privacidade.Desempenho de query aprimorado em qualquer escalaO Unity Catalog oferece desempenho de query aprimorado por meio de um servi\u00e7o de metadados de baixa lat\u00eancia e ajuste autom\u00e1tico de tabela. As queries s\u00e3o executadas mais rapidamente em todas as escalas. A compacta\u00e7\u00e3o autom\u00e1tica e ass\u00edncrona de dados otimiza os tamanhos dos arquivos e reduz automaticamente a lat\u00eancia de entrada\/sa\u00edda (E\/S) em segundo plano.Linhagem de dados automatizada e em tempo realObtenha visibilidade de ponta a ponta do fluxo de dados em seu lakehouse com linhagem de dados automatizada em tempo real em todas as cargas de trabalho em SQL, Python, Scala e R. Realize rapidamente verifica\u00e7\u00f5es de qualidade de dados, analise profundamente o impacto das altera\u00e7\u00f5es e depure quaisquer erros em seus pipelines de dados. Aproveite a verdadeira linhagem entre tabelas, colunas, notebooks, fluxos de trabalho e dashboards. Os gr\u00e1ficos de linhagem do Unity Catalog representam diferentes n\u00edveis de acesso. Sua disponibilidade \u00e9, portanto, limitada de acordo com os privil\u00e9gios de acesso dos usu\u00e1rios. Uma API REST tamb\u00e9m pode ser usada para recuperar a linhagem para integra\u00e7\u00f5es com outros cat\u00e1logos.Compartilhamento seguro de dados entre organiza\u00e7\u00f5esO Unity Catalog oferece suporte nativo ao\u00a0Delta Sharing, o primeiro protocolo aberto do mundo para compartilhamento seguro de dados. Ele permite que voc\u00ea compartilhe facilmente dados existentes nos formatos Delta Lake e Apache Parquet em qualquer plataforma de computa\u00e7\u00e3o. Os usu\u00e1rios n\u00e3o precisam estar na plataforma Databricks ou na mesma nuvem tamb\u00e9m. Na verdade, eles nem precisam estar em uma nuvem. Voc\u00ea pode compartilhar dados em tempo real sem precisar replic\u00e1-los ou copi\u00e1-los para outro sistema. Gra\u00e7as \u00e0s integra\u00e7\u00f5es nativas com Power BI, Tableau, Spark, Pandas e Java, os destinat\u00e1rios podem usar os dados compartilhados na ferramenta de sua escolha. Voc\u00ea pode centralizar o gerenciamento, a governan\u00e7a, a auditoria e o rastreamento do uso de dados compartilhados em uma \u00fanica plataforma.Integra\u00e7\u00f5es perfeitas com suas ferramentas existentesO Unity Catalog funciona com seus cat\u00e1logos de dados, sistemas de armazenamento de dados e solu\u00e7\u00f5es de governan\u00e7a existentes para que voc\u00ea possa aproveitar seus investimentos existentes e criar um modelo de governan\u00e7a preparado para o futuro sem custos de migra\u00e7\u00e3o caros.Dados e armazenamento na nuvemGovernan\u00e7a de dados e parceiros de cat\u00e1logoClientes\u201cO Unity Catalog nos ajudou a simplificar o gerenciamento de dados e os controles de acesso em toda a empresa. A equipe de dados da Compass integrou com seguran\u00e7a mais de 100 fontes de dados, migrou todos os workspaces para o Unity Catalog e criou uma camada de ouro para as principais partes interessadas explorarem para obter insights sobre \u00e1reas como clientes, produtos, uso, receita e muito mais, criando uma \u00fanica fonte da verdade, com controles de acesso abrangentes em toda a empresa.\u201d\u2014 Rajesh Nagpal, diretor s\u00eanior de engenharia de dados\u201cO Unity Catalog simplificou muito nossa implementa\u00e7\u00e3o de controle de acesso baseado em fun\u00e7\u00f5es. Agora, temos a capacidade de proteger dados em n\u00edvel de cat\u00e1logo, banco de dados, tabela e coluna. Fornecemos, de forma transparente, o n\u00edvel adequado de acesso a todos os usu\u00e1rios. Conseguimos adequar o gerenciamento e a seguran\u00e7a do acesso aos dados com confian\u00e7a para atender \u00e0s nossas r\u00edgidas pol\u00edticas de conformidade e privacidade.\u201d\u2014 Chris Locklin, gerente de engenharia de plataformas de dados da Grammarly\u201cAo adotar o Unity Catalog, a Milliman conseguiu criar um v\u00ednculo direto entre seus vastos ativos de dados e seus usu\u00e1rios, por meio de gerenciamento de acesso simplificado e complexidade de armazenamento reduzida. O Unity Catalog oferece \u00e0 Milliman a capacidade de explora\u00e7\u00e3o colaborativa de dados e armazenamento simplificado, atendendo aos rigorosos padr\u00f5es do setor de sa\u00fade. Com o Unity Catalog, podemos escalar rapidamente com base nas necessidades dos nossos clientes.\u201d\u2014 Dan McCurley, arquiteto de solu\u00e7\u00f5es em nuvem da Milliman\u201cO Unity Catalog nos permite construir uma plataforma de \u00faltima gera\u00e7\u00e3o que libera todo o potencial de ve\u00edculos definidos por software que evoluem e melhoram \u00e0 medida que acumulam quil\u00f4metros \u2013 melhorando assim a experi\u00eancia de dire\u00e7\u00e3o para os clientes e maximizando os benef\u00edcios ambientais do transporte el\u00e9trico. Agora, temos um cat\u00e1logo de dados centralizado e gerenciamento de acesso em v\u00e1rias equipes e workspaces, o que abriu oportunidades sem precedentes para colabora\u00e7\u00e3o e inova\u00e7\u00e3o.\u201d\u2014 Venkat Sivasubramanian, diretor s\u00eanior de Big Data\u201cO Unity Catalog realmente mudou o jogo para n\u00f3s. Nossos analistas podem acessar as tabelas externas da AWS em tempo real nos workspaces da Databricks e junt\u00e1-los \u0000\u00e0s tabelas do Delta Lake. Assim, aproveitamos as vantagens de desempenho oferecidas pelo Databricks SQL sem migrar nossas tabelas Glue. Com o Unity Catalog, diferentes equipes podem colaborar umas com as outras sem ter que mover dados constantemente.\u201d\u2014 Rajat Gupta, gerente de engenharia da Warner Bros. DiscoveryRecursosApresenta\u00e7\u00f5es e webinars[Apresenta\u00e7\u00e3o] Governan\u00e7a de dados e compartilhamento de lakehouse no Data + AI Summit 2022[Webinar sob demanda] Como simplificar dados e governan\u00e7a de IAe-books e blogs[e-book] Data, Analytics and AI governanceAn\u00fancio da disponibilidade geral da linhagem de dados no Unity CatalogAn\u00fancio da disponibilidade da linhagem de dados com o Unity CatalogApresentamos o Unity Catalog da Databricks: Governan\u00e7a refinada para dados e IA no LakehouseDocumenta\u00e7\u00e3oDocumenta\u00e7\u00e3o da AWSDocumenta\u00e7\u00e3o do AzureTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
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\u793e\u3068\u3057\u3066\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c918 \u304b\u56fd\u300114 \u306e\u696d\u754c\u3001600 \u540d\u306e CIO \u306e\u610f\u8b58\u8abf\u67fbAI \u306e\u6210\u529f\u306b\u306f\u30c7\u30fc\u30bf\u6226\u7565\u304c\u4e0d\u53ef\u6b20\u3067\u3042\u308b\u3053\u3068\u304c\u6700\u65b0\u306e\u8abf\u67fb\u3067\u660e\u3089\u304b\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3067\u306f\u3001CIO \u306e\u8996\u70b9\u3092\u6398\u308a\u4e0b\u3052\u3066\u89e3\u8aac\u3057\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9MLOps \u306e\u6539\u5584\u3092\u8ffd\u6c42\u3059\u308b ML \u30a8\u30f3\u30b8\u30cb\u30a2\u3084\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u5411\u3051\u306b MLOps \u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u89e3\u8aac\u3057\u3066\u3044\u307e\u3059\u3002eBook \u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-and-booz-allen-team-to-bring-unified-analytics-to-us-government-clients","text":"Databricks and Booz Allen Team to Bring Unified Analytics to US Government ClientsPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks and Booz Allen Team to Bring Unified Analytics to US Government ClientsBooz Allen Integrates Databricks\u2019 Product into its Open Data Platform for On-Premises Deployments; Supports Government Agencies\u2019 Ability to Manage Big Data\nJune 11, 2019Share this postSAN FRANCISCO \u2014 June 11, 2019\u00a0\u2014 Databricks, the leader in Unified Analytics and founded by the original creators of Apache Spark\u2122, and Booz Allen Hamilton, a leading provider of machine learning services to the U.S. Federal Government, today announced the two companies are teaming up to help Federal agencies scale their data analytics capabilities and accelerate AI initiatives across on-premise, hybrid and cloud environments. Booz Allen will integrate Databricks\u2019 product and the open source technology Delta Lake into its Open Data Platform and offer the unique ability to deploy on cloud, hybrid, or on-premises infrastructure along with their expert services for data science and data engineering.\nAccording to a 2019 Gartner survey of CIOs and other IT leaders, \u2018When asked what technology areas will be game changers, all industries and levels of government see the top three game-changing technologies as artificial intelligence (AI)\/machine learning (27%), data analytics\/predictive analytics (22%) and cloud technologies (19%).\u2019 However, right now the industry continues to see government organizations encounter challenges when trying to pursue these initiatives due to complex security and compliance requirements, poor scalability of legacy IT infrastructure, and perceived risks associated with cloud and IT modernization efforts.\n\u201cBy leveraging a solution that integrates Databricks\u2019 product and Delta Lake into the Booz Allen Hamilton Open Data Platform, government organizations can accelerate current data initiatives no matter where their data lives today,\u201d said Dan Tucker, vice president at Booz Allen Hamilton. \u201cMany of our clients are interested in moving to cloud but leverage on premise or hybrid environments today. The joint solution is designed to improve the reliability and performance of today\u2019s on premise infrastructure and makes future migration to cloud faster and easier because these workloads can also run on the secure, cloud-based version of Databricks Unified Analytics Platform.\u201d\nBooz Allen\u2019s Open Data Platform\u2122 (ODP) features best-of-breed open source software to manage the full lifecycle of big data from ingest to insight. Now Booz Allen can integrate Databricks\u2019 product and Delta Lake with ODP and offer U.S. Government clients the unique ability to deploy it on-premises or onto hybrid infrastructure\u2014along with expert data science and data engineering insights\u2014to help government agencies accelerate current data initiatives no matter where their data lives today.\nThrough this relationship, U.S. Federal Government clients can rapidly deploy state of the art big data and analytics technology with Databricks\u2019 product and Delta Lake at the highest levels of classified networks.\n\u201cBooz Allen and Databricks recognize Federal customers are at varying levels of adoption when it comes to cloud adoption. Together we are providing a solution that is ready now and future proof,\u201d said Michael Hoff, senior vice president of Business Development and Partners at Databricks. \u201cThe ability to gain new insights for data-driven decisions is no longer limited by legacy infrastructure or complex security and compliance requirements. Our solution set enables organizations to gain value, regardless of where they are in the IT modernization journey, and it provides a path for continued evolution.\u201d\nDatabricks and Booz Allen have worked together to deliver high-scale data engineering and data science use cases for multiple government agencies. Customer examples include a government agency working with Booz Allen and Databricks to ingest and transform data from multiple streaming sources and make the data ready for data scientists and analysts in real time. These users perform interactive data exploration and advanced analytics at scale including geospatial and spatiotemporal correlations. Another government agency is working with Booz Allen and Databricks to move an on-premises data lake to a public cloud provider to develop advanced analytics on structured and unstructured data while maintaining sophisticated security controls. This solution lowered infrastructure cost by reducing several million hours of compute resources\u00a0 for the same workload and also enabled elastic scaling and easier collaboration for users. In recognition of these clients projects and impact in the market, Databricks recently awarded Booz Allen Hamilton as its 2019 Industry Partner of the Year.\nGartner, \u201c2019 CIO Agenda: Government Insights\u201d, Alia Mendonsa and Rick Howard, October 22, 2018\nAbout Databricks\nDatabricks\u2019 mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the original creators of Apache Spark, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership. Databricks has secured investments from Andreessen Horowitz, Coatue Management, Microsoft, New Enterprise Associates (NEA), Battery Ventures, Green Bay Ventures, and Geodesic, among others, and has a global customer base that includes Viacom, Shell and HP.\nApache, Apache Spark and Spark are trademarks of the Apache Software Foundation.\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/retail-industry-solutions","text":"The Data Lakehouse Solution for Retail and CPG - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDiscover Lakehouse for RetailThe unified data, analytics and AI platform retailers use to deliver more in every phase of the customer journeySign upContact usBetter performance, greater scale, lower TCOLakehouse for RetailUnify your data and AI workloads with sharing and governance built in, so internal and external teams can get access to the data they need when they need itImpact across the entire value chainCustomer EngagementBring relevance and hyper-personalization to every touchpointWith real-time, accurate 360\u00b0 views of their customers, retailers have everything they need to create relationships on each customer\u2019s terms: understanding sentiment across channels and personalizing recommendations. The result? Increased profitability and loyalty.Operational EfficiencyEmployee ProductivityProduct PerformanceRetail Solutions and PartnersNo-compromise data analytics and AI solutions purpose-built for your industryDatabricks Solution Accelerators are purpose-built guides \u2014 fully functional notebooks and best practices \u2014 that speed up retail results. Save time on discovery, design, development and testing in use cases like propensity scoring, customer lifetime value, order picking optimization and more.Fine-Grained ForecastingGenerate forecasts at scale in less time\nPerform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.Get startedCustomer SegmentationSegment your customers for better targeting\nCreate advanced customer segments using sales data, campaigns, promotion systems and more to drive better purchasing predictions based on behaviors.Get startedReal-Time Point-of-Sale AnalyticsCalculate real-time inventories across multiple store locations to improve retail margins\nRapidly ingest all point-of-sale data sources and types at scale to derive real-time insights that tackle pressing in-store information needs.Get startedExplore Retail acceleratorsWe\u2019ve partnered with leading consulting firms to deliver innovative, industry-specific solutions. Databricks Brickbuilder Solutions help you cut costs and increase value from your data. Backed by decades of industry expertise \u2014 and built for the Databricks Lakehouse Platform \u2014 Brickbuilder Solutions are tailored to your exact needs.Unified View of DemandMaximize accuracy, granularity and timeliness with a single-source-of-truth demand plan.Learn moreRevenue Growth ManagementRapidly perform analysis of invoice data, external market data, news and web scraping data to explore retail patterns.Learn moreTrellisSolve challenges around demand forecasting, replenishment, procurement, pricing and promotion services.Learn moreExplore Brickbuilder Solutions\u201cWe\u2019re now able to combine, on a customer level, information about purchases made online and offline, which was very challenging before. This omnichannel view allows us to create a more comprehensive recommendation engine online, which has seen tremendous engagement.\u201d\n\u2014 Wendell Kuling, Manager of Data Science and Analytics, Jumbo\n\u201cDatabricks enables us to outperform and deliver best-in-class customer experiences in every market. With its Lakehouse Platform, our stakeholders and developers can work more collaboratively and unlock critical trends and insights needed to serve our 180 million customers.\u201d\n\u2014 Sergiy Tkachuk, Head of Data Science, Reckitt\n\u201cMore business units are using the platform in a self-service manner that was not possible before. I can\u2019t say enough about the positive impact that Databricks has had on Columbia.\u201d\n\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear\nResourcesSelf-Guided TourAll the resources you need to explore the Lakehouse for RetailWebinarsDriving Real-Time Decisions in RetaileBookBig Book of Retail Use CasesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hari-rajaram\/#","text":"Hari Rajaram - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHari RajaramSr Director \/ Principal Data Architect at ProcoreBack to speakersHari is an accomplished technologist leader with more than two decades of experience in the data field. In addition, he is a tech enabler who has designed several technical architecture solutions for start-ups to enterprise.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ruifeng-zheng\/#","text":"Ruifeng Zheng - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRuifeng ZhengSenior Software Engineer at DatabricksBack to speakersRuifeng is currently a Databricks software engineer, Apache Spark committer, working on several different modules in Apache Spark including Spark Connect, Pandas API on Spark, PySpark, MLlib, Spark SQL, SparkR, etc. Prior to Databricks, he worked on applied machine learning for 10+ years. He holds a Master degree in Electronics Engineering from Peking University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tony-wang","text":"Tony Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTony WangPhD student at StanfordBack to speakersTony Wang is a PhD student at Stanford University working on an open-source query engine in Python: https:\/\/github.com\/marsupialtail\/quokka, for emerging data applications like vector embeddings and feature engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christian-acuna","text":"Christian Acu\u00f1a - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristian Acu\u00f1aSenior Data Engineer at GrammarlyBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/blog\/category\/company","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/fr\/company\/about-us","text":"\u00c0 propos de Databricks, fond\u00e9e par les cr\u00e9ateurs originaux d'Apache Spark\u2122Skip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks est l'inventeur du lakehouseIssue du milieu universitaire et de la communaut\u00e9 open source, Databricks a \u00e9t\u00e9 fond\u00e9e en 2013 par les cr\u00e9ateurs d'Apache Spark\u2122, Delta Lake et MLflow. En tant que premi\u00e8re et seule plateforme lakehouse mondiale dans le cloud, Databricks combine le meilleur des data warehouses et des data lakes pour vous offrir une plateforme ouverte et unifi\u00e9e pour les donn\u00e9es et l'IA.\n\u00a0Explorez la plateforme LakehouseAujourd'hui, plus de 7\u00a0000\u00a0organisations dans le monde, dont ABN AMRO, Cond\u00e9 Nast, Regeneron et Shell, s'appuient sur Databricks pour mener \u00e0 bien le data engineering \u00e0 grande \u00e9chelle, la data science collaborative, le machine learning \u00e0 cycle de vie complet et l'analytique business.\nBas\u00e9e \u00e0 San Francisco, avec des bureaux pr\u00e9sents dans le monde entier et des centaines de partenaires internationaux, dont Microsoft, Amazon, Tableau, Informatica, Capgemini et Booz Allen Hamilton, Databricks s'est donn\u00e9e pour mission de simplifier et d\u00e9mocratiser les donn\u00e9es et l'IA en aidant les \u00e9quipes data \u00e0 r\u00e9soudre les probl\u00e8mes les plus complexes au monde.D\u00e9couvrez les t\u00e9moignages clientsVoir les partenairesNos clientsVoir tous les clients\nNotre leadership\u00c9quipe de directionRencontrez nos dirigeantsFoundersRencontrez nos fondateursConseil d'administrationRencontrez notre conseil d'administrationNos investisseursProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
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{"source":"https:\/\/www.databricks.com\/kr\/company\/about-us","text":"Apache Spark\u2122\uc758 \ucc3d\ub9bd\uc790\uac00 \uc138\uc6b4 Databricks \uc18c\uac1cSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uae30\uc5c5\uc785\ub2c8\ub2e4Databricks\ub294 \ud559\uacc4\uc640 \uc624\ud508 \uc18c\uc2a4 \ucee4\ubba4\ub2c8\ud2f0\uc5d0 \uae30\ubc18\uc744 \ub454 \uae30\uc5c5\uc73c\ub85c, \uc9c0\ub09c 2013\ub144 Apache Spark\u2122, Delta Lake\uc640 MLflow\ub97c \uac1c\ubc1c\ud55c \uc8fc\uc5ed\ub4e4\uc774 \ubaa8\uc5ec \ucc3d\uc5c5\ud588\uc2b5\ub2c8\ub2e4. Databricks\ub294 \uc138\uacc4 \ucd5c\ucd08\uc774\uc790 \uc720\uc77c\ud55c \ud074\ub77c\uc6b0\ub4dc \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc73c\ub85c\uc11c, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc640 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uac00\uc7a5 \uc88b\uc740 \uc810\ub9cc \ubaa8\uc544 \ub370\uc774\ud130\uc640 AI\ub97c \uc704\ud55c \ud1b5\ud569\ud615 \uc624\ud508 \ud50c\ub7ab\ud3fc\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\n\u00a0\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc \ub458\ub7ec\ubcf4\uae30\uc694\uc998\uc740 \uc804 \uc138\uacc4 7,000\uc5ec \uae30\uc5c5\uc5d0\uc11c(ABN AMRO, Cond\u00e9 Nast, Regeneron\uacfc Shell \ub4f1\uc774 \ub300\ud45c\uc801) \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ud611\uc5c5\ud615 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4, \uc804\uccb4 \uc218\uba85 \uc8fc\uae30 \uba38\uc2e0 \ub7ec\ub2dd\uacfc \ube44\uc988\ub2c8\uc2a4 \ubd84\uc11d \ub4f1\uc744 Databricks\uc5d0 \ubbff\uace0 \ub9e1\uae30\uace0 \uc788\uc2b5\ub2c8\ub2e4.\nDatabricks\ub294 \uc0cc\ud504\ub780\uc2dc\uc2a4\ucf54\uc5d0 \ubcf8\uc0ac\ub97c \ub450\uace0 \uc138\uacc4 \uac01\uc9c0\uc5d0 \uc9c0\uc0ac\ub97c \uc6b4\uc601\ud558\uba70 Microsoft, Amazon, Tableau, Informatica, Cap Gemini \ubc0f Booz Allen Hamilton\uc744 \uc704\uc2dc\ud55c \uc218\ubc31 \uacf3\uc758 \uae00\ub85c\ubc8c \ud30c\ud2b8\ub108\uc640 \ud611\ub825\ud558\uace0 \uc788\uc73c\uba70, \ub370\uc774\ud130\uc640 AI\ub97c \uac04\uc18c\ud654, \ubbfc\uc8fc\ud654(democratize)\ud558\uace0 \ub370\uc774\ud130 \ud300\uc5d0\uc11c \uc804 \uc138\uacc4\uc758 \uc5b4\ub835\uae30\ub85c \uc190\uaf3d\ud788\ub294 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub3c4\ub85d \ub3d5\ub294 \uac83\uc774 \uc0ac\uba85\uc785\ub2c8\ub2e4.\uace0\uac1d \uc0ac\ub840 \ub458\ub7ec\ubcf4\uae30\ud30c\ud2b8\ub108 \ubcf4\uae30\uace0\uac1d \uc18c\uac1c\ubaa8\ub4e0 \uace0\uac1d \ubcf4\uae30\n\ub9ac\ub354\uc2ed \uc18c\uac1c\uacbd\uc601\uc9c4\uacbd\uc601\uc9c4 \uc18c\uac1c\ucc3d\uc5c5\uc790\ucc3d\uc5c5\uc790 \uc18c\uac1c\uc774\uc0ac\ud68c\uc774\uc0ac\uc9c4 \uc18c\uac1c\ud22c\uc790\uc790\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amir-skovronik","text":"Amir Skovronik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmir SkovronikDistinguished Software Engineer at AkamaiBack to speakersAmir is a distinguished engineer at Akamai with more than 10 years of experience in big data systems, and today functions as the technical leader of Asgard, the Akamai cloud base data warehouseLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-spark-sql","text":"What is Spark SQL?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark SQLAll>Spark SQLMany data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data. It also provides powerful integration with the rest of the Spark ecosystem (e.g., integrating SQL query processing with machine learning).What is Apache Spark SQL?Spark SQL brings native support for SQL to Spark and streamlines the process of querying data stored both in RDDs (Spark\u2019s distributed datasets) and in external sources. Spark SQL conveniently blurs the lines between RDDs and relational tables. Unifying these powerful abstractions makes it easy for developers to intermix SQL commands querying external data with complex analytics, all within in a single application. Concretely, Spark SQL will allow developers to:Import relational data from Parquet files and Hive tablesRun SQL queries over imported data and existing RDDsEasily write RDDs out to Hive tables or Parquet filesSpark SQL also includes a cost-based optimizer, columnar storage, and code generation to make queries fast. At the same time, it scales to thousands of nodes and multi-hour queries using the Spark engine, which provides full mid-query fault tolerance, without having to worry about using a different engine for historical data. \u00a0Additional ResourcesThe Data Scientist\u2019s Guide to Apache Spark\u2122 eBookDatabricks for SQL Developers DocumentationBucketing 2.0: Improve Spark SQL Performance by Removing ShuffleIntroducing Apache Spark 3.0: Now available in Databricks Runtime 7.0Lakehouse Architecture: From Vision to RealityBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Prova Databricks gratis | DatabricksProva Databricks gratisProva la piattaforma Databricks completa per 14 giorni su AWS, Microsoft Azure o Google Cloud.Semplifica l\u2019acquisizione dei dati e automatizza i processi ETLAcquisisci i dati da centinaia di sorgenti. Usa un semplice approccio dichiarativo per costruire le pipeline di dati.Collabora nella lingua che preferisciScrivi codice in Python, R, Scala e SQL con co-creazione, gestione automatica delle versioni, integrazioni Git e controllo degli accessi per ruoli (RBAC).Rapporto prezzo\/prestazioni 12 volte migliore rispetto ai data warehouse in cloudScopri perch\u00e9 oltre 7.000 clienti in tutto il mondo si affidano a Databricks per tutti i loro carichi di lavoro, dalla BI all\u2019AI.Crea il tuo account Databricks1\/2NomeCognomeE-mail aziendaleAziendaTitolo professionaleTelefono (Optional)Si prega di selezionareNazioneContinuaInformativa sulla privacy (aggiornata)Condizioni d'usoLe vostre scelte sulla privacyI vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thomas-la-piana\/#","text":"Thomas La Piana - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThomas La PianaSenior Software Engineer at EthycaBack to speakersThomas La Piana is a data engineer turned product engineer with experience building out modern data stacks across multiple startups. Thomas joined Ethyca in 2021 to help create data privacy tools that engineers might actually want to use and shift the consideration of data privacy left.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/model-risk-management","text":"What is Model Risk Management?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWModel Risk ManagementAll>Model Risk ManagementTry Databricks for freeGet StartedModel risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and mitigate model risks i.e. the possibility of model error or wrongful model usage. In financial services, model risk is the risk of loss resulting from using insufficiently accurate models to make decisions, frequently in the context of valuing financial securities, and becoming prevalent in activities such as assigning consumer credit scores, real-time probability prediction of fraudulent credit card transactions, and money-laundering.\u00a0 Financial institutions are highly reliant on credit, market, and behavioral models for model risk has become a core component of risk management and operational efficiency. These institutions primarily make money by taking risks -\u00a0 they maximize models to evaluate risks, understand customer behavior, assess capital adequacy for compliance, make investment decisions, and manage data analytics. Implementing an effective model risk management framework is a requisite for organizations that are heavily reliant on quantitative models for operations and decision-making.Additional ResourcesSmarter risk and compliance with data and AIModernizing risk managementHow to modernize and scale VaR calculations and risk management with Apache Spark, Delta Lake and MLflow BlogHow to build: A modern risk management solution in financial servicesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/learn\/executive-insights","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal\/training-services-schedule","text":"Training Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTraining Services ScheduleThis Schedule sets forth terms related to the Training Services and is incorporated as part of the Master Cloud Services Agreement (\u201cMCSA\u201c). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Other Schedules do not apply to the services ordered under this Schedule unless expressly referenced as being applicable. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Additional Definitions.\u201cCourse\u201d means an instance of either Instructor-Led Training Services or Self-Paced Training Services\u201cCourse Materials\u201d means the training materials and other information and content provided by Databricks in conducting the Training ServicesGenerally. Databricks may provide, as set forth in an Order, certain Training Services, delivered (i) by instructors (\u201cInstructor-led Training Services\u201d), either in person or online-only; or (ii) as a self-paced online training course (\u201cSelf-Paced Training Services\u201d). If we have agreed to provide you with Training Services, we will provide qualified training personnel and\/or suitable training materials. You will make available to Databricks any materials Databricks reasonably requires to perform the Training Services, but unless agreed between the parties in writing, you will not provide Databricks any Customer Content for use with the Training Services.Instructor-led Training Services. If we have agreed to provide you with Instructor-led Training Services, except as otherwise mutually agreed upon by the parties, you will, as reasonably applicable: (i) provide qualified personnel to assist in coordinating and implementing the Instructor-led Training Services; (ii) provide Databricks with access to your sites and facilities (or temporary off-site facilities) during normal business hours and as otherwise reasonably required by Databricks to perform the Instructor-led Training Services; (iii) provide Databricks with such working space and office support as Databricks may reasonably request; and (iv) perform such tasks as may be reasonably required to permit Databricks to perform the Instructor-led Training Services.Self-Paced Training Services. Databricks may make available certain Self-Paced Training Services. Unless otherwise set forth in an Order or when signing up for a Self-Paced Training Service, the Self-Paced Training Services will expire 12 months from the earlier of purchase or activation and are licensed on a per-user basis.Course Materials.Ownership of Course Materials. Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Course Materials. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Course Materials as delivered to you. You agree that the Course Materials are provided on a non-exclusive basis and not sold. You further acknowledge and agree that portions of the Course Materials, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Course Materials License. Databricks grants a limited, non-sublicensable, non-transferable, license to the Course Materials, solely for the internal educational use by individuals who attend a training course (\u201cStudents\u201d). Unless indicated by a Databricks instructor, Students are permitted to retain any Course Materials provided during the Course for continued learning following the conclusion of the Course. For the avoidance of doubt, Course Materials may not be used other than by the Students who received them, and may not be shared with individuals who did not attend a Course.Expenses. Customer will reimburse Databricks for reasonable travel expenses. Customer is responsible for all training venue expenses.Compliance with your Onsite Access Policies. If, in the course of providing Databricks Services, Databricks personnel go onsite at your premises, Databricks will require such personnel to comply with your commercially reasonable onsite access policies that have been provided by you to such personnel reasonably in advance. For the avoidance of doubt, no such policies will be deemed to modify the terms of the Agreement.Use of Workspace during Performance of Training Services. You may be required to use a Workspace in order to receive the benefit of the Training Services. Your use of the Workspace constitutes acceptance of the Platform Services terms of the MCSA unless the Workspace is provided as part of a Databricks Powered Service. If the Workspace is created for you by Databricks, it may be terminated following the conclusion of the Training Services without prior notice or any liability to you unless you enter into an Order with Databricks for its continued use.\u00a0Last Updated August 12, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).\u00a0ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pakshal-kumar-h-dhelaria","text":"Pakshal Kumar H Dhelaria - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPakshal Kumar H DhelariaSenior Software Engineer 1 at CitrixBack to speakersA strong leader with an overall experience of 6+ years solving critical problems in the industry and passionate about innovative architecture\/solutions. Expertise in Kafka, Apache Spark, Streaming, Spring, Spring Boot Framework Interested in Machine learning and NLP. Worked on RDBMS (MySQL, Postgres,), Time-Series DB(Druid). Extensively using Functional\/Reactive Programming, Java, NodeJS.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/professional-services","text":"Databricks Professional Services | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks Professional ServicesContattaci per maggiori informazioniI progetti arrivano velocemente al successo con competenze avanzate di data engineering, data science e gestione di progetto. I servizi professionali di Databricks possono essere utili in qualsiasi fase del ciclo di gestione dei dati e AI:VantaggiAccelerare il ciclo di gestione dei dati e AI\nLe nostre offerte e servizi qualificati supportano il percorso di gestione dei dati e AI per ottenere un'accelerazione ottimale e mirata dall'attivazione iniziale dello spazio di lavoro alla costruzione di pratiche di Data Ops e Center of Excellence (COE) su scala aziendale.\nRidurre i rischi di progetto\nPer migrazioni da carichi di lavoro esistenti a Databricks, costruzione di nuovi prodotti di dati o progetti di pipeline per dati e AI e di Machine Learning, ci proponiamo come partner e consulenti di fiducia per ridurre al minimo il rischio e massimizzare il valore in ogni fase del percorso.\nOperazionalizzare su larga scala\nCostruire un POC di una pipeline di dati o sviluppare un modello a nodo singolo \u00e8 relativamente semplice. La sfida consiste nell'adottare ed estendere con successo pratiche di gestione dei dati e AI su tutta l'organizzazione. Noi possiamo aiutare a realizzare questo obiettivo con le nostre offerte e competenze.\nOffertePortare rapidamente al successo progetti con competenze avanzate di data engineering, data science e gestione di progettoJumpstartAccelera le tempistiche di progetto familiarizzando con la piattaforma Databricks e le funzionalit\u00e0 chiave che seguono le best practice.Hadoop MigrationIl nostro approccio prescrittivo massimizza il valore degli investimenti esistenti nei dati e nella pipeline, oltre a consentire una migrazione senza problemi.Lakehouse Build-outAccelera l'implementazione di una piattaforma semplificata per analisi dei dati, data science e ML, gettando le basi della tua visione del lakehouse.Machine LearningPotenzia le iniziative di ML aziendali e l'adozione con la nostra metodologia prescrittiva.Shared Services AcceleratorAccelera il modello operativo su scala aziendale per sostenere l'eccellenza di dati e AI con la nostra metodologia prescrittiva.Servizi personalizzatiContattaci per richiedere uno Statement of Work su misura per le tue esigenze specifiche.I nostri esperti di servizi professionali hanno dimostrato il loro valore nella realizzazione di progetti per l'intero ciclo di vita, per soddisfare requisiti complessi, molto specifici e mirati.Architetti per soluzioni residenti | data scientistRisorse tecniche di grande esperienza con solide capacit\u00e0 di leadership e di consulenza. Per garantire il successo dei nostri clienti, collaboriamo con un ampio ecosistema di partner e realizziamo insieme a loro le soluzioni richieste.Esperti di Databricks e Spark10 anni di esperienza\nSolido background nei Big Data\nCompetenze di implementazione pratiche\nPianificazione ed esecuzione di progettoAssistenza per progettazione e architettura\nSupporto per allineare il progetto alle funzionalit\u00e0 della piattaforma\nIndicazioni per tempistiche di progetti e necessit\u00e0 di risorse\nPianificazione dell'implementazione e della produzioneArchitettare le soluzioni nell'ottica della scalabilit\u00e0\nAssistenza nello sviluppo di prototipi\nRisolvi i requisiti di integrazione DevOps\nAssistenza nell'implementazione di un COESviluppare standard e framework comuni\nEssere disponibile come risorsa per diversi team\nAgevolare le interazioni con altri team di Databricks\nRisorsePanoramica del programma Success CreditModulo di richiesta di riscattoPerch\u00e9 Databricks AcademyLe persone sono il fulcro del successo dei nostri clienti e, grazie alla formazione e alle certificazioni della Databricks Academy, tutti possono imparare l'arte dell'analisi dei dati dal team che ha avviato il progetto di ricerca Spark all'Universit\u00e0 di Berkeley. Migliora le tue competenze pi\u00f9 velocemente con Databricks Academy.Migliora le tue competenze subitoPronto per cominciare?ContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/explore\/migration-modernization\/migration-guide-hadoop","text":"\n\n\n\n\n\n\n\nMigration Guide: Hadoop to Databricks\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=tokyo%2C%20japan","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/trust\/security-features","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueSecurity FeaturesWe provide comprehensive security to protect your data and workloads, such as encryption, network controls, data governance and auditing.Customer-Managed KeysGain greater control over the encryption of your data with customer-managed keys on Databricks.Learn morePrivate LinkConnect privately and securely to Databricks from your network with Private Link.Learn moreEnhanced Security and ComplianceTake advantage of the highest standard for Databricks security using Enhanced Security and Compliance.Learn moreExpand all | Collapse all\u00a0column1column2Network accessCloudUser and group administrationCloudAccess managementCloudData securityCloudData governanceCloudWorkload securityCloudAuditing and loggingCloudSecurity validations (Compliance)Cloud* Azure Databricks is integrated with Azure Active Directory, and Databricks on GCP is integrated with Google Identity. You can\u2019t configure these in Databricks itself, but you can configure Azure Active Directory or Google Identity as needed.Security Best PracticesDatabricks has worked with thousands of customers to securely deploy the Databricks platform, with the security features that meet their architecture requirements. This document provides a checklist of security practices, considerations and patterns that you can apply to your deployment, learned from our enterprise engagements.\nView document for\u00a0AWS,\u00a0Azure\u00a0and\u00a0GCPSecurity Analysis ToolSecurity Workspace Analysis Tool (SAT) monitors your workspace hardening by reviewing the deployments against our security best practices. It programmatically verifies workspaces using standard API calls and reports deviations by severity, with links that explain how to improve your security.\nView our\u00a0blog\u00a0for more detail and\u00a0Github\u00a0to get started on AWS, Azure and GCP.Databricks Security DocumentationDatabricks includes documentation on how to operate our security features and best practices to help our customers deploy quickly and securely. The documentation is targeted primarily at teams that deploy or use Databricks.\nAccess documentation for\u00a0AWS,\u00a0GCP\u00a0or\u00a0AzureDatabricks Security and Trust Overview WhitepaperThe Security Overview Whitepaper is designed to provide a summary of all aspects of Databricks for security teams to quickly review.\nView documentShared Responsibility ModelThe Databricks shared responsibility model outlines the security and compliance obligations of both Databricks and the customer with respect to the data and services on the Databricks platform.\nView documentProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/technology","text":"Databricks \uae30\uc220 \ud30c\ud2b8\ub108 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 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\uc5f0\uacb0\ud558\uace0, \ub370\uc774\ud130 \uc218\uc9d1, \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4, \uac70\ubc84\ub10c\uc2a4 \uae30\ub2a5\uc744 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uacfc \ud1b5\ud569\ud558\uc138\uc694.\u201cDatabricks\uc640 Fivetran\uc744 \uc0ac\uc6a9\ud55c \ub355\ubd84\uc5d0 \uc55e\uc73c\ub85c \ub9c8\ucf00\ud305 \uc778\uc0ac\uc774\ud2b8\ub97c \uc0c1\ub2f9\ud788 \uac1c\uc120\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uae30\uc220\uc801 \uad00\uc810\uc5d0\uc11c \uc774 \ub450 \uac00\uc9c0 \ub3c4\uad6c\ub294 \uc11c\ub85c \uc870\ud654\ub86d\uac8c \uc791\ub3d9\ud558\uba70, \ud1b5\ud569\uc774 \ub9e4\uc6b0 \uc790\uc5f0\uc2a4\ub7fd\uac8c \ub290\uaef4\uc9d1\ub2c8\ub2e4.\u201d\u2014 Jan-Niklas M\u00fchlenbrock, Paul Hewitt \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4 \ubc0f ERP \ud300 \ub9ac\ub354Databricks \uae30\uc220 \ud30c\ud2b8\ub108\ub294 \uc790\uc0ac \uc194\ub8e8\uc158\uc744 Databricks\uc640 \ud1b5\ud569\ud558\uc5ec ETL, \ub370\uc774\ud130 \uc218\uc9d1, \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4, \uba38\uc2e0 \ub7ec\ub2dd\uacfc \uac70\ubc84\ub10c\uc2a4 \ub4f1\uc5d0 \ubcf4\uc644\uc801\uc778 \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\uace0\uac1d\uc740 \uc774\ub7ec\ud55c \ud1b5\ud569\uc744 \ud1b5\ud574 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \uc548\uc815\uc131\uacfc \ud655\uc7a5\uc131\uc744 \ud65c\uc6a9\ud558\uc5ec \uadc0\uc911\ud55c \ub370\uc774\ud130 \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\ub294 \ub3d9\uc2dc\uc5d0 \ud601\uc2e0 \uc18d\ub3c4\ub97c \ub192\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4.Partner Connect\ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \ub3c4\uad6c\ub97c \ub2e8\uc77c\ud55c \uc624\ud508 \ud50c\ub7ab\ud3fc\uc5d0 \ud1b5\ud569\ud558\uc138\uc694. Databricks\ub294 Partner Connect\ub97c \ud1b5\ud574 \uac80\uc99d\ub41c \ud1b5\ud569 \ud658\uacbd\uc5d0\uc11c \uae30\uc874\uc758 \ub3c4\uad6c\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \ube60\ub974\uace0 \uc27d\uac8c \uc5f0\uacb0\ud558\ub294 \uc218\ub2e8\uc744 \uc81c\uacf5\ud558\uba70, \uc0c8\ub85c\uc6b4 \uc194\ub8e8\uc158\uc744 \ubc1c\uacac\ud558\uace0 \uccb4\ud5d8\ud574\ubcfc \uc218 \uc788\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\ud30c\ud2b8\ub108 \ub418\uae30\uc790\uc138\ud788Loading...\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\u0000\u0000\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/discover\/notebook-gallery","text":"Databricks Solution Accelerators - Deliver Data & AI Value Faster - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIndustry SolutionsDeliver the data and AI-driven outcomes that matter most \u2014 fasterStart your free trialDatabricks Solution AcceleratorsSave hours of discovery, design, development and testing with Databricks Solution Accelerators. Our purpose-built guides \u2014 fully functional notebooks and best practices \u2014 speed up results across your most common and high-impact use cases. Go from idea to proof of concept (PoC) in as little as two weeks.\n\u00a0\nStart using Solution Accelerators with your free Databricks trial or your existing account.\n\u00a0\nStart your free trial todayBrowse AcceleratorssearchHide filtersIndustrySortDatabricksToxicity Detection in GamingfeaturedDatabricksOn-Shelf AvailabilityfeaturedDatabricksFine-Grained Demand Forecastingfeatured\ud83d\udd25DatabricksAutomated PHI RemovalfeaturednewDatabricksAbstracting Real-World Data for OncologyDatabricksAnti-Money LaunderingDatabricksCohort Building with Knowledge GraphsDatabricksComputer Vision FoundationsDatabricksCustomer Entity ResolutionDatabricksCustomer Lifetime Value\ud83d\udd25DatabricksCustomer SegmentationSplunkCyber Analytics (Splunk Connector)DatabricksDetecting Adverse Drug EventsnewDatabricksDigital Pathology Image AnalysisDatabricksDigital TwinsDatabricksESG Performance Analytics\ud83d\udd25DatabricksFHIR Interoperability with dbigniteDatabricksFuzzy Item MatchingDatabricksGenome-Wide Association StudiesDatabricksGeospatial Analytics to Identify FraudDatabricksHL7v2 Interoperability With SmolderDatabricksMedia Mix Modeling (MMM)DatabricksMedicare Risk AdjustmentDatabricksMerchant ClassificationDatabricksModern Investment PlatformDatabricksMulti-Touch AttributionDatabricksOptimized Order PickingDatabricksOverall Equipment EffectivenessDatabricksPredictive Maintenance (IoT)DatabricksPrice TransparencynewDatabricksProduct Quality InspectionDatabricksPropensity ScoringnewDatabricksR&D Optimization with Knowledge GraphsnewDatabricksReal-Time Bidding OptimizationDatabricksReal-Time Financial Fraud PreventionDatabricksReal-Time Point-of-Sale AnalyticsnewDatabricksReal-world EvidenceDatabricksRecommendation EngineDatabricksRegulatory ReportingDatabricksReputation RiskDatabricksRetention ManagementDatabricksRisk ManagementDatabricksSafety StockDatabricksSales Forecasting & Ad Attribution\ud83d\udd25DatabricksScalable Route GenerationDatabricksSocial Determinants of HealthDatabricksSubscriber Churn PredictionDatabricksSupply Chain Distribution OptimizationDatabricksSurvival Analysis & Lifetime ValueDatabricksThreat Detection with DNSDatabricksVideo Quality of ExperienceFAQHow much do Solution Accelerators cost?Solution Accelerators are available to any Databricks customer free of charge.Do I need to be a Databricks customer to use a Solution Accelerator?You can implement Solution Accelerators with a free Databricks trial or with your existing Databricks account.What can I expect from a Solution Accelerator?Solution Accelerators are designed to help you save hours of discovery, design, development and testing. Our goal is to jump-start your data and AI use cases by providing the right resources (notebooks, proven patterns and best practices). You can expect to go from idea to proof of concept (PoC) in as little as two weeks.See how actual customers use DatabricksExplore Customer StoriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dan-houston","text":"Dan Houston - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDan HoustonManager, Data Science and Exploration Advanced Analytics at USPSBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-announces-emea-expansion-databricks-infrastructure-aws","text":"Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) Region - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionMarch 30, 2023Share this postData and AI leader announces new offices, Databricks infrastructure in AWS France (Paris) Region, and initiatives to accelerate lakehouse adoption in 2023\nParis, France - March 30, 2023 - Databricks, the lakehouse company, today announced the opening of Databricks offices in Tel Aviv and Zurich, in addition to expanding its footprint in\u00a0 London and opening a new office in Munich. The company also announced the coming availability of Databricks infrastructure in the AWS France (Paris) Region in the first half of 2023. The state-of-the-art AWS-based Databricks infrastructure in France will support the growing customer base and demand for the Databricks Lakehouse. These investments will further Databricks\u2019 commitment to EMEA, its open, multi-cloud strategy, and accelerate lakehouse adoption.\u00a0\nDatabricks Opens Offices in Munich, Tel Aviv and Zurich; Expands in London\nDatabricks today announced continued expansion in EMEA with the opening of new offices: Tel Aviv and Zurich, as well as expanding its existing office space in London and opening a new office for Munich. Databricks\u2019 office in Stockholm will open in the first half of 2023. The Databricks EMEA team grew 75% in the last fiscal year and the business expects to surpass 1,000 employees in the region in the coming months.\n\u201cInvesting in our team and offices, and launching Databricks infrastructure in France are initiatives that play critical roles in helping even more AWS customers realize the massive potential of the Databricks Lakehouse,\u201d said Samuel Bonamigo, SVP & GM, EMEA, Databricks. \u201cWith these strategic investments, we will not only attract diverse, world-class talent, but we will also continue to \u2018be where our customers are\u2019 to support them with rapidly evolving business challenges, all in accordance with local regulations.\u201d\nPlan to Launch Infrastructure in the AWS France (Paris) Region First Half of 2023\nThe launch of Databricks infrastructure in the AWS France (Paris) Region will support the most innovative, forward-looking French organizations, as they leverage AWS Databricks to transform their businesses with data-driven applications and use cases, whilst ensuring minimal latency.\u00a0\n\u201cWe are thrilled to deepen our partnership with AWS in France and ensure our customers have the best possible experience whilst adopting the Databricks Lakehouse Platform,\u201d said Stan Hutten Czapski, Senior Cloud Director, EMEA, Databricks. \u201cLaunching Databricks infrastructure in France is a crucial step in our AWS partnership for 2023 and beyond.\u201d\nInnovative EMEA Customers Continue to Adopt the Lakehouse Platform; New Digital Native and Startup Practice\nDatabricks\u2019 EMEA launches come on the heels of continued success of the organization. Databricks works with over 9,000 customers to unify their data, analytics and AI. EMEA helps major French and European-headquartered brands such as Rolls-Royce, Shell, Marks & Spencer, SNCF and TotalEnergies solve some of the world\u2019s toughest problems with data and AI.\u00a0\n\u201cWe are seeing massive acceleration and adoption of the Databricks Lakehouse Platform in France because we\u2019re helping French companies handle all their data, analytics and AI use cases in one simple platform \u2014 the Lakehouse, which is a category we pioneered,\u201d said Guillaume Brandenburg, RVP SEMEA, Databricks. \u201cA lakehouse architecture is the ideal data architecture for data-driven organizations like SNCF and TotalEnergies. It combines the best of data warehouses and data lakes to provide a single solution for all major data workloads and supports a range of data and AI use cases for our customers in France and beyond.\u201d\nDatabricks also announced a new dedicated EMEA team to drive innovation for digital natives and start-up communities. Called the Velocity practice, this team of specialists will drive growth in fast paced accounts and with digital natives such as Gousto.\n\u201cWe have the opportunity to drive significant value for digital native customers who are born in the cloud, move quickly, and require massive scale for their data and AI use cases. I\u2019m excited to see what our Velocity team can achieve in the coming year, and what more we can do to drive Databricks Lakehouse adoption with customers of all sizes across multiple countries, all with a growing and highly-skilled team,\u201d concluded Bonamigo.\n\u00a0\nAbout Databricks\nDatabricks is the lakehouse company. More than 9,000 organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, and over 50% of the Fortune 500 \u2014 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\nContact: [email\u00a0protected]\u00a0\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shawn-benjamin\/#","text":"Shawn Benjamin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShawn BenjaminData and Business Intelligence Chief at U.S. Department of Homeland Security - USCISBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\ubc1c\uacac \ubc0f \uacf5\uc720\ubd84\uc11d\uc744 \ub3d9\uc801 \ub300\uc2dc\ubcf4\ub4dc\ub85c \uac04\ub2e8\ud558\uac8c \ubc14\uafb8\uc5b4 \uacb0\uacfc\ub97c \uac04\ud3b8\ud558\uac8c \uacf5\uc720\ud558\uace0 \ub0b4\ubcf4\ub0bc \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub300\uc2dc\ubcf4\ub4dc\ub294 \ud56d\uc0c1 \ucd5c\uc2e0 \uc0c1\ud0dc\ub85c \uc720\uc9c0\ub418\uba70 \ub300\ud654\ud615 \ucffc\ub9ac\ub3c4 \uc2e4\ud589\ud569\ub2c8\ub2e4. \uc5ed\ud560 \uae30\ubc18 \uc561\uc138\uc2a4 \uad00\ub9ac\ub97c \ud1b5\ud574 \uc140, \uc2dc\uac01\ud654\ub098 \ub178\ud2b8\ubd81\uc744 \uacf5\uc720\ud560 \uc218\ub3c4 \uc788\uace0 HTML\uc640 IPython Notebook\uc744 \ube44\ub86f\ud55c \uc5ec\ub7ec \uac00\uc9c0 \ud615\uc2dd\uc73c\ub85c \ub0b4\ubcf4\ub0bc \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130 \uc0ac\uc77c\ub85c, \ub290\ub9b0 \uc131\ub2a5, Hadoop\uc774\ub098 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub192\uc740 \ube44\uc6a9\uc5d0 \uc9c0\uce58\uc168\ub098\uc694? \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc138\uc694.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub9ac\uc18c\uc2a4\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\u0000\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2dd \uc8fc\uc81c\uc5d0 \ub300\ud55c ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ucc3e\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30\ubcf4\uace0\uc11c \ubc0f eBook\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 Big Book\ub300\uaddc\ubaa8 \ud611\uc5c5 \ub370\uc774\ud130 \uacfc\ud559\uc758 \uae30\uc220\ucd5c\uc2e0 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \ud50c\ub7ab\ud3fcMLflow - \uc624\ud508 \uc18c\uc2a4 \uba38\uc2e0 \ub7ec\ub2dd \ud50c\ub7ab\ud3fc\uc0c8\ub85c\uc6b4 Delta Sharing \uc194\ub8e8\uc158 \uc54c\uc544\ubcf4\uae30Databricks, 2021 Gartner\u00ae Magic Quadrant\u2122 DBMS\uc640 DSML \ubd80\ubb38\ubaa8\ub450 \ub9ac\ub354\ub85c \uc120\uc815\ub9c8\uc774\uadf8\ub808\uc774\uc158 \uac00\uc774\ub4dc: \ud558\ub461\uc5d0\uc11c Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ube14\ub85c\uadf8\ud558\ub461\uc5d0\uc11c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uae30 \uc704\ud55c 5\uac00\uc9c0 \ub2e8\uacc4\uac00\uc0c1 \uc774\ubca4\ud2b8\ud558\ub461 \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ub2e8\uacc4\ubcc4 \uac00\uc774\ub4dc\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/esg-analytics-ai","text":"Taking ESG From Buzzword to Reality With Data Analytics and AI | DatabrickseBookTaking ESG From Buzzword to Reality With Data Analytics and AIUnlike with financial statements, there are no generally accepted principles for how ESG metrics are disclosed by companies. As a result, it has become nearly impossible today for investors, partners and the public to independently measure and verify how companies are progressing toward their sustainability goals at scale.This eBook walks you through how data analytics and AI can help organizations process vast amounts of ESG data \u2014 often unstructured data \u2014 to make smarter investment decisions.Download the eBook to:Understand how to apply advanced analytics to ESG dataLearn about preparing ESG data for insights at scaleSee how Databricks enables a data-driven approach to ESG for sustainabilityGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-are-spark-applications","text":"What are Spark Applications?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark ApplicationsAll>Spark ApplicationsTry Databricks for freeGet StartedSpark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; responding to a user\u2019s program or input; and analyzing, distributing, and scheduling work across the executors (defined momentarily). The driver process is absolutely essential - it\u2019s the heart of a Spark Application and maintains all relevant information during the lifetime of the application. The executors are responsible for actually executing the work that the driver assigns them. This means, each executor is responsible for only two things: executing code assigned to it by the driver and reporting the state of the computation, on that executor, back to the driver node.  The cluster manager controls physical machines and allocates resources to Spark Applications. This can be one of several core cluster managers: Spark\u2019s standalone cluster manager, YARN, or Mesos. This means that there can be multiple Spark Applications running on a cluster at the same time. We will talk more in depth about cluster managers in Part IV: Production Applications of this book. In the previous illustration we see on the left, our driver and on the right the four executors on the right. In this diagram, we removed the concept of cluster nodes. The user can specify how many executors should fall on each node through configurations. [glossary-cta]Additional Resources8 Steps for a Developer to Learn Apache Spark with Delta Lake eBookThe Data Engineer's Guide to Apache Spark and Delta Lake eBookComparing Apache Spark and DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-inkpen","text":"Chris Inkpen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris InkpenSolutions architect at HoneywellBack to speakersChris Inkpen has written software now since 1987. He has a PhD in Knowledge modeling from Brighton University in the UK. He is currently working within Honeywell Building Technologies as a technical evangelist and data engineer specialist helping the scrum teams design and develop solutions using the most appropriate technological solutions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/blog\/category\/company","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacek-laskowski\/#","text":"Jacek Laskowski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacek LaskowskiIT Freelancer at japila.plBack to speakersI\u2019m Jacek Laskowski, an IT freelancer specializing in Apache Spark, Delta Lake, Databricks and Apache Kafka (incl. Kafka Streams and ksqlDB) (with brief forays into a wider data engineering space, e.g. Trino, Dask and dbt, mostly during Warsaw Data Engineering meetups). He is best known by The Internals Of online books at https:\/\/books.japila.pl.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/glossary","text":"Glossaries Archive | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGlossaryA-ZsearchACID Transactions What is a transaction?\nIn the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a cons{...}AdaGrad Gradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.\nTypes of Gradient Descent\nThere are three primary types of gradient descent {...}Alternative Data What is Alternative Data?\nAlternative data is information gathered by using alternative sources of data that others are not using; &nbsp;non-traditional information sources. Analysis of alternative data can provide insights beyond that which an in{...}Anomaly Detection Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like{...}Apache Hive What is Apache Hive?\nApache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.\nWith exten{...}Apache Kudu What is Apache Kudu?\nApache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows to{...}Apache Kylin What is Apache Kylin?\nApache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/S{...}Apache Spark What Is Apache Spark?\nApache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.&nbsp;Apache Spark started in 2009 as a research project at {...}Apache Spark as a Service What is Apache Spark as a Service?\nApache Spark is an open source cluster computing framework for fast real-time large-scale data processing.&nbsp;Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently ra{...}Artificial Neural Network What is an Artificial Neural Network?\nAn artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.\nHow Do Artificial Neural Networks Work?\nArtificial Neural Networks can be best viewed{...}Automation Bias What is Automation Bias?\nAutomation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, {...}Bayesian Neural Network What Are Bayesian Neural Networks?\nBayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology {...}Big Data Analytics The Difference Between Data and Big Data Analytics\nPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relat{...}Bioinformatics Bioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.\nBioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data.{...}Catalyst Optimizer At the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional program{...}Complex Event Processing What is Complex Event Processing [CEP]?\nComplex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being s{...}Continuous Applications Continuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate{...}Convolutional Layer In deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language {...}Data Analysis Platform What is a Data Analysis Platform?\nA data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visua{...}Data Governance What is Data Governance?\nData governance is the oversight to ensure data brings value and supports the business strategy. Data governance is more than just a tool or a process. It aligns data-related requirements to the business strategy using a f{...}Data Lakehouse What is a Data Lakehouse?\nA data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business int{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Data Sharing What is data sharing?\nData sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or external{...}Data Vault What is a data vault?\nA data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.\nHubs represent core business concepts, {...}Data Warehouse What is a data warehouse?\nA data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business i{...}Databricks Runtime Databricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of {...}DataFrames What is a DataFrame?\nA DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are {...}Datasets Datasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recal{...}Deep Learning What is Deep Learning?\nDeep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referre{...}Demand Forecasting What is demand forecasting?\nDemand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.\nRet{...}Dense Tensor Dense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software prod{...}Digital Twin What is a Digital Twin?\nThe classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers {...}DNA Sequence What is a DNA Sequence?\nThe DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). &nbsp;Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine {...}Extract Transform Load (ETL) What is ETL?\nAs the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to pr{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Genomics Genomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DN{...}Hadoop Cluster What Is a Hadoop Cluster?\nApache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by{...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hadoop Ecosystem What is the Hadoop Ecosystem?\nApache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of{...}Hash Buckets In computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from whic{...}Hive Date Function What is a Hive Date Function?\nHive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditi{...}Hosted Spark What is Hosted Spark?\nApache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Py{...}Jupyter Notebook What is a Jupyter Notebook?\nA Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.\nWhat are Jupyter Notebooks used fo{...}Keras Model What is a Keras Model?\nKeras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.&nbsp;Keras has become one of {...}Lakehouse for Retail What is Lakehouse for Retail?\nLakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.\nLakehouse fo{...}Lambda Architecture What is Lambda Architecture?\nLambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solv{...}Machine Learning Library (MLlib) Apache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and mod{...}Machine Learning Models What is a machine learning Model?\nA machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recogni{...}Managed Spark What is Managed Spark?\nA managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, m{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}Materialized views Delta Pipelines \/ Materialized Views in Databricks Delta\nIntro\nDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve dat{...}Medallion Architecture What is a medallion architecture?\nA medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through ea{...}ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and c{...}MLOps What is MLOps?\nMLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. M{...}Model Risk Management Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and{...}Neural Network What is a Neural Network?\nA neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an outpu{...}Open Banking What is Open Banking?\nOpen banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of custo{...}Orchestration What is Orchestration?\nOrchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of {...}Overall Equipment Effectiveness What is Overall Equipment Effectiveness?\nOverall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to{...}pandas DataFrame \nWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as ef{...}Parquet What is Parquet?\nApache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in {...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}Predictive Analytics What is Predictive Analytics?\nPredictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.\nHow Does Predictive Analytics Work?\nPredictive analytics {...}Predictive Maintenance What is predictive maintenance?\nPredictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rath{...}PyCharm PyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to crea{...}PySpark What is PySpark?\nApache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface wi{...}Real-Time Retail What is real-time data for Retail?\nReal-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. {...}Resilient Distributed Dataset (RDD) \nRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API {...}Snowflake Schema What is a snowflake schema?\nA snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and re{...}Spark API If you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDs\nWhat are Resilient Distributed Datasets?\nRDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are {...}Spark Applications Spark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; res{...}Spark Elasticsearch What is Spark Elasticsearch?\nSpark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and r{...}Spark SQL Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can al{...}Spark Streaming Apache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Stre{...}Spark Tuning What is Spark Performance Tuning?\nSpark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also preven{...}Sparklyr What is Sparklyr?\nSparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little l{...}SparkR SparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follow{...}Sparse Tensor Python offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library. Sptensor is a class that represents the sparse tensor. A spa{...}Star Schema What is a star schema?\nA star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The st{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a stre{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API What is the Tensorflow Estimator API?\nEstimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow {...}Transformations What Are Transformations?\nIn Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d {...}Tungsten What is the Tungsten Project?\nTungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance{...}Unified AI Framework Unified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute r{...}Unified Data Analytics Unified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it e{...}Unified Data Analytics Platform Databricks' Unified Data Analytics Platform&nbsp;helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at mass{...}Unified Data Warehouse What is a Unified Data Warehouse?\nA unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in {...}What Is Hadoop? Apache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them{...}ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Databricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb | DatabricksDatabricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebDatabricks \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u5168\u6a5f\u80fd\u3092 14 \u65e5\u9593\u7121\u6599\u3067\u304a\u8a66\u3057\u3044\u305f\u3060\u3051\u307e\u3059\u3002AWS\u3001Microsoft Azure\u3001Google Cloud \u306e\u3044\u305a\u308c\u304b\u3092\u304a\u9078\u3073\u304f\u3060\u3055\u3044\u3002\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3001ETL \u3092\u81ea\u52d5\u5316\u6570\u767e\u306b\u304a\u3088\u3076\u30bd\u30fc\u30b9\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3068\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308b\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u4efb\u610f\u306e\u8a00\u8a9e\u3067\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032Python\u3001R\u3001Scala\u3001SQL \u306b\u3088\u308b\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u304c\u53ef\u80fd\u3067\u3059\u3002\u5171\u540c\u7de8\u96c6\u3001\u81ea\u52d5\u30d0\u30fc\u30b8\u30e7\u30f3\u7ba1\u7406\u3001Git \u7d71\u5408\u3001RBAC \u3082\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e 12 \u500d\u306e\u4fa1\u683c\u6027\u80fdDatabricks \u306f\u3001\u4e16\u754c 7000 \u793e\u4ee5\u4e0a\u306e\u304a\u5ba2\u69d8\u306b\u63a1\u7528\u3055\u308c\u3001BI \u3084 AI \u306e\u3042\u3089\u3086\u308b\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002Databricks \u30a2\u30ab\u30a6\u30f3\u30c8\u3092\u4f5c\u6210\u3059\u308b1\/2\u304a\u540d\u524d\uff08\u59d3)\u304a\u540d\u524d\uff08\u540d)\u696d\u52d9\u7528\u30e1\u30fc\u30eb\u30a2\u30c9\u30ec\u30b9\u4f01\u696d\uff0f\u56e3\u4f53\u540d\u5f79\u8077\u540d\u96fb\u8a71\u756a\u53f7\uff08\u4efb\u610f)\u9078\u629e\u3057\u3066\u304f\u3060\u3055\u3044\u56fd\u540d\u9001\u4fe1\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5 (\u66f4\u65b0)\u5229\u7528\u898f\u7d04\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maciej-szpakowski\/#","text":"Maciej Szpakowski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaciej SzpakowskiCo-founder at ProphecyBack to speakersMaciej is the co-founder @ Prophecy, where he's building the first low-code data engineering platform. Having previously built a startup making medical research accessible through ML\/Spark, he dreams of a world where data is not feared but leveraged.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jordan-donmoyer","text":"Jordan Donmoyer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJordan DonmoyerManager, Customer Data Solutions at The Hershey CompanyBack to speakersJordan leads the Customer Data Solutions team at The Hershey Company, and in his role, he partners with key strategic\nCategory Management teams and retailer commercial data partners to develop and manage the multi-year strategic plans to enable and unlock organizational topline growth for Hershey. Jordan also partners with internal IS teams to drive the development of strategic policies impacting data sharing, maintaining data literacy, and cataloging key strategic retailer data. Jordan brings over 6 years of supply chain, logistics, reporting & analytics, and leadership\/management experience to his role within the Commercial Data team. Jordan currently resides with his family in Fayetteville, Arkansas, but was born and raised in Lititz, Pennsylvania, just forty minutes outside of Hershey, PA. He played baseball at Pennsylvania State University where he graduated with a Bachelor\u2019s in Supply Chain and Information Systems and a minor in Information Systems Management.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/privacynotice#dbhowweuseyourinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/company\/leadership-team","text":"Equipe de lideran\u00e7a | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLideran\u00e7aCom uma vis\u00e3o de longo prazo, nossa equipe de lideran\u00e7a conta com d\u00e9cadas de experi\u00eancia para tra\u00e7ar um novo curso para dados e IAConhe\u00e7a nossa equipeEquipe executivaEquipe fundadoraConselho de Administra\u00e7\u00e3oAli GhodsiCofundador e diretor executivoAndy KofoidPresidente de Global Field OperationsDavid ConteDiretor financeiroAmy ReichanadterDiretora de pessoasTr\u00e2m PhiVice-presidente s\u00eanior e conselheira geralRon GabriskoDiretor de receitaRick SchultzDiretor de marketingHatim ShafiqueDiretor de opera\u00e7\u00f5esFerm\u00edn SernaDiretor de seguran\u00e7aNaveen ZutshiDiretor de informa\u00e7\u00f5esVinod MarurVice-presidente s\u00eanior de engenhariaDavid MeyerVice-presidente s\u00eanior de produtosAdam ConwayVice-presidente s\u00eanior de produtosArsalan Tavakoli-ShirajiCofundador e SVP de Engenharia de CampoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/br\/professional-services","text":"Servi\u00e7os profissionais Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWServi\u00e7os profissionais DatabricksEntre em contato conosco para obter mais informa\u00e7\u00f5esGaranta o r\u00e1pido sucesso dos seus projetos gra\u00e7as \u00e0 experi\u00eancia avan\u00e7ada em data engineering, data science e gerenciamento de projetos. Os servi\u00e7os profissionais Databricks oferecem suporte na sua jornada de dados e IA:Benef\u00edciosAcelere sua jornada de dados e IA\nNossas ofertas e servi\u00e7os especializados auxiliam voc\u00ea em sua jornada de dados e IA para uma acelera\u00e7\u00e3o ideal e personalizada. Estamos envolvidos desde a integra\u00e7\u00e3o inicial do seu workspace at\u00e9 o estabelecimento de pr\u00e1ticas de DataOps e um Centro de Excel\u00eancia em toda a empresa.\nElimine os riscos do seu projeto\nDeseja migrar cargas de trabalho antigas para o Databricks, desenvolver novos produtos de dados ou projetos de pipeline de dados e IA e machine learning? Ficaremos felizes em acompanhar e aconselhar de forma a minimizar o risco e maximizar o valor em todas as fases da sua jornada.\nOperacionaliza\u00e7\u00e3o em escala\nA cria\u00e7\u00e3o de um POC de pipeline de dados ou desenvolvimento de modelo de n\u00f3 \u00fanico \u00e9 relativamente f\u00e1cil de gerenciar. O desafio est\u00e1 em adotar e dimensionar pr\u00e1ticas de dados e IA com sucesso em toda a organiza\u00e7\u00e3o. Podemos ajudar voc\u00ea a atingir essa meta ambiciosa com nossa experi\u00eancia e ofertas baseadas em padr\u00f5es.\nOfertasGaranta o r\u00e1pido sucesso dos seus projetos gra\u00e7as \u00e0 experi\u00eancia avan\u00e7ada em data engineering, data science e gerenciamento de projetosInicializa\u00e7\u00e3o r\u00e1pidaAcelere o planejamento do seu projeto familiarizando-se com a plataforma Databricks e seus principais recursos que aplicam as pr\u00e1ticas recomendadas.Migra\u00e7\u00e3o do HadoopNossa abordagem prescritiva maximiza o valor dos seus investimentos existentes em dados e pipelines, garantindo uma migra\u00e7\u00e3o tranquila.Desenvolvimento do lakehouseAcelere a implementa\u00e7\u00e3o de uma plataforma simplificada para an\u00e1lise de dados, data science e ML, estabelecendo as bases para sua vis\u00e3o de lakehouse.Machine LearningCapacite as iniciativas de ML da sua empresa e sua ado\u00e7\u00e3o com nossa metodologia prescritiva.Acelerador de servi\u00e7os compartilhadosAcelere seu modelo operacional em escala empresarial para impulsionar a excel\u00eancia em dados e IA com nossa metodologia prescritiva.Servi\u00e7os personalizadosEntre em contato conosco para obter uma especifica\u00e7\u00e3o sob medida que atenda \u00e0s suas necessidades.Nossos especialistas em servi\u00e7os profissionais entregaram com sucesso projetos de ciclo de vida completo para atender a requisitos complexos, altamente espec\u00edficos e direcionados.Arquitetos de solu\u00e7\u00f5es residentes | data scientistsRecursos t\u00e9cnicos e altamente experientes, com fortes habilidades de lideran\u00e7a e consultoria. Para garantir seu sucesso, aproveitamos nosso amplo ecossistema de parceiros e, se necess\u00e1rio, fornecemos servi\u00e7os conjuntos com eles.Especialistas em Databricks e Spark10 anos de experi\u00eancia\nS\u00f3lida experi\u00eancia em big data\nHabilidades pr\u00e1ticas de implementa\u00e7\u00e3o\nPlanejamento e execu\u00e7\u00e3o de projetoAuxiliar com design e arquitetura\nAjudar a alinhar o projeto com os recursos da plataforma\nContribuir para o cronograma do projeto e requisitos de recursos\nPlanejamento de implementa\u00e7\u00e3o e produ\u00e7\u00e3oArquitetar solu\u00e7\u00f5es para escalabilidade\nAuxiliar no desenvolvimento de prot\u00f3tipos\nAtender aos requisitos de integra\u00e7\u00e3o do DevOps\nAux\u00edlio na implementa\u00e7\u00e3o de um COEDesenvolver padr\u00f5es e estruturas comuns\nEstar dispon\u00edvel como um recurso para v\u00e1rias equipes\nFacilitar as intera\u00e7\u00f5es com outras equipes do Databricks\nRecursosVis\u00e3o geral do programa de cr\u00e9dito de sucessoFormul\u00e1rio de Solicita\u00e7\u00e3o de ResgatePor que Databricks AcademyAs pessoas est\u00e3o no centro do sucesso do cliente. Com o treinamento e as certifica\u00e7\u00f5es da Databricks Academy, voc\u00ea aprender\u00e1 a dominar a an\u00e1lise de dados com a equipe que lan\u00e7ou o projeto de pesquisa Spark na UC Berkeley. Avance mais r\u00e1pido com a Databricks Academy.Aprimore suas habilidades agoraTudo pronto para come\u00e7ar?Entre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/big-book-of-data-engineering","text":"\n\n\n\n\n\n\n\nBig Book of Data Engineering Use Cases | Databricks\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alexander-vanadio\/#","text":"Alexander Vanadio - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlexander VanadioPrincipal Consultant at OptivBack to speakersAlex has studied Computer Science at the University of Maryland, College Park. He has been doing some combination of software engineering, data engineering, and ML engineering for over 15 years. Most recently, he has been working on PB scale streaming workloads for a Fortune 500 company.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=it","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/srinivasa-kanamatha","text":"Srinivasa Kanamatha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSrinivasa KanamathaSenior Manager at BlackBerryBack to speakersSrinivasa have worked in the cybersecurity industry for over 13 years. His primary focus have always been in Data Engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-powers\/#","text":"Matthew Powers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew PowersDeveloper Advocate at DatabricksBack to speakersMatthew is a Developer Advocate for Databricks on the Delta Lake team. He's a longtime Spark blogger (mungingdata.com) and Spark open-source contributor. His project include quinn, chispa, spark-daria, spark-fast-tests, and the spark-style-guide. He's passionate about Spark, Delta Lake, traveling, and learning languages.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/datasentics-sap-migration-accelerator","text":"SAP Migration Accelerator by DataSentics and DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionSAP Migration Accelerator by DataSenticsMigration solution developed by DataSentics and powered by the Databricks Lakehouse PlatformLearn moreMigrate 6,000 tables in just 6 monthsDataSentics has developed the\u00a0ODAP Accelerator\u00a0to help you migrate over 6,000 tables from SAP Business Warehouse and S\/4 Hana in less than 6 months with only limited need for human resources. To accelerate and validate the migration process, the ODAP Accelerator has tooling for semi-automated data reconciliation. And once migrated, the client\u2019s data is immediately used for creating dashboards and advanced ML-based use cases. Data can be ingested and processed in both batch and near real-time (Spark Streaming), and new data sets can be onboarded easily and at scale.The ODAP Accelerator greatly simplifies the creation and management of business logic transformations, quality rules, enforcement and data masking to achieve GDPR compliance. Moreover, the accelerator contains mature tooling for building a fine-grained data governance model, as well as access management with automatically created views. With the DataSentics ODAP Accelerator, you can:Migrate more than 6,000 tables in less than 6 monthsGet near real-time insights and ensure compliant access to all dataLeverage new data structures for ML-based use casesLearn moreDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leo-duncan\/#","text":"Leo Duncan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeo DuncanSr. Solutions Architect at Kyvos Insights Inc.Back to speakersLeo Duncan is a Senior Solutions Architect at Kyvos Insights Inc. With over 18 years of analytics experience, he has designed and developed game-changing BI solutions for some of the world's most recognized brands. Leo's innovative approach and strategic vision have earned him a reputation as an analytics genius, empowering organizations to make informed, data-driven decisions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/?itm_data=events-hp-bigpromo-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/wassym-bensaid\/#","text":"Wassym Bensaid - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWassym BensaidSr. Vice President, Software Development at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/learn","text":"\ud559\uc2b5 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ud559\uc2b5\ubc14\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 Databricks \ub9ac\uc18c\uc2a4\uc758 - \uc138\uacc4\ub97c \ubcf8\uaca9\uc801\uc73c\ub85c \ud0d0\uad6c\ud574\ubcf4\uc138\uc694. \uad50\uc721, \uc778\uc99d\uacfc \uc608\uc815\ub41c \uc774\ubca4\ud2b8, \uc720\uc6a9\ud55c \ubb38\uc11c \ub4f1 \ub2e4\uc591\ud55c \ub9ac\uc18c\uc2a4\uac00 \uc900\ube44\ub418\uc5b4\uc788\uc2b5\ub2c8\ub2e4.Databricks \uc2dc\uc791\ud558\uae30\uae30\ucd08 \ubc30\uc6b0\uae30Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\uba74 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uac04\ud3b8\ud558\uac8c \ube4c\ub4dc\ud558\uace0 \uc2e4\ud589\ud558\uba70 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubc0f \ubd84\uc11d \ud504\ub85c\uc81d\ud2b8\uc5d0\uc11c \uc6d0\ud65c\ud558\uac8c \ud611\uc5c5\uc744 \uc9c4\ud589\ud558\uace0, \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\ub3c4 \ube4c\ub4dc\ud558\uc5ec \ubc30\ud3ec\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\uc758 \uc2dc\uc791\ud558\uae30 \uac00\uc774\ub4dc\ub97c \ucc38\uc870\ud558\uc138\uc694.Databricks\ub97c \ucc98\uc74c \uc0ac\uc6a9\ud558\uc2dc\ub098\uc694? 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\uae30\uc6b8\uc774\ub294 \ucee4\ubba4\ub2c8\ud2f0 \ud68c\uc6d0\ub4e4\ub85c \uad6c\uc131\ub41c \uadf8\ub8f9\uc778 Databricks Beacons\ub97c \uc18c\uac1c\ud569\ub2c8\ub2e4.\uc790\uc138\ud788University AllianceDatabricks University Alliance\uc5d0\uc11c Databricks\ub97c \uc0ac\uc6a9\ud558\uc5ec \uad50\uc721\ud558\uace0\uc790 \ud558\ub294 \uad50\uc721\uc790\ub97c \uc704\ud55c \ubb34\ub8cc \ub9ac\uc18c\uc2a4\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788Data Brew Vidcast\uc804\ubb38\uac00\uc640 \ud568\uaed8 \ub370\uc774\ud130 + AI \uc54c\uc544\ubcf4\uae30Brooke Wenig, Denny Lee\ub3d9\uc601\uc0c1 \uc2dc\ub9ac\uc988\uc628\ub77c\uc778 Tech Talks\uc640 \ubaa8\uc784Brooke Wenig, Denny Lee\ud14c\ud06c \ud1a0\ud06cMLflow\ub97c \uc0ac\uc6a9\ud55c \uc644\ubcbd\ud55c \uba38\uc2e0 \ub7ec\ub2dd \uc218\uba85 \uc8fc\uae30 \uad00\ub9ac\uc904\uc2a4 \ub2f4\uc9c0\ud14c\ud06c \ud1a0\ud06cDelta Lake \uc2dc\uc791\ud558\uae30\ub370\ub2c8 \ub9ac\ud14c\ud06c \ud1a0\ud06cDelta Lake \uc2ec\uce35 \ud0d0\uad6c(\uace0\uae09)\ub370\ub2c8 \ub9acDatabricks \ub370\ubaa8 \ud5c8\ube0c(\uc81c\ud488 \ub370\ubaa8)\ub370\uc774\ud130 + AI \uc5f0\uad6c\ub9c8\ud14c\uc774 \uc790\ud558\ub9ac\uc544\uacf5\ub3d9 \ucc3d\uc5c5\uc790 \uacb8 Chief Technologistdatabricks\ub808\uc774\ub180\ub4dc \uc2e0\uacf5\ub3d9 \ucc3d\uc5c5\uc790 \uacb8 Chief ArchitectdatabricksSue Ann Hong\uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc5d4\uc9c0\ub2c8\uc5b4databricksDatabricks \ucc3d\uc5c5\uc790, \uc2a4\ud0dc\ud504\uc640 \uc5f0\uad6c\uc9c4\uc774 \ubd84\uc0b0\ud615 \uc2dc\uc2a4\ud15c, AI \ubc0f \ub370\uc774\ud130 \ubd84\uc11d \ub4f1\uc744 \uc8fc\uc81c\ub85c UC \ubc84\ud074\ub9ac\uc640 \uc2a4\ud0e0\ud37c\ub4dc \ub4f1 \uba85\ubb38 \ub300\ud559\uad50\uc640 \ud611\uc5c5\ud574 \uc800\uc220\ud558\uc5ec \ucd5c\uadfc \uacf5\uac1c\ud55c \ub17c\ubb38\uc744 \uc77d\uc5b4\ubcf4\uc138\uc694.\uc5f0\uad6c\uc5d0 \uc561\uc138\uc2a4\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/basak-eskili\/#","text":"Basak Eskili - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBasak EskiliML Engineer at Ahold DelhaizeBack to speakersBasak Eskili is a Machine Learning Engineer at Ahold Delhaize. She is working on creating new tools and infrastructure that enable data scientists to quickly operationalise algorithms. She is bridging the gap between data scientists and platform engineers while improving the way of working in accordance with MLOps principles, and ensuring that the models are reliable, scalable, and secure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/contact","text":"Entre em contato conosco - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWEntre em contatoVoc\u00ea precisa de ajuda com o treinamento ou suporte? Consulte estes recursos adicionais.Documenta\u00e7\u00e3oLeia a documenta\u00e7\u00e3o t\u00e9cnica para Databricks na AWS, Azure ou Google CloudComunidade do DatabricksDiscuta, compartilhe e interaja com especialistas e usu\u00e1rios da DatabricksTreinamentoTorne-se especialista na Databricks Lakehouse Platform com um treinamento conduzido por instrutor ou individualizado. Voc\u00ea tamb\u00e9m pode se tornar um desenvolvedor certificadoSuporteJ\u00e1 \u00e9 cliente? Clique aqui se tiver um problema t\u00e9cnico ou de pagamentoNossos escrit\u00f3riosDescubra todos os nossos escrit\u00f3rios ao redor do mundo e entre em contato conoscoBase de conhecimentoEncontre respostas r\u00e1pidas para as perguntas frequentes sobre produtos e servi\u00e7os da DatabricksProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vinit-doshi\/#","text":"Vinit Doshi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVinit DoshiSenior Manager at TredenceBack to speakersVinit Doshi leads the MLOps delivery practice at Tredence, He has over 14 years of experience in building and managing ML solutions with a focus on building scalable MLOPs practices for clients over the past 3 years.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/abn-amro","text":"Customer Story: ABN AMRO | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYFinancial services digital transformation at a global scale\u200c10xFaster time to market \u2014 use cases deployed in 2 months100+Use cases to be delivered over the coming year500+Empowered business and IT usersRead story INDUSTRY: Financial services SOLUTION: Customer segmentation,data-driven ESG,fraud detection,risk management,threat detection PLATFORM USE CASE: Lakehouse,Delta Lake,data science,machine learning,Databricks SQL,ETL CLOUD: Azure\u201cDatabricks has provided one platform for our data and analytics teams to access and share data across ABN AMRO, delivering ML-based solutions that drive automation and insight throughout the company.\u201d\n\u2013 Stefan Groot, Head of Analytics Engineering, ABN AMROAs an established bank, ABN AMRO\u2019s ability to modernize their business was hamstrung by legacy infrastructure and data warehouses that complicated access to data across various sources and created inefficient data processes and workflows. Today, Azure Databricks empowers ABN AMRO to democratize data and AI for a team of 500+ empowered engineers, scientists and analysts, who work collaboratively on improving business operations and introducing new go-to-market capabilities across the company.The impossibility of tackling new ambitions with old technologyOver the years, ABN AMRO has grown to become the third-largest bank in the Netherlands, generating a wealth of data with hundreds of terabytes of data across hundreds of disparate data sources \u2014 but their approach to data and analytics was far from where they needed it to be in order to realize their data-driven aspirations. Hampered by a centralized on-premises data warehouse and inefficient workflows, they struggled to transform into a truly digital bank that could realize the full potential of their data.\u201cIn order to capitalize on the opportunity in front of us, we needed the ability to harness the data at our disposal and work in a different way than we are used to,\u201d explained Stefan Groot, the head of analytics engineering at ABN AMRO. \u201cOur organization suffered from highly disparate teams working in isolation without true collaboration and sharing of best practices. Although people were communicating, they weren\u2019t working together around data as a cohesive organization, which created mass inefficiencies.\u201dGroot understood the importance of moving away from their traditional big data warehouse toward a domain-driven lakehouse and a data mesh approach where the creation and processing of data is federated across domains by using a proven, standardized platform.He also envisioned an InnerSource culture among the hundreds of data professionals in which everyone is working collaboratively and sharing data insights seamlessly to support business goals.A new mode of operation: Federating all data for all analyticsWith the goal of transforming the bank into a data-driven organization, ABN AMRO shifted toward the Azure cloud for ease of use and scalability and was able to operationalize the Databricks Lakehouse Platform within a couple months. With Databricks, they are now able to accelerate innovation by introducing data-driven solutions that improve strategic decision-making, operational efficiency, cybersecurity and the overall customer experience.Databricks eases access to multiple data sources and simplifies infrastructure management at any scale. Delta Lake allows ABN AMRO to create data pipelines that are not only fast but highly reliable \u2014 critical for analytics and the data science teams who rely on complete and accurate data for decision-making, analytics and model training.With data at their fingertips, ABN AMRO\u2019s data analysts are now able to easily perform analytics and transform data to feed business reports and dashboards via PowerBI.The data scientists and machine learning engineers can also easily deploy models into production with MLflow. What used to be a highly disjointed and manual process filled with inefficiencies is now consistent and automated.Putting data into action: Banking digital transformation at scaleWith Databricks, including a new marketing automation stack, ABN AMRO is now able to react to customer preferences faster, allowing them to serve relevant product recommendations or deliver a relevant service to ensure satisfaction and reduce churn.Fraud detection is also a focal point for the bank. Through the use of machine learning, they can identify anomalous behavior to prevent fraudulent activity such as money laundering, which is a common means to fund terrorism around the world.Business operations is also an area that is greatly benefiting from data and AI. From a customer support perspective, Databricks powers a client dashboard that provides a complete view of the customer and all their assets and transactions in near real-time. This provides the insights their help desk and support teams need in an easy-to-consume format to better serve their customers. Additionally, they can monitor how many calls each support representative has made and identify opportunities to improve efficiencies and reduce operational costs.Unlocking data-driven opportunities faster and cost-efficientlyToday, ABN AMRO has flipped their data strategy on its head. Rather than technology being the problem, now it\u2019s an enabler. Because of this paradigm shift, the data teams at ABN AMRO have been able to deliver nearly dozens of use cases across the business at lightning speeds \u2014 10x faster than with their existing infrastructure. But that\u2019s just the tip of the iceberg. Groot estimates that they\u2019ve only delivered 5% of the total use cases they have on their road map, with over 100 additional use cases, and even more machine learning models, planned over the coming months.Most importantly, as the company grows so does the data team\u2019s ability to grow and support the business. \u201cWe are a truly agile organization now,\u201d expressed Stefan Boom, Solutions Architect at ABN AMRO. \u201cThere were things that weren\u2019t even possible before. Now we have the flexibility and capability to do anything.\u201dWith Databricks playing a pivotal role in their data-driven decision-making, ABN AMRO has opened the floodgates to empower over 500 team members across data engineering, analytics, data science and the business to leverage data to experiment and build solutions that deliver on use cases across the organization.Looking ahead, Groot feels that in the coming year they will see exponential growth in models with 100+ additional use cases on the road map. Now that they have the technology stack, organizational structure and processes, and collaborative culture in place, they will be able to shift their focus and accelerate value creation across the enterprise.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/partnerconnect","text":"Contact partenaires | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWContact partenairesD\u00e9couvrez et int\u00e9grez facilement des solutions de donn\u00e9es, d'analytique et d'IA avec votre lakehouse.Regarder les d\u00e9mosGr\u00e2ce \u00e0 Partner Connect, d\u00e9couvrez facilement les donn\u00e9es, l'analytique et l'IA directement au sein de la plateforme Databricks et int\u00e9grez rapidement les outils que vous utilisez d\u00e9j\u00e0 actuellement. Avec Partner Connect, vous pouvez simplifier l'int\u00e9gration des outils en quelques clics et \u00e9tendre rapidement les capacit\u00e9s de votre lakehouse.Connectez vos donn\u00e9es et vos outils d'IA au lakehouseConnectez facilement vos donn\u00e9es et outils d'IA pr\u00e9f\u00e9r\u00e9s au lakehouse et alimentez n'importe quel cas d'usage analytiqueD\u00e9couvrez des solutions de donn\u00e9es et d'IA valid\u00e9es pour de nouveaux cas d'usageUn portail unique pour les solutions partenaires valid\u00e9es afin que vous puissiez cr\u00e9er votre prochaine application de donn\u00e9es plus rapidement.Configuration en quelques clics gr\u00e2ce \u00e0 des int\u00e9grations pr\u00e9d\u00e9finiesPartner Connect simplifie vos int\u00e9grations en configurant automatiquement les ressources (y compris les clusters, les jetons et les fichiers de connexion) pour vous connecter aux solutions partenairesCommencez en tant que partenaireLes partenaires de Databricks sont id\u00e9alement positionn\u00e9s pour fournir des insights d'analytique plus rapides aux clients. Tirez parti du d\u00e9veloppement et des ressources partenaires de Databricks pour d\u00e9velopper votre activit\u00e9 aux c\u00f4t\u00e9s de notre plateforme ouverte et bas\u00e9e dans le cloud.Devenir partenaire\u00ab\u00a0S'appuyant sur un partenariat de longue date, Partner Connect permet de concevoir une exp\u00e9rience int\u00e9gr\u00e9e entre nos entreprises et nos clients. Avec Partner Connect, nous proposons une exp\u00e9rience simplifi\u00e9e qui permet aux milliers de clients de Databricks, qu'ils utilisent Fivetran aujourd'hui ou qu'ils nous d\u00e9couvrent par le biais de Partner Connect, de d\u00e9bloquer les informations au sein de leurs donn\u00e9es, de d\u00e9couvrir davantage de cas d'usage en termes d'analytique et de tirer profit de la valeur du lakehouse plus rapidement en connectant facilement des centaines de sources de donn\u00e9es \u00e0 leur lakehouse.\u00a0\u00bb\u2014 George Fraser, P-DG de FivetranD\u00e9mosFivetranConnectez les donn\u00e9es de plus de 180 applications populaires, y compris les applications SaaS (Salesforce, Google Analytics, etc.) dans le lakehousedbtCr\u00e9er des transformations de donn\u00e9es avec dbt Cloud et DatabricksPower BIMettez les avantages des performances et de la technologie Databricks Lakehouse au service de tous vos utilisateursTableauOffrez \u00e0 tous les utilisateurs la puissance d'un data lakehouse pour l'analytique moderne en connectant Tableau Desktop \u00e0 Databricks SQLRiverySimplifiez le parcours des donn\u00e9es, de l'ingestion \u00e0 la transformation, en passant par la livraison dans le Delta LakeLabelboxPr\u00e9parez facilement des donn\u00e9es non structur\u00e9es pour l\u2019IA et l\u2019analyse dans le LakehouseProphecyCr\u00e9ez et d\u00e9ployez des pipelines Spark et Delta \u00e0 l'aide d'une interface visuelle par \u00ab\u00a0glisser-d\u00e9poser\u00a0\u00bbArcionConnectez des sources de donn\u00e9es au lakehouse \u00e0 l'aide d'une plateforme de r\u00e9plication bas\u00e9e sur CDCEssai gratuitRessourcesBlogF\u00e9v 2023 - Annonce de nouvelles int\u00e9grations de partenaires dans Partner ConnectSept 2022 - Introduction de nouvelles int\u00e9grations de partenaires dans Partner ConnectJuin 2022 - Annonce de nouvelles int\u00e9grations de partenaires dans Partner ConnectCr\u00e9ez votre entreprise sur Databricks avec Partner ConnectDocumentationGuide de Databricks Partner ConnectVous voulez en savoir plus\u00a0?Tirez parti du d\u00e9veloppement et des ressources partenaires de Databricks pour d\u00e9velopper votre activit\u00e9 aux c\u00f4t\u00e9s de notre plateforme ouverte et bas\u00e9e dans le cloud.Devenir partenaireNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/satya-nadella","text":"Satya Nadella - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSatya NadellaChairman and CEO at Microsoft, Live Virtual GuestBack to speakersSatya Nadella is Chairman and Chief Executive Officer of Microsoft. Before being named CEO in February 2014, Nadella held leadership roles in both enterprise and consumer businesses across the company. Joining Microsoft in 1992, he quickly became known as a leader who could span a breadth of technologies and businesses to transform some of Microsoft\u2019s biggest product offerings. Most recently, Nadella was executive vice president of Microsoft\u2019s Cloud and Enterprise group. In this role he led the transformation to the cloud infrastructure and services business, which outperformed the market and took share from competition. Previously, Nadella led R&D for the Online Services Division and was vice president of the Microsoft Business Division. Before joining Microsoft, Nadella was a member of the technology staff at Sun Microsystems. Originally from Hyderabad, India, Nadella lives in Bellevue, Washington, with his family. He earned a bachelor\u2019s degree in electrical engineering from Mangalore University, a master\u2019s degree in computer science from the University of Wisconsin \u2013 Milwaukee and a master\u2019s degree in business administration from the University of Chicago. Nadella serves on the board of trustees to his alma mater the University of Chicago, as well as the Starbucks board of directors.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/test1-testcfp1102","text":"Test1 TestCFP1102 - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTest1 TestCFP1102 testBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/douglas-moore","text":"Douglas Moore - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDouglas MooreLead Specialist Solutions Architect at DatabricksBack to speakersSince 2011 Douglas Moore been making Big Data Analytics a lot easier for customers. His current role is that of an HLS Lead Specialist Solutions Architect with Databricks. Douglas brings a long tenure in enterprise data architecture and building data analytics platforms. Past roles have included: Solutions Architect, Data Architect, CTO, Engineer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/real-time-retail","text":"What is Real-Time Retail?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWReal-Time RetailAll>Real-Time RetailTry Databricks for freeGet StartedWhat is real-time data for Retail?Real-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. Real-time use cases, such as demand forecasting, personalization, on-shelf availability, arrival time prediction and order picking and consolidation, provide value to the organization through improved supply chain agility, reduced cost to serve, optimized product availability, and stocking replenishment.Why is real-time data for Retail important?We witnessed the move to e-commerce and omni-channel commerce happen over the past 20 years, only to see consumer behaviors fundamentally shift once the COVID-19 pandemic occurred. In just 10 weeks, we witnessed a rate of change that took the previous 10 years to accomplish. As physical stores faced lockdown orders, consumers shifted purchasing to digital channels. Restaurants saw internal dining evaporate, while drive-thru and delivery skyrocketed. With the shift in dollars came other changes: increased fraud, shifting customer expectations, a higher volume of returns, and increased costs to serve customers curb-side service and delivery.Compounding consumer-led changes has been the recent volatility in supply chains. The greatest risk to retail and consumer goods for the next several years is volatility.Legacy business strategies were instantly outdated - demand forecasting predicted the wrong demand, customer preferences changed, which precipitated stock outages, hence retailer\u2019s margins suffered. As consumers purchased in real-time, businesses had to shift their outdated data warehouse architectures to those that could run and respond in real-time - hence Lakehouse for Retail.What are the benefits of real-time access to data?Rapid data ingestion at scale makes advanced insights available across the value chain in real-time, reducing costs and minimizing errors. Retailers make mistakes when they make decisions without information. These mistakes can manifest in many ways, including some of the following:\nUnderestimating demand leads to expedited shipping costs for rush deliveryIncorrectly predicting how much of an item to produce leads to excess carrying costs, missed sales, and higher wasteReacting to breakdowns leads to unplanned outages that disrupt full production cyclesOrder fulfillment with incomplete or inaccurate data leads to additional shipping costs or higher rates of returnMissing an opportunity to engage a consumer based on current data leads to missed sales opportunitiesProcessing data in real-time enables all parts of the value chain to see the status of operations without delay and make better-informed decisions that help avoid these problems.What are Databricks\u2019 real-time data differentiated capabilities?Databricks\u2019 Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader and Photon to enable customers to make data available for real-time decisions.Lakehouse for Retail supports the largest data jobs at near real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.A Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for real-time stream ingestion of data and analytics on streaming data. Data warehouses require the extraction, transformation, loading, and additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest of data sets to power real-time decisions in BI tools.Learn more about Lakehouse for Retail solutions.Additional ResourcesCollaborating Across the Retail Value Chain with Data and AIReal-time Point-of-Sale Analytics With a Data LakehouseImproving On-Shelf Availability for Items With AI Out of Stock ModelingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brooke-wenig\/#","text":"Brooke Wenig - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrooke WenigDirector, Machine Learning Practice at DatabricksBack to speakersBrooke Wenig is a Machine Learning Practice Lead at Databricks. She leads a team of data scientists who develop large-scale machine learning pipelines for customers, as well as teach courses on distributed machine learning best practices. She is a co-author of Learning Spark, 2nd Edition, co-instructor of the Distributed Computing with Spark SQL Coursera course, and co-host of the Data Brew podcast. She received an MS in Computer Science from UCLA with a focus on distributed machine learning and a BA in Chinese. She enjoys cycling and taking her dog, Bingo, to the beach.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=customer%20success","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/legal\/privacynotice#dbadditionalinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\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\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{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases","text":"Press releases | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPress releasesNews and announcementsPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/keshav-santhanam","text":"Keshav Santhanam - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKeshav SanthanamPhD Student at Stanford UniversityBack to speakersKeshav is a 4th-year PhD student at Stanford University advised by Matei Zaharia. His research is broadly centered on optimizing systems for machine learning, with a recent focus on improving resource efficiency for neural information retrieval systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/simon-whiteley","text":"Simon Whiteley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSimon WhiteleyCTO at Advancing AnalyticsBack to speakersSimon is a Databricks Beacon, Microsoft MVP and owner of Advancing Analytics. A deep techie with a focus on emerging cloud technologies and applying \u201cbig data\u201d thinking to traditional analytics problems, Simon also has a passion for bringing it back to the high level and making sense of the bigger picture. When not tinkering with tech, Simon is a death-dodging London cyclist, a sampler of craft beers, an avid chef, and a generally nerdy person.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stan-lin\/#","text":"Stan Lin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStan LinSenior Software Engineer at Microsoft CorporationBack to speakersTech lead at Microsoft, MSAI. Experience in large-scale machine learning, graph intelligence, performant web services and compliance. Building the large-scale ML platform powering Microsoft 365 knowledge mining, search and recommendation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/category\/engineering\/open-source","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adam-wilson","text":"Adam Wilson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdam WilsonCo-Founder, Chief of Product at Divirod, Inc.Back to speakersAdam is a serial entrepreneur. He co-founded Sphero in 2010, the robot company responsible for bringing joy and education to millions of kids through programmable robots and amazing educational content. He has a unique talent for product development, visionary ideas and relentless drive to focus on execution and is a contributor to over 15 technology patents. Adam\u2019s real passion is \u201cmaking,\u201d he has a full size R2-D2 in his living room, loves to judge kid\u2019s science fairs, sits on the NHS board of University of Northern Colorado where he graduated with a undergraduate degree in math and physics and you may have even seen some of his work as a spokesperson from past Microsoft commercials!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Essayer gratuitement Databricks | DatabricksEssayer gratuitement DatabricksExp\u00e9rimentez pleinement la plateforme Databricks gratuitement pendant 14 jours, sur AWS, Microsoft Azure ou Google Cloud, au choix.Simplification de l'ingestion des donn\u00e9es et automatisation de l\u2019ETLImportez des donn\u00e9es depuis des centaines de sources. Utilisez une approche d\u00e9clarative simple pour cr\u00e9er des pipelines de donn\u00e9es.Collaborez dans votre langage pr\u00e9f\u00e9r\u00e9Codez en Python, R, Scala et SQL. B\u00e9n\u00e9ficiez du RBAC, d\u2019int\u00e9grations avec Git et d\u2019outils comme la r\u00e9daction collaborative et la gestion automatique des versions.Un rapport performance \/ prix jusqu'\u00e0 12 fois sup\u00e9rieur \u00e0 celui des data warehousesD\u00e9couvrez pourquoi plus de 7 000 clients dans le monde s\u2019appuient sur Databricks pour toutes leurs charges de travail de la BI \u00e0 l\u2019IA.Cr\u00e9ez votre compte Databricks1\/2Pr\u00e9nomNomE-mail professionnelEntrepriseIntitul\u00e9 de posteNum\u00e9ro de t\u00e9l\u00e9phone (facultatif)Veuillez s\u00e9lectionnerPaysContinuerAvis de confidentialit\u00e9 (mis \u00e0 jour)Conditions d'utilisationVos choix de confidentialit\u00e9Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/code-of-conduct\/","text":"Code of Conduct - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCode of ConductData + AI Summit Event , Organized by DatabricksSummit Organizers are committed to creating a safe and inclusive experience for our conference attendees, regardless of gender, sexual orientation, disability, physical appearance, body size, race, or religion. We do not tolerate harassment in any form. All communication \u2014 including at the event and various associated venues, as well as online \u2014 should be appropriate for a professional audience, including people of many different backgrounds and experiences. Be kind to others. Do not insult or put down other attendees. Act professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate at any time at any event organized by Databricks.\nInteraction Guidelines for AttendeesFor all interactions during the Data + AI Summit Event, we expect participants to abide by the event\u2019s Code of Conduct to ensure the environment remains productive and respectful. The following guidelines will further help ensure we maintain an inclusive experience throughout our event:\n\nBe respectful of others.\nAvoid conflicts and arguments.\nUse common sense, kindness, and consideration together with the guidelines outlined above.\nIf you intend to participate in the event, please make sure to dress appropriately.\n\nEnforcementIf a participant engages in behavior that doesn\u2019t comply with these expectations, Summit Organizers may take any action that we deem appropriate, including warning the participant, excluding the participant from certain activities, prohibiting the participant from attending future events organized by Databricks, expelling the participant from the event without a refund, banning the participant from online forums, and other similar type experiences. Participants asked to stop any harassing or other unacceptable behaviors are expected to comply immediately. Anyone violating these rules may be asked to leave the experience without a refund at the sole discretion of Summit Organizers.\n\nPlease note, while we take all concerns raised seriously, we will use our discretion to determine when and how to follow up on reported incidents, and may decline to take any further action and\/or may direct the participant to other resources to address the concern.\nReporting an IssueIf you are being harassed, notice that someone else is, or have any concerns, please contact Summit Organizers at [email\u00a0protected] and provide your name, phone number, email, and a description of the situation. Summit Organizers can only address complaints about behavior at the Event.\nThe reporting mechanisms under this Code of Conduct are not intended to address criminal activity or emergency situations. If you have been the victim of a crime or there is an emergency, please contact the appropriate municipal authorities, such as the police, fire, medical, or other emergency responders.\nThank you for helping make Databricks Data + AI Summit a welcoming, friendly place for all to share new ideas, learn, and connect.\n\nInformation for Presenters: Presenters who are unsure whether their presentations or other materials and communications are consistent with these expectations, please contact Toby Malina at\u00a0 [email\u00a0protected] in advance of the experience.\n\u00a0\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=product","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/learn","text":"Aprender | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWAprenderDescubra e explore um mundo de recursos da Databricks na ponta dos seus dedos. Voc\u00ea encontrar\u00e1 treinamento e certifica\u00e7\u00e3o, pr\u00f3ximos eventos, documenta\u00e7\u00e3o \u00fatil e muito mais.Comece a usar a DatabricksAprenda o b\u00e1sicoA Databricks Lakehouse Platform facilita a cria\u00e7\u00e3o e execu\u00e7\u00e3o de pipelines de dados, a colabora\u00e7\u00e3o em projetos de data science e an\u00e1lise, e a cria\u00e7\u00e3o e implementa\u00e7\u00e3o de modelos de machine learning. Confira nossos guias de introdu\u00e7\u00e3o abaixo.Novo na Databricks? Comece sua jornada com a Databricks guiado por um experiente engenheiro de sucesso do cliente.Integra\u00e7\u00e3o da Databricks\nLakehouse Fundamentals Training\nWatch 4 short videos, take the quiz and get your badge\nto share on LinkedIn or your r\u00e9sum\u00e9\nGet startedData science e data engineeringAdministradores DatabricksAn\u00e1lise de SQLMachine leaningTreinamentoFa\u00e7a treinamentos pela Databricks Academy. Aprenda a dominar a an\u00e1lise de dados da equipe por tr\u00e1s do projeto de pesquisa Apache Spark\u2122 na Universidade da Calif\u00f3rnia, em Berkeley.Databricks AcademyCertifica\u00e7\u00e3oOs exames de certifica\u00e7\u00e3o avaliam seu n\u00edvel de conhecimento da Databricks Lakehouse Platform e os m\u00e9todos necess\u00e1rios para implementar projetos de qualidade com sucesso. Eles ajudam voc\u00ea a ganhar reconhecimento do setor, diferencia\u00e7\u00e3o competitiva, maior produtividade e resultados e uma medida tang\u00edvel de seu investimento educacional.Certifica\u00e7\u00e3o DatabricksEncontre respostas para suas perguntasEscolha uma das seguintes maneiras de esclarecer quaisquer d\u00favidas que possam surgir quando voc\u00ea est\u00e1 come\u00e7ando:Pergunte a um especialista t\u00e9cnico da Databricks em tempo realComunidade onlineExplore t\u00f3picos populares dentro da comunidade Databricks.Conecte-se com a comunidadeT\u00f3picos populares do f\u00f3rumDatabricksDelta LakeSparkSQLPySparkAzureAWSGCPPrecisa de ajuda?Se voc\u00ea tiver um contrato de suporte ou estiver interessado em um, confira nossas op\u00e7\u00f5es abaixo. Para obter orienta\u00e7\u00f5es estrat\u00e9gicas de neg\u00f3cios (com um engenheiro de sucesso do cliente ou um contrato de servi\u00e7os profissionais), entre em contato com o administrador do workspace para falar com o executivo de contas da Databricks.Confira nossas op\u00e7\u00f5es de suporteGaleria de NotebookEsta galeria apresenta algumas das possibilidades por meio de notebooks focados em tecnologias e casos de uso que podem ser facilmente importados para seu pr\u00f3prio ambiente da Databricks ou para a edi\u00e7\u00e3o gratuita da comunidade.Galeria de notebooks da DatabricksDocumenta\u00e7\u00e3oO site de documenta\u00e7\u00e3o t\u00e9cnica da Databricks fornece orienta\u00e7\u00e3o e informa\u00e7\u00f5es de refer\u00eancia para data science e data engineering da Databricks, machine learning da Databricks e ambientes baseados em configura\u00e7\u00f5es do Databricks SQL.Documenta\u00e7\u00e3o da AWSDocumenta\u00e7\u00e3o do AzureDocumenta\u00e7\u00e3o do GoogleEventos e comunidade da DatabricksData+AI SummitParticipe de palestras, an\u00fancios de produtos e mais de 200 sess\u00f5es t\u00e9cnicas \u2014 incluindo um time especialistas no setor, em pesquisa e acad\u00eamicos.Saiba maisEventos globaisEconomize seu lugar em uma de nossas confer\u00eancias globais ou regionais, demonstra\u00e7\u00f5es de produtos ao vivo, webinars, eventos patrocinados por parceiros ou encontros.Saiba maisEncontros online sobre dados e IADescubra o que est\u00e1 acontecendo nos grupos Databricks Meetup em todo o mundo e participe virtualmente.Saiba maisBeaconsConhe\u00e7a os Databricks Beacons, um grupo de membros da comunidade que fazem todo o poss\u00edvel para promover a comunidade de dados e IA.Saiba maisAlian\u00e7a com universidadesJunte-se \u00e0 Databricks University Alliance para acessar recursos gratuitos para educadores que desejam ensinar usando a Databricks.Saiba maisVidcast sobre prepara\u00e7\u00e3o de dadosExplorar dados + IA com especialistasBrooke Wenig e Denny LeeS\u00e9rie de v\u00eddeosPalestras e encontros de tecnologia onlineBrooke Wenig e Denny LeePalestras de tecnologiaGerenciamento do ciclo de vida completo de machine learning usando o MLflowJules DamjiPalestras de tecnologiaIntrodu\u00e7\u00e3o ao Delta LakeDenny LeePalestras de tecnologiaMergulhar no Delta Lake (Avan\u00e7ado)Denny LeeHub de demonstra\u00e7\u00e3o da Databricks (demonstra\u00e7\u00f5es do produto)Dados e pesquisa de IAMatei ZahariaCofundador e tecn\u00f3logo-chefeDatabricksReynold XinCofundador e arquiteto-chefeDatabricksSue Ann HongEngenheiro de softwareDatabricksLeia artigos recentes de fundadores, funcion\u00e1rios e pesquisadores da Databricks sobre sistemas distribu\u00eddos, IA e an\u00e1lise de dados, em colabora\u00e7\u00e3o com as principais universidades, como UC Berkeley e Stanford.Acessar pesquisaProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/antoni-baum\/#","text":"Antoni Baum - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAntoni BaumSoftware Engineer at AnyscaleBack to speakersAntoni is a Software Engineer at Anyscale, working on Ray AIR and the rest of Ray ML ecosystem.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deepak-sekar","text":"Deepak Sekar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeepak SekarSr. Solution Architect at DatabricksBack to speakersA Data & AI enthusiast from the down under! Extensive experience in building Enterprise\/ SMB Data & AI solutions in ASEAN and Australia\/NZ across Energy & Utilities\/ Oil & Gas\/ Telecommunication\/ Retail. I love guiding organizations to embrace data & unlock the never-ending value that data brings to them. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/cloud-partners","text":"Parceiro provedor de servi\u00e7os em nuvem da Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWParceiros em nuvem da DatabricksO Databricks Lakehouse funciona em todas as principais nuvens p\u00fablicas, totalmente integrado com os servi\u00e7os de seguran\u00e7a, compute, armazenamento, an\u00e1lise e intelig\u00eancia artificial oferecidos nativamente pelos provedores de nuvem. Isso fornece a agilidade de que voc\u00ea precisa para aproveitar seu provedor de nuvem preferido, quando e como quiser.O Azure Databricks \u00e9 um servi\u00e7o prim\u00e1rio desenvolvido em conjunto entre a Databricks e a Microsoft. Comece com um \u00fanico clique no portal do Azure e integre-se nativamente aos servi\u00e7os de seguran\u00e7a e dados do Azure.Saiba maisA Databricks no AWS permite que voc\u00ea armazene e gerencie todos os seus dados em uma plataforma simples e aberta de lakehouse que combina o melhor dos data warehouses e data lakes para unificar todas as suas an\u00e1lises e cargas de trabalho de IA.Saiba maisA Databricks no Google Cloud traz a plataforma lakehouse aberta para a nuvem aberta para unificar data engineering, data science e an\u00e1lise, com uma estreita integra\u00e7\u00e3o ao Google Cloud Storage, BigQuery e a plataforma de IA do Google Cloud.Saiba maisRegi\u00f5es de nuvem\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0\u25cfAlibabaProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-hecht","text":"Chris Hecht - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris Hecht DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/beth-mattson","text":"Beth Mattson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeth MattsonSenior Data Engineer at Our Family WizardBack to speakersPragmatic data engineer with a keen interest in data as actionable information, always striving to provide users opportunities for data discovery, creativity, and iteration. Background spans healthcare to software start-ups.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jamie-baker\/#","text":"Jamie Baker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJamie BakerDirector of Product at MatillionBack to speakersJamie Baker is an accomplished product, domain leader\/manager, solutions consultant, and an industry-recognized subject matter expert, with a proven track record delivering enterprise on-premise and SaaS software products and solutions across IT infrastructure and Data Integration markets. Jamie has presented at global IT conferences on capacity management, digital transformation, and ITIL process implementation and maturity.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=DataScience-HeroCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/product\/delta-lake-on-databricks","text":"Delta Lake in Databricks \u2013 jetzt Demo planen!Skip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDelta LakeLeistung, Sicherheit und Zuverl\u00e4ssigkeit f\u00fcr Ihren Data LakeKostenlos testenDemo ansehenWas ist Delta Lake?Delta Lake ist ein formatoffener Speicher-Layer, der die in Ihrem Data Lake f\u00fcr Leistung, Sicherheit und Zuverl\u00e4ssigkeit sorgt \u2013 sei es im Streaming- oder im Batch-Betrieb. Dabei ersetzt Delta Lake vorhandene Datensilos durch ein zentrales Repository f\u00fcr strukturierte, teilstrukturierte und unstrukturierte Daten und bildet so die Grundlage f\u00fcr ein kosteng\u00fcnstiges und hochgradig skalierbares Lakehouse.Hochwertige und zuverl\u00e4ssige DatenImplementieren Sie eine belastbare Single Source of Truth f\u00fcr alle Ihre Daten (inklusive Echtzeit-Streams). So k\u00f6nnen Ihre Teams jederzeit mit den aktuellsten Daten arbeiten. Dank Unterst\u00fctzung f\u00fcr ACID-Transaktionen und Schemaerzwingung bietet Delta Lake das Mehr an Zuverl\u00e4ssigkeit, das herk\u00f6mmlichen Data Lakes fehlt. So k\u00f6nnen Sie aussagekr\u00e4ftige Erkenntnisse aus Ihren Daten unternehmensweit skalieren, Analysen und weitere Datenprojekte direkt f\u00fcr Ihren Data Lake ausf\u00fchren und die Time-to-Insight sage und schreibe um den Faktor 50 beschleunigen.Offener und sicherer DatenaustauschDelta Sharing\u00a0ist das branchenweit erste offene Protokoll f\u00fcr die sichere Datenfreigabe. Mit Delta Sharing wird der Datenaustausch mit anderen Organisationen zum Kinderspiel \u2013 ganz gleich, wo die Daten gespeichert sind. Die native Integration mit dem\u00a0Unity-Katalog\u00a0gestattet organisations\u00fcbergreifend das zentrale Verwalten und Auditing freigegebener Daten. So k\u00f6nnen Sie Datenbest\u00e4nde vertrauensvoll mit Lieferanten und Partnern teilen, damit Unternehmensabl\u00e4ufe besser koordiniert und Sicherheits- und Compliance-Anforderungen zuverl\u00e4ssig erf\u00fcllt werden. Die Integration mit f\u00fchrenden L\u00f6sungen und Plattformen erm\u00f6glichen es Ihnen, freigegebene Daten aus den Tools Ihrer Wahl zu visualisieren, abzufragen und anzureichern und eine ordnungsgem\u00e4\u00dfe Governance zu gew\u00e4hrleisten.Performance in LichtgeschwindigkeitDank Apache Spark\u2122 unter der Haube liefert Delta Lake Skalierung und Verarbeitung in rasanter Geschwindigkeit. Und weil Delta Lake mit leistungsstarken Funktionen optimiert wurde \u2013 beispielsweise einer Indizierung \u2013, werden ETL-Workloads nach Angaben unserer Kunden jetzt um bis zu 48 % schneller ausgef\u00fchrt.Offen und agilAlle Daten in Delta Lake werden im offenen Apache Parquet-Format gespeichert. So k\u00f6nnen die Daten von jedem kompatiblen Reader gelesen werden. Auch die APIs sind offen und kompatibel mit Apache Spark. Mit Delta Lake auf Databricks erhalten Sie Zugang zu einem riesigen Open-Source-\u00d6kosystem und vermeiden technologische Abh\u00e4ngigkeiten Ihrer Daten von propriet\u00e4ren Formaten (\u201eLock-in\u201c).Automatisiertes und vertrauensw\u00fcrdiges Data EngineeringMit Delta Live Tables wird das Data Engineering zum Kinderspiel: Noch nie war es so einfach, Daten-Pipelines f\u00fcr aktuelle und hochwertige Daten in Delta Lake zu erstellen und zu verwalten. Delta Live Tables unterst\u00fctzt Data-Engineering-Teams beim Erstellen des Lakehouse-Unterbaus. Die L\u00f6sung vereinfacht die ETL-Entwicklung und -Verwaltung durch deklarative Pipeline-Entwicklung, h\u00f6here Datenzuverl\u00e4ssigkeit und einen Produktionsbetrieb im Cloud-Ma\u00dfstab.Sicherheit und Governance im gro\u00dfen Ma\u00dfstabDelta Lake erlaubt eine hochdifferenzierte Zugriffssteuerung f\u00fcr die Daten-Governance \u2013 eine Funktionalit\u00e4t, die bei Data Lakes normalerweise nicht gegeben ist \u2013 und tr\u00e4gt so zur Risikominderung bei. Daten in Ihrem Data Lake k\u00f6nnen schnell und sorgf\u00e4ltig ge\u00e4ndert werden, um Regelungen wie etwa die DSGVO einzuhalten und durch Audit-Protokollierung eine bessere Daten-Governance zu gew\u00e4hrleisten. Diese Funktionen sind in Databricks als Bestandteil des Unity-Katalogs \u2013 des ersten Multicloud-Datenkatalogs f\u00fcr das Lakehouse \u2013 nativ integriert und erweitert.Anwendungsf\u00e4lleBI f\u00fcr Ihre DatenF\u00fchren Sie Business-Intelligence-Workloads direkt auf Ihrem Data Lake aus, um neue Echtzeitdaten sofort f\u00fcr die Abfrage durch Data Analysts bereitzustellen und aktuellste Erkenntnisse zu Ihrem Unternehmen zu gewinnen. Mit Delta Lake k\u00f6nnen Sie eine Multicloud-Lakehouse-Architektur betreiben, die Data-Warehousing-Leistung zum g\u00fcnstigen Data-Lake-Preis bietet. Profitieren Sie von einem bis zu 6-mal besseren Preis-Leistungs-Verh\u00e4ltnis f\u00fcr SQL-Workloads im Vergleich zu herk\u00f6mmlichen Cloud-Data-Warehouses.Mehr InformationenBatch und Streaming zusammenf\u00fchrenVergessen Sie komplexe und redundante Systeme oder betriebliche Herausforderungen: F\u00fchren Sie Batch- und Streaming-Operationen ganz unkompliziert auf derselben vereinfachten Architektur aus. In Delta Lake ist eine Tabelle sowohl Batch-Tabelle als auch Streaming-Quelle und -Senke. Ob Erfassung von Streaming-Daten, zeitlich versetzter Batch-Abgleich oder interaktive Abfragen: Alles funktioniert von Anfang an erwartungsgem\u00e4\u00df und mit direkter Integration in Spark Structured Streaming.Gesetzliche Anforderungen erf\u00fcllenDelta Lake beseitigt s\u00e4mtliche Probleme beim Erfassen fehlerhaft formatierter Daten, beim Compliance-bedingten L\u00f6schen von Daten und beim \u00c4ndern von Daten f\u00fcr die Daten\u00e4nderungserfassung (Change Data Capture, CDC). Dank Unterst\u00fctzung von ACID-Transaktionen an Ihrem Data Lake sorgt Delta Lake daf\u00fcr, dass jede Operation entweder vollst\u00e4ndig abgeschlossen oder \u2013 f\u00fcr sp\u00e4tere Wiederholungen \u2013 vollst\u00e4ndig zur\u00fcckgenommen wird, ohne dass neue Daten-Pipelines erstellt werden m\u00fcssten. Au\u00dferdem zeichnet Delta Lake alle vergangenen Transaktionen an Ihrem Data Lake auf. Das macht den Zugriff auf fr\u00fchere Versionen Ihrer Daten zum Kinderspiel und erlaubt die zuverl\u00e4ssige Erf\u00fcllung von Compliance-Standards wie DSGVO und CCPA.Netzwerk zur DatenaufnahmeSchnelles und zuverl\u00e4ssiges Einlesen von Daten aus allen Anwendungen, Datenbanken und Dateispeichern in Delta Lake \u2013 dank nativer KonnektorenKunden\u201eDank Databricks konnten wir unsere Time-to-Market deutlich reduzieren und bekamen genau die Analysefunktionen und den betrieblichen Schub, die wir brauchten, um den aktuellen Anforderungen im Gesundheitswesen gerecht zu werden.\u201c\n\u2013 Peter James, Chief Architect, Healthdirect AustraliaMehr Informationen\u201eAllein durch den Einsatz von Databricks und Delta Lake konnten wir Daten bereits umfassend demokratisieren und gleichzeitig die Kosten f\u00fcr die Ausf\u00fchrung von Produktions-Workloads um 60\u00a0% senken. So haben wir mehrere Millionen Dollar eingespart.\u201c\n\u2013 Steve Pulec, Chief Technology Officer, YipitDataMehr Informationen\u201eDelta Lake bietet ACID-Funktionen, mit denen sich der Betrieb von Daten-Pipelines vereinfachen l\u00e4sst. Dadurch konnten wir die Zuverl\u00e4ssigkeit der Pipelines und die Datenkonsistenz verbessern. Gleichzeitig erm\u00f6glichen Funktionen wie Caching und Auto-Indizierung einen effizienten und leistungsstarken Zugriff auf die Daten.\u201c\n\u2013 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearMehr Informationen\u201eDank Delta Lake konnten wir die Verwaltung unserer Daten-Pipelines verschlanken. Das hat zur Senkung der Betriebskosten beigetragen und gleichzeitig die Time-to-Insight f\u00fcr nachgelagerte Analytik und Data Science beschleunigt.\u201c\n\u2013 Parijat Dey, Assistant Vice President of Digital Transformation and Technology, Viacom18Mehr InformationenRessourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu den Vorteilen von Data Engineering in Databricks.\nRessourcen erkundenE-BooksDas gro\u00dfe Buch der Anwendungsf\u00e4lle f\u00fcr das Data EngineeringDaten, Analysen und KI-GovernanceGrundlagen der Datenverwaltung kennenlernen\u201eErrichten eines Data Lakehouse\u201c von Bill Inmon, dem Vater des Data WarehouseTech Talks und SchulungenErste Schritte mit Delta Lake \u2013 Tech Talk-ReiheWebinareThe Good, The Bad & The UglyVertiefende Beschreibung von Lakehouse mit Delta LakeM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENDelta Lake-DokumentationProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/it\/product\/machine-learning","text":"Databricks Machine Learning | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWMachine LearningAccelera i progetti AI con un approccio al Machine Learning incentrato sui datiProva gratuitaProgramma una demo\nCostruite il vostro modello di lingua grande come Dolly\n26 April, 2023 | 9:00AM BST I 10AM CEST\nRegistratiUn approfondimento sul Machine Learning in DatabricksManaged MLFlowModel RegistryRuntime MLNotebook collaborativiFeature StoreAutoMLIntelligenza artificiale spiegabileRepositoryMonitoraggio di modelliModel ServingBasato su un'architettura lakehouse aperta, Databricks Machine Learning consente ai team ML di preparare ed elaborare dati, snellisce la collaborazione fra i team e standardizza tutto il ciclo di vita ML, dalla sperimentazione alla produzione.Oltre 6 milioni di dollari risparmiatiCONA Services usa Databricks per l'intero ciclo di vita del ML per ottimizzare la supply chain per centinaia di migliaia di negozi.Maggiori informazioni3,9 milioni di real risparmiatiVia sfrutta il machine learning per fare previsioni accurate della domanda, riducendo i costi di elaborazione del 25%.Maggiori informazioniOltre 50 milioni di dollari risparmiatiAmgen migliora la collaborazione nella data science per accelerare la scoperta di farmaci e ridurre i costi operativi.Maggiori informazioniSemplificare tutti gli aspetti dei dati per il MLPoich\u00e9 Databricks ML \u00e8 basato su una piattaforma lakehouse aperta con Delta Lake, il team di machine learning potr\u00e0 accedere, esplorare e preparare qualsiasi tipo di dati in qualsiasi quantit\u00e0. Le feature possono essere trasformate in pipeline di produzione con una modalit\u00e0 self-service senza dipendere dagli ingegneri dei dati.Automatizzare il tracciamento e la governance degli esperimentiManaged MLflow traccia automaticamente gli esperimenti e registra parametri, metriche, versioni di dati e codice, oltre agli artefatti dei modelli a ogni ciclo di addestramento. Si possono visualizzare velocemente cicli precedenti, confrontare i risultati e riprodurre un risultato passato, secondo necessit\u00e0. Una volta individuata la versione migliore di un modello per la produzione, il modello pu\u00f2 essere registrato nel Model Registry per semplificare i passaggi di consegne lungo tutto il ciclo di vita dello sviluppo.Gestisci l'intero ciclo di vita del modello, dai dati alla produzione... e ritornoUna volta registrati, i modelli addestrati possono essere gestiti in maniera collaborativa lungo tutto il ciclo di vita con Model Registry. Si possono gestire diverse versioni e i modelli possono passare attraverso diversi stadi, ad esempio sperimentazione, staging, produzione e archiviazione. La gestione del ciclo di vita si integra con i flussi di lavoro di approvazione e governance, con controlli di accesso basati sui ruoli. Commenti e notifiche via mail offrono un ambiente di collaborazione ricco per i team di gestione dei dati.Implementare modelli ML su larga scala con bassa latenzaImplementa modelli con un solo clic senza preoccuparti di gestione del server o vincoli dimensionali. Databricks consente di implementare i modelli come endpoint di API REST ovunque, con disponibilit\u00e0 in tutta l'impresa.Componenti del prodottoNotebook collaborativiI notebook di Databricks supportano in modo nativo Python, R, SQL e Scala, consentendo ai professionisti di lavorare insieme con i linguaggi e le librerie preferiti, per scoprire, visualizzare e condividere informazioni approfondite e dettagliate.Maggiori informazioniRuntime Machine LearningAccesso con un solo clic a cluster preconfigurati ottimizzati per ML, sostenuti da una distribuzione scalabile e affidabile dei framework ML pi\u00f9 popolari (come PyTorch, TensorFlow e scikit-learn), con ottimizzazioni integrate per prestazioni impareggiabili su larga scala.Maggiori informazioniFeature StoreFacilita il riutilizzo di feature con una ricerca basata sulla loro provenienza, che sfrutta automaticamente le sorgenti di dati registrati. Le feature possono essere messe a disposizione per addestramento e serving con un'implementazione semplificata del modello che non richiede modifiche all'applicazione client.Maggiori informazioniAutoMLTutti gli utenti, dagli esperti di ML ai \"citizen data scientist\", possono contare su un approccio trasparente ad AutoML, che non solo offre il modello con le migliori prestazioni, ma genera anche codice per ulteriori perfezionamenti da parte degli esperti.Maggiori informazioniManaged MLFlowBasato su MLflow (la principale piattaforma open-source al mondo per il ciclo di vita ML), Managed MLflow accompagna velocemente i modelli ML dalla sperimentazione alla produzione, con volumi e livelli di sicurezza e affidabilit\u00e0 elevati.Maggiori informazioniServizio di modelli in produzioneSi possono servire modelli su qualsiasi scala con la semplicit\u00e0 di un clic, con l'opzione di sfruttare il calcolo serverless.Maggiori informazioniMonitoraggio di modelliLe prestazioni dei modelli possono essere monitorate, verificando come incidono sulle metriche di business in tempo reale. Databricks offre visibilit\u00e0 a 360 gradi e ricostruisce la provenienza dei modelli in produzione risalendo ai sistemi di dati sorgente, aiutando ad analizzare la qualit\u00e0 dei modelli e dei dati lungo tutto il ciclo di vita ML ed evidenziando eventuali problemi prima che producano danni rilevanti.Maggiori informazioniRepositoryCon Repos, gli ingegneri possono seguire i flussi di lavoro Git in Databricks, consentendo ai team di gestione dei dati di sfruttare flussi di lavoro CI\/CD automatizzati e portabilit\u00e0 del codice.Maggiori informazioniMigrazione a DatabricksStanco dei silos di dati, della lentezza e dei costi esorbitanti di sistemi obsoleti come Hadoop e i data warehouse aziendali? Migra a Databricks Lakehouse, la piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI.Migrazione a DatabricksRisorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video su data science e machine learning.\nEsplora risorseeBookThe Big Book of MLOpsScopri la nuova soluzione Delta SharingGuida alla migrazione: da Hadoop a DatabricksDemo e blogScopri le soluzioni Databricks Machine Learning5 mosse fondamentali per una migrazione efficace da Hadoop all'architettura lakehouseEventi virtualiAutoML: Machine Learning rapido e semplificato per tuttiEvento virtuale MLOps: Standardizing MLOps at ScaleAutomatizzare il ciclo di vita ML con Databricks Machine LearningEvento virtuale MLOps \u201cOperationalizing Machine Learning at Scale\u201dCostruire piattaforme di Machine LearningDelta Lake: la tecnologia alla base del LakehouseGuida passo-passo alla migrazione da HadoopPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/de\/partnerconnect","text":"Partner Connect | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWPartner ConnectEntdecken und integrieren Sie Daten, Analysen und KI-L\u00f6sungen ganz unkompliziert in Ihr LakehouseDemos ansehenPartner Connect macht es Ihnen leicht, Daten-, Analyse- und KI-Tools direkt auf der Databricks-Plattform zu entdecken \u2013 und L\u00f6sungen, die Sie bereits nutzen, im Handumdrehen zu integrieren. Mit Partner Connect ist die Tool-Integration mit nur wenigen Klicks erledigt, und Sie haben die Funktionalit\u00e4t Ihres Lakehouse im Handumdrehen erweitert.Daten- und KI-Tools mit dem Lakehouse vernetzenVerbinden Sie Ihre bevorzugten Daten- und KI-Tools kinderleicht mit dem Lakehouse und nutzen Sie Analyseanwendungen aller ArtEntdecken Sie validierte Daten und KI-L\u00f6sungen f\u00fcr neue Anwendungsf\u00e4lleEin zentraler Anlaufpunkt f\u00fcr gepr\u00fcfte Partnerl\u00f6sungen, damit Sie Ihre n\u00e4chste Datenanwendung schneller erstellen k\u00f6nnenMit ein paar Klicks eingerichtet dank vorgefertigter IntegrationenPartner Connect vereinfacht Ihre Integrationen durch die automatische Konfiguration von Ressourcen wie Clustern, Token und Verbindungsdateien f\u00fcr eine Verbindung mit Partnerl\u00f6sungenIhr Einstieg als PartnerDatabricks-Partner sind ideal positioniert, um Kunden schneller Analyseerkenntnisse zu liefern. Nutzen Sie die Entwicklungs- und Partnerressourcen von Databricks, um gemeinsam mit unserer offenen, Cloud-basierten Plattform zu wachsen.Partner werden\u201ePartner Connect baut auf unserer langj\u00e4hrigen Partnerschaft auf und erm\u00f6glicht es uns, eine integrierte Erfahrung f\u00fcr unsere Unternehmen und Kunden zu schaffen. Mit Partner Connect bieten wir ein ma\u00dfgeschneidertes Erlebnis, das es vielen Tausend Databricks-Kunden einfacher denn je macht, Erkenntnisse aus ihren Daten zu gewinnen, zus\u00e4tzliche Analyseanwendungen zu entdecken und schneller Mehrwert aus ihrem Lakehouse zu generieren \u2013 einfach dadurch, dass sie Hunderte von Datenquellen mit ihrem Lakehouse verbinden.\u201c\u2013 George Fraser, CEO FivetranDemosFivetranVernetzen Sie Daten aus \u00fcber 180 beliebten Anwendungen, darunter auch SaaS-Anwendungen (Salesforce, Google Analytics usw.), mit dem LakehousedbtErste Schritte mit dbt Cloud und Databricks, um Datentransformationen zu erstellenPower BIAlle Ihre Benutzer von der Leistung und Technologie von Databricks Lakehouse profitieren lassenTableauTableau Desktop mit Databricks SQL verbinden und so allen Benutzern ein Data Lakehouse f\u00fcr moderne Analysen bietenRiveryVereinfachen Sie den Weg der Daten von der Erfassung \u00fcber die Transformation bis zur Bereitstellung in Delta LakeLabelboxUnstrukturierte Daten f\u00fcr KI und Analytics im Lakehouse einfach vorbereitenProphecyErstellen und Bereitstellen von Spark- und Delta-Pipelines \u00fcber eine visuelle Drag\u00a0&\u00a0Drop-Oberfl\u00e4cheArcionDatenquellen mithilfe einer verteilten CDC-basierten Replikationsplattform mit dem Lakehouse verbindenKostenlos testenRessourcenBlogFebruar 2023 \u2013 Ank\u00fcndigung neuer Partnerintegrationen in Partner ConnectSeptember 2022 \u2013 Einf\u00fchrung neuer Partnerintegrationen in Partner ConnectJuni 2022 \u2013 Ank\u00fcndigung neuer Partnerintegrationen in Partner ConnectIhr Unternehmen mit Partner Connect auf Databricks zum Erfolg f\u00fchrenDokumentationDatabricks Partner Connect-LeitfadenM\u00f6chten Sie mehr wissen?Nutzen Sie die Entwicklungs- und Partnerressourcen von Databricks, um gemeinsam mit unserer offenen, Cloud-basierten Plattform zu wachsen.Partner werdenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alon-gubkin\/#","text":"Alon Gubkin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlon GubkinCo-Founder & CTO at AporiaBack to speakersWriting code from the age of 7, Alon has a fairly healthy obsession with programming. He\u2019s also an avid fan of all things machine learning, software architecture, video games, and biology. At the age of 17, Alon created his first successful open source project, a video chat platform for mobile. Before joining Aporia, Alon served as an R&D Lead in the elite 81 intelligence unit of the Israel Defense Forces.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/company\/contact","text":"\ubb38\uc758\ud558\uae30 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ubb38\uc758\uad50\uc721\uc774\ub098 \uc9c0\uc6d0\uc5d0 \ub3c4\uc6c0\uc774 \ud544\uc694\ud558\uc2e0\uac00\uc694?\n\uae30\ud0c0 \ub9ac\uc18c\uc2a4\ub97c \ucc38\uc870\ud558\uc138\uc694.\uad00\ub828 \ubb38\uc11cAWS, Azure \ub610\ub294 Google Cloud\uc5d0 \uad00\ud55c Databricks\uc758 \uae30\uc220 \ubb38\uc11c \uc77d\uc5b4\ubcf4\uae30Databricks \ucee4\ubba4\ub2c8\ud2f0Databricks \uc0ac\uc6a9\uc790, \uc804\ubb38\uac00\uc640 \ub17c\uc758, \uacf5\uc720\ud558\uace0 \ub124\ud2b8\uc6cc\ud0b9\ud558\uae30\uad50\uc721\uac15\uc0ac \uc8fc\ub3c4\ud615, \uc790\uae30 \uc8fc\ub3c4\ud615 \uad50\uc721\uc744 \ud1b5\ud574 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uc815\ubcf5\ud558\uac70\ub098 \uacf5\uc778 \uac1c\ubc1c\uc790 \ub418\uae30\uc9c0\uc6d0\uc774\ubbf8 \uace0\uac1d\uc774\uc2e0\uac00\uc694? \uae30\uc220\uc801 \ubb38\uc81c\ub098 \uacb0\uc81c \ubb38\uc81c\uac00 \uc0dd\uae34 \uacbd\uc6b0 \uc5ec\uae30\ub97c \ud074\ub9ad\ud558\uc138\uc694\uc9c0\uc0ac \uc704\uce58\uc138\uacc4 \uac01\uc9c0\uc758 Databricks \uc9c0\uc0ac \uc704\uce58\ub97c \ud655\uc778\ud558\uace0 \ubb38\uc758\uc9c0\uc2dd \uae30\ubc18Databricks \uc81c\ud488\uacfc \uc11c\ube44\uc2a4\uc5d0 \uad00\ud574 \uac00\uc7a5 \uc790\uc8fc \ud558\ub294 \uc9c8\ubb38\uc5d0 \ub300\ud55c \uac04\ub2e8\ud55c \ub2f5\ubcc0 \ucc3e\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/glossary\/jupyter-notebook","text":"What is a Jupyter Notebook?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWJupyter NotebookAll>Jupyter NotebookTry Databricks for freeGet StartedWhat is a Jupyter Notebook?A Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.What are Jupyter Notebooks used for?Jupyter notebooks are used for all sorts of data science tasks such as exploratory data analysis (EDA), data cleaning and transformation, data visualization, statistical modeling, machine learning, and deep learning.What are the benefits of using Jupyter Notebooks?Jupyter notebooks are especially useful for \"showing the work\" that your data team has done through a combination of code, markdown, links, and images. They are easy to use and can be run cell by cell to better understand what the code does.Jupyter notebooks can also be converted to a number of standard output formats (HTML, Powerpoint, LaTeX, PDF, ReStructuredText, Markdown, Python) through the web interface. This flexibility makes it easy for data scientists to share their work with others.How do Jupyter Notebooks work?A Jupyter notebook has two components: a front-end web page and a back-end kernel. The front-end web page allows data scientists to enter programming code or text in rectangular \"cells.\" The browser then passes the code to the back-end kernel which runs the code and returns the results.What are the downsides of using Jupyter Notebooks?Difficult to maintain and keep in sync when collaboratively working on code.Difficult to operationalize your code when using Jupyter notebooks as they don't feature any built-in integration or tools for operationalizing your machine learning models.Difficult to scale \u2014 Jupyter notebooks are designed for single-node data science. If your data is too big to fit in your computer's memory, using Jupyter notebooks becomes significantly more difficult.Are Jupyter Notebooks available on Databricks?Looking for a powerful data science collaboration tool? Look no further than Databricks! Our notebooks allow you to work together with colleagues across engineering, data science, and machine learning teams in multiple languages, with built-in data visualizations, and operationalization with jobs. Sign up for a free trial.Does Databricks offer support for Jupyter Notebooks?Yes. Databricks clusters can be configured to use the IPython kernel in order to take advantage of the Jupyter ecosystem's open source tooling (display and output tools, for example). Databricks also offers support for importing and exporting .ipynb files, so you can easily pick up right where you left off in your Jupyter notebook, on Databricks \u2014 and vice versa. Finally, Databricks has long supported the core open source Jupyter libraries within the Databricks Machine Learning Runtime.How to use the IPython kernel on DatabricksIt's easy. View the documentation, then sign up for a free trial of Databricks.\u00a0Additional ResourcesCollaborative Notebooks - DatabricksJupyterLab-Databricks Integration Bridges Local and Remote WorkflowsNotebook Gallery: Example notebooks for data science, data engineering, ML and moreBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-breese","text":"Justin Breese - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin BreeseSr. Product Manager at DatabricksBack to speakersJustin is a Product Manager at Databricks and works on areas like query processing and SQL. \nHe has a ton of interests: soccer, hiking, brewing beer, roasting coffee, and older cars. \nJustin lives in Topanga, CA with his wife and a baby boy (due in July).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/delta-live","text":"Delta Live Tables Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWorkflows & Streaming: Delta Live Tables PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorDelta Live TablesEasily ingest and transform batch and streaming data on the Databricks Lakehouse PlatformSelect planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudLoading...Compare featuresDLT Core\nDLT Core PhotonDLT Pro\nDLT Pro PhotonDLT Advanced\nDLT Advanced PhotonSQL APIPython APIStreaming TablesContinuous PipelinesAuto-Loader IntegrationObservability Metrics with Event LogTable LineageAccess Controls (ACL)Enhanced AutoscalingChange Data Capture (CDC) (link)Slowly Changing Dimension (SCD) Type 2 (Preview)Data Quality Expectation RulesData Quality Expectation PoliciesData Quality ObservabilityPhoton Engine Performance (Massively parallel processing)Optional\n(DBU emission rate 2.9x vs. non-Photon. See the Pricing calculator.)Observability Data Retention5 days\n30 days\n30 days\nGovernance and ManageabilitySee Platform Capabilities and Add-Ons for detailsEnterprise SecuritySee Platform Capabilities and Add-Ons for detailsPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements.\nCalculate priceStart free trialContact usFAQ Can I pick a different DLT Product Edition for each pipeline in my workspace?Yes. You can specify a different edition for each DLT pipeline in the pipeline settings.How do I select a DLT Product Edition for my pipeline?You will have the option to choose a DLT product edition when a pipeline is created. Simply click \u201cCreate Cluster\u201d from the Delta Live Tables page, and you will see an option to choose the DLT product edition on the subsequent window.Am I able to change the DLT Product Edition after I\u2019ve created the pipeline?Yes. You may change the DLT Edition of a pipeline at any time through the DLT settings UI.What happens if I attempt to set DLT quality expectations and my pipeline is not using the Advanced Edition?When you attempt to run a pipeline that includes features which are not included in the DLT Product Edition selected for that pipeline, you will receive an error message that will include a reason for the error. You may then modify the product edition for the pipeline to choose an edition that includes the desired feature, and attempt to re-run the pipeline.Are there any other charges associated with DLT?Yes, a DLT cluster will automatically run a periodic system-generated job to maintain the Delta Live Table that will consume DBUs at the Jobs Compute Rate.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-powers","text":"Matthew Powers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew PowersDeveloper Advocate at DatabricksBack to speakersMatthew is a Developer Advocate for Databricks on the Delta Lake team. He's a longtime Spark blogger (mungingdata.com) and Spark open-source contributor. His project include quinn, chispa, spark-daria, spark-fast-tests, and the spark-style-guide. He's passionate about Spark, Delta Lake, traveling, and learning languages.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/harrison-chase","text":"Harrison Chase - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarrison ChaseCEO at LangChainBack to speakersHarrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python\/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup), and studied stats and CS at Harvard.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si","text":"Databricks Consulting Partners - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Consulting PartnersConnect with Databricks Partners globally to help you build, deploy or migrate to the Databricks Lakehouse PlatformDatabricks Consulting Partners are experts uniquely positioned to help you implement and scale data engineering, collaborative data science, full-lifecycle machine learning and business analytics initiatives.\nThey bring technology, industry and use case expertise to help you make the most of the Databricks Lakehouse Platform. Services include designing a data transformation strategy unique to your business, data modernization and migration, data management and governance, and much more.Loading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta SharingAn open standard for secure sharing of data assetsGet StartedWatch DemoDatabricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform.Key benefitsOpen cross-platform sharingAvoid vendor lock-in, and easily share existing data in Delta Lake and Apache Parquet formats to any data platform.Share live data with no replicationShare live data across data platforms, clouds or regions without replicating or copying it to another system.Centralized governanceCentrally manage, govern, audit and track usage of the shared data on one platform.Marketplace for data productsBuild and package data products, including data sets, ML models and notebooks once and distribute anywhere through a central marketplace.Privacy-safe data cleanroomsEasily collaborate with your customers and partners on any cloud via a secure hosted environment while safeguarding data privacy.How it worksNative integration with the Databricks platformNative integration with the\u00a0Unity Catalog\u00a0allows you to centrally manage and audit shared data across organizations. This lets you confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs.Easily manage sharesCreate and manage providers, recipients, and shares with a simple-to-use UI, SQL commands or REST APIs with full CLI and Terraform supportDiscover and access data products through an open marketplaceEasily discover, evaluate and gain access to data products including data sets, machine learning models, dashboards and notebooks from anywhere, without the need to be on the Databricks platform.Privacy-safe data cleanroomsCollaborate with your customers and partners on any cloud in a privacy-safe environment. Securely share data from your data lakes without data replication. Meet collaborators on their preferred cloud and provide them the flexibility to run complex computations and workloads in any language \u2014 SQL, R, Scala, Java and Python. Guide collaborators through common use cases using predefined templates, notebooks and dashboards, accelerating time to insights.Use casesInternal line of business sharingBuild Data Mesh with Delta Sharing to securely share data with business units and subsidiaries across clouds or regions without copying or replicating the data.B2B SharingData monetizationCustomers\u201cDelta Sharing helped us streamline our data delivery process for large data sets. This enables our clients to bring their own compute environment to read fresh curated data with little-to-no integration work, and enables us to continue expanding our catalog of unique, high-quality data products.\u201d\u2014 William Dague, Head of Alternative Data\u201cAs a data company, giving our customers access to our data sets is critical. The Databricks Lakehouse Platform with Delta Sharing really streamlines that process, allowing us to securely reach a much broader user base regardless of cloud or platform.\u201d\u2014 Felix Cheung, VP of Engineering\u201cLeveraging the powerful capabilities of Delta Sharing from Databricks enables Pumpjack Dataworks to have a faster onboarding experience, removing the need for exporting, importing and remodeling of data, which brings immediate value to our clients. Faster results yield greater commercial opportunity for our clients and their partners.\u201d\u2014 Corey Zwart, Head of Engineering\u201cWith Delta Sharing, our clients can access curated data sets nearly instantly and integrate them with analytics tools of their choice. The dialogue with our clients shifts from a low-value, technical back-and-forth on ingestion to a high-value analytical discussion where we drive successful client experiences. As our client relationships evolve, we can seamlessly deliver new data sets and refresh existing ones through Delta Sharing to keep clients appraised of key trends in their industries.\u201d\u2014 Anup Segu, Data Engineering Tech LeadAn open ecosystemAccess the latest published version directly from the provider in easy-to-use SQL, Python or BI tools.ResourcesKeynote and Webinar[Keynote] Data Governance and sharing on the lakehouse at Data + AI Summit 2022[On-demand Webinar] Accelerate Business Value With Delta SharingBlogsAnnouncing General Availability of Delta SharingIntroducing Delta Sharing: An Open Protocol for Secure Data SharingTop Three Data Sharing Use Cases With Delta SharingSolution Sheet & eBook[eBook] Explore the new Delta Sharing SolutionDelta Sharing: An open standard for secure data sharingRise of the Data Lakehouse by Bill Inmon, father of the data warehouseReady to get started with Databricks?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the \u201cPlatform Services\u201d), which are subject to the\u00a0Databricks Terms of Service\u00a0(or with respect to the Community Edition, the\u00a0Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (\u201cDatabricks\u201d) and our subscribers (\u201cSubscribers\u201d) (any such agreement, a \u201cServices Agreement\u201d).PLEASE READ CAREFULLY THESE TERMS AND THE\u00a0DATABRICKS PRIVACY POLICY\u00a0(\u201cPRIVACY POLICY\u201d) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gregory-little\/#","text":"Gregory Little - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGregory LittleDCDAO for Enterprise Platforms and Business Optimization at DoD CFO Transformation OfficeBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/glossary\/data-governance","text":"What Is Data Governance? A Comprehensive Guide | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData GovernanceA comprehensive guide to the processes, policies and tech that organizations use to manage and get the most from their dataDownload free eBookIntroductionWhat is data governance?Data governance is a comprehensive approach that comprises the principles, practices and tools to manage an organization\u2019s data assets throughout their lifecycle. By aligning data-related requirements with business strategy, data governance provides superior data management, quality, visibility, security and compliance capabilities across the organization. Implementing an effective data governance strategy allows companies to make data easily available for data-driven decision-making while safeguarding their data from unauthorized access, and ensuring compliance with regulatory requirements.What are the business benefits of data governance?Data governance is essential for unlocking the value of data, which is a critical asset for organizations. By implementing a robust data governance approach, businesses can leverage their data assets, gain a competitive edge, and earn and maintain customer trust by ensuring sound data and privacy practices.Increased operational efficiency and reduced costsEffective data governance allows organizations to create a single source of truth for their data estate, preventing data sprawl and silos, and reducing duplication. This leads to increased efficiency, reduced costs and easier management of security and governance concepts across the data estate.Improved productivity and faster decision-makingData governance promotes data democratization by ensuring data accuracy, consistency, and trustworthiness. It helps data users find high-quality data quickly, promoting a better understanding of the data\u2019s meaning and context, leading to increased productivity and faster decision-making.Enhanced collaboration and value realizationA strong data governance program lays the foundation for enhanced data collaboration and sharing across teams, business units, and partners. This helps organizations promote knowledge sharing and build a better data culture, leading to increased innovation, better decision-making, and maximizing the value of their data.Enhanced security and privacyData governance mitigates security and privacy risks by implementing controls and processes to prevent unauthorized access and misuse of sensitive data. It promotes a culture of trust and transparency with stakeholders.Better compliance with regulations and standardsEffective data governance results in better compliance with regulatory requirements, such as HIPAA, FedRAMP, GDPR or CCPA. This protects the organization\u2019s reputation, avoids potential financial and legal consequences, and increases stakeholder trust.Key elements of data governanceData catalogingEffective data governance requires knowledge of the data that exists within an organization. This is where a data catalog comes in, as it provides a centralized metadata repository for an organization\u2019s data assets. A data catalog allows stakeholders to quickly discover, understand and access the data they need, improving data-related activities such as discovery, governance and analytics. It acts as a searchable index of all the data available, including information about its format, structure, location and usage, providing semantic value to an otherwise unidentifiable sea of information. Incorporating a data catalog into a governance program can help organizations improve their data management, enhance collaboration, reduce redundancy and ensure proper access controls and audit information retrieval.\u00a0Data qualityIn today\u2019s data-driven world, ensuring high data quality is crucial for accurate analytics, informed decision-making and cost-effectiveness. Data quality directly impacts the reliability of data-driven decisions and is a key aspect of data governance. To maintain effective data governance, organizations must prioritize the evaluation of key data quality attributes such as accuracy, completeness, freshness and compliance with data-quality rules. Therefore, a strong focus on data quality is essential in any data governance strategy, as it helps trace data lineage, enforce data quality rules, and track changes. Don\u2019t let poor data quality compromise your business decisions and resource allocation \u2014 prioritize data quality as a critical part of your data governance efforts for better outcomes.\u00a0Data classification\u00a0Data classification is a crucial part of data governance that involves organizing and categorizing data based on its sensitivity, value and criticality. With the exponential growth of data, businesses are increasingly concerned about protecting sensitive data, mitigating risks and ensuring data quality. Classification allows organizations to identify and classify data based on its risk level and importance, allowing them to apply appropriate security measures and policies. A robust data classification system enhances data governance, reduces risks and ensures data quality and protection at scale.\u00a0Data securityOrganizations understand the significance of granting high-quality data access to their teams to drive insights and business value, while prioritizing sensitive data protection against unauthorized access. Effective data access management is crucial for data security and governance, and a good data security governance program should include access controls that define which groups or individuals can access what data. These controls can be highly specific, down to the individual record or file. As data breaches and regulations such as GDPR and CCPA pose increased risks, businesses must establish clear governance policies that define who can access sensitive data sets and how to track any misuse. Unauthorized access to private or sensitive information should not occur, and implementing effective access management strategies is essential to safeguard data and maintain customer trust.\u00a0Auditing data entitlements and accessEffective data access auditing is a critical aspect of data governance and security governance programs, particularly in regulated industries. By understanding who has access to what data and tracking recent access, organizations can proactively identify overentitled users or groups and adjust their access accordingly, minimizing the risk of data misuse. Without proper audit mechanisms in place, an organization may not be fully aware of their risk surface area, leaving them vulnerable to data breaches and regulatory noncompliance. Therefore, a well-designed audit team within a data governance or security governance organization plays a key role in ensuring data security and compliance with regulations such as GDPR and CCPA. By implementing effective data access auditing strategies, organizations can maintain the trust of their customers and protect their data from unauthorized access or misuse.\u00a0Data lineageData lineage is a powerful tool that helps organizations ensure data quality and trustworthiness by providing a better understanding of data sources and consumption. It captures relevant metadata and events throughout the data\u2019s lifecycle, providing an end-to-end view of how data flows across an organization\u2019s data estate. As an essential pillar of a pragmatic data governance strategy, data lineage enables organizations to become compliant and audit-ready while reducing the operational overhead of creating audit trails manually, and providing trusted sources for audit reports. Additionally, data lineage empowers data consumers to perform better analyses, and helps data teams perform root cause analysis of any errors, significantly reducing debugging time.\u00a0Data discoveryAs organizations continue to gather massive amounts of data from various sources, it\u2019s becoming increasingly important to make this data easily discoverable for analytics, AI or ML use cases. This is critical to accelerate data democratization and unlock the true value of the data. Furthermore, with the emergence of modern data assets like dashboards, machine learning models, queries, libraries and notebooks, data discovery has become a key pillar of a robust data governance strategy. Organizations should view data discovery as a fundamental aspect of their data governance strategy. It enables data teams to easily locate data assets across the organization, collaborate on various projects, and innovate quickly and efficiently. This helps to prevent data duplication, which can be problematic as it costs money to persist them, and may lead to governance challenges at different security levels.\u00a0Data sharing and collaboration\u00a0Data sharing and collaboration are vital components in today\u2019s business environment, with organizations exchanging data with internal teams, external partners, and customers across multiple clouds, data platforms and regions. As the demand for external data continues to grow, it is critical for organizations to securely exchange data while maintaining control and visibility over how their sensitive information is used. Data cleanrooms play a critical role in secure and controlled data collaboration, ensuring that data privacy regulations are upheld. It is essential for organizations to invest in open format, interoperable and multicloud data sharing technologies to meet their data-driven innovation needs. Moreover, data marketplaces serve as a bridge between data providers and consumers, facilitating the discovery and distribution of data sets. Therefore, it is crucial to recast data sharing as a business necessity and a crucial pillar of a robust data governance strategy.What does a good data governance solution look like?Data-forward organizations prioritize data, analytics and AI to drive business outcomes, and build their data strategies around a data lakehouse architecture, which unifies data, analytics and AI on a single platform. This architecture combines the best features of data warehouses and data lakes to handle all data, analytics and AI use cases. All data is stored in a cloud data lake and managed by a unified layer, allowing analytics to be performed directly on a single copy of the data. This approach simplifies data governance and security, reduces functional silos and makes collaboration easier. By instilling high trust in data, organizations can operate with confidence and better understand how data is acquired, changed, used and impacted across every analytics workload.A data governance solution for a data lakehouse provides a number of key capabilities:Centralized data catalog: A centralized data catalog stores all your data, ML models and analytics artifacts as well as metadata for each object. The unified catalog also blends in data from other catalogs such as an existing Hive metastore.Unified data access controls: A single and unified permissions model across all assets and all clouds. This includes attribute-based access control (ABAC) for personally identifiable information (PII).Data auditing: Data access is centrally audited with alerts and monitoring capabilities to promote accountability and securityData quality management: Robust data quality management with built-in quality controls, testing, monitoring and enforcement to ensure accurate and useful data is availableData lineage: Data lineage to get end-to-end visibility into how data flows in the lakehouse, from source to consumption, down to the column levelData discovery: Easy data discovery to enable data scientists, analysts, engineers and stakeholders to quickly discover and reference relevant data and accelerate time to valueData sharing and collaboration: Data can be shared \u2014 with fine-grained access controls \u2014 across clouds, regions and platforms, preventing silos from formingData cleanrooms for privacy-safe collaboration: Collaborate on sensitive data with internal or external stakeholders in a privacy preserving environmentOpen marketplace for data, analytics and AI: Discover, access and deploy data sets, as well as AI and analytical assets \u2014 such as ML models, notebooks, applications\u00a0and dashboards \u2014 without proprietary platform dependencies, complicated ETL\u00a0or expensive replication.Who oversees data governance?Chief Data OfficerYour Chief Data Officer (CDO) is the most senior executive on your governance team. Ultimately, they\u2019re responsible for your data\u2019s security, accessibility and usability.A CDO\u2019s role involves setting the system up, securing funding and staff for its operation (and for related aspects like tools to automate some processes), and performing regular checks on its overall status.Data ownersData owners are individuals or teams responsible for the technical administration of your data sets. They might make decisions on which team members should have access to which kinds of information. If their policies (or lack thereof) lead to a data breach, they could be held accountable.To fulfill this role and its many responsibilities, data owners are typically also senior members of your organization.Data stewardsTo assist in the day-to-day running of your data governance workflows, data owners and CDOs will appoint data stewards. Data stewardship essentially involves implementing the program that has been set out for them, and ensuring both old and new data is managed appropriately. They\u2019re responsible for monitoring compliance from both employees and customers, and escalating issues if they arise.Data governance committeesThis committee will be the main body that creates relevant policies in your organization.Often, it will consist of senior executives and data owners, who have a keen interest in the security and usability of data. Once their policies have been approved, they may set out procedures for stewards to follow, and also resolve disputes between parties.What is the difference between data management and data governance?Effective data management and data governance are crucial for any organization that handles data. Despite the frequent interchangeable use of these terms, they have distinct differences. Data management focuses on the technical aspects of data lifecycle management, including data ingestion, integration, organization, transformation and persistence, such as backup, retrieval and archiving. In contrast, data governance is about defining organizational policies, frameworks and tools to ensure that data-related requirements are aligned with the business strategy. This includes data accuracy, consistency, compliance with regulations, and internal organizational policies as well as data quality, security, privacy, auditing and risk management. Furthermore, data governance involves defining data ownership, roles and responsibilities, and enforcing policies and procedures throughout the organization. As a key pillar of a long-term data strategy that leverages data as a strategic asset, data governance plays a significant role, while data management deals with the operational aspect of delivering on that strategy.Learn more about data governance and data sharing on DatabricksUnity CatalogData SharingDatabricks MarketplaceCleanroomsFAQWhat are the main steps of data governance?The principal steps required include:Identifying all sources of dataPreparing metadata for the data and organizing a metadata storage optionSetting up mechanisms to track data lineage for data flow and usageScanning for sensitive data in your data estateCreating a governance framework, with set policies and procedures for the various overseersChecking the framework\u2019s compliance with relevant regulatory instrumentsPerforming data quality checks by creating a rules library that is centrally managed and versioned. Update the rules library periodically with new rules.Regularly audit data entitlements and access to ensure complianceIdentifying further risks, such as lack of data security or excess access to sensitive data setsSecuring the go-ahead from the senior executive team and data governance committeeHiring or training essential staff members, such as data stewardsEstablishing a means of data distribution, so everyone in your organization can locate the centralized data catalogHaving regular reviews with senior executives (inviting team member feedback)Constantly adapting the governance model, such as when new data sets are introducedOften, the CDO would begin creating a framework to follow these steps, with additional actors assisting them as the project grows in size.What are some basic data governance principles?Several principles are associated with sound data governance. These ideas developed in the field of data ethics and, today, many are enshrined in regulatory laws. Here are three of the most important:Accountability: This is important from two perspectives. First, you need accountability when setting up and maintaining a data governance framework. Each agent, steward and owner must know what their task is and how they can perform it. Second, if something does go wrong, there must be a clear process for holding that individual\/team to account and ensuring it does not happen again.Standardization: Understanding and following regulatory laws is key to creating a successful strategy. These rules on data security and storage should be followed by businesses as standard practice to ensure your data framework may operate universally across legal jurisdictions.Transparency: Data governance has everything to do with managing other people\u2019s data, such as your employees, clients or customers. You must make it clear to everyone what your policies are, what data is collected and why.What is at the core of data governance?As an organization, the democratization of data, analytics and AI is at the core of data governance. It\u2019s about making data accessible \u2014 and usable \u2014 throughout your organization, without compromising on quality or security. Your clients and customers should have full confidence that their information is kept in accordance with regulations, while your teams can make the best use of all the data you\u2019ve gathered. This blend of accessibility and security is at the heart of data governance.ResourcesKeynoteData Governance and Sharing on the Lakehouse at Data + AI Summit 2022WebinarHow to Simplify Data and AI GovernanceeBooksData, Analytics and AI GovernanceA New Approach to Secure Data SharingProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2023\/02\/16\/announcing-new-partner-integrations-databricks-partner-connect.html","text":"Announcing New Partner Integrations in Databricks Partner Connect - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing New Partner Integrations in Databricks Partner ConnectFive additional, validated partner solutions enhance the capabilities of your lakehouseby Riley Maris, Zaheera Valani and Maraki KetemaFebruary 16, 2023 in Platform BlogShare this postNew year, new integrations to announce! We're excited to introduce five new additions to Databricks Partner Connect\u2013 a centralized portal to help you find and integrate data, analytics, and AI solutions with your Lakehouse. We're happy to share that we've added our first partners for both the Data Governance and Data Security categories in Partner Connect! We are also continuing to add Data Ingestion, Semantic Layer and BI and Visualization partners. This reinforces our commitment to providing innovative partner solutions that extend the breadth and depth of the Databricks Lakehouse Platform through Partner Connect.Learn more about these five new integrations below!Data SecurityPrivacera\nPrivacera is a unified Data Security Platform that integrates sensitive data discovery, masking, encryption, compliance workflow, audit, and fine-grained data access control across the Databricks Lakehouse Platform, including Unity Catalog and Databricks SQL. Privacera's new connector to Unity Catalog enables customers to manage data access, including integration with IAM solutions for attribute-based access control (ABAC), data tags for tag-based access control (TBAC), file and object level access control, dynamic row level filtering, as well as column level data access, masking, and encryption. These features enable consistent and simplified access and security policies to be applied across Databricks workspaces. Learn more about the Privacera and Databricks partnership here.Data Governanceerwin by Quest\nerwin by Quest provides the tools needed to help you fast-track your Databricks migration, design and optimize the lakehouse data models you employ, and efficiently catalog and govern data across multiple data platforms. Use erwin Data Modeler by Quest to auto-convert legacy data models for use in Databricks and quickly design and evolve new Lakehouse data models using market-leading data modeling capabilities like model comparison. Ingest Databricks metadata from Databricks Unity Catalog into the erwin Data Catalog to auto-document end-to-end data lineage and gain data quality visibility, impact analysis and more across your data landscape. Enrich collected metadata with business context and governance, and deliver business-friendly data discovery, data literacy and risk compliance across your organization. Learn more about using erwin by Quest here.Data IngestionHevo Data\nAutomate and simplify your data integration process with Hevo Data. This no-code, user-friendly ELT platform helps you set up reliable data pipelines for your Databricks Lakehouse in minutes, with access to 150+ plug-and-play connectors, including popular SaaS applications, business tools, and databases. With Hevo Data, your team saves hours of engineering time and enjoys access to advanced ELT features like automated schema mapping, change data capture, post-load transformations, and more. You can now deliver data to your business team in near real-time! Sign up for a free trial today.BI and visualizationSigma\nSigma is a cloud-native exploratory analytics platform with a familiar spreadsheet-like interface. Today, approximately one billion people use spreadsheets monthly. Sigma breaks down data silos and enables data teams and business analysts to align around a unified data language. Sigma leverages the Databricks SQL Driver for Go and lets users connect to the Databricks Lakehouse Platform in seconds, accelerating time to insight and removing language barriers between data and business teams. Learn more about the integration here.Semantic LayerAtScale\nAtScale enables smarter decision-making by accelerating the flow of data-driven insights. The AtScale semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across all industries. With AtScale, customers are empowered to democratize data, implement self-service BI, and build a more agile analytics infrastructure for better, more impactful decision-making. Get started with AtScale on Databricks via Partner Connect, including an interactive getting-started guide available exclusively on Databricks Partner Connect. To learn more about the AtScale and Databricks partnership, watch this on-demand webinar.Customer spotlightGreenland Capital Management improves financial analysis using Sigma and Databricks in its modern data stackGreenland Capital Management, a small hedge fund, uses Sigma for its speed, scale and ease of use. One of Greenland's main decision criteria included data self-service to create live dashboards, P&L calculations, and most importantly, ensuring strong data governance across the organization. The Databricks and Sigma integration further enabled the data science team to access real-time data faster, securely, and more accurately, enabling improved financial modeling.\"Greenland has been thoughtful in its approach to its data stack. We needed a platform to bridge the gap between our data warehouse, our data catalog, and, ultimately, the analysis we do on a day-to-day basis. Partnering with Databricks and Sigma allowed us to organize, explore and analyze our data in order to deliver data outputs for general consumption.\"\n- Nan Xiao, Chief Technology Officer at Greenland Capital ManagementGet started with Partner ConnectSign up for a free trial of Databricks to try Partner Connect at no additional cost, and keep an eye out as we unveil more integrations in the coming months.Try Databricks for freeGet StartedRelated postsLaunching dbt Cloud in Databricks Partner ConnectApril 14, 2022 by Bilal Aslam, Hiral Jasani, Shant Hovsepian, Dave Eyler, Daniel Rosenthal and Bemnet Merha in Partners\nWe are delighted to announce that dbt Cloud, the fastest and most reliable way to build, manage and monitor dbt projects, is now...\nBuild Your Business on Databricks With Partner ConnectNovember 18, 2021 by Dave Eyler, Pankaj Dugar and Zaheera Valani in Platform Blog\nAt Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and...\nAnnouncing New Partner Integrations in Partner ConnectJune 15, 2022 by Hiral Jasani, Bilal Aslam, Zaheera Valani and Katie Cummiskey in Company Blog\nWe are excited to announce six new integrations in Databricks Partner Connect. Our expanding partnerships enable our users to integrate the freshest data...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/careers","text":"Offres d'emploi chez Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Offres d'emploi chez DatabricksNotre mission\u00a0: aider les \u00e9quipes data \u00e0 r\u00e9soudre les probl\u00e8mes les plus complexes au monde. Voulez-vous nous rejoindre\u00a0?Voir les postes ouverts OverviewCultureBenefitsDiversityStudents & new gradsFaites passer votre carri\u00e8re au niveau sup\u00e9rieur. Misez sur l'avenir.Databricks est \u00e0 la pointe de la r\u00e9volution des donn\u00e9es et de l'IA. Nous avons cr\u00e9\u00e9 une nouvelle cat\u00e9gorie, le lakehouse. Et aujourd'hui, des milliers d'entreprises l'utilisent pour r\u00e9soudre des probl\u00e8mes comme le changement climatique, la fraude, la perte de client\u00e8le et bien d'autres encore. Si vous \u00eates en qu\u00eate d'une opportunit\u00e9 qui pourrait r\u00e9ellement marquer votre carri\u00e8re, vous avez trouv\u00e9.Pourquoi l'avenir est au lakehousePourquoi choisir Databricks\u00a0?Nous nous d\u00e9veloppons rapidement et nous recrutons les meilleurs talents au monde. Nous sommes les Bricksters \u2013 uniques, intelligents, curieux et vifs. Demandez \u00e0 un Brickster ce qu'il appr\u00e9cie dans son travail, et vous entendrez probablement parler de notre culture.D\u00e9couvrez les principes de notre culture d'entrepriseTrouvez votre \u00e9quipeAdministrationD\u00e9veloppement commercialSucc\u00e8s clientIng\u00e9nierieIng\u00e9nierie de terrainFinanceITJuridiqueMarketingOp\u00e9rationsRHProduitServices professionnelsRecrutementVentesS\u00e9curit\u00e9Stages et d\u00e9but de carri\u00e8reAvantages et travail hybridePour donner le meilleur de vous-m\u00eame au travail, votre sant\u00e9 et votre bien-\u00eatre sont essentiels. C'est pourquoi nous offrons une attractive palette d'avantages et proposons des pratiques de travail flexibles. L'important est que vous trouviez ce qui fonctionne le mieux pour vous et votre \u00e9quipe.D\u00e9couvrez nos avantagesDiversit\u00e9, \u00e9galit\u00e9 et inclusionNous avons la conviction que la diversit\u00e9 des parcours, des perspectives et des comp\u00e9tences est le moteur de notre r\u00e9ussite. Pour cette raison, nous mettons tout en \u0153uvre pour cr\u00e9er et entretenir un environnement inclusif et bienveillant. D\u00e9couvrez comment nous r\u00e9duisons les \u00e9carts de salaire, luttons contre les biais inconscients lors du recrutement et bien plus encore.D\u00e9couvrez l'inclusion en actionNos sitesNotre si\u00e8ge social est situ\u00e9 \u00e0 San Francisco, en Californie, et nous disposons de plus de 20\u00a0bureaux dans 12\u00a0pays. Avec plus de 4\u00a0500\u00a0Bricksters dans le monde et une strat\u00e9gie de d\u00e9veloppement ambitieuse, notre croissance compte parmi les plus fortes du secteur du cloud d'entreprise.D\u00e9couvrez nos bureaux dans le monde entierAm\u00e9rique\n\u00a0San FranciscoSeattleWashington, D.C.New YorkAfficher plusEurope\n\u00a0LondresAmsterdamBerlinMunichAfficher plusAsie-Pacifique\n\u00a0TokyoSingapourS\u00e9oulHangzhouAfficher plusOpportunit\u00e9s pour \u00e9tudiants et jeunes dipl\u00f4m\u00e9sNous sommes d\u00e9termin\u00e9s \u00e0 d\u00e9velopper la prochaine g\u00e9n\u00e9ration de leaders Databricks. Nous tenons donc \u00e0 ce que nos stagiaires et nos jeunes dipl\u00f4m\u00e9s jouent un r\u00f4le essentiel dans le d\u00e9veloppement de notre plateforme.Notre programme de formation est con\u00e7u pour que vous profitiez au maximum de votre exp\u00e9rience\u00a0: hackathons d'ing\u00e9nierie, Jeux Olympiques de stagiaires, mais aussi soir\u00e9es de jeux de plateau et happy hours.Explorez les opportunit\u00e9s de stage Transparence de la couverture du r\u00e9gime d'assurance sant\u00e9 (\u00c9tats-Unis uniquement)ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/data-pipelines","text":"\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub9e4\uc77c \uc218\ucc9c \ub9cc \uac1c\uc758 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ub85c\ub4dc\uac00 Databricks\uc5d0\uc11c \uc2e4\ud589\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uc218\uc9d1\ud558\uace0 \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks\uc5d0\uac8c \uc778\ud504\ub77c\uc758 \ub300\uaddc\ubaa8 \uc790\ub3d9 \uad00\ub9ac\ub97c \ub9e1\uae30\uace0 \uc548\uc815\uc801\uc778 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c\ub97c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud558\uc138\uc694. \uae30\ubcf8 \ub370\uc774\ud130 \ud488\uc9c8 \ud14c\uc2a4\ud2b8 \uae30\ub2a5\uacfc \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uac1c\ubc1c \ubaa8\ubc94 \uc0ac\ub840 \uc9c0\uc6d0\uc73c\ub85c \ud300 \uc0dd\uc0b0\uc131\uc744 \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ubc30\uce58\uc640 \uc2a4\ud2b8\ub9ac\ubc0d \ud1b5\ud569\ud558\ub098\uc758 \ud1b5\ud569 API\ub97c \uc0ac\uc6a9\ud558\ub294 \ub2e8\uc77c \ud50c\ub7ab\ud3fc\uc744 \ud1b5\ud574 \uc0ac\uc77c\ub85c\ub97c \uc81c\uac70\ud558\uace0 \ub300\uaddc\ubaa8\ub85c \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uc218\uc9d1, \ubcc0\ud658 \ubc0f \uc99d\ubd84 \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \uac00\uce58 \ucc3d\ucd9c\uc5d0 \uc9d1\uc911Databricks\uac00 \uc778\ud504\ub77c\uc640 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c\uc758 \uc6b4\uc601 \ubd80\ubb38\uc744 \uc790\ub3d9\uc73c\ub85c \uad00\ub9ac\ud558\ubbc0\ub85c \uace0\uac1d\uc740 \ud234\ub9c1\uc774 \uc544\ub2c8\ub77c \uac00\uce58 \ucc3d\ucd9c\uc5d0 \uc9d1\uc911\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \ub3c4\uad6c\uc640 \uc5f0\uacb0\uac1c\ubc29\uc801 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130 \uc218\uc9d1, ETL\/ELT, \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc5d0 \uc0ac\uc6a9\ud558\uace0 \uc2f6\uc740 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ub3c4\uad6c\ub97c \uc5f0\uacb0\ud558\uace0 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc \uae30\ubc18\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \uc790\uc0b0\uc744 \uad6c\ucd95 \ubc0f \uacf5\uc720\ud558\ub294 \ub370 \uac00\uc7a5 \uc801\uc808\ud55c \uae30\ubc18\uc744 \uc81c\uacf5\ud558\uba70, \uc774\ub7ec\ud55c \ub370\uc774\ud130 \uc790\uc0b0\uc740 \uc911\uc559\uc5d0\uc11c \uad00\ub9ac\ud558\uace0 \uc548\uc815\uc801\uc774\uba74\uc11c\ub3c4 \ub9e4\uc6b0 \ube60\ub978 \uc18d\ub3c4\ub97c \uc790\ub791\ud569\ub2c8\ub2e4.\u201c\uc6b0\ub9ac\uc5d0\uac8c Databricks\ub294 \ubaa8\ub4e0 ETL \uc791\uc5c5\uc744 \ucc98\ub9ac\ud558\ub294 \uc6d0\uc2a4\ud1b1 \uc0f5\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \ub9ce\uc774 \uc0ac\uc6a9\ud560\uc218\ub85d \uc0ac\uc6a9\uc790\uc640 \ud50c\ub7ab\ud3fc \uad00\ub9ac\uc790 \ubaa8\ub450\uc5d0\uac8c \ud6e8\uc52c \ud3b8\ub9ac\ud574\uc9d1\ub2c8\ub2e4.\u201d\u2014 Hillevi Crognale, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uad00\ub9ac\uc790, YipitData\uc5b4\ub5bb\uac8c \uc791\ub3d9\ud558\ub098\uc694?\ub370\uc774\ud130 \uc218\uc9d1 \uac04\uc18c\ud654\uc790\ub3d9 ETL \ucc98\ub9ac\uc548\uc815\uc801\uc778 \uc6cc\ud06c\ud50c\ub85c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc804\uccb4\uc801 \uad00\ucc30 \uae30\ub2a5 \ubc0f \ubaa8\ub2c8\ud130\ub9c1\ucc28\uc138\ub300 \ub370\uc774\ud130 \ucc98\ub9ac \uc5d4\uc9c4\uac70\ubc84\ub10c\uc2a4, \uc548\uc815\uc131 \ubc0f \uc131\ub2a5\uc758 \uae30\ubc18\ub370\uc774\ud130 \uc218\uc9d1 \uac04\uc18c\ud654\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ub370\uc774\ud130\ub97c \uc785\ub825\ud558\uace0 \ud55c \uacf3\uc5d0\uc11c \ubd84\uc11d, AI \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc9c0\uc6d0\ud574 \ubcf4\uc138\uc694.Auto Loader\ub294 \ud074\ub77c\uc6b0\ub4dc \uc2a4\ud1a0\ub9ac\uc9c0\uc5d0 \uc800\uc7a5\ub418\ub294 \ud30c\uc77c\uc744 \uc99d\ubd84 \ubc29\uc2dd\uc73c\ub85c \uc790\ub3d9 \ucc98\ub9ac\ud558\ubbc0\ub85c \uc0c1\ud0dc \uc815\ubcf4\ub97c \uc608\uc57d \uc791\uc5c5\uc774\ub098 \uc5f0\uc18d\uc801 \uc791\uc5c5\uc73c\ub85c \uad00\ub9ac\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4. \ub514\ub809\ud130\ub9ac\uc5d0\uc11c \ubaa8\ub2c8\ud130\ub9c1\ud558\uc9c0 \uc54a\uc544\ub3c4 \uc0c8\ub85c\uc6b4 \ud30c\uc77c\uc744 \ud6a8\uc728\uc801\uc73c\ub85c \ucd94\uc801\ud558\uba70(\uc218\uc2ed\uc5b5 \uac1c\uae4c\uc9c0 \ud655\uc7a5 \uac00\ub2a5), \uc18c\uc2a4 \ub370\uc774\ud130\uc5d0\uc11c \uc2a4\ud0a4\ub9c8\ub97c \uc790\ub3d9 \ucd94\ub860\ud558\uc5ec \ub098\uc911\uc5d0 \ubcc0\uacbd\uc774 \ubc1c\uc0dd\ud558\uba74 \uadf8\uc5d0 \ub9de\ucdb0 \uc870\uc815\ud569\ub2c8\ub2e4. COPY INTO \uba85\ub839\uc744 \uc0ac\uc6a9\ud558\uba74 \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 SQL\uc744 \ud1b5\ud574 \uc190\uc27d\uac8c Delta Lake\ub85c \ubc30\uce58 \ud30c\uc77c\uc744 \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u201c\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc758 \uc0dd\uc0b0\uc131\uc774 40% \ud5a5\uc0c1\ub418\uc5b4\uc11c \uc0c8\ub85c\uc6b4 \uc544\uc774\ub514\uc5b4\ub97c \uac1c\ubc1c\ud558\uae30\uae4c\uc9c0 \uac78\ub9ac\ub294 \uc2dc\uac04\uc774 \uba70\uce60\uc5d0\uc11c \uba87 \ubd84\uc73c\ub85c \ub2e8\ucd95\ub41c \ub370\ub2e4, \ub370\uc774\ud130 \uac00\uc6a9\uc131\uacfc \uc815\ud655\uc131\uc774 \ub192\uc544\uc84c\uc2b5\ub2c8\ub2e4.\u201d\u2014 Shaun Pearce, \ucd5c\uace0 \uae30\uc220 \ucc45\uc784\uc790,\u00a0Gousto\uc790\uc138\ud788\uc790\ub3d9 ETL \ucc98\ub9ac\ud30c\uc77c\uc774 \uc218\uc9d1\ub418\uace0 \ub098\uba74 \ubd84\uc11d\uacfc AI\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \uac00\uacf5\ub418\uc9c0 \uc54a\uc740 \ub370\uc774\ud130\ub97c \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4. Databricks\ub294 Delta Live Tables(DLT)\ub85c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8, \uc560\ub110\ub9ac\uc2a4\ud2b8\uc5d0\uac8c \uac15\ub825\ud55c ETL \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. DLT\ub294 \uac04\ub2e8\ud55c \uc120\uc5b8\uc801 \ubc29\uc2dd\uc73c\ub85c \ubc30\uce58 \ub610\ub294 \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uc704\ud55c ETL \ubc0f ML \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\ub294 \ucd5c\ucd08\uc758 \ud504\ub808\uc784\uc6cc\ud06c\uc774\uba70, \uc778\ud504\ub77c \uad00\ub9ac\ub098 \uc791\uc5c5 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158, \uc624\ub958 \ucc98\ub9ac, \ubcf5\uad6c\uc640 \uac19\uc740 \uc6b4\uc601 \ubcf5\uc7a1\uc131\uacfc \uc131\ub2a5 \ucd5c\uc801\ud654\ub97c \uc790\ub3d9\ud654\ud569\ub2c8\ub2e4. DLT\ub97c \uc0ac\uc6a9\ud558\ub294 \uc5d4\uc9c0\ub2c8\uc5b4\ub294 \ub370\uc774\ud130\ub97c \ucf54\ub4dc\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\uace0, \ud14c\uc2a4\ud2b8, \ubaa8\ub2c8\ud130\ub9c1 \ubc0f \ubb38\uc11c\ud654 \ub4f1\uc758 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubaa8\ubc94 \uc0ac\ub840\ub97c \uc801\uc6a9\ud558\uc5ec \ub300\uaddc\ubaa8\ub85c \uc548\uc815\uc801\uc778 \ud30c\uc774\ud504\ub77c\uc778\uc744 \ubc30\ud3ec\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\uc548\uc815\uc801\uc778 \uc6cc\ud06c\ud50c\ub85c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158Databricks Workflows\ub294 \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ub124\uc774\ud2f0\ube0c\uc778 AI\uc5d0 \ub300\ud55c \uc644\uc804 \uad00\ub9ac\ud615 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158 \uc11c\ube44\uc2a4\uc785\ub2c8\ub2e4. Delta Live Tables, Jobs for SQL, Spark, \ub178\ud2b8\ubd81, dbt, ML \ubaa8\ub378 \ub4f1\uc744 \ud3ec\ud568\ud55c \uc804\uccb4 \uc218\uba85 \uc8fc\uae30\uc5d0 \ub300\ud574 \ub2e4\uc591\ud55c \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud569\ub2c8\ub2e4. \uae30\uc874 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uacfc \uae34\ubc00\ud788 \ud1b5\ud569\ub418\ubbc0\ub85c \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc548\uc815\uc801\uc778 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc0dd\uc131 \ubc0f \uc2e4\ud589\ud558\uba74\uc11c\ub3c4 \ucd5c\uc885 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uac04\ub2e8\ud558\uac8c \uc2ec\uce35\uc801 \uc911\uc559 \uc9d1\uc911\ud615 \ubaa8\ub2c8\ud130\ub9c1\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\uc6b0\ub9ac\uc758 \uc784\ubb34\ub294 \uc9c0\uad6c\uc5d0 \uc804\ub825\uc744 \uacf5\uae09\ud558\ub294 \ubc29\uc2dd\uc744 \ubcc0\ud654\uc2dc\ud0a4\ub294 \uac83\uc785\ub2c8\ub2e4. \uc5d0\ub108\uc9c0 \ubd80\ubb38\uc758 \uace0\uac1d\uc740 \uc774\ub7ec\ud55c \ubcc0\ud654\ub97c \ub2ec\uc131\ud558\uae30 \uc704\ud574 \ub370\uc774\ud130, \ucee8\uc124\ud305 \uc11c\ube44\uc2a4 \ubc0f \uc5f0\uad6c\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. Databricks \uc6cc\ud06c\ud50c\ub85c\ub294 \uace0\uac1d\uc774 \ud544\uc694\ub85c \ud558\ub294 \uc778\uc0ac\uc774\ud2b8\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\ub294 \uc18d\ub3c4\uc640 \uc720\uc5f0\uc131\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\u2014 Yanyan Wu, \ub370\uc774\ud130 \ubd80\ubb38 \ubd80\uc0ac\uc7a5,\u00a0Wood Mackenzie\uc790\uc138\ud788\uc804\uccb4\uc801 \uad00\ucc30 \uae30\ub2a5 \ubc0f \ubaa8\ub2c8\ud130\ub9c1\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ubaa8\ub4e0 \ub370\uc774\ud130\uc640 AI \uc218\uba85 \uc8fc\uae30\uc5d0 \ub300\ud55c \uac00\uc2dc\uc131\uc744 \uc81c\uacf5\ud558\ubbc0\ub85c, \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\uc640 \uc6b4\uc601 \ud300\uc5d0\uc11c \uc2e4\uc2dc\uac04\uc73c\ub85c \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ud50c\ub85c \uc0c1\ud0dc\ub97c \ud655\uc778\ud558\uace0, \ub370\uc774\ud130 \ud488\uc9c8\uc744 \uad00\ub9ac\ud558\uba70, \uacfc\uac70\uc758 \ud2b8\ub80c\ub4dc\ub97c \ud30c\uc545\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks Workflows\uc5d0\uc11c\ub294 \ud504\ub85c\ub355\uc158 \uc791\uc5c5\uacfc Delta Live Tables \ud30c\uc774\ud504\ub77c\uc778\uc758 \uc0c1\ud0dc\uc640 \uc131\ub2a5\uc744 \ucd94\uc801\ud558\ub294 \ub370\uc774\ud130 \ud50c\ub85c \uadf8\ub798\ud504 \ubc0f \ub300\uc2dc\ubcf4\ub4dc\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ubca4\ud2b8 \ub85c\uadf8\ub294 Delta Lake \ud14c\uc774\ube14\ub85c \ub178\ucd9c\ub418\uc5b4, \ubaa8\ub4e0 \uac01\ub3c4\uc5d0\uc11c \uc131\ub2a5\uacfc \ub370\uc774\ud130 \ud488\uc9c8, \uc548\uc815\uc131 \uc9c0\ud45c\ub97c \ubaa8\ub2c8\ud130\ub9c1\ud558\uace0 \uc2dc\uac01\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ucc28\uc138\ub300 \ub370\uc774\ud130 \ucc98\ub9ac \uc5d4\uc9c4Databricks \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc740 Apache Spark API\uc640 \ud638\ud658\ub418\ub294 \ucc28\uc138\ub300 \uc5d4\uc9c4\uc778 Photon\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uc5ec \uc218\ucc9c \uac1c\uc758 \ub178\ub4dc\ub85c \uc790\ub3d9 \ud655\uc7a5\ud558\uba74\uc11c\ub3c4 \ub3c5\ubcf4\uc801\uc778 \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.Spark Structured Streaming\uc740 \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ucc98\ub9ac\uc5d0 \ud558\ub098\uc758 \ud1b5\ud569\ub41c API\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ucf54\ub4dc\ub97c \ubcc0\uacbd\ud558\uac70\ub098 \uc0c8\ub85c\uc6b4 \uae30\uc220\uc744 \ubc30\uc6b0\uc9c0 \uc54a\uace0\ub3c4 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \uc190\uc27d\uac8c \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \ub3c4\uc785\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ucd5c\ucca8\ub2e8 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4, \uc548\uc815\uc131 \ubc0f \uc131\ub2a5Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \uc0ac\uc6a9\ud558\uba74 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \uae30\ubcf8 \uad6c\uc131 \uc694\uc18c(Unity Catalog \ubc0f Delta Lake)\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4. ACID \ud2b8\ub79c\uc7ad\uc158\uc744 \ud1b5\ud574 \uc548\uc815\uc131\uc744 \uc81c\uacf5\ud558\uace0 \ud655\uc7a5 \uac00\ub2a5\ud55c \uba54\ud0c0\ub370\uc774\ud130\ub97c \ub9e4\uc6b0 \ube60\ub978 \uc18d\ub3c4\ub85c \ucc98\ub9ac\ud558\ub294 \uc624\ud508 \uc18c\uc2a4 \uc2a4\ud1a0\ub9ac\uc9c0 \ud615\uc2dd\uc778 Delta Lake\ub85c \uac00\uacf5\ub418\uc9c0 \uc54a\uc740 \ub370\uc774\ud130\ub97c \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4. \uc5ec\uae30\uc5d0 Unity Catalog\ub97c \uacb0\ud569\ud558\uba74 \ubaa8\ub4e0 \ub370\uc774\ud130\uc640 AI \uc790\uc0b0\uc5d0 \uc138\ubd84\ud654\ub41c \uac70\ubc84\ub10c\uc2a4\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\uc744 \ubfd0\ub9cc \uc544\ub2c8\ub77c, \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc77c\uad00\uc801\uc778 \ub370\uc774\ud130 \ud0d0\uc0c9, \uc561\uc138\uc2a4, \uacf5\uc720 \ubaa8\ub378\uc744 \uc801\uc6a9\ud558\uc5ec \uac70\ub108\ubc88\uc2a4 \ubc29\uc2dd\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4. \ub610\ud55c, Unity Catalog\ub294 \ub2e4\ub978 \uc870\uc9c1\uacfc \uac04\ub2e8\ud558\uace0 \uc548\uc804\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\ub294 \uc5c5\uacc4 \ucd5c\ucd08\uc758 \uc624\ud508 \ud504\ub85c\ud1a0\ucf5c\uc778 Delta Sharing\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130 \uc0ac\uc77c\ub85c, \ub290\ub9b0 \uc131\ub2a5, Hadoop\uc774\ub098 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub192\uc740 \ube44\uc6a9\uc5d0 \uc9c0\uce58\uc168\ub098\uc694? \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc138\uc694.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud1b5\ud569\ub370\uc774\ud130 \ud300\uc5d0 \ucd5c\ub300\uc758 \uc720\uc5f0\uc131\uc744 \uc81c\uacf5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Partner Connect \ubc0f \uae30\uc220 \ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud65c\uc6a9\ud558\uc5ec \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ub3c4\uad6c\uc640 \ub9e4\ub044\ub7fd\uac8c \ud1b5\ud569\ud574 \ubcf4\uc138\uc694. \uc608\ub97c \ub4e4\uc5b4 Fivetran\uc73c\ub85c \ube44\uc988\ub2c8\uc2a4\uc5d0 \uc911\uc694\ud55c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\uace0, dbt\ub85c \ubc14\ub85c \ubcc0\ud658\ud558\uc5ec, Apache Airflow\ub85c \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \uc218\uc9d1 \ubc0f ETL+ \uc5ec\ud0c0 \ubaa8\ub4e0 Apache Spark\u2122\ufe0f \ud638\ud658 \ud074\ub77c\uc774\uc5b8\ud2b8\uace0\uac1d \uc0ac\ub840\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30Delta Lake\uc6cc\ud06c\ud50c\ub85c\uc6b0Delta Live \ud14c\uc774\ube14Delta Sharing\uad00\ub828 \ucf58\ud150\uce20\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ud1b5\ud574 Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \ud65c\uc6a9\ud558\ub294 \uc7a5\uc810\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0 Bill Inmon\uc774 \uad6c\ucd95\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uad00\ub9ac \uae30\ucd08\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 Big Book\uc0c8\ub85c\uc6b4 Delta Sharing \uc194\ub8e8\uc158 \uc54c\uc544\ubcf4\uae30\uc655\ucd08\ubcf4\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc774\ubca4\ud2b8Delta Live Tables\ub85c \ub370\uc774\ud130 \ubcc0\ud658 \ucc98\ub9ac\uac04\ud3b8\ud55c \ub370\uc774\ud130 \uc218\uc9d1 \uc6e8\ube44\ub098 \uc2dc\ub9ac\uc988DATA + AI SUMMIT 2022\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \ud604\ub300\ud654\ube14\ub85c\uadf8Databricks Delta Live Tables(DLT) \uc815\uc2dd \ucd9c\uc2dcDatabricks Workflows \uc18c\uac1c2021\ub144\uc5d0 Databricks \ubc0f Apache Spark\uc6a9\uc73c\ub85c \uac1c\ubc1c\ub41c \uc0c8\ub85c\uc6b4 \uad6c\uc870\ud654 \uc2a4\ud2b8\ub9ac\ubc0d \uae30\ub2a5 \uc804\uccb4 \uac1c\uad00Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc18\uad6c\uc870\ud654\ub41c \ub370\uc774\ud130 \uacfc\ub2c8\ub97c \ub2e8\uc21c\ud654\ud558\uae30 \uc704\ud55c 10\uac00\uc9c0 \uac15\ub825\ud55c \uae30\ub2a5\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ucee4\ubba4\ub2c8\ud2f0 \uac00\uc785AWSAzureGCP\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/technology","text":"Partenaires technologiques de Databricks - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires technologiques DatabricksInteragissez avec les partenaires technologiques Databricks pour int\u00e9grer les capacit\u00e9s d'ingestion de donn\u00e9es, de business intelligence et de gouvernance \u00e0 la plateforme Lakehouse de Databricks.\u00ab\u00a0Avec Databricks et Fivetran, nous allons consid\u00e9rablement am\u00e9liorer les insights marketing \u00e0 l'avenir. D'un point de vue technique, les deux outils interagissent harmonieusement et l'int\u00e9gration est parfaitement transparente.\u00a0\u00bb\u2013 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP chez Paul HewittLes partenaires technologiques Databricks int\u00e8grent leurs solutions \u00e0 Databricks pour offrir des fonctionnalit\u00e9s compl\u00e9mentaires en mati\u00e8re d'ETL, d'ingestion de donn\u00e9es, de business intelligence, de machine learning et de gouvernance.Ces int\u00e9grations permettent aux clients de tirer parti de la fiabilit\u00e9 et de l'\u00e9volutivit\u00e9 de la plateforme Lakehouse de Databricks pour innover plus rapidement tout en obtenant de pr\u00e9cieux insights de donn\u00e9es.Contact partenairesRassemblez tous vos outils de donn\u00e9es, d'analytique et d'IA sur une seule plateforme ouverte. Avec Partner Connect, Databricks offre un moyen rapide et facile de connecter vos outils existants \u00e0 votre lakehouse \u00e0 l'aide d'int\u00e9grations valid\u00e9es. Il vous aide aussi \u00e0 d\u00e9couvrir et \u00e0 essayer de nouvelles solutions.Devenir partenaireEn savoir plusLoading...ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/company\/awards-and-recognition","text":"Auszeichnungen und Anerkennungen | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWAuszeichnungen und AnerkennungenErfahren Sie, welche Anerkennung Databricks unter Branchenf\u00fchrern genie\u00dftLeader im Magic Quadrant for Cloud Database Management Systems 2022Customer Choice Award 2022 f\u00fcr Cloud-DatenbankmanagementsystemeLeader im Magic Quadrant for Cloud Database Management Systems 2021Leader im Magic Quadrant 2021 f\u00fcr Data Science und Machine LearningLakehouse: Hype Cycle for Data Management 2022Hot Companies to Watch in 2023Most Innovative Companies in Data ScienceThe Cloud 100The AI 50America\u2019s Best Startup EmployersBest Workplaces in TechnologyBest Workplaces in the Bay AreaBest Workplaces for MillennialsCNBC Disruptor 50Bester Arbeitgeber 2022M\u00f6chten Sie mehr wissen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/de\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected]om and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions","text":"Partner Solutions - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner SolutionsPartner-developed industry and migration solutions for the lakehouseWe have partnered with leading consulting partners to build innovative solutions for industry and migration use cases. Databricks Brickbuilder Solutions are expertly designed by our partners to help you cut costs and increase value from your data. Backed by their years of industry experience \u2014 and built for the Databricks Lakehouse Platform \u2014 you can be confident that you get solutions that are tailored for your business.Search available partnerssearchPublic SectorCloud Data Migration by Accenture - DatabricksLearn moreRetail and Consumer GoodsUnified View of Demand by AccentureLearn moreAdvertising and Marketing TechnologyCPG Control Tower by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent Healthcare on Azure Databricks by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent ManufacturingLearn moreAdvertising and Marketing TechnologyLegacy System Migration by AvanadeLearn moreAdvertising and Marketing TechnologyRisk Management by AvanadeLearn moreTechnology and SoftwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksLearn moreTechnology and SoftwareMigrate to Cloud and Databricks by Capgemini and DatabricksLearn moreTechnology and SoftwareCapgemini Revenue Growth ManagementLearn moreTechnology and SoftwareMigrate to Databricks by Celebal Technologies and DatabricksLearn moreTechnology and SoftwareCognizant Video Quality of ExperienceLearn moreAdvertising and Marketing TechnologyPersona 360 by DataSentics and DatabricksLearn moreAdvertising and Marketing TechnologySAP Migration Accelerator by DataSentics - DatabricksLearn moreAdvertising and Marketing TechnologyPrecisionView\u2122 by DeloitteLearn moreAdvertising and Marketing TechnologyTrellis by DeloitteLearn moreAdvertising and Marketing TechnologySmart Migration to Databricks by EPAMLearn moreAdvertising and Marketing TechnologyLeapLogic Migration Solution by ImpetusLearn moreLoad MoreReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/celia-kung\/#","text":"Celia Kung - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCelia KungEngineering Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ian-sotnek\/#","text":"Ian Sotnek - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIan SotnekDirector of Product at AI Squared, IncBack to speakersIan Sotnek is co-founder and Director of Product of AI Squared, Incorporated. Ian's multidisciplinary background encompasses degrees and academic work in applied neuroscience as well as in machine learning governance and policy. This experience has prepared him to contribute to the human-computer interaction focus of AI Squared, where he leads the design and development of their open data science platform for machine learning development, governance, and integration.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/migrating-from-hadoop-to-data-lakehouse-for-dummies","text":"Migrating From Hadoop to Data Lakehouse for Dummies | DatabrickseBookMigrating From Hadoop to Data Lakehouse for DummiesLeave Hadoop behind for faster insightsHadoop platforms have failed to deliver business value due to the lack of data science capabilities, the high cost of operations and the inability to scale. As a result, enterprises are looking to migrate off of Hadoop.The Databricks Lakehouse is a cloud-native platform for all your data, analytics and AI use cases. It provides a single platform for developers, analysts, data scientists and business users, enabling them to build, deploy, scale and manage analytical applications in minutes instead of hours or days. It is built on modern, open standards and provides a common unified approach to data governance and data sharing.This book will help you discover why you should migrate from Hadoop to Databricks and how to drive business value through data science, AI and ML use cases.You\u2019ll find out:How the lakehouse can help you meet 3 essential data and AI goals5 key steps for your migration from Hadoop to the lakehouseHow CBC Radio-Canada reduced time to insight by 50%10 steps to enable and scale your data, analytics and AI strategyGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#3f4f4d56495e5c467f5b5e4b5e5d4d565c544c115c5052","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c2fcffada57b2\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/financial-services","text":"Lakehouse para o setor de servi\u00e7os financeirosSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLakehouse para o setor de servi\u00e7os financeirosImpulsionando institui\u00e7\u00f5es de servi\u00e7os financeiros orientadas a dados e IA do futuroComece agoraAgendar uma demonstra\u00e7\u00e3oO quatro desafios de dados no setor de servi\u00e7os financeirosGovernan\u00e7a e gerenciamento de dados\nA falta de agilidade dos dados e reprodutibilidade do modelo dificulta o cumprimento dos requisitos regulat\u00f3rios espec\u00edficos dos servi\u00e7os financeiros.Insights mais profundos dos clientes\nOs silos de dados impedem ter uma vis\u00e3o completa dos comportamentos dos clientes, das oportunidades de vendas cruzadas e dos insights necess\u00e1rios para hiperpersonaliza\u00e7\u00e3o em escala.Decis\u00f5es em tempo real\nFerramentas isoladas e restritas ao fornecedor dificultam a capacidade de realizar an\u00e1lises em tempo real que impulsionam e democratizam decis\u00f5es financeiras mais inteligentes.Acesso a dados de terceiros\nAs tecnologias legadas n\u00e3o podem aproveitar os insights financeiros e de clientes de conjuntos de dados n\u00e3o estruturados e alternativos que est\u00e3o se desenvolvendo rapidamente. Elas tamb\u00e9m n\u00e3o oferecem recursos de compartilhamento de dados abertos para promover a colabora\u00e7\u00e3o.Lakehouse para o setor de servi\u00e7os financeirosPlataforma unificada de dados e IA\nUma plataforma \u00fanica que re\u00fane todas as suas cargas de trabalho de dados e an\u00e1lises para permitir inova\u00e7\u00f5es profundas para institui\u00e7\u00f5es de servi\u00e7os financeiros modernas.\n\u00a0\nSolu\u00e7\u00f5es para parceiros\nOs principais provedores de solu\u00e7\u00f5es do mundo usam o lakehouse para o setor de servi\u00e7os financeiros. Aproveite as ofertas predefinidas que aceleram a transforma\u00e7\u00e3o orientada por dados.\nFerramentas para acelerar os resultados dos neg\u00f3cios\nA Databricks e seus parceiros criaram uma variedade de aceleradores de solu\u00e7\u00f5es que ajudam a lidar com casos comuns de uso de servi\u00e7os financeiros, desde investimentos ESG at\u00e9 preven\u00e7\u00e3o de fraudes.\nColabora\u00e7\u00e3o no setor\nPermita o compartilhamento seguro e aberto de dados por meio do nosso ecossistema de dados, incluindo S&P Global, Intercontinental Exchange, FactSet e Nasdaq, para liberar inova\u00e7\u00f5es que impulsionam a cria\u00e7\u00e3o de valor sustent\u00e1vel.\nTransforma\u00e7\u00e3o dos servi\u00e7os financeiros com\nLakehouse\n\u201cA vis\u00e3o da Nasdaq para dados e IA \u00e9 alimentada pelo Databricks Lakehouse. Usamos essa solu\u00e7\u00e3o para processar grandes quantidades de dados financeiros e alternativos complexos a fim de criar dados e insights para nossos clientes. Al\u00e9m disso, a Databricks desempenha um papel importante em nossos esfor\u00e7os de modernizar a entrega e o consumo de dados. A Databricks nos permite enviar dados diretamente para workspaces anal\u00edticos, para que nossos clientes possam analisar e integrar dados cr\u00edticos rapidamente sem precisar mover terabytes.\u201d\u2014 Bill Dague, Head do Nasdaq Data Link, NasdaqPor que lakehouse para o setor de servi\u00e7os financeiros?\nRe\u00fana dados e IA em uma plataforma aberta e colaborativa que ajuda voc\u00ea a minimizar riscos, proporcionar experi\u00eancias ricas aos clientes e acelerar a inova\u00e7\u00e3oAbordagem de governan\u00e7a para conformidade e gerenciamento de riscos\nSimplifique a complexidade dos relat\u00f3rios regulat\u00f3rios, gerenciamento de riscos e conformidade, otimizando com seguran\u00e7a a aquisi\u00e7\u00e3o, o processamento e a transmiss\u00e3o de dados para implementar as melhores pr\u00e1ticas de governan\u00e7a.Produtos e servi\u00e7os personalizados\nRe\u00fana uma variedade de dados \u2014 de dados de mercado a dados alternativos \u2014 para experi\u00eancias hiperpersonalizadas que geram oportunidades de vendas cruzadas, satisfa\u00e7\u00e3o do cliente e aumento de share of wallet.Insights em tempo real, decis\u00f5es mais inteligentes\nIngira rapidamente todas as suas fontes de dados em escala para tomar melhores decis\u00f5es de investimento, detecte rapidamente novos esquemas de fraude e traga recursos em tempo real para pr\u00e1ticas de gerenciamento de riscos.Monetiza\u00e7\u00e3o e compartilhamento de dados abertos\nRe\u00fana grandes quantidades de dados internos e de terceiros para compartilhar solu\u00e7\u00f5es financeiras inovadoras, monetizar novos produtos de dados e entregar recursos anal\u00edticos avan\u00e7ados para qualquer nuvem ou ferramenta sem se prender a tecnologias propriet\u00e1rias.Baixar e-bookParceiros e solu\u00e7\u00f5esMude para formatos abertos e padroniza\u00e7\u00e3o de dados para an\u00e1lises e IAGerenciamento de riscosImplemente dados rapidamente em modelos de valor em risco para identificar riscos emergentes e poss\u00edveis amea\u00e7as.Introdu\u00e7\u00e3oModerniza\u00e7\u00e3o de cart\u00f5es obsoletos e portf\u00f3lios de servi\u00e7os banc\u00e1rios principaisPermita a convers\u00e3o r\u00e1pida de sistemas externos e obtenha uma capacidade de convers\u00e3o totalmente configur\u00e1vel e industrializada.Introdu\u00e7\u00e3oPersona 360Crie perfis de clientes completos e unificados em um modelo de dados inteligente.Introdu\u00e7\u00e3oVer todas as solu\u00e7\u00f5es de parceirosSeguran\u00e7a cibern\u00e9tica em grande escalaDetecte amea\u00e7as rapidamente, investigue seu impacto e reduza os riscos com o Splunk e DatabricksIntrodu\u00e7\u00e3oClassifica\u00e7\u00e3o ESGTenha uma vis\u00e3o quantitativa da sustentabilidade e garanta que as empresas sejam respons\u00e1veis por suas a\u00e7\u00f5esIntrodu\u00e7\u00e3oGerenciamento moderno de riscosAdote uma abordagem mais \u00e1gil ao gerenciamento de riscos unificando dados e IA no lakehouseIntrodu\u00e7\u00e3oIdentifique fraudes com an\u00e1lises geoespaciais e IAUse dados geoespaciais para entender melhor os comportamentos de compra dos clientes, em termos de quem s\u00e3o e como fazem transa\u00e7\u00f5es banc\u00e1riasIntrodu\u00e7\u00e3oEnriquecimento de transa\u00e7\u00f5es com classifica\u00e7\u00e3o de comerciantesAutomatize o enriquecimento de transa\u00e7\u00f5es para entender melhor os comportamentos dos clientes e impulsionar a hiperpersonaliza\u00e7\u00e3oIntrodu\u00e7\u00e3oModelos de IA baseados em regras para combater fraudes financeirasModernize as estrat\u00e9gias de preven\u00e7\u00e3o contra fraudes para reduzir custos operacionais e aumentar a confian\u00e7a dos clientesIntrodu\u00e7\u00e3oTransmiss\u00e3o oportuna e confi\u00e1vel de relat\u00f3rios regulat\u00f3riosCombine modelos de dados do setor de servi\u00e7os financeiros com a nuvem para permitir altos padr\u00f5es de governan\u00e7a com custos de desenvolvimento reduzidosIntrodu\u00e7\u00e3oModerniza\u00e7\u00e3o das plataformas de dados de investimentoUse todo o poder dos dados do mercado financeiro para se concentrar na entrega de produtos aos clientesIntrodu\u00e7\u00e3oCombate \u00e0 lavagem de dinheiro (AML)Habilite casos de uso com IA, como fuzzy match e an\u00e1lise de imagens, para combater a lavagem de dinheiro e o financiamento do terrorismoIntrodu\u00e7\u00e3oVer todas as solu\u00e7\u00f5esLakehouse para o setor de servi\u00e7os financeiros na pr\u00e1ticaSucesso conjunto: Como dados e IA impulsionam a colabora\u00e7\u00e3o no lakehouseParticipe \u2192Recursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre dados e IA para o setor de servi\u00e7os financeiros.\nExplorar recursose-books e infogr\u00e1ficos[Infogr\u00e1fico] Dados para ancorar uma nova era de gest\u00e3o de riscosSaiba como aproveitar facilmente os benef\u00edcios dos dados e da IA no setor de servi\u00e7os financeirosAproveitamento de dados alternativos e de terceiros em servi\u00e7os financeirosTornar o ESG uma realidade com an\u00e1lise de dados e IA Preven\u00e7\u00e3o de fraudes com dados + IA: uma cartilha para amea\u00e7as modernas V\u00eddeos e downloadsMetodologias de investimento ESG explic\u00e1veis e transparentesSeguran\u00e7a cibern\u00e9tica no setor de servi\u00e7os financeirosAceleramento a inova\u00e7\u00e3o orientada por dados e IA no setor de servi\u00e7os financeirosAn\u00e1lise ESG: v\u00eddeo explicativoModerniza\u00e7\u00e3o do gerenciamento de riscosPlataformas de investimento modernas com lakehouse para o setor de servi\u00e7os financeirosFolha de solu\u00e7\u00e3o do Industry Lakehouse BlueprintsBlogsAcelerador para bancos e fintechs que usam transa\u00e7\u00f5es com cart\u00e3o de cr\u00e9ditoUma abordagem orientada por dados para o meio ambiente, quest\u00f5es sociais e governan\u00e7aConstru\u00e7\u00e3o de uma plataforma moderna de gerenciamento de risco de servi\u00e7os financeirosUso de seus dados para impedir fraudes com cart\u00f5es de cr\u00e9dito: Capital One e outras pr\u00e1ticas recomendadasEstrat\u00e9gias de moderniza\u00e7\u00e3o de plataformas de dados de investimentoMelhore a experi\u00eancia do cliente por meio do enriquecimento de transa\u00e7\u00f5es Destaques Data + AI Summit 2022 para o setor de servi\u00e7os financeirosLakehouse para o setor de servi\u00e7os financeirosTudo pronto para come\u00e7ar?Adorar\u00edamos saber sobre seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteAgendar uma demonstra\u00e7\u00e3oProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/legal\/privacynotice","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeffrey-hess","text":"Jeffrey Hess - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey HessLead Technologist at Booz Allen HamiltonBack to speakersJeff is a Lead Technologist at Booz Allen Hamilton responsible for standardizing enterprise data environments and has led multiple large-scale transformation projects to help stakeholders make the most of their data. Jeff oversees the entire data ecosystem, from moving and storing data, transforming and prepping data, visualizing data, and securing data. Jeff began as a business intelligence developer and continued to grow his passion for analytics, leading to a diverse skillset that sets his clients up for success.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/us-pub-sector-services","text":"Public Sector Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPublic Sector Services ScheduleThis Schedule sets forth terms related to use by Public Sector Customers of Databricks Services and is incorporated as part of the\u00a0Master Cloud Services Agreement\u00a0(the \u201cMCSA\u201d). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Contracting Entity and Order of Precedence.\u00a0If an Order identifies the Databricks contracting party as Databricks Federal, LLC (\u201cDBF\u201d), then any references in the Agreement to Databricks, including those contained in this Schedule, will be deemed to refer to DBF. Orders referencing DBF or any Order between Databricks and a Public Sector Customer will be deemed to incorporate this Schedule. In the event of a conflict between this Schedule and the MCSA or another Schedule thereto, this Schedule will be deemed to control solely for such DBF Order or other Public Sector Order.Databricks Services.\u00a0This Schedule establishes the terms and conditions enabling Databricks to provide Databricks Services to Public Sector Customers. For the purposes of this Schedule, references to \u201cCustomer\u201d in an Order, the MCSA or any Schedule thereto will be deemed to refer to Public Sector Customer or Customer Representative, as applicable. This Schedule does not grant you access to the Databricks Services without mutual agreement to an Order and applicable Databricks Services Schedule.Additional Definitions.\u201cCustomer Information\u201d\u00a0means Customer Content (if\u00a0you are purchasing Platform Services) and \/ or Customer Materials (if you are purchasing Advisory Services).\u201cCustomer Representative\u201d\u00a0means an organization authorized on behalf of a Public Sector Customer to purchase Databricks Services on its behalf, as designated in an applicable Order.\u201cFederal Customer\u201d\u00a0means any United States federal government branch or agency Customer of Databricks Services subject to this Schedule, including agencies and departments from the Executive Branch, the Congress, or the Military.\u201cPublic Sector Customer\u201d\u00a0means any Federal Customer or other United States state or local government, or entity, authority, agency, or body exercising executive, legislative, judicial, regulatory or administrative functions of any such government, who purchases Databricks Services subject to this Schedule. Public Sector Customer(s) may include public universities and hospitals.Modification.\u00a0Notwithstanding anything contained in the MCSA or any other Schedule, you agree as follows:\nU.S. Government License Rights.\u00a0If Customer is a Federal Customer, or the Agreement otherwise become subject to the Federal Acquisition Regulation (FAR), Customer acknowledges and agrees that the Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation constitute \u201ccommercial computer software\u201d and \u201ccommercial computer software documentation\u201d, respectively, provided as \u201cCommercial Items\u201d as defined in FAR 2.101. The Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation have been developed solely at private expense, and as set forth in FAR 12.212 and DFARS Section 227.7202, any use, modification, reproduction release, performance, display or disclosure thereof shall be solely in accordance with the terms of the MCSA as modified by this Schedule.Customer Representative Obligations.\u00a0Customer Representative will have no rights to the Databricks Services if purchasing Databricks Services on behalf of a Public Sector Customer except to the extent that a Public Sector Customer provides access to Customer Representative as its Authorized User. Customer Representative agrees to bind Public Sector Customer to the terms of the Agreement, including this Schedule, and will ensure that Databricks will be a third party beneficiary to such agreement. Customer Representative acknowledges that submission of a purchase order or Order will be deemed to be a representation to Databricks that the applicable Public Sector Customer has assented to the terms of the Agreement. Customer Representative will use commercially reasonable efforts to enforce the terms of the Agreement in the event it becomes aware that the Public Sector Customer has breached any terms and conditions of the Agreement where such breach adversely affects Databricks\u2019 rights or contractual protections. Customer Representative will notify Databricks promptly upon learning of any such breach.Acceptance.\u00a0Any Advisory Services or Training Services provided under the MCSA shall be deemed accepted upon delivery.Confidentiality.\u00a0Any provisions contained in the Agreement that require a Public Sector Customer to keep certain information confidential may be subject to the Freedom of Information Act, 5 U.S.C. \u00a7552 or similar applicable state or local state law, and any order by a United States Federal Court or court of appropriate jurisdiction.Equitable Relief.\u00a0Orders entered into directly with Databricks by a Federal Customer subject to this Schedule will only allow equitable relief when explicitly provided by statute (e.g., Prompt Payment Act or Equal Access to Justice Act).Auto Renewal, Customer Responsibility, and Indemnification.\u00a0If you are a Federal Customer subject to the Anti-Deficiency Act or similar limitations on fees or payment absent approved allocation of funding, any auto-renewal of Databricks Services, penalty fees or interest accrual associated with late payment, or Customer indemnification obligations in the Agreement will be deemed inapplicable. Federal Customer agrees to be responsible to Databricks for any claim (i) by a third party alleging that Customer Information or its use with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights; and \/ or (ii) arising from or related to your use of the Databricks Services allegedly in violation of any applicable law or the Agreement. Any clause in the Agreement requiring Databricks to defend or indemnify a Public Sector Customer is hereby amended solely to the extent that (a) the U.S. Department of Justice has the sole right to represent the Federal Customers in any such action in accordance with 28 U.S.C. 516, and (b) representation on behalf of Public Sector Customers may lie solely with the applicable state attorney general\u2019s office if you are a state or local government entity.Governing Law.\u00a0Orders entered into directly by a Federal Customer subject to this Schedule, the MCSA and any other applicable Schedules will be governed by and construed in accordance with the laws of the United States, and venue and jurisdiction of any dispute will be determined by applicable federal statute. If the federal laws of the United States are not dispositive, then to the extent permitted by federal law, the Agreement will be governed by the laws of the State of California, excluding its conflict of law principles. If you are a state or local government entity, the Agreement is governed by the laws of your state, excluding its conflict of laws principles. In the event the Uniform Computer Information Transactions Act (UCITA) or any similar laws or regulations are enacted, to the extent allowed by law, such law or regulation will not apply to the Agreement, and the governing law will remain as if such law or regulation had not been enacted. The Agreement does not affect statutory rights that cannot be waived or changed by contract.Disputes.\u00a0Notwithstanding any other provision in the Agreement, any dispute between Databricks and any Federal Customer arising under or related to the Agreement will be resolved exclusively under the terms and procedures of the Contract Disputes Act (41 U.S.C. Chapter 71).Assignment.\u00a0If you are a Federal Customer purchasing directly from Databricks, then except to the extent transfer may not be legally restricted, you may not assign the Agreement, any Order, or any right or obligation under the Agreement, or delegate any performance, without Databricks\u2019 prior written consent, which consent will not be unreasonably withheld. Databricks may assign its right to receive payment in accordance with the Assignment of Claims Act (31 U.S.C. 3727) and FAR 52.212-4(b), and may assign the Agreement to the extent not prohibited by the Anti-Assignment Act (41 U.S.C. 15). Subject to the requirements of FAR 42.12 (Novation and Change-of-Name Agreements), you agree to recognize Databricks\u2019 successor in interest following a transfer of assets or a change in name. Any attempted assignment or transfer in violation of the foregoing will be void. Subject to the foregoing, the Agreement will be binding upon and will inure to the benefit of the parties and their respective successors and assigns.Taxes.\u00a0References to taxes payable by Customer will not apply to your purchases of Databricks Services to the extent You are exempt from such taxes, provided that you agree to provide documentation reasonably acceptable to Databricks evidencing your tax-exempt status.Last Updated August 12, 2022. For earlier versions, please send a request to\u00a0[email\u00a0protected]\u00a0(with \u201cTOS Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=san%20francisco%2C%20california","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"\ud30c\ud2b8\ub108 \ud398\uc774\uc9c0: \ucee8\uc124\ud305 \ubc0f SI \ud30c\ud2b8\ub108 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 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\ud50c\ub7ab\ud3fc \uc561\uc138\uc2a4\uae30\uc220 \ubc0f \uc601\uc5c5 \uc9c0\uc6d0\uc601\uc5c5 \uae30\ud68c \ub4f1\ub85d \ubc0f \ucd94\ucc9c \uc218\uc218\ub8cc\uace0\uac1d \ud22c\uc790 \uae30\uae08\uc2dc\uc7a5 \uc9c4\ucd9c \uc9c0\uc6d0 \ubc0f \ub9ac\uc18c\uc2a4\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uc9c0\uae08 \uc2e0\uccad\ud558\uae30\ud30c\ud2b8\ub108 \ucc3e\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \u0000\uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hitesh-sahni","text":"Hitesh Sahni - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHitesh SahniHead of Cloud Data Platforms and Data Engineering Solutions at Deutsche Post DHLBack to speakersHitesh is head of Cloud Data Platforms and Solutions and Lead architect at DPDHL Group responsible for developing, scaling global cloud data management capabilities, delivering cloud data analytics projects including both data platforms and data engineering solutions.\nHitesh is results oriented Technology Leader with business acumen enabling data driven digital transformation, diverse experience in Big Data Analytics and Cloud Space across various industry verticals (banking, Logistics, etc.).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/david-tempelman","text":"David Tempelman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid TempelmanResident Solutions Architect at DatabricksBack to speakersDavid is a Resident Solutions Architect at Databricks and helps customers to get most value out of their data. He has several years of experience in the Big Data and Machine Learning domain across different industries including manufacturing, retail & finance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/beinan-wang\/#","text":"Beinan Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeinan WangSenior Staff Software Engineer at AlluxioBack to speakersDr. Beinan Wang is a Senior Staff Software Engineer from Alluxio and is the committer of PrestoDB. He is leading the engineer efforts of the next generation distributed cache. Prior to Alluxio, he was the Tech Lead of the Presto team in Twitter and he built large-scale distributed SQL systems for Twitter\u2019s data platform. He has twelve-year experience of working on performance optimization. He received his Ph.D. in computer engineering from Syracuse University on distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/migration","text":"Migre para a Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWMigre para a DatabricksModernize sua plataforma de dados migrando para o Databricks Lakehouse\nExperimente o Databricks gratuitamenteEntre em contato com DatabricksReduza custos, inove mais r\u00e1pido e simplifique sua plataforma de dados migrando para o Databricks Lakehouse a partir de seu data warehouse corporativo ou data lake legado. Agora, voc\u00ea pode executar todos os seus dados, fun\u00e7\u00f5es anal\u00edticas e cargas de trabalho de IA em uma plataforma unificada moderna, baseada em padr\u00f5es abertos e protegida com uma abordagem de governan\u00e7a comum.Por que migrar para a Databricks?Simplifique sua plataforma de dadosUse uma plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA. Unifique a governan\u00e7a e a experi\u00eancia do usu\u00e1rio nas equipes de nuvem e dados.\nEscale de forma econ\u00f4micaPare de gerenciar servidores. Escale de acordo com suas necessidades de serverless. Escale o data warehousing com desempenho at\u00e9 12 vezes melhor em rela\u00e7\u00e3o ao pre\u00e7o.\nAcelerar a inova\u00e7\u00e3oCrie rapidamente recursos de IA, ML e an\u00e1lise em tempo real com ferramentas colaborativas de autoatendimento e tecnologias de c\u00f3digo aberto, como MLflow e Apache Spark\u2122.\nMigrar do Hadoop\nSaiba maisMigrar de um data warehouse\nSaiba maisMigre com confian\u00e7aAjudamos centenas de clientes a migrar de plataformas de dados legados. O uso de um processo de migra\u00e7\u00e3o de ponta a ponta em fases fornece um modelo previs\u00edvel para entender os custos durante e ap\u00f3s a migra\u00e7\u00e3o. E uma abordagem com foco no lakehouse para migrar todos os workloads garante suporte para casos de uso existentes e novos. O resultado \u00e9 menor risco, obten\u00e7\u00e3o mais r\u00e1pida de valor e maior ROI.As 5 fases da migra\u00e7\u00e3o de dadosFase 1:\nDescoberta\nUse criadores de perfil para automatizar a descoberta. Obtenha insights sobre cargas de trabalho de plataformas legadas e estime os custos de consumo da plataforma Databricks.\nFase 2:\nAvalia\u00e7\u00e3o\nUse analisadores para uma avalia\u00e7\u00e3o detalhada da complexidade do c\u00f3digo e para estimar os custos do projeto de migra\u00e7\u00e3o.\nFase 3:\nEstrat\u00e9gia\nFinalize o mapeamento de tecnologia e desenvolva caminhos ideais para cada migra\u00e7\u00e3o de plataforma de origem, com orienta\u00e7\u00e3o especializada da Databricks.\nFase 4:\nPiloto de produ\u00e7\u00e3o\nExecute um piloto com seus casos de uso e use conversores de c\u00f3digo quando aplic\u00e1vel para transportar o c\u00f3digo legado para o c\u00f3digo compat\u00edvel com a Databricks. Desenvolva um plano de implementa\u00e7\u00e3o de migra\u00e7\u00e3o e um plano de a\u00e7\u00e3o.\nFase 5:\nExecu\u00e7\u00e3o\nRepeti\u00e7\u00e3o para todas as cargas de trabalho. Obtenha ajuda com a execu\u00e7\u00e3o da migra\u00e7\u00e3o e suporte de parceiros certificados ou servi\u00e7os profissionais Databricks.\nClientes que migraram com sucesso para a DatabricksHist\u00f3ria de clientePersonalizar o atendimento farmac\u00eautico para melhorar os resultados dos pacientes\nLeia maisBLOG DO CLIENTEEliminar on-prem totalmente, obtendo ganhos de economia de custos e acelerando o sucesso\nLeia maisHist\u00f3ria de clienteA migra\u00e7\u00e3o para a nuvem \u00e9 necess\u00e1ria em uma nova era de varejo orientado a dados\nLeia maisSolu\u00e7\u00f5es BrickbuilderAproveite as solu\u00e7\u00f5es Brickbuilder dos principais parceiros de consultoria criadas para migrar para o Databricks LakehouseMigra\u00e7\u00e3o de dados na nuvem pela AccentureMenos adivinha\u00e7\u00e3o, mais valor\nComece agoraMigra\u00e7\u00e3o do sistema legado por AvanadeMova seus dados para desbloquear seu valor total\nComece agoraMigra\u00e7\u00e3o para a nuvem e o Databricks com CapgeminiSimplifique a migra\u00e7\u00e3o de dados para a Plataforma Databricks Lakehouse\nComece agoraMigra\u00e7\u00e3o para Databricks com Celebal TechnologiesMigra\u00e7\u00e3o mais r\u00e1pida de on-premises a um custo menor\nComece agoraSolu\u00e7\u00e3o de migra\u00e7\u00e3o da LeapLogic com ImpetusTransforme automaticamente cargas de trabalho de ETL, data warehouse, an\u00e1lises e Hadoop em Databricks\nComece agoraAssistente de dados para migra\u00e7\u00f5es Hadoop\/EDW com InfosysTransfira seus dados com confian\u00e7a para o Databricks\nComece agoraMigra\u00e7\u00e3o de snowflake-to-Databricks com LovelyticsGaranta um processo de migra\u00e7\u00e3o r\u00e1pido e s\u00f3lido\nComece agoraAcelerador de migra\u00e7\u00e3o SAS com Tensile AISolu\u00e7\u00e3o de migra\u00e7\u00e3o desenvolvida pela Tensile AI e com tecnologia da Plataforma Databricks LakehouseComece agoraData Intelligence Suite com WiproMigre com confian\u00e7a para o Databricks\nComece agoraA sabedoria da transi\u00e7\u00e3o para uma estrat\u00e9gia de data lakehouseComo uma abordagem de data lakehouse pode ajudar sua empresa a superar as limita\u00e7\u00f5es comuns de data warehouses e data lakesBaixarRecursose-booksMigrating From Hadoop to Data Lakehouse for DummiesLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosGuia passo a passo para migra\u00e7\u00e3o do HadoopModernize seu data warehouseBlogsCinco etapas principais para uma migra\u00e7\u00e3o bem-sucedida do Hadoop para a arquitetura de lakehouseSete motivos para migrar de seu Hadoop baseado na nuvem para a Plataforma Databricks LakehouseComece agoraA migra\u00e7\u00e3o n\u00e3o precisa ser uma dor de cabe\u00e7a. Entre em contato conosco hoje para conversarmos sobre como sua empresa pode proceder.Experimente o Databricks gratuitamenteEntre em contato com DatabricksProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-johnson\/#","text":"Ryan Johnson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan JohnsonSenior Staff Engineer at DatabricksBack to speakersRyan Johnson is a Senior Staff Software Engineer and tech lead at Databricks, working with the Delta Lake table format at the boundary between the storage system and the query layer. Before joining Databricks, he worked on the storage layer at Amazon Redshift and previously did database systems research as a professor at the University of Toronto. He loves writing code and solving low-level systems problems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/improving-health-outcomes-with-data-and-ai","text":"Improving Health Outcomes With Data and AI - DatabrickseBookImproving Health Outcomes With Data and AIHow a modern data lakehouse can help you innovate in research and patient careHealthcare and life sciences are generating more data than ever \u2014 in the form of electronic medical records, genomics and medical imaging.But data teams at leading companies, such as Regeneron, CVS Health and Sanford Health, aren\u2019t struggling to keep up. Instead, they\u2019re using a modern data lakehouse to harness all their data and improve patient outcomes.Read this eBook to find out how:Sanofi reduced data processing costs by 30%Biogen analyzed 2 million genomic variants in under 15 minutesRegeneron reduced data processing time from 3 weeks to 5 hoursCVS Health increased medication adherence by nearly 2%Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeffrey-chou","text":"Jeffrey Chou - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey ChouCo-Founder, CEO at Sync ComputingBack to speakersJeff received his PhD in EECS from UC Berkeley as an NDSEG fellow, was a Battelle Post-Doctoral Scholar at MIT, and is an Entrepreneurial Research Fellow at Activate. Prior to Sync he was a technical staff member at MIT Lincoln Laboratory.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/product\/data-science","text":"Data Science | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWData ScienceData science colaborativa em escalaExperimente gratuitamenteAgendar uma demonstra\u00e7\u00e3oAprofunde-se na Ci\u00eancia de Dados no DatabricksDatabricks NotebooksIDE IntegrationsReposMachine LearningSimplifique o fluxo de trabalho de data science de ponta a ponta, da prepara\u00e7\u00e3o de dados \u00e0 modelagem e ao compartilhamento de insights, com um ambiente colaborativo e unificado criado em uma funda\u00e7\u00e3o aberta de\u00a0lakehouse. Obtenha acesso r\u00e1pido a dados confi\u00e1veis, recursos de computa\u00e7\u00e3o pr\u00e9-configurados,\u00a0integra\u00e7\u00e3o de IDE, compatibilidade com v\u00e1rias linguagens e ferramentas de visualiza\u00e7\u00e3o avan\u00e7adas integradas para flexibilidade m\u00e1xima de equipes de an\u00e1lise de dados.Colabora\u00e7\u00e3o em todo o fluxo de trabalho de data scienceEscreva c\u00f3digos em Python, R, Scala e SQL, explore dados com visualiza\u00e7\u00f5es interativas e descubra novos insights com notebooks da Databricks. Compartilhe c\u00f3digos com confian\u00e7a e seguran\u00e7a com coautoria, coment\u00e1rios, controle autom\u00e1tico de vers\u00f5es, integra\u00e7\u00f5es Git e controles de acesso baseados em fun\u00e7\u00e3o.Foco em data science, n\u00e3o em infraestruturaVoc\u00ea n\u00e3o precisa mais se limitar \u00e0 capacidade de armazenamento do seu computador ou pelo poder de processamento dispon\u00edvel para voc\u00ea. Migre rapidamente seu ambiente local para a nuvem e conecte notebooks a seus recursos de computa\u00e7\u00e3o pessoal e clusters gerenciados automaticamente.Use sua IDE local favorita com computa\u00e7\u00e3o escal\u00e1velA escolha de uma IDE \u00e9 muito pessoal e tem grande impacto na produtividade.\u00a0Conecte sua IDE favorita\u00a0 \u00e0 Databricks para continuar aproveitando o armazenamento e a capacidade de computa\u00e7\u00e3o ilimitados. Ou simplesmente use o RStudio ou o JupyterLab diretamente na Databricks para uma experi\u00eancia tranquila.Prepare seus dados para para data scienceLimpe e catalogue todos os seus dados \u2014 em batch,\u00a0streaming, estruturados ou n\u00e3o \u2014 em um s\u00f3 lugar com o\u00a0Delta Lake\u00a0e torne-os acess\u00edveis a toda a sua empresa por meio de um armazenamento de dados centralizado. Quando os dados chegam, as verifica\u00e7\u00f5es autom\u00e1ticas de qualidade garantem que eles atendam \u00e0s expectativas e estejam prontos para an\u00e1lise. \u00c0 medida que os dados s\u00e3o alimentados com novas entradas e transforma\u00e7\u00f5es adicionais, o controle de vers\u00f5es ajuda voc\u00ea a atender \u00e0s necessidades de conformidade.Ferramentas visuais com pouco c\u00f3digo para explorar dadosUse\u00a0ferramentas visuais\u00a0nativas em notebooks da Databricks para preparar, transformar e analisar seus dados. Capacite equipes de todos os n\u00edveis de habilidade para trabalhar com dados. Depois que suas transforma\u00e7\u00f5es e visualiza\u00e7\u00f5es de dados estiverem conclu\u00eddas, voc\u00ea pode gerar o c\u00f3digo que \u00e9 executado em segundo plano. Como n\u00e3o precisa mais escrever o c\u00f3digo base, voc\u00ea pode dedicar mais tempo a tarefas mais produtivas.Descubra e compartilhe novos insightsCompartilhe e exporte facilmente seus resultados, transformando com rapidez suas an\u00e1lises em \u00a0dashboards din\u00e2micos. Os dashboards s\u00e3o sempre atualizados e tamb\u00e9m podem executar queries interativas. C\u00e9lulas, visualiza\u00e7\u00f5es ou notebooks podem ser compartilhados com controle de acesso baseado em fun\u00e7\u00e3o e exportados em v\u00e1rios formatos, incluindo HTML e IPython Notebook.Migre para a DatabricksN\u00e3o aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA.Migre para a DatabricksRecursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre data science e machine learning.\nExplorar recursosRelat\u00f3rios e e-booksThe Big Book of Data ScienceThe Art of Collaborative Data Science at ScaleThe Modern Cloud Data PlatformMLflow \u2013 Uma plataforma de machine learning de c\u00f3digo abertoExplore a nova solu\u00e7\u00e3o de Delta SharingDatabricks nomeada l\u00edder no Gartner\u00ae Magic Quadrant\u2122 de 2021 para as categorias DBMS e DSMLGuia de migra\u00e7\u00e3o: Do Hadoop para DatabricksBlogsCinco etapas principais para uma migra\u00e7\u00e3o bem-sucedida do Hadoop para a arquitetura de lakehouseEventos virtuaisGuia passo a passo para migra\u00e7\u00e3o do HadoopTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dipankar-mazumdar\/#","text":"Dipankar Mazumdar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDipankar MazumdarDeveloper Advocate at DremioBack to speakersDipankar is currently a Developer Advocate at Dremio where his focus is helping data\/platform engineering teams on lakehouse platform & various open-sourced projects such as Apache Iceberg & Arrow that allows data teams to apply & scale analytics. In his past roles, he worked at the intersection of Machine Learning & Data visualization. Dipankar is a co-author of the upcoming O\u2019Reilly book on Apache Iceberg. He also holds a MS in Computer Science with research focused on ExplainableAI.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sidharth-kunnath","text":"Sidharth Kunnath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSidharth KunnathPrincipal Architect at American Airlines, IncBack to speakersOver 18 years of IT experience exclusively in designing and building enterprise data analytical solutions deployed over enterprise data warehouses and data lakes, both within on-premises and cloud (Azure)\nOver 4 years of experience implementing data analytics projects within Azure data analytical ecosystem, leveraging Azure services like Event Hub (AEH), Stream Analytics (ASA), Azure Functions (AF), Databricks (ADB) and Azure Datalake Storage (ADLS)\nExperience in defining enterprise data strategy and its physical implementation across the organization\nExperience in Application, Solution and Data Architecture, working both with technology and the business, translating between the two\nExperience in implementation of real-time data streaming layer using Azure streaming architecture as well as real-time data serving layer using APIs installed over NoSQL databases like Cassandra\nExtensive experience implementing data warehousing projects based on Teradata\nDomain knowledge of airline business including subject areas like revenue management & performance, customer loyalty, flight operations, inventory, maintenance & engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/huaxin-gao\/#","text":"Huaxin Gao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHuaxin GaoSoftware Engineer at AppleBack to speakersHuaxin Gao is an Apache Spark committer and a software engineer at Apple, focusing on Spark SQL. Prior to joining Apple, she worked on a number of SQL and ML projects at IBM.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dilip-biswal\/#","text":"Dilip Biswal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDilip BiswalSenior Architect at AdobeBack to speakersDilip Biswal is a Software Architect at Adobe working on Adobe Experience Platform. He is an active Apache Spark contributor and works in the open source community. He is experienced in Relational Databases, Distributed Computing and Big Data Analytics. He has extensively worked on SQL engines like Informix, Derby, and Big SQLLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/media-and-entertainment","text":"Media and Entertainment Solutions - Databricks Lakehouse - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for Media & EntertainmentPowering the data, analytics and AI-driven future of mediaGet startedSchedule a demoFour data challenges in media and entertainmentCreating a unified audience profile\nData captured, stored and managed in disparate systems prevents media organizations from having a full view of audience and advertiser data.Delivering an outstanding user experience\nConsumers expect frictionless 1:1 personalized experiences at all times, across their devices. The challenge is to deliver these experiences in real time, at scale.Maximizing all your media data\nLegacy data warehouses cannot handle unstructured data such as video, image and audio files, which prevents organizations from unlocking the full potential of their most valuable assets.Moving beyond aggregation to advanced analytics\nComplex AI use cases for the advertising and consumer lifecycle currently require the expensive acquisition and harmonization of massive data sets.Meet Data Lakehouse: The Best of Both Worlds in One PlatformA data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It\u2019s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all of your data and cloud platforms.Learn moreThe lakehouse in actionLearn how the Databricks Lakehouse empowers your unique industryAdvertising & Marketing TechnologiesManage margin and add data-focused rigor to operations, improve media performance, and optimize creative to streamline work for teams.Learn moreBroadcasting & StreamingCreate personalized 1:1 experiences at scale, improve advertising performance and optimization, and derive more value from your entire content portfolio.Learn moreGamingHarness data and AI to drive better game design, improve gamer acquisition and engagement, and increase player monetization and retention.Learn moreWhy Databricks for media and entertainmentAll of your data, analytics and AI on one platform\nExtract the full value of your data to power breakthroughs in audience engagement, monetization and advertising optimization.Optimized for real-time\nUncover actionable insights, drive 1:1 personalization and enhance your audience experience with machine learning at the core.Accelerate your business outcomes\nTap Solution Accelerators that make it easy to ingest consumer data \u2014 such as clickstream engagement \u2014 and deliver on use cases like recommendation engines and multi-touch attribution.Best-in-class reliability and performance\nThe Databricks Lakehouse offers unparalleled scale, speed and cost savings. It\u2019s no wonder the best data warehouse is a lakehouse.Transforming media and entertainment with the lakehouse\n\u201cWith Databricks Lakehouse Platform on AWS, Warner Bros. Discovery is powering the future of content discovery and audience experiences. By leveraging data to better predict consumer behavior and provide personalized content recommendations in real time, we are able to customize the viewer experience and improve overall engagement for our customers.\u201d\u2014 Martin Ma, GVP, Engineering at Warner Bros. DiscoveryExecutive insights on data, analytics and AILearn more about what other media and entertainment executives are doing to power their data strategyLearn moreWhat can you do with the lakehouse?\nAccelerate audience and advertiser outcomes on an open, collaborative platform for data, analytics and AI360\u00b0 view of your audience\nBring together all your structured and unstructured data \u2014 clickstream, demographic, social \u2014 in a single platform for analytics and AI. With a holistic view of the consumer journey, organizations can understand content preferences that help deliver more personalized experiences and develop more targeted advertising and engagement.Mitigate churn and increase ARPU\nWith an agile cloud-based platform, organizations can quickly and reliably process massive amounts of data and feed it to downstream systems to deliver a 1:1 experience on any channel at any time. As consumers\u2019 expectations around real-time recommendations keep rising \u2014 and media companies fight for consumer attention \u2014 ensuring that personalization approaches real time is becoming a requirement for many organizations.Drive revenue from a content library\nMedia companies are built on unstructured data like video, images and audio files, so the ability to analyze unstructured data is essential for effective media asset management. Lakehouse for M&E can be used by marketers to leverage archived content for campaigns, production teams looking for existing content to include in new productions and sales teams seeking IP they can sell to other media companies.Leverage pre-built models for ML\/AI. Put ML at the core of your business\nUnlock the power of machine learning to better understand consumer, employee and advertiser needs. When all your data is centralized and seamlessly connected by a full suite of collaborative analytics and machine learning tools, data teams can work together to build powerful predictive models that drive new innovations in personalization, content monetization and advertiser outcomes.Download the eBookPartners and solutions\nGet started with a variety of data and analytics solutions and templates specific to media and entertainment\nExplore our Partners PortalMulti-touch attributionMeasure ad effectiveness and optimize marketing spend with better channel attributionGet startedGamer\/user toxicityFoster healthier user communities with real-time detection of toxic language and behaviorGet startedSurvival analysis\/LTVPredict which consumers are at risk of churning and what factors extend the consumer lifecycleGet startedPropensity to churnEffectively manage retention, understand lifecycle and reduce your churn rateGet startedBehavioral segmentationCreate advanced segments to drive better purchasing predictions based on behaviorsGet startedSales forecasting and attributionIncrease advertising outcomes by optimizing and focusing on the best-performing channelsGet startedRecommendationsIncrease conversions and engagement with personalized omnichannel recommendationsGet startedComputer vision\/LabelboxAnnotate images and videos to help drive contextual ad targeting in the Lakehouse\n\u00a0\nComing soonVideo quality of experienceAnalyze batch and streaming data to ensure a performant streaming content experienceGet startedReal-time biddingLearn how to predict ad viewability in real time to enhance your RTB strategyGet startedSee all solutionsLakehouse for Media & Entertainment in actionResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on data, analytics and AI for Media & Entertainment\nExplore resourceseBookDownload nowWebinarsLearn moreBlogsLearn moreReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nicolas-pelaez","text":"Nicolas Pelaez - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNicolas PelaezTechnical Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/luyang-wang","text":"Luyang Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLuyang WangLead Distinguished Scientist at VerizonBack to speakersLu is a Lead Distinguished Scientist at Verizon, where he leads a cross functional team focus on developing large scale search & recommendation services.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-green\/#","text":"Michael Green - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael GreenSenior Data Scientist at Hitachi Solutions AmericaBack to speakersMichael holds a doctorate in artificial intelligence from NYU's Tandon School of Engineering. He's been researching artificial intelligence for more than 6 years, with successful projects using tree-search, evolutionary optimization, deep learning, and reinforcement learning techniques, with more than 25 peer-reviewed papers. \nToday, Michael works as a product manager and senior data scientist at Hitachi Solutions America, leading the AI initiative for the Empower Platform team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/gousto","text":"Customer Story: Gousto | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYStreamlining food delivery fulfillment to delight customers60%Infrastructure cost reduction40%Productivity benefit for data engineering delivery99.6%End-to-end ingestion time reduction INDUSTRY: Retail and consumer goods SOLUTION: Customer retention,customer segmentation,demand forecasting,ML-based item matching,subscriber churn prediction PLATFORM USE CASE: Lakehouse,Delta Lake,data science,machine learning,ETL CLOUD: AWS\u201cWe\u2019ve seen a 40% productivity uplift for data engineering \u2014 reducing the time it takes to develop new ideas from days to minutes and increasing the availability and accuracy of our data.\u201d\n\u2014 Shaun Pearce, Chief Technology Officer, GoustoThe COVID-19 pandemic has created a demand boom for eating in and new recipe subscription services, in ways that will change consumer habits once the crisis has passed. Within this increasingly crowded field of food services, Gousto is different: They\u2019ve always placed data at the very heart of their business to help them deliver exactly what the customer wants, every time and on time. Gousto doubled deliveries to 5 million recipe meals a month in the first half of 2020, but were held back by systems that couldn\u2019t ingest data fast enough, couldn\u2019t talk to each other and wouldn\u2019t scale. Just when the pandemic exploded demand, Gousto had to temporarily stop accepting new customers. Now, with Databricks in place, Gousto is set up to achieve exciting ambitions for menu expansion, sophisticated personalization and next-day delivery.Delivery potential limited by slow data ingestion and analysisGousto\u2019s mission is to change the way people eat through the delivery of boxes of fresh ingredients and easy-to-follow recipes. But the company is much more than a food delivery service. Gousto aims to leverage data and AI to create a more convenient and personalized experience for their customers. In the words of Gousto\u2019s Chief Technology Officer, Shaun Pearce, \u201cGousto is a data company that loves food.\u201d However, even before the massive pandemic-driven increase in demand, Gousto was at a crossroads. \u201cWe were at capacity. Demand was huge, but we couldn\u2019t scale the fulfillment supply chain,\u201d said Pearce.At Gousto, recipe boxes take a journey through a fulfillment center on a conveyor belt, past a series of stations where boxes stop for an agent to pack ingredients. An efficient journey means more boxes per hour. Detailed box ingredients and stock inventory data were being collected, but couldn\u2019t be analyzed quickly enough to optimize their route or anticipate ingredient availability. The ETL batch process was taking over two hours \u2014 if it worked \u2014 meaning Gousto was always looking back at historical data and relying on ad hoc observations to make strategic decisions for the business. This latency was impacting a key performance measure \u2014 on time in full (OTIF). \u201cWe knew we had to rethink our ETL to deliver production-line data in near real-time,\u201d said Eoin O\u2019Flanagan, who heads up data engineering at Gousto.Added to this, Gousto had disparate systems and data sources managing warehouse stock levels and ingredient replenishment at each pick station, so it was impossible to gain a unified view into the data without significant manual effort. \u201cThe systems were not designed for querying and analytics, and we needed visibility across the whole line to make efficiency improvements,\u201d said O\u2019Flanagan.The time wasted on troubleshooting failed data ingest batch jobs, and maintaining infrastructure was time taken away from developing the more sophisticated data analytics. \u201cWe needed to reduce infrastructure tasks so we could focus on collaborating to write code, not dealing with pipeline and EMR issues, so that new ideas could become a reality much faster,\u201d said O\u2019Flanagan. Gousto needed to move from daily batch updates using costly EMR to near real-time streaming data.Optimizing recipe box fulfillment to boost conversionGousto realized they needed a cost-effective cloud-based platform on AWS that would deliver on their current challenges and ambitions for the future. With the Databricks Lakehouse Platform in place, Gousto now enjoys a coherent view of supply chain events. Merging the incoming stream of pick station inventory-level data and warehouse-stock-level data into Delta Tables in Delta Lake, using Merge and CDC, has given Gousto visibility of pick-line status refreshed in near real-time, and agents have the right ingredients on their stations to pack their assigned boxes. \u201cGetting a near real-time view on inventory data is unlocking much more capability in our stock management, giving us a view on stock movement to the line and improved planning. We couldn\u2019t do it without Delta Lake,\u201d said O\u2019Flanagan.The Databricks platform also means Gousto now has the right tooling to spin up new clusters in minutes to work on new ideas without delay. \u201cData preparation time has reduced from 3 hours to 5 minutes. We can easily attach notebooks to prototype new features and debug issues, collaborate on the same data, and the feedback loop for trying out new code has gone down from 20 minutes to 20 seconds,\u201d said O\u2019Flanagan.Running a sequence of batch jobs used to be a complex pipeline with multiple points of failure for Gousto\u2019s data engineers, slowing their ability to feed clean data for downstream analytics to optimize their supply chain. Now, \u201cwe\u2019ve switched off the batch pipeline, and our supply chain ETL stack is 100% streaming, with no failures since deployment,\u201d said O\u2019Flanagan.Serving up success with near real-time insightsGousto now enjoys near real-time reporting on fulfillment center performance and inventory levels. End-to-end ingestion time has been reduced by 99.6% \u2014 a job that took two hours is down to 15 seconds, and the ingestion infrastructure costs have been reduced. \u201cNow we can drill down to see the reason for bottlenecks on the fulfillment line and optimize box routing and inventory slotting. It\u2019s a proactive rather than reactive approach,\u201d said O\u2019Flanagan. \u201cWhich is good news for our OTIF measure, even in times of record demand,\u201d said Pearce.The improved availability and accuracy of data mean Gousto can easily expand their customer fulfillment capacity \u2014 from two factories to four in the next year \u2014 and, as a bonus, this has also created significant infrastructure cost savings, the big one around EMR. \u201cThere\u2019s more data running in real-time but with no increase in costs versus EMR. Like for like, it works out as a 60% cost improvement,\u201d said O\u2019Flanagan.In fact, because Gousto tracks ticket metrics in every development sprint, they know there\u2019s been a 40% productivity benefit for data engineering delivery. \u201cWe have reduced the time it takes to develop new ideas from days to minutes and increased the availability and accuracy of our data,\u201d said Pearce.Databricks is helping Gousto deliver on today\u2019s known challenges and has Gousto ready for the unknown ones of the future \u2014 positioning the team to harness AI and ML and realize their objectives around menu personalization and next-day delivery. \u201cDatabricks has helped us take giant steps toward our ambitions. It\u2019s a platform with a huge potential,\u201d said Pearce.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/engineering-at-databricks","text":"Engineering at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWEngineering at DatabricksWork with the teams solving the world\u2019s toughest problemsSee open jobs OverviewCultureBenefitsDiversityStudents & new gradsMake an impact with our engineering teamsAt Databricks, we believe that we win by empowering our engineering teams to iterate rapidly from idea to production. Our engineering teams constantly push the boundaries of data and AI technology \u2014 while simultaneously operating with the resilience, security and scale that are critical to making customers successful on our platform.\nWe build highly technical products that enable data teams to solve the world\u2019s toughest problems, from cybersecurity threat detection to cancer drug development to pioneering the next mode of transportation.Learn more about the Data Team EffectLearn more about the Databricks Lakehouse PlatformDevelop with an innovative global teamFounded in 2013 by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks has grown from a tiny corner office in Berkeley, California, to a company with employees all over the world.\nDatabricks has since become the industry leader for data-driven decision-making with its cloud-based infrastructure, collaborative workspace, team-based version control, integrated libraries for data manipulation and visualization, Spark-compatible optimized runtime environment, and robust security.\nWorldwide openings\nThere are openings in our engineering centers in San Francisco, Mountain View, Seattle\/Bellevue, Amsterdam and Berlin - as well as remote opportunities worldwide - to continue our momentum.\nApply todayMeet the engineers of DatabricksWhat is mentorship like at Databricks?What is the most impactful project you\u2019ve worked on at Databricks?What is an unexpected reward you\u2019ve experienced as an engineer?Find out what inspires our engineersTo learn more, check out our Culture Blog and Technical BlogPlatform EngineeringThe platform teams are responsible for datacenter-scale infrastructure with millions of virtual machines under management, supporting hundreds of thousands of customers. These teams build scalable infrastructure for building, deploying, monitoring and operating fleets of services across multiple cloud platforms (AWS, GCP and Azure). Areas of focus include the core application architecture, distributed systems, networking, security and API infrastructure.Core Storage and Data ProcessingData Science ApplicationsSee open jobsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2019\/11\/20\/azure-databricks-highlights-adoption-of-delta-lake-mlflow-and-integration-with-azure-machine-learning-at-microsoft-ignite-2019.html","text":"Azure Databricks Momentum at Microsoft Ignite 2019Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAzure Databricks Highlights Adoption of Delta Lake, MLflow, and Integration with Azure Machine Learning at Microsoft Ignite 2019by Abhinav Garg and Clinton FordNovember 20, 2019 in Company BlogShare this postAt Microsoft Ignite 2019, thousands of attendees participated in hands-on workshops, breakout sessions, and theater presentations to learn how customers are achieving phenomenal results with Azure Databricks! It was an action-packed week of making new connections and learning about new innovation across data science, data engineering, and business analytics.\nWe shared the news that over 75% of data processed on Azure Databricks is in Delta Lake -- the new open source standard for data lakes. Hands-on labs and breakout sessions gave attendees an opportunity to see and experience Delta Lake on Azure Databricks first hand.\n\nDelta Lake\u2019s openness and extensibility enable faster innovation and more effective use of data. Azure Databricks has seen amazing growth over the past two years. This rapid growth has created the need for new tools and capabilities such as the MLflow Model Registry and ML lifecycle management which help customers track, deploy, and update their ML models. Attendees learned three ways Azure Databricks works with Azure Synapse Analytics to bring analytics, business intelligence (BI), and data science together in one solution architecture.\nAzure Databricks momentum and acceleration were highlighted in many sessions during the week of Ignite 2019. Below are just a few sessions to give you an idea of the breadth of customer use cases driving such phenomenal growth.\nAzure Databricks Sessions at Ignite 2019Delta Lake on Azure Databricks: Implementing a new open source standard for Data Lakes (THR2339) - Ajay Singh from Databricks shared how you can enhance your data lakes for greater value by adding new capabilities for transactions, version control and indexing using the latest open source innovations. Founded by the original creators of Apache Spark, Databricks has continued to innovate by launching a new open source project called Delta Lake designed to make existing data lakes more scalable and reliable. Built on top of infinitely scalable Azure Data Lake Storage and deeply integrated with Azure SQL Data Warehouse, Delta Lake on Azure Databricks makes data better prepared for analytic and machine learning workloads. Available today as part of Azure Databricks, see why large organizations are upgrading their data lake in-place with zero migration to Delta Lake!Managing your ML lifecycle with Azure Databricks and Azure Machine Learning (BRK3245) - Premal Shah from Microsoft and Mike Cornell from Databricks shared how machine learning development has new complexities beyond software development. There are a myriad of tools and frameworks which make it hard to track experiments, reproduce results, and deploy machine learning models. Learn how you can accelerate and manage your end-to-end machine learning lifecycle on Azure Databricks using MLflow and Azure ML to reliably build, share, and deploy machine learning applications using Azure Databricks.Hands-on with Azure Databricks Delta Lake (WRK2013) - In this lab, Kyle Weller, Premal Shah, Shiva Nimmagadda Venkata, and Santosh Perla from Microsoft guided attendees as they learned how to increase performance and reliability of their data engineering pipelines with Azure Databricks Delta Lake. Delta Lake provides optimized layouts to enable big data use cases, from batch and streaming ingests, fast interactive queries, to machine learning.Maximizing your Azure Databricks deployment (BRK3043) - Yatharth Gupta from Microsoft shared insights and key steps to get the most out of your Azure Databricks resources. Whether you\u2019re new to Spark or an Azure Databricks veteran, attend and learn the tips, tricks, and best practices for working with Azure Databricks. Based on experiences with real industry customers, these best practices cover deployments, management, security, networking, monitoring, machine learning, and more. See how the power of Azure Databricks\u2019 managed Spark experience can benefit your analytics pipeline!Azure Databricks and Azure Machine Learning better together (THR2186) - In this theater session, Premal Shah from Microsoft demonstrated the new integrations between Azure Databricks and Azure Machine Learning to realize comprehensive E2E machine learning scenarios for our customers.Data reproducibility, audits, immediate rollbacks and other applications of time travel with Delta Lake in Azure Databricks (BRK3254) - Time travel is now possible with Azure Databricks Delta Lake! Kyle Weller from Microsoft uncovered how Delta Lake makes time travel possible and why it matters to you. Through presentation, notebooks, and code, he showcased several common applications and how they can improve your modern data engineering pipelines. Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark(TM). It provides snapshot isolation for concurrent read\/writes. Enables efficient upserts, deletes, and immediate rollback capabilities. It allows background file optimization through compaction and z-order partitioning achieving up to 100x performance improvements. In this presentation, learn what challenges Delta Lake solves, how Delta Lake works under the hood, and applications of the new Delta Time Travel capability.Get Started with Azure DatabricksThe fun doesn\u2019t stop there! Keep learning more:\nWebinars\nCheck out our on-demand webinar, From Data to AI with Microsoft Azure Databricks, where you will see how to accelerate your data and AI journey end-to-end with Azure Databricks and our natively integrated data services on Azure. Then see how to accelerate and manage your end-to-end machine learning lifecycle with Azure Databricks\u2014using MLflow and Azure Machine Learning to build, share, deploy, and manage machine learning applications.Try Azure Databricks\nGet started with Azure Databricks. Sign up for an Azure free account to get instant access. Continue your learning by using Azure Databricks directly.Talk to an expertContact us get answers to questions you might have as you start your first project or to learn more about available training.Follow us on Twitter, LinkedIn, and Facebook for more Azure Databricks news, customer highlights, and new feature announcements.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/12\/17\/enabling-computer-vision-applications-with-the-data-lakehouse.html","text":"How to Enable Computer Vision on a Lakehouse, Part 1 - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorEnabling Computer Vision Applications With the Data Lakehouseby Paulo Borges, Bala Amavasai and Bryan SmithDecember 17, 2021 in Engineering BlogShare this postThe potential for computer vision applications to transform retail and manufacturing operations, as explored in the blog Tackle Unseen Quality, Operations and Safety Challenges with Lakehouse enabled Computer Vision, can not be overstated. That said, numerous technical challenges prevent organizations from realizing this potential. In this first introductory installment of our multi-part technical series on the development and implementation of computer vision applications, we dig deeper into these challenges and explore the foundational patterns employed for data ingestion, model training and model deployment.The unique nature of image data means we need to carefully consider how we manage these information assets, and the integration of trained models with frontline applications means we need to consider some non-traditional deployment paths. There is no one-size-fits-all solution to every computer vision challenge, but many techniques and technologies have been developed by companies who've pioneered the use of computer vision systems to solve real-world business problems. By leveraging these, as explored in this post, we can move more rapidly from demonstration to operationalization.Data ingestionThe first step in the development of most computer vision applications (after design and planning) is the accumulation of image data. Image files are captured by camera-enabled devices and transmitted to a central storage repository, where they are prepared for use in model training exercises.It's important to note that many of the popular formats, such as PNG and JPEG, support embedded metadata. Basic metadata, such as image height and width, supports the conversion of pixel values into two-dimensional representations. Additional metadata, such as Exchange Information File Format (Exif) metadata, may be embedded as well to provide additional details about the camera, its configuration, and potentially its location (assuming the device is equipped with GPS sensors).When building an image library, metadata as well as image statistics, useful to data scientists as they sift through the thousands or even millions of images typically accumulating around computer vision applications, are processed as they land in Lakehouse storage. Leveraging common open-source libraries such as Pillow, both metadata and statistics can be extracted and persisted to queryable tables in a Lakehouse environment for easier access. The binary data comprising the image may also be persisted to these tables along with path information for the original file in the storage environment.Model trainingThe size of the individual image files combined with the large number of them needed to train a robust model means that we need to carefully consider how they will be handled during model training. Techniques commonly used in data science exercises such as collecting model inputs to a pandas dataframe will not often work at an enterprise scale due to memory limitations on individual computers. Spark\u2122 dataframes, which distribute the data volumes over multiple computer nodes configured as a computing cluster, are not accessible by most computer vision libraries so another solution to this problem is needed.\nTo overcome this first model training challenge, Petastorm, a data caching technology built specifically for the large-scale training of advanced deep learning model types, can be used. Petastorm allows retrieval of large volumes of data from the Lakehouse and places it in a temporary, storage-based cache. Models leveraging Tensorflow and PyTorch, the two most popular libraries for deep neural network development and commonly employed in computer vision applications, can read small subsets of data in batches from the cache as they iterate over the larger Petastorm dataset.With data volumes manageable, the next challenge is the acceleration of the model training itself. Machine learning models learn through iteration. This means that training will consist of a series of repeated passes over the input dataset. With each pass, the model learns optimized weights for various features that lead to better prediction accuracy.The model's learning algorithm is governed by a set of parameters referred to as hyperparameters. The values of these hyperparameters are often difficult to set based on domain knowledge alone, and so the typical pattern for discovering an optimal hyperparameter configuration is to train multiple models to determine which performs best. This process, referred to as hyperparameter tuning, implies iterations on top of iterations.The trick to working through so many iterations in a timely manner is to distribute the hyperparameter tuning runs across the cluster's compute nodes so that they may be performed in a parallel manner. Leveraging Hyperopt, these runs can be commissioned in waves, between which the Hyperopt software can evaluate which hyperparameter values lead to which outcomes and then intelligently set the hyperparameter values for the next wave. After repeated waves, the software converges on an optimal set of hyperparameter values much faster than if an exhaustive evaluation of values were to have been performed.Once the optimal hyperparameter values have been determined, Horovod can be used to distribute the training of a final model across the cluster. Horovod coordinates the independent training of models on each of the cluster's compute nodes using non-overlapping subsets of the input training data. Weights learned from these parallel runs are consolidated with each pass over the full input set, and models are rebalanced based on their collective learning. The end result is an optimized model, trained using the collective computational power of the cluster.Model deploymentWith computer vision models, the goal is often to bring model predictions into a space where a human operator would typically perform a visual inspection. While centralized scoring of images in the back office may make sense in some scenarios, more typically, a local (edge) device will be handed responsibility for capturing an image and calling the trained model to generate scored output in real time. Depending on the complexity of the model, the capacity of the local device and the tolerance for latency and\/or network disruptions, edge deployments typically take one of two forms.With a microservices deployment, a model is presented as a network-accessible service. This service may be hosted in a centralized location or across multiple locations more closely aligned with some number of the edge devices. An application running on the device is then configured to send images to the service to receive the required scores in return. This approach has the advantage of providing the application developer with greater flexibility for model hosting and access to far more resources for the service than are typically available on an edge device. It has the disadvantage of requiring additional infrastructure, and there is some risk of network latency and\/or disruption affecting the application.With an edge deployment, a previously trained model is sent directly to the local device. This eliminates concerns over networking once the model has been delivered, but limited hardware resources on the device can impose constraints. In addition, many edge devices make use of processors that are significantly different from the systems on which the models are trained. This can create software compatibility challenges, which may need to be carefully explored before committing resources to such a deployment.In either scenario, we can leverage MLflow, a model management repository, to assist us with the packaging and delivery of the model.Bringing it all together with DatabricksTo demonstrate how these different challenges may be addressed, we have developed a series of notebooks leveraging data captured from a PiCamera-equipped Raspberry Pi device. Images taken by this device have been transmitted to a cloud storage environment so that these image ingestion, model training and deployment patterns can be demonstrated using the Databricks ML Runtime, which comes preconfigured with all the capabilities described above. To see the details behind this demonstration, please refer to the following notebooks:Get the notebookTry Databricks for freeGet StartedRelated postsEnabling Computer Vision Applications With the Data LakehouseDecember 17, 2021 by Paulo Borges, Bala Amavasai and Bryan Smith in Engineering Blog\nThe potential for computer vision applications to transform retail and manufacturing operations, as explored in the blog Tackle Unseen Quality, Operations and Safety...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/cloud-partners","text":"Databricks \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4 \uc81c\uacf5\uc5c5\uccb4 \ud30c\ud2b8\ub108 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \u0000\u0000\uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 \ubaa8\ub4e0 \uc8fc\uc694 \ud37c\ube14\ub9ad \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc2e4\ud589\ub418\uba70, \ud074\ub77c\uc6b0\ub4dc \uacf5\uae09\uc5c5\uccb4\uac00 \uae30\ubcf8\uc801\uc73c\ub85c \uc81c\uacf5\ud558\ub294 \ubcf4\uc548, \ucef4\ud4e8\ud305, \uc2a4\ud1a0\ub9ac\uc9c0, \ubd84\uc11d, AI \uc11c\ube44\uc2a4\uc640 \uae34\ubc00\ud788 \ud1b5\ud569\ub429\ub2c8\ub2e4. \uc774\ub294 \uc5b4\ub514\uc11c\ub098 \uc5b4\ub5a4 \ubc29\uc2dd\uc73c\ub85c\ub4e0 \uc6d0\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc81c\uacf5\uc5c5\uccb4\ub97c \ud65c\uc6a9\ud558\uae30 \uc704\ud55c \ubbfc\ucca9\uc131\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.Azure Databricks\ub294 Databricks\uc640 Microsoft\uac00 \uacf5\ub3d9\uc73c\ub85c \uac1c\ubc1c\ud55c \uc790\uccb4 \uc11c\ube44\uc2a4\uc785\ub2c8\ub2e4. Azure Portal\uc5d0\uc11c \ud074\ub9ad \ud55c \ubc88\uc73c\ub85c \uc2dc\uc791\ud558\uba74, Azure \ubcf4\uc548 \ubc0f \ub370\uc774\ud130 \uc11c\ube44\uc2a4\uc640 \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569\ub429\ub2c8\ub2e4.\uc790\uc138\ud788AWS \uae30\ubc18 Databricks\ub97c \uc0ac\uc6a9\ud558\uba74 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc640 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uc7a5\uc810\uc744 \uacb0\ud569\ud55c \uac04\ub2e8\ud55c \uac1c\ubc29\ud615 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \uc800\uc7a5\ud558\uc5ec \uad00\ub9ac\ud558\uace0, \ubaa8\ub4e0 \ubd84\uc11d \ubc0f AI \uc6cc\ud06c\ub85c\ub4dc\ub97c \ud1b5\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788Google Cloud\uc758 Databricks\ub294 Google Cloud Storage, BigQuery \ubc0f Google Cloud AI \ud50c\ub7ab\ud3fc\uacfc \uae34\ubc00\ud55c \ud1b5\ud569\uc73c\ub85c \uc624\ud508 \ud074\ub77c\uc6b0\ub4dc\uc5d0 \uac1c\ubc29\ud615 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uc81c\uacf5\ud558\uc5ec \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4, \ubd84\uc11d\uc744 \ud1b5\ud569\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ud074\ub77c\uc6b0\ub4dc \ub9ac\uc804\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0\u25cfAlibaba\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/cloud-partners","text":"Partenaire fournisseur de services cloud Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires cloud DatabricksLakehouse de Databricks fonctionne sur tous les principaux clouds publics, en \u00e9tant \u00e9troitement int\u00e9gr\u00e9 aux services de s\u00e9curit\u00e9, de calcul, de stockage, d'analytique et d'IA propos\u00e9s en mode natif par les fournisseurs de cloud. Vous disposez ainsi de la souplesse n\u00e9cessaire pour tirer parti du fournisseur de cloud de votre choix, quand et comme vous le souhaitez.Azure Databricks est un service de premi\u00e8re main d\u00e9velopp\u00e9 conjointement par Databricks et Microsoft. Commencez par un simple clic dans le portail Azure et int\u00e9grez en mode natif les data services et services de s\u00e9curit\u00e9 Azure.En savoir plusDatabricks sur AWS vous permet de stocker et de g\u00e9rer toutes vos donn\u00e9es\u00a0S3 sur une plateforme lakehouse simple et ouverte qui combine le meilleur des data warehouses et des data lakes pour unifier toutes vos charges de travail d'analytique et d'IA.En savoir plusDatabricks sur Google Cloud apporte la plateforme lakehouse ouverte au cloud ouvert pour unifier le data engineering, la data science et l'analytique, avec une int\u00e9gration \u00e9troite \u00e0 Google Cloud Storage, BigQuery et \u00e0 la plateforme d'IA Google Cloud.En savoir plusR\u00e9gions cloud\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0\u25cfAlibabaProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=marketing","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal\/aup","text":"Acceptable Use Policy | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAcceptable Use PolicyAcceptable Use Policy for the paid (including trial) version of DatabricksAcceptable Use Policy for Databricks Community EditionProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/big-book-of-machine-learning-use-cases","text":"The Big Book of Machine Learning Use Cases | DatabrickseBookThe Big Book of Machine Learning Use Cases \u2013 2nd EditionYour complete how-to guide to putting machine learning to work \u2014 plus use cases, code samples and notebooksThe world of machine learning is evolving so quickly that it\u2019s challenging to find real-life use cases that are relevant to your day-to-day work.That\u2019s why we\u2019ve created this comprehensive guide you can start using right away. Get everything you need \u2014 use cases, code samples and notebooks \u2014 so you can start putting the Databricks Lakehouse Platform to work today.Plus, you\u2019ll get case studies from leading companies like Comcast, Regeneron and Nationwide.Learn how to:Improve on-shelf availability with out of stock modelingMake real-time decisions in professional sports using quantitative modelingUse dynamic time warping and MLflow to detect sales trends seriesPerform multivariate time series forecasting with recurrent neural networksAccess new product capabilities with demosDetect financial fraud at scale with decision trees and MLflow on DatabricksDownload your copyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yeshwanth-vijayakumar","text":"Yeshwanth Vijayakumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYeshwanth VijayakumarSr Engineering Manager\/Architect at AdobeBack to speakersYeshwanth Vijayakumar is a Sr Engineering Manager\/Architect on the Unified Profile Team in the Adobe Experience Platform; it\u2019s a PB scale store with a strong focus on millisecond latencies and analytical abilities and easily one of Adobe\u2019s most challenging SaaS projects in terms of scale. He is actively designing\/implementing the Interactive segmentation capabilities which helps us segment over two million records per second using Apache Spark. He looks for opportunities to build new features using interesting data Structures and Machine Learning approaches. In a previous life, he was a ML Engineer on the Yelp Ads team building models for Snippet Optimizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-castle","text":"Scott Castle - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott CastleChief Strategy Officer at SisenseBack to speakersScott Castle is Chief Strategy Officer for Sisense, leading go-to-market, cloud, messaging and business strategy. He brings more than 25 years of experience in software development and product management at leading technology companies including Adobe, Periscope Data, Electric Cloud (acquired by Cloudbees), and FileNet (acquired by IBM).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/hls-resources\/watch-lakehouse-for-hls","text":"\n\n\n\n\n\n\n\nLakehouse for Healthcare and Life Sciences Video\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/06\/29\/celebrating-pride-month-at-databricks.html","text":"LGBTQ Pride Month at Databricks - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorCelebrating Pride Month at Databricksby Jess Chace and Stacy KerkelaJune 29, 2020 in Company BlogShare this postWith Pride month coming to an end, Databricks\u2019 newest Employee Resource Group, Queeries Network, is looking back at how we celebrated. The mission of this group is to create opportunities to come together to discuss topics important to the LGBTQ+ community, network and build community. To celebrate Pride Month, our Queeries Network Employee Resource Group hosted virtual pride socials, participated in virtual pride parades across the globe, and had dialogues around the history of Pride and the intersections with current events impacting the Black community.\nWhen we look back at how Pride started, from the Stonewall uprising to what is now an international celebration of the LGBTQ+ community and their contributions to the world, there has been a lot of progress in the fight for gay rights and equality, but there is also more we can do.\nAs we continue this reflection, we\u2019ve asked a few Bricksters, who have made amazing contributions to Databricks, for their thoughts on how we can all create a more inclusive workspace that encourages everyone to bring their authentic self to work. Read more below.\u00a0\nHow can we create an environment that encourages everyone to be their authentic self and do their best work?\nOne of our core values at Databricks is to be customer obsessed, which at first glance, can sound like a narrow and hyperfocused attention to a singular goal. In practice, what I think it actually means is to be genuinely curious about our customers \u2014 to struggle along with them in their challenges and to celebrate in their victories. I think the same applies to how we treat each other. Taking the time to be genuinely curious about someone\u2019s lived experience is hard because it requires a willingness to not have all the answers. But when we spend time and energy investing in and learning from each other, that\u2019s when, in my experience, real success is realized.\n \u2014 Jess Chace (she\/her), Customer Success Engineer (New York)\nIt\u2019s critical to show everyone in the company, particularly the newer members who might have less confidence, that there are many ways to be, to find personal success, and to develop as an individual. Offices are usually pretty homogeneous. We have to raise up the less obvious people in our midst, to showcase the realities and the successes of people of all colours, creeds, kinds, sexual and gender identities. A lot of people I speak to who don\u2019t fit naturally into the white, male, heteronormative milieu will talk about the first time they met someone who was different, but successful in their own way. Someone they wanted to emulate. That\u2019s powerful \u2014 to show that there are many paths, all of them perfectly valid. It creates new leaders, and it creates the foundation for the next generation of difference and variety, of authenticity.\n \u2014 Rob Anderson (he\/him), Director of Field Engineering (London)\nI start by focusing on the details of things like inclusive language, especially within an interview setting. Those early interactions are some of the most stressful moments in anyone\u2019s life, we shouldn\u2019t make them more difficult. I\u2019ve been particularly thoughtful about my choice of words while answering questions during the hiring process about the challenges of relocating with a partner or family or when discussing parental benefits. I\u2019ve had some people mention, after joining Databricks, how significant these small choices were to them as a signal of our values.\n \u2014 Stacy Kerkela (she\/her), Director of Engineering (Amsterdam)\nCreating an environment at work for Bricksters to be their most authentic selves is critical to building an inclusive and collaborative culture.\u00a0 Being \u201cauthentic\u201d might seem like a simple concept; however, many individuals from marginalized backgrounds are oftentimes code switching or shrinking pieces of themselves to fit into the majority culture. One of our company values that is most salient to me is: Teamwork makes the dream work. To promote authenticity within the workplace, we should encourage our team members to build genuine connections with one another, amplify our strengths and, most importantly, actively listen and promote empathy \u2014 even during challenging or unpredictable times.\u00a0\n As a queer Black femme, who holds many other marginalized identities, oftentimes I am navigating various environments and interacting with diverse audiences and stakeholders. I am always looking to build strong partnerships and bring my authentic self to interactions with candidates, colleagues and executives.\u00a0 Promoting an inclusive environment where trust and vulnerability are at the core is extremely important for me to do my best work and feel supported in doing so.\u00a0\n \u2014 Kaamil Al-Hassan (she\/her), Talent Acquisition (San Francisco)How does focusing on nurturing this inclusive environment help us have a greater impact at Databricks and in our communities?\nAnother one of our core values at Databricks is to let the data decide, and it\u2019s no secret that having a more diverse and inclusive work environment correlates with many positive business outcomes like higher innovation revenues, greater market share and greater returns to shareholders. The true value of promoting diversity and inclusion, however, is so much more than monetary gains. When our work reflects the voices and minds of our actual communities, it is better positioned to serve us all.\n \u2014 Jess Chace (she\/her), Customer Success Engineer (New York)\nDatabricks is a member of the technology community, where there is a great opportunity to continue to increase the representation of women, ethnic minorities, and people of various ages as well as sexual and gender identities. I believe that we will make the biggest impact by investing in how we hire diverse teams and support the incredible talent from these under-represented groups. There is a lot we can do to have a big impact on our companies and our communities at large.\n \u2014 Rob Anderson (he\/him), Director of Field Engineering (London)\nAt Databricks, I build teams that I would want to belong to. That means having the safety to be my authentic self and providing that same comfort zone to everyone around me. This year as entire companies have moved to work-from-home models, there\u2019s a lot of visibility into all of our home lives that makes it impossible for me to live less openly. Engaging with teammates via video calls at home can make it difficult to create separate home and work identities, especially for members of the LGBTQ+ community. It is important that we focus on creating an inclusive culture so everyone can feel comfortable and confident being their authentic selves and doing their best work without the stress or anxiety of wondering if they will be accepted. The impact of that care we show for one another and our dedication to inclusion is huge for our entire community.\u00a0\n \u2014 Stacy Kerkela (she\/her), Director of Engineering (Amsterdam)\nBeing queer means that every day I am \u201dcoming out.\u201d\u00a0 When I go to the grocery store with my partner, when someone inquires about my \u201dboyfriend,\u201d or when I attend our company holiday party and my partner is slaying in her tuxedo but is also wearing makeup. Coming out is not a singular moment. Creating an inclusive culture includes feeling supported by my colleagues and exemplifying my authentic queer self.\n Our impact will be even greater when we invite members of the LGBTQ+ community to join our global teams through investing in targeted outreach events. Building an inclusive culture means exploring the possibility of gender-neutral bathrooms and encouraging pronoun usage in everyday conversations. I am excited for us to celebrate Pride and for the resilience of this particular community that is still fighting every day for equal rights and visibility. I look forward to getting more involved in the newly formed LGBTQ+ ERG and exploring ways to create inclusivity and highlight the queer experience here at Databricks.\u00a0\u00a0\u00a0\u00a0\n \u2014 Kaamil Al-Hassan (she\/her), Talent Acquisition (San Francisco)It was great to launch our Queeries Network Employee Resource Group and celebrate Pride Month together. To learn more about how you can join us, check out the Careers page.\u00a0Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/03\/30\/creating-growth-and-advancement-opportunities-introducing-the-women-in-tech-mentorship-program.html","text":"Databricks\u2019 Women in Tech Mentorship Program - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorCreating Growth and Advancement Opportunities: Introducing the Women in Tech Mentorship Programby Alexandra Bellogini, Christina Patel and Samantha MenotMarch 30, 2021 in Company BlogShare this postAt Databricks, we recognize the importance of offering professional growth and advancement opportunities for all communities and are committed to fostering a work environment where every employee can contribute the best work of their careers.\nThis week, we\u2019re wrapping up our celebration of\u00a0 Women\u2019s History Month. In alignment with our commitment to employee growth, we wanted to highlight our newly launched global Women in Tech Mentorship pilot program. We strongly believe that mentorship is a key piece to driving more career advancement, especially for women in technology and STEM fields such as computer science. With this growth mindset, as well as direct feedback from our employees, we're proud to launch this program.\nThe objective of the mentorship program is to support the professional development of women across the company while building a community and support network within all functions and geographies. The initiative is a 6-month long program consisting of two main components: monthly group sessions with the entire cohort and monthly individual mentoring sessions with an assigned role model.\nTo assess the value of the program, participants were asked to complete a pre-program survey to clarify their current understanding of the topics mentioned above. Over the course of the program, participants will be asked to complete a monthly survey and final questionnaire once the program has come to a close.\nLearn more about our employee perspectives on mentorship in this conversation between a current program pairing: mentee Samantha Menot (Senior Customer Growth Program Manager) and mentor Alexandra Bellogini (Manager, Technical Solutions):\u00a0What is the most valuable aspect of participating in a mentorship program at Databricks?\u00a0Sam: For me, I\u00a0 think it\u2019s being able to build relationships with people who we wouldn\u2019t normally connect with back in the office. It gives us great networking opportunities. That\u2019s definitely the number one reason why I decided to join the mentorship program.\nAlex: I would agree with you Sam. The most valuable part of this program is having the opportunity to connect with others outside of our own team. I also love having the opportunity to mentor and being able to share my own experiences with you and watch you grow in your career.\nOut of the topics we are covering during the program, such as personal branding and negotiating, which one are you most passionate about and why?\u00a0Sam: I would definitely like to learn more about negotiating, as I have only really thought about negotiating a few times in my career. I am still learning how to go into a negotiation, what makes a strong negotiator and how to present and position yourself in a negotiation.\nAlex: Negotiating is a big area I would like to learn more about also, but personal branding is an important one for me. It\u2019s great to have the opportunity to really stop and think about who I am now and what I want to be, as personal branding is something that shifts throughout your career.\nWhat do you hope to learn from each other during this experience?Sam: Based on the first couple of sessions that we\u2019ve had, I\u2019m looking forward to learning more about personal branding. I\u2019m trying to figure out what my brand is right now and what I would like it to be. It\u2019s been helpful being able to have an honest conversation with [Alex], and to hear about the experiences you have had within your own career.\nAlex: One of the biggest parts and for me as a mentor is to learn from you and the experiences you have had. I think it\u2019s important to hear about how you have dealt with certain situations in your career and to compare them to my own similar situations in order to understand what could have been done better. I\u2019m also interested in hearing about your role, how you interact with others and the challenges you face, and what I can learn from that.\nOur goal is for the program to serve as a valuable tool in providing guidance, advocacy and navigation through important career milestones. As the Women in Tech mentorship program continues to grow, we look forward to hearing about the continued positive impact it will have for both mentors and mentees across the company.\nInterested in joining Databricks?Visit our careers page to explore our global opportunities and to learn more about how you can join our Databricks community.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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Catalog\u00a0\u3068\u306e\u30cd\u30a4\u30c6\u30a3\u30d6\u306a\u7d71\u5408\u306b\u3088\u308a\u3001\u7d44\u7e54\u9593\u306e\u5171\u6709\u30c7\u30fc\u30bf\u3092\u4e00\u5143\u7ba1\u7406\u3001\u76e3\u8996\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30a2\u30bb\u30c3\u30c8\u3092\u30d9\u30f3\u30c0\u30fc\u3084\u30d1\u30fc\u30c8\u30ca\u30fc\u3068\u30bb\u30ad\u30e5\u30a2\u306b\u5171\u6709\u3057\u3066\u9023\u643a\u3092\u5f37\u5316\u3059\u308b\u3068\u540c\u6642\u306b\u3001\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u304a\u3088\u3073\u30b3\u30f3\u30d7\u30e9\u30a4\u30a2\u30f3\u30b9\u306e\u8981\u4ef6\u3092\u6e80\u305f\u3057\u307e\u3059\u3002\u307e\u305f\u3001\u4e3b\u8981\u306a\u30c4\u30fc\u30eb\u3084\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3068\u306e\u7d71\u5408\u306b\u3088\u308a\u3001\u4efb\u610f\u306e\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u305f\u5171\u6709\u30c7\u30fc\u30bf\u306e\u8996\u899a\u5316\u3001\u30af\u30a8\u30ea\u3001\u30a8\u30f3\u30ea\u30c3\u30c1\u30e1\u30f3\u30c8\u3001\u30ac\u30d0\u30ca\u30f3\u30b9\u304c\u53ef\u80fd\u3067\u3059\u3002\u8d85\u9ad8\u901f\u6027\u80fdApache Spark\u2122 \u3092\u57fa\u76e4\u3068\u3059\u308b Delta Lake \u306f\u3001\u5927\u898f\u6a21\u306a\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u3068\u9ad8\u901f\u6027\u3092\u5b9f\u73fe\u3057\u307e\u3059\u3002\u6027\u80fd\u3092\u5de6\u53f3\u3059\u308b\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u6a5f\u80fd\u306a\u3069\u306e\u6700\u9069\u5316\u306b\u3088\u308a\u3001ETL \u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u304c\u6700\u5927 48 \u500d\u9ad8\u901f\u5316\u3057\u305f\u3053\u3068\u304c\u5b9f\u8a3c\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30aa\u30fc\u30d7\u30f3\u3001\u30a2\u30b8\u30e3\u30a4\u30ebDelta Lake \u306e\u30c7\u30fc\u30bf\u306f\u30aa\u30fc\u30d7\u30f3\u306a Apache Parquet \u5f62\u5f0f\u3067\u4fdd\u5b58\u3055\u308c\u308b\u305f\u3081\u3001\u3042\u3089\u3086\u308b\u4e92\u63db\u30ea\u30fc\u30c0\u30fc\u3067\u8aad\u307f\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002API \u306f\u30aa\u30fc\u30d7\u30f3\u3067\u3001Apache Spark \u3068\u4e92\u63db\u6027\u304c\u3042\u308a\u3001\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u5909\u66f4\u306f\u6700\u5c0f\u9650\u3067\u3059\u307f\u307e\u3059\u3002Databricks \u3067 Delta Lake \u3092\u5229\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u5e83\u7bc4\u306a\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3078\u306e\u30a2\u30af\u30bb\u30b9\u304c\u53ef\u80fd\u306b\u306a\u308a\u3001\u72ec\u81ea\u5f62\u5f0f\u306b\u3088\u308b\u30c7\u30fc\u30bf\u306e\u30ed\u30c3\u30af\u30a4\u30f3\u3092\u56de\u907f\u3067\u304d\u307e\u3059\u3002\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u81ea\u52d5\u5316\u3068\u9ad8\u4fe1\u983c\u6027Delta Live Tables \u304c Delta Lake \u306e\u30c7\u30fc\u30bf\u3092\u6700\u65b0\u304b\u3064\u9ad8\u54c1\u8cea\u306b\u4fdd\u3064\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u30fb\u7ba1\u7406\u3092\u5bb9\u6613\u306b\u3057\u3001\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3057\u307e\u3059\u3002\u307e\u305f\u3001\u5ba3\u8a00\u578b\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u958b\u767a\u3001\u9ad8\u4fe1\u983c\u6027\u30c7\u30fc\u30bf\u3001\u30af\u30e9\u30a6\u30c9\u30b9\u30b1\u30fc\u30eb\u306e\u672c\u7a3c\u50cd\u74b0\u5883\u304c\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u57fa\u76e4\u306e\u69cb\u7bc9\u3092\u53ef\u80fd\u306b\u3057\u3001\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306b\u3088\u308b ETL \u306e\u958b\u767a\u30fb\u7ba1\u7406\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3057\u307e\u3059\u3002\u5927\u898f\u6a21\u904b\u7528\u306e\u305f\u3081\u306e\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u3068\u30ac\u30d0\u30ca\u30f3\u30b9Delta Lake 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
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\ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/explainable-ai","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/leadership-team","text":"\u00c9quipe de direction | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLeadershipAvec une vision \u00e0 long terme, notre \u00e9quipe de direction s'appuie sur des d\u00e9cennies d'exp\u00e9rience pour mettre en place une nouvelle voie pour les donn\u00e9es et l'IAD\u00e9couvrez notre \u00e9quipe\u00c9quipe de directionFoundersConseil d'administrationAli GhodsiCofondateur et directeur g\u00e9n\u00e9ralAndy KofoidPresident, Global Field OperationsDavid ConteDirecteur financierAmy ReichanadterDirecteur des ressources humainesTr\u00e2m PhiSVP, General CounselRon GabriskoChief Revenue OfficerRick SchultzDirecteur marketingHatim ShafiqueDirecteur des op\u00e9rationsFerm\u00edn SernaDirecteur de la s\u00e9curit\u00e9Naveen ZutshiDSIVinod MarurSVP of EngineeringDavid MeyerSVP of ProductsAdam ConwaySVP of ProductsArsalan Tavakoli-ShirajiCofondateur, SVP of Field EngineeringProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/miao-wang\/#","text":"Miao Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMiao WangSenior Engineering Manager at AdobeBack to speakersMiao is a Senior Engineering Manager at Adobe, where he works with a great team on platform engineering with Spark and other open-source technologies. He was an active Spark contributor before changing to his manager role. His interests span high-speed networks, data center infrastructure, data processing, and machine learning. Prior to joining Adobe, he worked at A10 Networks, IBM, and Alibaba in various engineering roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/data-vault","text":"What is a Data Vault?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData VaultAll>Data VaultTry Databricks for freeGet StartedWhat is a data vault?A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.Hubs represent core business concepts, links represent relationships between hubs, and satellites store information about hubs and relationships between them.The data vault is a data model that is well-suited to organizations that are adopting the lakehouse paradigm.Data vault modeling: Hubs, links, and satellitesHubs - Each hub represents a core business concept, such as they represent Customer Id\/Product Number\/Vehicle identification number (VIN). Users will use a business key to get information about a Hub. The business key may have a combination of business concept ID and sequence ID, load date, and other metadata information.Links - Links represent the relationship between Hub entities.Satellites - Satellites fill the gap in answering the missing descriptive information on core business concepts. Satellites store information that belongs to Hub and relationships between them.A few additional things to keep in mind:A satellite cannot have a direct connection to another satellite.A hub or link may have one or more satellites.Data vault benefitsAgileStructured, with flexibility for refactoringExtremely scalable, up to PBs volumesUses patterns that support ETL code generationFamiliar architecture: data layers, ETL, star schemasData vaults are based on agile methodologies and techniques, which means that they can adapt to fast-paced changing business requirements. One of the major advantages of using the Data Vault methodology is that ETL jobs need less refactoring when the model changes.Modeling techniques by lakehouse layerWith these concepts in mind, let's explore how Data Vault fits into our Bronze, Silver and Gold data layers where data goes from a raw to a refined state that is ready for analytics. In this multi-hop architecture, raw data gets stored in a Bronze layer with minimum transformation and data structure as close to the source system. The Data Vault methodology can be applied to the Silver layer where data is transformed into Hubs, links and satellites.In the Gold layer, multiple data marts\/data warehouses can be built as per dimensional modeling\/Kimball methodology. As discussed earlier, the Gold layer is for reporting and uses more de-normalized and read-optimized data models with fewer joins. Sometimes tables in the Gold Layer can be completely denormalized, typically if the Data Scientists want it that way to feed their algorithms for feature engineering.If a Data Vault model is used in the Silver layer it simplifies and significantly reduces the changes needed to perform ETL into the Data Marts and Data Warehouses, as Hubs make key management (surrogate key \/ natural keys) easier. Satellites make loading dimensions easier because they have all the attributes, and links make loading fact tables quite straightforward because they have all the relationships.ResourcesData Lakehouse Platform by DatabricksDatabricks SQL product pageDatabricks Blog: Different Data Warehousing Modeling Techniques and How to Implement them on the Databricks Lakehouse PlatformDatabricks Blog: What\u2019s a Data Vault and How to Implement It on the Databricks Lakehouse PlatformBack to GlossaryLearn what\u2019s driving the Lakehouse pattern.REGISTER NOWProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners","text":"Parceiros | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWParcerias com DatabricksA Databricks conta com mais de 1200+ parcerias em todo o mundo, fornecendo solu\u00e7\u00f5es e servi\u00e7os de dados, an\u00e1lises e IA para nossos clientes m\u00fatuos usando a Databricks Lakehouse Platform. Essas parcerias permitem aproveitar a Databricks para unificar todos os dados e cargas de trabalho de IA e obter insights mais relevantes.\u201cA Databricks gerencia a quantidade de dados enquanto o Tableau acelera a visualiza\u00e7\u00e3o. Essas solu\u00e7\u00f5es formam um conjunto perfeito no centro da nossa plataforma, oferecendo aos nossos clientes o desempenho de que precisam para fornecer recursos de ve\u00edculos aut\u00f4nomos de ponta.\u201d\u2014 Patrick McAuliffe, engenheiro l\u00edder da InciteParceiros de nuvemA Databricks \u00e9 executada em AWS, Microsoft Azure, Google Cloud e Alibaba Cloud, com integra\u00e7\u00e3o profunda com a infraestrutura, os dados e os servi\u00e7os de IA de cada provedorSaiba maisParcerias de tecnologiaAs parcerias de tecnologia integram suas solu\u00e7\u00f5es com a Databricks para fornecer recursos complementar de ETL, ingest\u00e3o de dados, BI, ML e governan\u00e7aSaiba maisParcerias de consultoriaAs parcerias de consultoria contam com especialistas que ajudam voc\u00ea a criar, implementar e dimensionar dados, an\u00e1lises e iniciativas de IA com a DatabricksSaiba maisComece uma parceriaNossos parceiros trabalham com a Databricks para desenvolver e fornecer solu\u00e7\u00f5es inovadoras para os clientes. Participe do Databricks Partner Program e obtenha acesso a ferramentas, treinamento, aceleradores de solu\u00e7\u00f5es e programas de lan\u00e7amento no mercado.Saiba maisProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/202109-amer-ve-healthcare-and-life-sciences-workshop-accelerate-rd-with-r","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-mracek\/#","text":"Paul Mracek - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MracekSenior Solutions Architect at DatabricksBack to speakersPaul Mracek has 15 years of Data and AI experience. He joined Databricks in 2021 and has supported Honeywell since 2022.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/antonio-castelo","text":"Antonio Castelo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAntonio Castelo CollibraBack to speakersAntonio built the first partner integration with Unity Catalog, and has been instrumental in building customer momentum around the partnership with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Databricks \uace0\uac1d | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 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All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/faq","text":"FAQ - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQA's to your Q'sWhat is Data + AI Summit?This year, Data + AI Summit will be both in-person and online, bringing together the open source community to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse.\nJoin in-person in San Francisco to experience two keynotes, 200+ sessions, meetups, industry forums, an expo hall with over 100 sponsors, add-ons like hands-on training and certifications, and fun events like the Welcome Reception and Summit party. Learn more by exploring the Session Catalog or the Why Attend pages.\nCan\u2019t make it to the in-person event? Join thousands of attendees online to view the two keynotes, \u00a010live streamed breakout sessions and live interviews with Databricks executives and industry experts for the virtual event.\nWhen and where will the Data + AI Summit take place?Data + AI Summit will take place in San Francisco, CA at the Moscone Center, South during June 26 - 29. A few select Summit events will take place at the Intercontinental, San Francisco - a short walk from Moscone Center. Learn more about the in-person event and register now.\nHow much does the in-person Data + AI Summit cost to attend? Are there any group or special discounts?A full conference pass costs $1,795. Group discounts are available for purchases of 4 or more and a special discount for GOV\/EDU\/NFP. Visit the pricing page for details.\nWhen and where will the free virtual event take place?The free Virtual Data + AI Summit will be held June 28 - 29 on https:\/\/www.databricks.com\/dataaisummit\/. Learn more about the free virtual event and register now.\u00a0\nWill sessions be recorded and available after the event?Majority of the 200 breakout sessions delivered at the in-person event in San Francisco will be recorded and available on-demand on https:\/\/www.databricks.com\/dataaisummit\/. On-demand sessions can be accessed by registering for either the in-person and virtual events. These sessions will be available within a week of the live event.\nWhat topics and technologies will be covered and who are the speakers at the Data + AI Summit?With more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, lightning talks, industry forums, and more. Speakers include top experts, researchers and open source contributors from Databricks and across the data and AI community. \u00a0Learn more by exploring the Session Catalog, Speaker and \u00a0Why Attend pages.\nCan I pre-register or reserve a seat for sessions?There is no reserved seating or pre-registration for sessions. The most popular sessions will be repeated. Attendees can also plan ahead by viewing the session scheduler (available at the end of May) and creating their own custom agenda.\nWhat training course add-ons are available?Build and expand skills with pre-conference training. More than 15 instructor-led, hands-on training courses are available to be added on to your full conference pass. The trainings are either full or half-day, include both lecture, hands-on exercises and live Q&A and are available for all levels. See the full training schedule here.\nTraining add-ons are available for a fee. View prices here. Sign up for training during your Summit registration or if you have already registered but didn\u2019t add training, you can edit your registration details to add it at any time via the registration portal.\nCan I attend a training without attending the Summit?No. To sign up for trainings, you must select your desired course during registration or if you are already registered, you can add it any time via the registration portal.\nHow do I qualify for a group rate for training?Group rates are offered to groups of four or more attendees registering for training together. Contact [email\u00a0protected] to receive a group rate discount code.\nWill certification exams be available?Yes, we are offering the opportunity for in-person attendees to leverage complimentary Databricks certification exams ($200 USD value). The exams are 90-120 minutes long. The following Databricks certification exams qualify:\n\nDatabricks Certified Associate Developer for Apache Spark\u2122 3.0 \u2013 Python\nDatabricks Certified Associate Developer for Apache Spark\u2122 3.0 \u2013 Scala\nDatabricks Certified Data Analyst Associate \u00a0\nDatabricks Certified Data Engineer Professional\nDatabricks Certified Data Engineer Associate\nDatabricks Certified Hadoop Migration Architect\nDatabricks Certified Machine Learning Associate\nDatabricks Certified Machine Learning Professional\n\nHow do I make a change to my registration?If you need to update your registration, please send an email to the registration help desk.\nWhat is the cancellation policy?Substitutions\nSubstitution requests can be processed in person onsite or via written request, please contact the Help Center. If requested in writing, please provide the names and emails of both the original and substitute registrants with both parties copied in the email. All requests for substitutions must be received no later than 5:00 PM (PDT) on June 23, 2023. Onsite substitutions will incur a US $50 processing fee.\nCancellations\nThe Databricks Registration Team must receive all cancellation requests in writing; please contact the Help Center by June 21, 2023.\nRefunds\nWe will issue a full refund, minus a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PDT. Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PDT, will be issued a 50% refund, minus a 10% cancellation fee. No refunds will be offered for paid items after May 26, 2023.\nRefunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record. If you have not received a refund by July 1, 2023, please contact the Help Center.\n\u00a0\nCan someone attend in my place?Yes, if you are unable to attend please send an email to the registration help desk to initiate the substitution.\nAre there hotel blocks available?Yes, Databricks has reserved hotel blocks for Data + AI Summit. During your registration process, you will have the opportunity to book your room. Inventory is limited, available on a first-come, first-booked basis, and our discounted rates are only available until June 1 so book now in the attendee portal.\nReserved hotel blocks are available at The Canopy, Hyatt Regency Soma, Intercontinental, Marriott Union Square, Parc 55, The Clancy, The W and Westin St Francis.\nWhat prices are secured for attendees looking to book a hotel?\u00a0\n\n\n\nHotel\nGroup Rate\n\n\n\n\nW Hotel\n$349\n\n\nParc 55\n$309\n\n\nThe Clancy\n$339\n\n\nJW Marriott\n$329\n\n\nMarriott Union Square\n$309\n\n\nSt Regis\n$565\n\n\nHyatt Downtown SOMA\n$329\n\n\nIntercontinental\n$365\n\n\nWestin St Francis\n$359\n\n\nHilton San Francisco\n$309\n\n\n\n\u00a0\nHow do I make changes to an existing hotel reservation?Attendees may access their existing reservation to make changes via their confirmation email. Please click on the registration link within the email and make desired edits. Please remember to submit your changes.\nWhat is the hotel cancellation policy?The cancellation policy varies from property to property; typically 24 or 72 hours. Each cancellation policy is published within the housing portion of the registration. After the cancellation deadline has passed, attendees will be charged for the cost of one room night should they cancel or postpone their arrival date.\nIf I cancel my Summit registration, can I transfer my hotel reservation to another attendee?No. Credit card data may not transfer from one attendee to another, which makes transferring hotel confirmations from one to another not feasible.\nCan I book multiple rooms on my registration for myself and a colleague?Attendees may book only one hotel reservation under their registration.\nWhat if I don\u2019t check in on my scheduled arrival date?Guests who do not arrive on their confirmed check-in date will be charged a no-show fee by the hotel property, equal to (1) nights rate.\nDo I need a credit card to reserve a room?Yes. All attendees must provide a credit card in order to secure a guest room.\nCan I contact the hotel directly to make a hotel reservation and receive the discounted Summit rate?The group rate is available through group registration only.\nCan I contact the hotel directly to change my existing reservation?Please make edits to your reservation directly in the registration so that when the hotel pulls your reservation information, they capture all changes you require.\nOnly after the hotel cut-off date (June 1 or June 9, depending on the property you secure) can you contact the hotel directly for changes.\u00a0\nWhen will I receive my hotel confirmation?Hotel confirmations will be shared on June 16th.\nI want to arrive earlier\/stay later than the system is showing as available. How can I adjust my reservation?Guest room inventory within the registration platform is based on first come\/first serve. You are welcome to secure your extension directly with the hotel (at rack rate) and then ask the hotel to \u201clink\u201d your two reservations.\u00a0\nYou may also secure your own reservation, including your early\/late stay dates, at a property outside of what is offered on the group registration.\u00a0\nWhat are the health protocols in place for the Data + AI Summit?The health of our attendees is very important to us. As of now, we are not requiring vaccinations or masks. We acknowledge this is an ever-changing landscape and we are deeply committed to staying abreast of updated guidance from the Centers for Disease Control and Prevention (CDC) and federal, state, and local governments. Databricks reserves the right to adjust these protocols if guidance changes.\nWhat are the safety and security protocols in place for the Data + AI Summit?Your safety at the event is our top priority. You will likely see a strong security presence, and there will also be many people working behind the scenes to help keep you safe. We\u2019re prepared to respond to incidents in partnership with local, state, and federal authorities.\nEveryone will be required to show an ID when checking in at registration and will be required to wear their badge for all Data + AI Summit official events. We\u2019ll have metal detectors at the entrances to Moscone South. All bags will be subject to search upon entering any conference site.\nAre there any items I can\u2019t bring to the event?Prohibited items within the event space and after hours event space include, but are not limited to:\n\nWeapons, firearms, or knives (regardless of size) or items that can be mistaken as a weapon.\nPets or other animals, except approved service animals. Service animals should remain on a leash or in a harness and under the control of the owner at all times.\nPersonal mobility devices (with or without a motor) unless for ADA use. This includes but is not limited to: skateboards, hoverboards, bicycles, scooters, uniwheels, and all similar products.\nNo smoking (including e-cigarettes) is allowed within the facility.\nPoles and sticks; selfie sticks.\nLaser lights, laser pointers.\nMace\/pepper spray, tasers, stun guns, or similar devices.\nSharp and\/or pointed objects: razor blades, scissors, knitting needles, screwdrivers, etc.\nWhistles, noisemakers, and\/or sound\/voice enhancement devices, such as bullhorns.\nBanners, signs, or placards unless authorized by production or security management.\nFlashlights, unless authorized by production or security management.\nWi-Fi and\/or Bluetooth signal disruptors.\nTripods for cameras (does not apply to media).\nInflatable items (e.g., balloons).\nDrones, unless authorized by production or security management.\nNo outside alcohol.\nNo illegal substances.\n\nCan I participate as a sponsor in the event?If you are interested in sponsorships or have any sponsorship questions, please contact [email\u00a0protected].\nWhen and how will I receive more information about how to navigate the in-person event in San Francisco?We will be launching a mobile app at the beginning of June. The mobile app will include everything needed to navigate the event including information about meals, transportation, map, agenda and more. We will be sending out a series of emails along with the mobile app launch, which will help you make the most of your experience at Summit.\nWhat is the Data + AI code of conduct and event policies?We are committed to fostering Diversity, Equity and Inclusion. We will continue to create an inclusive event where everyone can learn, collaborate, and build community.\nCode of Conduct\nEvent Policies\nPrivacy Notice\nI still have some unanswered questions. Who can I contact?Send any other questions to the help desk.\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/overall-equipment-effectiveness","text":"Overall Equipment EffectivenessPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWOverall Equipment EffectivenessAll>Overall Equipment EffectivenessTry Databricks for freeGet StartedWhat is Overall Equipment Effectiveness?Overall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to run. It identifies the percentage of manufacturing time that is truly productive. An OEE is a dashboard that shows the total performance of a discrete or continuous process. OEE is maximized at 100% and means that only good parts are produced (100% quality), at the maximum speed (100% performance), and without interruption (100% availability).Measuring OEE is a manufacturing best practice. By measuring OEE and the underlying losses, important insights can be gained on how to systematically improve the manufacturing process. OEE is an effective metric for identifying losses, bench-marking progress, and improving the productivity of manufacturing equipment (i.e., eliminating waste).Why Is this important?OEE has been used as the prime manufacturing metric for decades. Historically, OEE monitoring used manual data collection directly from the machines on a batch basis and calculated the metric. In itself, OEE is a reactive dashboard that monitors the past and historical performance - the true power of OEE is to guide to implement use cases that improve the components of OEE - the deployment of predictive maintenance to improve availability, or quality control leveraging computer vision to improve quality that are predictive in function.What are Databricks\u2019 differentiated capabilities?Databricks\u2019 Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader and Photon to enable customers to make data available for real-time decisions.Lakehouse for MFG supports the largest data jobs at near real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.A Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for real-time stream ingestion of data and analytics on streaming data. Data warehouses require the extraction, transformation, loading, and additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest of data sets to power real-time decisions in BI tools.What data challenges need to be addressed to build predictive OEE capabilities?Handling the volume and variety of IoT data\u2014To enable predictive use cases embedded in OEE manufactures, the Lakehouse handles all types of diverse data structures and schemas, including everything from intermittent readings of temperature, pressure, and vibrations per second to handling fully unstructured data (e.g., images, video, text, spectral data) or other forms such as thermographic or acoustic signals, from the edge delivered through diverse supported drivers and protocols.Managing the complexity of real-time data: In order to drive continuous process monitoring, throughput optimization or predictive maintenance, the Lakehosue enables real-time analytics on streaming data. The lakehouse effectively ingests, stores, and processes streaming data in real time or near-real time in order to instantly deliver insights and action.Freeing data from independent silos\u2014Specialized processes (innovation platforms, QMS, MES, etc) within the value chain reward disparate data sources and data management platforms that tailor to unique siloed solutions. These narrow point solutions limit enterprise value by considering only a fraction of the insight cross-enterprise data can offer, in addition, duplicate siloed solutions divide the business, limiting collaboration opportunities. Also, the Lakehouse ingests, stores, manages, and processes streaming data from all points in the value chain, combines it with Data Historians, ERP, MES and QMS sources and leverages it into actionable insights.Diverse analytical capabilities\u2014Legacy data warehouses offer limited ability to provide insights and analytics into platform usage and performance. For Connected Manufacturing IoT solutions, the Lakehouse provides a wide range of analytical options\u2014including everything from SQL analytics and search capabilities, to tools to support machine learning and modeling, along with tight integration with leading business intelligence (BI) solutions that offer specialized dashboard and business analytics capabilities.Predictive modeling capabilities\u2014Predictive modeling capabilities are key to delivering insights, and the Lakehouse provides notebook driven machine learning capabilities used to predict and prevent disturbances before they impact operations.Additional ResourcesDatabricks solutions for ManufacturingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/test-beckner","text":"TEST Beckner - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTEST BecknerTEST at TESTBack to speakersTESTLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the \u201cPlatform Services\u201d), which are subject to the\u00a0Databricks Terms of Service\u00a0(or with respect to the Community Edition, the\u00a0Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (\u201cDatabricks\u201d) and our subscribers (\u201cSubscribers\u201d) (any such agreement, a \u201cServices Agreement\u201d).PLEASE READ CAREFULLY THESE TERMS AND THE\u00a0DATABRICKS PRIVACY POLICY\u00a0(\u201cPRIVACY POLICY\u201d) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. BY ACCESSING OR USING ANY OF THE SITES, YOU REPRESENT THAT YOU ARE AT LEAST 18 YEARS OLD, YOU ACKNOWLEDGE AND AGREE THAT YOU HAVE READ AND UNDERSTOOD THESE TERMS, AND YOU AGREE TO BE LEGALLY BOUND BY ALL OF THESE TERMS. IF YOU DO NOT AGREE TO ALL OF THESE TERMS, DO NOT ACCESS OR USE THE SITES. WE SUGGEST YOU PRINT A COPY OF THESE TERMS FOR YOUR RECORDS.Throughout the Terms, \u201cwe,\u201d \u201cus,\u201d \u201cour\u201d and \u201cours\u201d refer to Databricks, and \u201cyou,\u201d \u201cyour\u201d or \u201cyours\u201d refer to you personally (i.e., the individual who reads and agrees to be bound by these Terms) and, if you access the Sites on behalf of a legal entity, to that entity. If you are using the Sites on behalf of any entity you represent and warrant that you are authorized to accept these Terms on such entity\u2019s behalf and, by accepting these Terms, you are hereby binding such entity to the Terms.Subject to your compliance with these Terms, solely for so long as you are permitted by Databricks to access and use the Sites, and provided that you keep intact all copyright and other proprietary notices, you may view Content and you may download and print the materials that Databricks specifically makes available for downloading from the Sites (such as white papers or user documentation), in each case solely for informational purposes and solely for personal or internal business use.ACCEPTANCE OF TERMS\nDatabricks provides the Sites to you conditioned upon your accepting all of the Terms, without modification. Your use of the Sites constitutes your agreement with such Terms. We reserve the right to change, modify, add to, or remove portions of these Terms in our sole discretion at any time and we will, at our sole discretion, either post the modification on\u00a0https:\/\/www.databricks.com\/terms-of-use\u00a0or provide you with email notice of the modification. You should check these Terms periodically for changes and you can determine when these Terms were last revised by referring to the \u201cLast Updated\u201d reference at the top of these Terms. Any modification shall be effective immediately upon the uploading of modified Terms. You indicate your agreement to comply with, and be bound by, any such modification by continuing to use or access the Sites after modified Terms are posted. If the modified Terms are not acceptable to you, your sole recourse is to discontinue your use of the Sites.\n\u00a0If you have registered for and opened an account through the Sites (an \u201cAccount\u201d), you are entirely responsible for maintaining the confidentiality of your Account information, including your password, and for any and all activity that occurs under your Account. You agree to notify Databricks immediately of any unauthorized use of your Account or password, or any other breach of security. However, you will remain responsible for losses incurred by Databricks or by any other party due to your knowingly or inadvertently permitting unauthorized use of your Account or your Account information. You may not use anyone else\u2019s ID, password or account at any time unless we expressly pre-approve such use, or unless expressly permitted under a Services Agreement. Databricks cannot and will not be liable for any loss or damage arising from your failure to comply with these obligations. Registration for any account is void where the user lacks the requisite eligibility for registration or if such registration is otherwise prohibited.Software (\u201cSoftware\u201d) or the Platform Services may be made available to you through the Sites. Your rights to access and use the Platform Services, including any Software will be subject to your agreement to the applicable Services Agreement governing your use of the Platform Services and to any terms and conditions of any applicable third party software license agreement (\u201cSoftware License\u201d) identified in the Software or on the web page providing access to the Software. You may not use any Software unless you agree to be bound by all terms and conditions of any applicable Software License. If there is a conflict between any Services Agreement and any Software License, the conflicting term of the Software License shall control but only to the extent necessary to eliminate the conflict.LICENSE GRANT AND PROPRIETARY RIGHTS\nProvided that you fully comply at all times with these Terms and any other policies or restrictions posted on or transmitted through the Sites, Databricks grants you a limited, non-exclusive, non-transferable, revocable license to access and use the Sites. Except as otherwise specifically noted in these Terms or on the Sites, the Software, Submissions (as later defined), and all other information, content, user interfaces, graphics, registered or unregistered trademarks, logos, images, artwork, videos, and documents, and the design, structure, selection, coordination, expression, \u201clook and feel\u201d and arrangement of such materials, made available through the Sites (collectively, the \u201cContent\u201d), regardless of its source or creation, is owned, controlled or licensed by or to Databricks, and is protected by trade dress, copyright, patent and trademark laws, and various other intellectual property rights and unfair competition laws, and Databricks reserves and retains all rights in and to such Content. Any reproduction, redistribution or other use or exploitation of Software in violation of any applicable Software License or in violation of any license granted under these Terms or, if applicable, under a Services Agreement, is expressly prohibited by law, and may result in civil and criminal penalties.\n\u00a0\u201cApache\u201d and \u201cSpark\u201d are trademarks of the Apache Software Foundation. Any other third party trademarks, service marks, logos, trade names or other proprietary designations, that are or may become present within the Sites, including within any Content, are the registered or unregistered trademarks of the respective parties.Except solely as necessary for you to access the Sites for the intended purpose pursuant to these Terms, you may not copy, collect, modify, create derivative works or uses of, translate, distribute, transmit, publish, re-publish, perform, display, post, download, upload, sublicense, transfer, dispose of, resell or sell the Content or any other part of the Services. Except as expressly set forth in these Terms, these Terms do not grant to you any license to any intellectual property rights or other proprietary rights, including any implied licenses or licenses granted by estoppel or otherwise.INFORMATION SUBMITTED THROUGH OR TO OUR SITES\nAt our sole discretion, you may be permitted to provide Submissions (as defined in the next sentence) to the Sites (e.g., through our forums). \u201cSubmissions\u201d are defined to include: any messages, emails, text, graphics, code, questions, suggestions, comments, feedback, ideas, plans, notes, drawings, sample data, sound, images, video, original or creative materials, and other items or materials that you may provide to discussion forums, blogs, or other interactive features or areas of the Services where you or other users can create, post, transmit or store Content. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speakers?itm_data=hp-hamburger-speakers-dais23","text":"Speakers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpeakersBrowse the roster to find new and familiar faces alike. The Data + AI Summit draws experts from all over the globe across a wide array of fields.\nFeatured speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAll speakersAayush PatelData & Platform EngineerSkywatchAbhishek PatelHead of Databricks COELTIMindtreeAdam WilsonCo-Founder, Chief of ProductDivirod, Inc.Adi PolakData & AI TechnologistTechnologistAdriana IspasStaff Product ManagerDatabricksAikaterini KalouPrincipal Data ScientistCitrixAjali SenSenior ManagerAccentureAjmal AzizSolutions ArchitectDatabricksAkira AjisakaSenior Software Development EngineerAmazon Web ServicesAlain BrianconVP Data Science Profiles by KantarKantar GroupAlbert HuSenior Analytics EngineerRec RoomAlessandro GaravagliaLead ML EngineerGucciAlexander BoothAssistant Director of Research & DevelopmentTexas Rangers Baseball Club, LLCAlexander VanadioPrincipal ConsultantOptivAli GhodsiCo-founder and CEODatabricksAlon GubkinCo-Founder & CTOAporiaAman KapoorHead of Data PlatformPetronasAmanda MilbergSenior Partner Sales EngineerDataikuAmine BenhamzaLead Solutions ArchitectDatabricksAmir SkovronikDistinguished Software EngineerAkamaiAmrinder Singh OberaiEMR Migrations LeadDatabricksAnanya GhoshBusiness Application Owner for DatabricksNationwide InsuranceAndrew BlanceInnovation ConsultantWaterstonsAndria FuquenTechnical Program ManagerImmutaAndy HanksSenior Data Architect, Analytics PlatformCRISP Shared ServicesAnfisa KaydakVP, Data Product & EngineeringHealthverityAngela ChuSenior Solution ArchitectDatabricksAnil PuliyerilSenior ArchitectHabuAnindita MahapatraLead Solutions ArchitectDatabricksAnindya SahaML Platform Software EngineerAnkit MathurTech Lead, Model Serving GPUsDatabricksAnna RussoGlobal Director of Data ScienceGucciAnton OkolnychyiSoftware EngineerAppleAntoni BaumSoftware EngineerAnyscaleAntonio CasteloCollibraAnup SeguCo-Head of Data EngineeringYipitDataArtem MeshcheryakovConsultantORAYLIS GmbHArthur LiSenior Software EngineerInstacartArujit PradhanSoftware EngineerCoinbaseArun PamulapatiSr. Staff Security Field EngineerDatabricksAshwin GangadharSenior Solutions ArchitectMongoDBAtiyah CurmallyPrincipal Environmental SpecialistInternational Finance CorporationAustin FordStaff Product ManagerDatabricksAvinash SooriyarachchiSenior Solutions ArchitectDatabricksBalaji RamanujamAVP - Senior Principal Technology ArchitectInfosysBasak EskiliML EngineerAhold DelhaizeBehzad BordbarLead Data ScientistMarks & SpencerBeinan WangSenior Staff Software EngineerAlluxioBen CoppersmithSr. Manager, Data PlatformDisney StreamingBen WilsonPrincipal Specialist Solutions ArchitectDatabricksBeth MattsonSenior Data EngineerOur Family WizardBin MuVice President and Head of Data & AnalyticsAdobeBinwei Yangsoftware engineerintelBlaise SandwidiLead Data Scientist, As. ESG Officer, PhDInternational Finance Corporation (IFC)\u2013World Bank GroupBob ZhangSenior Technical Program ManagerMicrosoftBrad CorwinChief Data ScientistBooz Allen HamiltonBradley AxenMachine Learning EngineerBlockBrendan BarsnessData and Analytics ArchitectDeloitteBrooke WenigDirector, Machine Learning PracticeDatabricksCan ElfeogluStaff Product ManagerDatabricksCelia KungEngineering ManagerDatabricksChang SheCEOLanceDBChao SunSoftware EngineerAppleChen GuoStaff Software EngineerCoinbaseChris StevensSenior Staff Software EngineerDatabricksChris VoLead Member of Tech StaffAT&TChris InkpenSolutions architectHoneywellChris HechtDatabricksChris MantzData ArchitectSlalomChristian Acu\u00f1aSenior Data EngineerGrammarlyChristian HamiltonDirector, Data Science Technology84.51Christina TaylorData EngineerToptalChristina TaylorSenior Staff Data EngineerCatalyst SoftwareChristopher LocklinEngineer Manager, Data PlatformGrammarlyChunxu TangResearch ScientistAlluxioCody FergusonData & AI Management Branch ChiefChief Digital and Artificial Intelligence Office - AdvanaCorey ZumarSoftware EngineerDatabricksCorey ZwartChief Technology OfficerPumpJack DataworksCort LunkeData & Analytics Lead - TruterraLand O'LakesCraig WileySr. Director of Product, Lakehouse AIDatabricksCyrielle SimeonePrincipal Product Marketing ManagerDatabricksDael WilliamsonField CTODatabricksDan HoustonManager, Data Science and Exploration Advanced AnalyticsUSPSDan SmithHead of Technology Data & AnalyticsPerenti GroupDanica FineSenior Developer AdvocateConfluentDaniel TenedorioSr. Staff Software EngineerDatabricksDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL)MITDarshana SivakumarStaff Product ManagerDatabricksDarth VaderSith LordThe Galactic EmpireDatin Ts. Habsah Binti NordinChief Data OfficerPETRONASDavid SkinnerChief Strategy OfficerAcxiomDavid TempelmanResident Solutions ArchitectDatabricksDawn SongProfessor, Department of Electrical Engineering and Computer ScienceUC BerkeleyDeepa ParanjpeDirector of EngineeringDiscoveryDeepak SekarSr. Solution ArchitectDatabricksDenny LeeSr. Staff Developer AdvocateDatabricksDerek SlagerCTOAmperityDerek SugdenAd Measurement Lead \u2013 Measurement & AttributionEffectvDevlina DasSenior Software EngineerInstacartDeylo WooData Engineer ArchitectProvidence Health ServicesDilip BiswalSenior ArchitectAdobeDillon BostwickSolutions ArchitectDatabricksDipankar MazumdarDeveloper AdvocateDremioDon ScottVP, New Product DevelopmentHitachi Solutions AmericaDon Bosco DuraiCofounder and CTOPrivaceraDonghwa KimSr. Director of IT ArchitectureOntada, a McKesson CompanyDouglas MooreLead Specialist Solutions ArchitectDatabricksDurga KalaSr. DirectorVisa Inc.Egor GryaznovCTO and Co-founderBigeyeEllen SulcsDirector, Data Products & EngineeringT-MobileEllie HajarianSnr IT ManagerTD BankElliot ShmuklerCo-Founder & CEOAnomaloEmad MostaqueCEOstability.aiEric PeterSr Staff Product ManagerDatabricksEric SchmidtFormer CEO and Chairman, Google; Co-FounderSchmidt FuturesErika EhrliSenior Director of Product MarketingDatabricksErin BoelkensVP of ProductLiveRampErni DurdevicSpecialist Solutions Architect (Geospatial)DatabricksFabian JakobsSr Staff Software EngineerDatabricksFabien CochetIT Expert on Data and AnalyticsMichelinFabio Luis Correia da SilvaArchitecture SpecialistBradescoFaraz YasrobiSoftware EngineerGrammarlyFrancisco RiusHead of Data Science and Data EngineeringMinecraft at MicrosoftFranco PatanoProduct SpecialistDatabricksFrank MunzPrincipal Technical Marketing EngineerDatabricksGanesh DeivarayanSr ManagerAmerican AirlinesGaurav SarafProduct ManagerDatabricksGavita RegunathPrincipal Data ScientistAdvancing AnalyticsGeoffrey FreemanSolutions ArchitectT-MobileGidon GershinskyLead Systems ArchitectAppleGilad AsulinBig Data Engineer Team LeaderAkamai Technologies, IncGreg NelsonVP of Data OperationsHighmark HealthGreg KroleskiProduct ManagementDatabricksGregory LittleDCDAO for Enterprise Platforms and Business OptimizationDoD CFO Transformation OfficeHannes M\u00fchleisenCo-Founder and CEODuckDB LabsHao ZhuSenior ManagerNVIDIAHari ShankarSenior Director, R&DVizioHari RajaramSr Director \/ Principal Data ArchitectProcoreHarrison ChaseCEOLangChainHarsh MishraLead Enterprise ArchitectAustralian Rail Track CorporationHeiko UdluftChief Technology OfficerDivirod, Inc.Himanshu AroraResident Solutions ArchitectDatabricksHimanshu RajaDatabricksHitesh SahniHead of Cloud Data Platforms and Data Engineering SolutionsDeutsche Post DHLHolly SmithSenior Resident Solutions ArchitectDatabricksHuaxin GaoSoftware EngineerAppleHyukjin KwonStaff Software EngineerDatabricksIan SotnekDirector of ProductAI Squared, IncIan GallowaySenior Director, ApplicationsCollins AerospaceIfigeneia DerekliField Engineering Manager & Unity Catalog SpecialistDatabricksIoannis PapadopoulosCloud TechnologistDatabricksItai YaffeSenior Big Data ArchitectAkamaiIvan PengSoftware EngineerDoorDashJacek LaskowskiIT Freelancerjapila.plJackie BrosamerDirector of Software EngineeringBlockJacob RennChief TechnologistAI Squared, IncJacolon WalkerCo-founder & CTOMonadJaison DominicSenior Manager Information SystemsAmgenJames DemmelDr. Richard Carl Dehmel Distinguished ProfessorUniversity of California, BerkeleyJames NormanPrincipal Software EngineerNikeJamie BakerDirector of ProductMatillionJason ShiverickData Platform ManagerRivianJay BhankhariaSenior Director, Data PartnershipsDatabricksJay YangPrincipal Data EngineerProcoreJeff Breeding-AllisonSenior Data ScientistMars PetcareJeff MrozTechnical SME for Cloud and Big DataWoolpert \/ US Army Corps of EngineersJeffrey HessLead TechnologistBooz Allen HamiltonJeffrey ParkinsonVP, Core Data EngineeringNorthwestern MutualJeffrey ChouCo-Founder, CEOSync ComputingJegadeesan PugazhenthiLead Big Data EngineerAT&TJeremy LewallenProduct ManagerDatabricksJiajun YaoSoftware EngineerAnyscaleJim HibbardSenior Developer AdvocateDatabricksJim ThorstadSolutions ArchitectDatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchUniversity of California at BerkeleyJoanna GurryExecutive, Data DeliveryNational Australia Bank (NAB)Joe WalshDirector of Measurement & AttributionEffectvJohn RousselCIOCalifornia Department of Public Health (CDPH)John ThompsonGlobal Head, Artificial IntelligenceEYJohn KutayDirector of Product ManagementStriimJon OsbornField CTOAscend.ioJonathan KellerSr. Director, Product ManagementDatabricksJonathan HollanderVP, Enterprise Data Technology PlatformsTD BankJonathan NeoData EngineerCanvaJordan PeckPrincipal Technical Account ManagerSnowplowJordan DonmoyerManager, Customer Data SolutionsThe Hershey CompanyJoseph SarsfieldMachine Learning EngineerMarks & SpencerJoseph BradleyLead Product SpecialistDatabricksJules DamjiLead Developer AdvocateAnyscaleJulie FerrisVice President, Commercial OptimizationDefinitive HealthcareJulien Le DemChief ArchitectAstronomerJun Rong LauData Engineer\/AnalystGrabTaxi Holding Pte LtdJunta NakaiRVP, Industry Solutions, Financial Services and SustainabilityDatabricksJustin BreeseSr. Product ManagerDatabricksJustin DeBrabantSVP of ProductActionIQJustin LaiDistinguished Data ArchitectBlackBerryJustin ThompsonDirector, IT Data and AnalyticsJetBlueKarthik RamasamyHead of StreamingDatabricksKasey UhlenhuthStaff Product ManagerDatabricksKeith AndersonSolution PrincipalHitachi SolutionsKeshav SanthanamPhD StudentStanford UniversityKetan GanatraSolution ArchitectDatabricksKieran TaylorSenior Software Engineer IIInstacartKrishti BikalSenior Executive - Director BI & AnalyticsEmeraldKyle HaleProduct SpecialistDatabricksKylie TaylorData ScientistMars PetcareLakhan PrajapatiDirector of Architecture and EngineeringZS associatesLarry FeinsmithHead of Global Tech Strategy, Innovation and PartnershipsJP Morgan Chase & Co.Lee YangSr. Principal SW EngineerNVIDIALeena DalviAssistant Vice President, Enterprise Data & AnalyticsNavy Federal Credit UnionLeo DuncanSr. Solutions ArchitectKyvos Insights Inc.Leon EllerSolutions ArchitectDatabricksLewis MbaeHead of Customer EngineeringRudderStackLin QiaoCo-creator of PyTorch, Co-founder and CEOFireworksLindsay MicoHead of Data ScienceProvidence HealthLindsey WoodlandExecutive Vice President, Client Data Science605Lior GavishCTO and Co-founderMonte Carlo DataLiping HuangSenior Solutions ArchitectDatabricksLorenzo De TomasiData Architect, Data Platforms Lead at BarillaBarilla G. e R. Fratelli S.p.A.Lucas dos Santos CelestinoPlatform Product ManagerAB InbevLuk VerhelstData ArchitectVolvo Group (consultant)Luyang WangLead Distinguished ScientistVerizonMacGregor WinegardAssociate Data EngineerKPMGMaciej SzpakowskiCo-founderProphecyMadalina TanasieChief Technology OfficerCollibraMaggie DavisPrincipal, Data EngineeringSlalomMahesh PrakriyaDirector in Intelligence PlatformMicrosoftMalav ShahSenior Data ScientistDIRECTVManbir PaulVP of Engineering, Data Insights and MarTechSephoraMani KandasamyTech FellowDeloitte Consulting LLPManu SharmaCEOLabelboxMarcel KramerHead of Data EngineeringABN AMRO Bank N.VMaria VechtomovaML EngineerAhold DelhaizeMaria DaibertData Platform Product ManagerAB InbevMarianna CervinoGlobal Data ScientistGucciMarius PangaSolutions ArchitectDatabricksMark LeeSenior Specialist Solutions ArchitectDatabricksMark D'AndreaGlobal Chief Revenue OfficerAccuweatherMartin GrundSenior Staff Software EngineerDatabricksMat KeepSenior Director, MongoDB Products TeamMongoDBMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflowDatabricksMatt McKenzieGM, TechnologyTabcorpMatteo QuattrocchiDirector, Policy-EMEABSAMatthew HayesVice President of SAP BusinessQlikMatthew PowersDeveloper AdvocateDatabricksMatthew HayesSoftware EngineerDatabricksMatthew DoxeySenior EpidemiologistWashington State Department of HealthMatthew KarasickChief Product OfficerHabuMaxime AgostiniCEOSarus Technologies IncMeena RamSr Director, Enterprise Data and Records Management OfficeCIBCMegan FogalSolutions ArchitectDatabricksMenglei SunSenior Software EngineerDatabricksMiao WangSenior Engineering ManagerAdobeMichael ShtelmaLead Specialist Solutions ArchitectDatabricksMichael ArmbrustDistinguished EngineerDatabricksMichael GreenSenior Data ScientistHitachi Solutions AmericaMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious DiseasesCalifornia Department of Public Health (CDPH)Michael SankyRVP, Industry Solutions, Healthcare and Life SciencesDatabricksMike ConoverSoftware EngineerDatabricksMike TangAssociate Director, Responsible AIVerizonMike Del BalsoCo-founder + CEOTectonMilos ColicTech Lead EMEA Public Sector - Sr. Solutions ArchitectDatabricksMiranda LunaProduct ManagementDatabricksMitch ErtlePartner Solutions EngineerSigma ComputingMohan KolliIT DirectorLabCorpMorgan HsuDirector, Data and ML EngineeringFanDuelMostafa MokhtarPrincipal Software EngineerDatabricksMurali MadireddiArchitectAccentureNabil RaadSVP of Data and AnalyticsGM FinancialNadine FarahHead of Dev RelOnehouseNaresh YegireddiStaff Data EngineerIndigo AGNat FriedmanCreator of Copilot; Former CEOGithubNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North AmericaHitachi Solutions America Ltd.Naveen ZutshiChief Information OfficerDatabricksNeil PatelLead Specialist Solutions ArchitectDatabricksNic JansmaSenior Principal Lead EngineerAkamaiNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, TechnologyGlaxoSmithKlineNick KingFounder & CEOData KineticNicolas PelaezTechnical MarketingDatabricksNihar ShethSenior Product ManagerAWS - AmazonNitu NiveditaManaging DirectorAccentureNoam BresslerML Team LeadDeepchecksNoritaka SekiyamaPrincipal Big Data ArchitectAmazon Web ServicesOliver DykstraData EngineerTexas RangersOnik KurktchianHead of S&P Global Marketplace WorkbenchS&P GLOBALOri ZoharPrincipal Product Marketing ManagerDatabricksOz KatzCTO @ Treeverse, co-creator of lakeFSTreeverse LTDPakshal Kumar H DhelariaSenior Software Engineer 1CitrixPamela PettitSolutions ArchitectDatabricksParth ChandraSoftware EngineerApplePascal van BellenSenior ConsultantORAYLIS GmbHPatrick HallPrincipal Scientist | Visiting FacultyBNH.AI | GWUPaul RoomeStaff Product ManagerDatabricksPaul MracekSenior Solutions ArchitectDatabricksPaul WellmanVP, Executive Product Owner, Data-as-a-ServiceTD BankPaul MarshSenior Director Application DevelopmentNew York JetsPaula MartinezCEO & CofounderMarvikPearl UbaruSr. Technical Marketing EngineerDatabricksPedro BoaretoChapter Leader of Analytics EngineeringBradescoPercy LiangProfessor of Computer ScienceStanfordPhilippe LeonhartDigital Transformer, Corporate Business ServicesMichelinPieter NoordhuisSr. Staff Software EngineerDatabricksPouya Barrach-YousefiData Pro and Director Strategic AccountsProphecyPrashanth BabuLead Product SpecialistDatabricksPrateek ChawlaFounding EngineerMonte CarloPraveen VemulapalliDirector- TechnologyAT&TPravin DarbareVice President of Data AnalyticsWorkdayPritesh PatelPublic Sector Leader, UK&IDatabricksPulkit ChadhaSr. Solutions ArchitectDatabricksRafael BarcelosSoftware ArchitectMicrosoft CorporationRafi KurlansikLead Solutions ArchitectDatabricksRaghu JayachandranSenior Manager Enterprise DataRaceTrac Inc.Rahil BhatnagarDevelopment Lead, LOLAAnheuser BuschRahul PandeySolution ArchitectadidasRajesh IyerVice President Financial Services Insights & DataCapgeminiRakesh KumarStaff Software EngineerLyft IncRakesh SinghLead ArchitectABN AMRO Bank N.VRashmi KansakarDirector, Data & Cloud Architect84.51Rekha BachwaniEngineering Director, ML EngineeringThe Walt Disney CompanyReynold XinCo-founder and Chief ArchitectDatabricksRicardo PortillaPrincipal Solution ArchitectDatabricksRisha RavindranathSr Manager, Data GovernanceComcast AdvertisingRob SakerGlobal VP, Retail and ManufacturingDatabricksRobin SutaraField CTODatabricksRobinson CreightonPrincipal Analyst, Enterprise Data OpsComcast AdvertisingRodrigo BeceiroCTO & CofounderMarvikRoger DunnCo-founder, CTOExponamRoie Schwaber-CohenStaff Developer AdvocatePineconeRomit JadhwaniSr. Director, Data Analytics, Engineering and IntegrationsDatabricksRong MaSoftware EngineerintelRuifeng ZhengSenior Software EngineerDatabricksRyan BoydCo-founderMotherDuckRyan HarrisPrincipal Cybersecurity EngineerHSBCRyan JohnsonSenior Staff EngineerDatabricksSaad AnsariSenior Staff Product ManagerDatabricksSachin Balgonda PatilSolutions ArchitectDatabricksSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSamrat RaySenior Staff Product ManagerDatabricksSanjeev KumarVice President, Data Analytics and AIGainwell TechnologiesSanket AminSenior Manager of CAS Data Science and AnalyticsCollins AerospaceSarah PollittGroup Product ManagerMatillionSatish GarlaSr Solutions ArchitectDatabricksSatya NadellaChairman and CEOMicrosoft, Live Virtual GuestScott MeierDirector, Data Analytics Service, Financial Services CenterU.S. Department of Veterans AffairsScott StarbirdGeneral Counsel, Public Affairs and Strategic PartnershipsDatabricksScott BellPrincipal Consultant and Databricks SMERapidDataScott CastleChief Strategy OfficerSisenseSean KnappFounder & CEOAscend.ioSean OwenPrincipal Product SpecialistDatabricksSeth BabcockHead of Connected Aviation Tech Ops Solutions and AnalyticsCollins AerospaceShasidhar ErantiSpecialist Solutions ArchitectDatabricksShawn GilleranPrincipal Cloud Solutions LeadLiveRampShawn BenjaminData and Business Intelligence ChiefU.S. Department of Homeland Security - USCISShir ChorevCTODeepchecksShiv TrisalGTM Director, Manufacturing & EnergyDatabricksSiddharth BhaiSr. Manager, Product ManagementDatabricksSidharth KunnathPrincipal ArchitectAmerican Airlines, IncSimon WhiteleyCTOAdvancing AnalyticsSirui SunDatabricksSlava FridCTOWorldQuant PredictiveSneh KakiletiVice President, Product ManagementZoomInfoSpencer CookSenior Solutions Architect - Financial ServicesDatabricksSreekanth RatakondaPrincipal Solutions ArchitectLabcorpSridhar DevarapalliSenior Director, Product ManagementDatabricksSrinivasa KanamathaSenior ManagerBlackBerryStan LinSenior Software EngineerMicrosoft CorporationStefania LeoneSr. Manager Product ManagementDatabricksStephen SheltonVice President, Business IntelligencePluto TVSteve MahoneySr Manager, Product ManagementDatabricksSteve SobelGlobal Lead - Communications, Media & EntertainmentDatabricksSteven YuPrincipal Solutions ArchitectDatabricksSumesh NairDirector of Engineering, Data and Cloud StrategyOptum, United HealthGroupSuneel KonidalaSr. ManagerAccentureSunil RanganathanDirector, MLOPsTredenceSuresh MatlapudiLead Solutions Architect and Specialist SME, MigrationsDatabricksSurya TuragaSr. Solutions ArchitectDatabricksSuze HowseHead of Enterprise DataMarks and SpencerTanmay KumarSenior ManagerDeloitte Consulting LLPTathagata DasDatabricksTaylor HosbachData ScientistDIRECTVTeja TangedaPrincipal Data EngineerAmerican AirlinesTEST BecknerTESTTESTTest1 TestCFP1102testThet KoPrincipal Data EngineerSEEKThomas La PianaSenior Software EngineerEthycaThomas RoachSr. Solutions ArchitectDatabricksThorsten JacobsSr. Solutions ArchitectDatabricksTianyu LiuLead Data Scientist (Analytics)GrabTimothy AhrensMessaging Design Division ChiefDepartment of StateTodd GreensteinProduct ManagerDatabricksTomer PatelSoftware Engineering ManagerAkamai TechnologiesTony WangPhD studentStanfordUri MayHuntersVadivel SelvarajStaff Software EngineerRivianVarun SharmaPrincipal Data EngineerVisa Inc.Vicky AndonovaManager, Applied Machine LearningAnomaloVika SmilanskyDirector of Product MarketingThoughtSpotVikas Reddy AravabhumiStaff Backline EngineerDatabricksVincent ChenDirect of Product \/ Founding EngineerSnorkel AIVinit DoshiSenior ManagerTredenceVinod MarurSVP of EngineeringDatabricksVolker TjadenManager Solution ArchitectsDatabricksVuong NguyenSenior Solutions ArchitectDatabricksWassym BensaidSr. Vice President, Software DevelopmentRivianWeston HutchinsProduct ManagerDatabricksWill GirtenSr. Specialist Solutions ArchitectDatabricksWilliam ZanineHead of Data Management, Channel and Specialty North AmericaIQVIAWilly LulciucSr. Software EngineerAstronomerXiao LiSenior Engineering ManagerDatabricksXuefu WangSr. Data ScientistThe Trade DeskYali SassoonCPOSnowplowYang YouPresidential Young ProfessorNational University of SingaporeYaniv KundaSenior Software ArchitectAkamaiYaron SingerCEO & Co-FounderRobust IntelligenceYeshwanth VijayakumarSr Engineering Manager\/ArchitectAdobeYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and TechnologyU.S. ArmyYuki SaitoTechnical EvangelistNTT DATA CorporationZachary BannorData Engineering ManagerCond\u00e9 NastZachary HuangPhDColumbia UniversityZaheera ValaniSenior Director of EngineeringDatabricksZeashan PappaSenior Product Specialist - Data GovernanceDatabricksZoe DurandSenior Product ManagerDatabricksSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amrinder-singh-oberai","text":"Amrinder Singh Oberai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmrinder Singh OberaiEMR Migrations Lead at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/diversity","text":"Diversidade e inclus\u00e3o | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWO futuro dos dados est\u00e1 aberto a todosDiversidade, Equidade e Inclus\u00e3o na DatabricksImpulsionado por dados. Desenvolvido por pessoas.Temos a miss\u00e3o de diversificar o big data, come\u00e7ando com nossa equipe. Acreditamos que origens, experi\u00eancias, perspectivas, insights e habilidades diferentes alimentam a inova\u00e7\u00e3o e aprofundam nossa conex\u00e3o uns com os outros e com nossos clientes. N\u00f3s nos esfor\u00e7amos para cultivar uma cultura de pertencimento onde todos s\u00e3o capacitados para fazer o melhor trabalho de suas carreiras. De garantir pagamento igual para trabalho igual at\u00e9 criar uma programa\u00e7\u00e3o que celebra, educa e eleva nossa equipe, Diversidade, Equidade e Inclus\u00e3o (DEI) est\u00e3o presentes em tudo o que fazemos.Certifica\u00e7\u00e3o Fair Pay Workplace\nTemos orgulho de ser uma das seis primeiras organiza\u00e7\u00f5es com certifica\u00e7\u00e3o\u00a0Fair Pay Workplace. Como parte dos esfor\u00e7os para alcan\u00e7ar a paridade salarial, a Databricks passou por uma avalia\u00e7\u00e3o rigorosa de nossos dados e pr\u00e1ticas salariais e se comprometeu a permanecer respons\u00e1vel por meio de an\u00e1lises cont\u00ednuas de equidade salarial.Gaingels e Flucas Ventures\nNosso compromisso com a diversidade, a equidade e a inclus\u00e3o (DEI) envolve toda a nossa equipe, das pessoas que trabalham conosco at\u00e9 as que investem em n\u00f3s. \u00c9 por isso que temos orgulho de fazer parceria com uma s\u00e9rie de investidores de classe mundial, incluindo a\u00a0Gaingels\u00a0e a\u00a0Flucas Ventures, que financiam empresas com um profundo compromisso com a DEI.\"Sabemos que, quanto mais dados tivermos, melhores ser\u00e3o os nossos insights. O mesmo acontece com a diversidade e a inclus\u00e3o; a Databricks prospera ao incluir a maior diversidade poss\u00edvel de origens, experi\u00eancias e pontos de vista.\"\u2014 Ali Ghodsi, cofundador e CEO da DatabricksNossas comunidadesAcreditamos que capacitar nossos funcion\u00e1rios \u00e9 essencial para liberar todo o nosso potencial. Os din\u00e2micos Grupos de Recursos de Funcion\u00e1rios (ERGs) s\u00e3o coletivos liderados por funcion\u00e1rios que desempenham um papel fundamental na cria\u00e7\u00e3o de um ambiente inclusivo e solid\u00e1rio na Databricks. Essas diversas comunidades de funcion\u00e1rios e aliados criam espa\u00e7o para conex\u00e3o e celebra\u00e7\u00e3o e conscientizam sobre quest\u00f5es significativas.Rede Queeries\nRede de veteranos\nRede de funcion\u00e1rios negros\nRede de mulheres\nRede LatinX\nRede de funcion\u00e1rios asi\u00e1ticos\nNossas experi\u00eancias\"Na Databricks, crio equipes das quais quero fazer parte. Isso significa ter a seguran\u00e7a de ser eu mesma e proporcionar essa mesma zona de conforto a todos ao meu redor. Nosso cuidado m\u00fatuo e nosso compromisso com a inclus\u00e3o t\u00eam um grande impacto em toda a nossa comunidade.\"\u2014 Stacy Kerkela, diretora de engenhariaLeia mais\"A rede LatinX na Databricks me d\u00e1 um forte senso de comunidade, uma comunidade aberta. De fato, na Databricks, nossos grupos de recursos de funcion\u00e1rios acolhem e informam todas as pessoas, independentemente de sua origem.\"\u0000\u0000\u2014 Miguel Peralvo, arquiteto de solu\u00e7\u00f5es s\u00eaniorLeia mais\"Muitas empresas est\u00e3o focadas em aumentar a diversidade de g\u00eanero, mas \u00e9 \u00f3timo fazer parte de uma empresa que est\u00e1 tomando medidas ativamente para fazer as coisas acontecerem.\"\u2014 Allie Emrich, gerenciamento de programas, produtoLeia maisInclus\u00e3o na pr\u00e1ticaRelat\u00f3rioParcerias com ColorStack e Rewriting the CodeNossa equipe de recrutamento universit\u00e1rio faz parceria com a\u00a0ColorStack\u00a0e\u00a0Rewriting the Code\u00a0para ajudar mais mulheres, bem como estudantes negros e LatinX, a seguirem carreira em tecnologia.Leia maisRelat\u00f3rioPrograma de mentoria Women in TechNa Databricks, reconhecemos a import\u00e2ncia de oferecer oportunidades de crescimento profissional e avan\u00e7o para comunidades historicamente sub-representadas.Leia maisRelat\u00f3rioPr\u00eamio InHerSight 2021Temos o prazer de ser um dos melhores lugares de trabalho para mulheres em software, de acordo com uma avalia\u00e7\u00e3o feita por mulheres. Para saber mais, visite nosso perfil InHerSight.Leia maisVamos construir o futuro dos dados juntosTemos a miss\u00e3o de simplificar e democratizar dados e IA, e precisamos de voc\u00ea para fazer isso acontecer.Explorar oportunidadesProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/legal\/databricks-community-edition","text":"Databricks Community Edition | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Community EditionCommunity Edition Terms of ServiceWelcome to Databricks Community Edition! We are pleased to provide Databricks Community Edition (the \u201cCommunity Edition Services\u201d) at no charge to those interested in learning and exploring the use of Databricks\u2019 cloud-based data analytics platform, which enables data analysts and others to easily tap the power of Apache Spark and Databricks\u2019 other proprietary functionality. \u00a0Your use of the Community Edition Services is governed by these Terms of Service, including the Arbitration Agreement (the \u201cTerms\u201d). \u00a0If you are using the Community Edition Services on behalf of an organization, you represent and warrant that you are authorized to bind that entity to these Terms, in which case \u201cyou\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind your entity or do not agree with these Terms, you must not accept these Terms and may not use the Community Edition Services. The effective date of these Terms is the earliest to occur of the date you explicitly accept these Terms, or the date you first access or use the Community Edition Services. BY CLICKING TO ACCEPT THESE TERMS OR USING THE COMMUNITY EDITION SERVICES, YOU ARE REPRESENTING THAT YOU HAVE CAREFULLY READ, UNDERSTOOD AND AGREE TO BE BOUND BY THESE TERMS, INCLUDING WITHOUT LIMITATION THE ACCEPTABLE USE POLICY, THE SECTION TITLED \u201cYOUR DATA AND USE OF COMMUNITY EDITION - RESTRICTIONS APPLY\u201d AND THE SECTION REGARDING MANDATORY, BINDING ARBITRATION OF DISPUTES ENTITLED \u201cDISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVER\u201d.YOUR DATA AND USE OF COMMUNITY EDITION \u2013 RESTRICTIONS APPLYThere Are Strict Limits On What Your Data Can Include. \u00a0In order for us to provide the Community Edition Services to you at no charge, we have implemented certain cost saving elements within the architecture of the Community Edition Services including, among other things, the use of a multi-tenant environment with limited data security protections. \u00a0In addition, Databricks personnel have generally unrestricted access to your account (\u201cYour Account\u201d) and any data used or exposed to the Community Edition Services for the purposes of monitoring and improving the quality of the service. \u00a0Therefore, you should have no expectation of privacy regarding the data you submit or otherwise make available in any way to the Community Edition Services (collectively, \u201cYour Data\u201d) or the notebooks you create within or upload to the Community Edition Services (\u201cYour Notebooks\u201d, and collectively with Your Data, \u201cYour Content\u201d) and you must limit Your Content to only that data and other information that you can afford to lose, or have accessed, obtained or disseminated by other parties. Without limiting the foregoing, under no circumstances are you permitted to use with or make available to the Community Edition Services (such data, \u201cProhibited Data\u201d):any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by this Agreement;any data with respect to which your use and provision to Databricks pursuant to this Agreement would breach any agreement between you and any third party;any data that includes pornography, incitements to violence, terrorism or other wrongdoing, or obscene, illicit or deceptive materials of any kind;any data with respect to which its usage as contemplated herein would violate any applicable local, state, federal or other laws, regulations, orders or rules, including without limitation any privacy laws;any (w) bank, credit card or other financial account numbers or login credentials, (x) social security, tax, driver\u2019s license or other government-issued identification numbers, (y) health information identifiable to a particular individual; or (z) any data that would constitute \u201cspecial categories of data,\u201d \u201csensitive personal data,\u201d or any similar concept under applicable law; orany data that is prohibited by the Acceptable Use Policy.You Must Protect Access to Your Account and to Your Content. \u00a0You are responsible for safeguarding your password and you must make sure no one else has access to it. \u00a0Additionally, in order to facilitate the sharing and widespread use of the Community Edition Services, we enable you, at your discretion, to share with others access to Your Content. \u00a0You bear sole responsibility for protecting access to Your Content and for any and all liabilities that may result from the misuse of any sharing privileges granted by you to others. You agree and acknowledge Databricks has a passive role in the transmission, reception and use of Your Content, and Databricks does not take any initiative in the transmission, reception, or use of Your Content. Moreover, as between you and Databricks, you agree and acknowledge that you are solely responsible for your use of Your Content and that Databricks cannot supervise, control, direct, choose, verify, investigate, or evaluate Your Content or your actions with respect to Your Content that you transmit or receive using the Community Edition Services. You acknowledge that we may (but are not obligated to) remove or disable access to any of Your Content, or interrupt any or all services, at any time at our own discretion. You understand and acknowledge that we have the right (but no obligation) to do so if we believe, or are notified, that you have breached any provision of this Agreement (including copyright breach), or if we discontinue or restrict the service that enables you to transmit or receive Your Content. Limits Apply to How You Can Use the Community Edition Services. \u00a0You agree that your use of the Community Edition Services is subject to the Acceptable Use Policy.DATABRICKS\u2019 LEGAL PROTECTIONS & OTHER PROVISIONSDatabricks Intellectual Property Rights. \u00a0The Community Edition Services are protected in various ways by copyright, trademark, and other laws of the United States and other countries. \u00a0These Terms don\u2019t grant you any rights to use of Databricks\u2019 intellectual property, including trademarks, logos and other brand features, except those rights necessary for you to use the Community Edition Services as contemplated under these Terms. \u00a0Databricks welcomes your feedback but please note that we may use your comments and suggestions freely to improve the Community Edition Services or any of our other products or services, and accordingly you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Community Edition Services or otherwise use any feedback Databricks receives from you. The Community Edition Services are Provided \u201cAs Is\u201d With No Warranty. \u00a0Databricks cannot provide guarantees regarding the Community Edition Services. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, DATABRICKS MAKES NO WARRANTIES, EXPRESS OR IMPLIED, ABOUT THE SERVICES, WHICH ARE PROVIDED \u201cAS IS.\u201d \u00a0WE DISCLAIM ALL WARRANTIES OF ANY KIND, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, NON-INTERRUPTION, ACCURACY OR DATA SECURITY. \u00a0Some jurisdictions don\u2019t allow certain of these disclaimers, so they may not apply to you. We Require Your Indemnification. \u00a0You understand and agree that Databricks bears no liability whatsoever in the event you violate the restrictions and obligations imposed by these Terms regarding your use of the Community Edition Services or for the loss of, or unauthorized access to, Your Data, and that Databricks\u2019 willingness and ability to provide access to you to the Community Edition Services at no charge is contingent upon this understanding, and upon your accepting and adhering to all other provisions of these Terms. \u00a0You agree to indemnify, defend and hold harmless each of Databricks and its investors, directors, officers, employees, representatives and affiliates from any claims, costs, damages, liabilities or expenses (including reasonable attorneys\u2019 fees) arising out of any third party claim alleging that Your Data or your use of our services infringes the rights of, or has caused harm to, any party, or violates any law or regulation. Limitation on Liability. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, IN NO EVENT WILL DATABRICKS BE LIABLE FOR ANY INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE, EXEMPLARY OR CONSEQUENTIAL DAMAGES OR ANY LOSS OF USE, DATA, BUSINESS OR PROFITS, REGARDLESS OF LEGAL THEORY, REGARDLESS OF WHETHER DATABRICKS HAS BEEN WARNED OF THE POSSIBILITY OF SUCH DAMAGES, AND EVEN IF A REMEDY FAILS OF ITS ESSENTIAL PURPOSE. \u00a0ADDITIONALLY, DATABRICKS\u2019 AGGREGATE LIABILITY TO YOU FOR ALL CLAIMS RELATING TO THE SERVICES SHALL NOT EXCEED THE GREATER OF THE TOTAL OF ANY AMOUNTS YOU MAY HAVE PAID US IN FEES FOR ANY SERVICE IN THE SIX MONTHS IMMEDIATELY PRIOR TO THE EVENT FIRST GIVING RISE TO ANY SUCH LIABILITY OR $500 (FIVE HUNDRED DOLLARS). THE FOREGOING LIMITATIONS AND EXCLUSIONS SHALL NOT APPLY WITH RESPECT TO ANY LIABILITY ARISING UNDER FRAUD, FRAUDULENT MISREPRESENTATION, GROSS NEGLIGENCE, OR ANY OTHER LIABILITY THAT CANNOT BE LIMITED OR EXCLUDED BY LAW. Some jurisdictions don\u2019t allow the types of limitations in this paragraph, so they may not apply to you. \u00a0IN THESE JURISDICTIONS, EACH PARTY\u2019S LIABILITY WILL BE FURTHER LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW. You agree that this limitation of liability section is intended to allocate the risks between the parties, and that but for this limitation of liability, Databricks would not make available the Community Edition Services. Entire Agreement; No Third Party Rights. These Terms constitute the entire agreement between you and Databricks concerning the Community Edition Services and these Terms create no third party beneficiary rights. Termination, Modification, Waiver & Assignment. \u00a0Either of us may suspend or terminate your use of the Community Edition Services or delete Your Account or Your Content at any time and for any reason (including without limitation for any suspected violations of the Acceptable Use Policy); however, obligations of these Terms that by their nature should survive termination shall so survive. \u00a0In addition, we may revise these Terms from time to time, and will always post the most current version on our website. \u00a0If we elect to terminate your access to the Community Edition Services or delete Your Account or Your Content, or if a revision of these Terms meaningfully reduces your rights, we will make a reasonable attempt to notify you (by, for example, sending a message to the email address associated with your account or posting for a reasonable time period a message to the login page of the Community Edition Services) unless Databricks deems it necessary to suspend or terminate Your Account without notice. \u00a0By continuing to use or access the Community Edition Services after the revisions come into effect, you agree to be bound by the revised Terms. Databricks' failure to enforce a provision of these Terms is not a waiver of its right to do so later. If a provision of these Terms is found unenforceable, the remaining provisions of the Terms will remain in full effect and an enforceable term will be substituted reflecting our intent as closely as possible, provided that questions of unenforceability regarding the Arbitration Agreement shall be resolved according to the Severability Section of the Arbitration Agreement. \u00a0You may not assign or transfer any of your rights under these Terms, and any such attempt will be void. Databricks may assign these Terms and\/or its rights under these Terms to any of its affiliates or to any successor in interest.DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVERInformal Resolution. You agree with us that, if either of us has concerns, we must first work together to resolve any dispute informally without resorting to legal action. \u00a0You agree to contact us at [email\u00a0protected] in the event you have a dispute prior to bringing a formal claim against Databricks. \u00a0If the dispute is not resolved within 30 calendar days from the notice date, either of us may bring a claim subject to the procedures set forth below. You and Databricks agree to the jurisdiction of the Northern District of California to resolve any dispute, claim, or controversy that relates to or arises in connection with these Terms (and any non-contractual disputes\/claims relating to or arising in connection with them) and is not subject to mandatory arbitration as set forth below (the \u201cArbitration Agreement\u201d). \u00a0Any disputes not subject to mandatory arbitration are subject to the laws of the state of California, without regard to choice or conflicts of law principles. Arbitration Agreement. \u00a0If you are located within the United States, you and Databricks agree that any dispute, claim, or controversy between you and Databricks arising in connection with or relating in any way to these Terms or to your relationship with Databricks as a user of the Community Edition Services (whether based in contract, tort, statute, fraud, misrepresentation, or any other legal theory, and whether the claims arise during or after the termination of these Terms) will be determined by mandatory binding individual (not class) arbitration. You and Databricks further agree that the arbitrator shall have the exclusive power to rule on his or her own jurisdiction, including any objections with respect to the existence, scope or validity of the Arbitration Agreement or to the arbitrability of any claim or counterclaim. The Arbitration Agreement will survive termination of the Terms. \u00a0You and Databricks agree that the Federal Arbitration Act applies and governs the interpretation and enforcement of the Arbitration Agreement (despite the choice of law provision above). Exceptions to Arbitration. Notwithstanding the prior clause, you and Databricks both agree that nothing in this Arbitration Agreement will be deemed to waive, preclude, or otherwise limit either of our rights, at any time, to (1) bring an individual action in a U.S. small claims court or (2) bring an individual action seeking only temporary or preliminary individualized injunctive relief in a court of law, pending a final ruling from the arbitrator. In addition, this Arbitration Agreement doesn\u2019t stop you or us from bringing issues to the attention of federal, state, or local agencies. Such agencies can, if the law allows, seek relief against us on your behalf (or vice versa). Prohibition of Class and Representative Actions and Non-Individualized Relief. You and Databricks agree that each of us may bring claims against the other only on an individual basis and not as a plaintiff or class member in any purported class or representative action or proceeding. \u00a0Unless both you and Databricks agree otherwise, the arbitrator(s) may not consolidate or join more than one person\u2019s or party\u2019s claims and may not otherwise preside over any form of a consolidated, representative or class proceeding. \u00a0Also, the arbitrator(s) may award relief (including monetary, injunctive and declaratory relief) only in favor of the individual party seeking relief and only to the extent necessary to provide relief necessitated by that party\u2019s individual claim(s). \u00a0Any relief awarded cannot affect other Databricks customers. Arbitration Procedures. Arbitration is more informal than a lawsuit in court. \u00a0Arbitration uses a neutral arbitrator or arbitrators instead of a judge or jury, and court review of an arbitration award is very limited. \u00a0However, the arbitrator(s) can award the same damages and relief on an individual basis that a court can award to an individual. The arbitrator(s) also must follow the terms of these Terms as a court would. \u00a0The arbitration will be conducted by the American Arbitration Association (referred to as the \"AAA\") under its rules and procedures, including the AAA's Consumer Arbitration Rules (as applicable), unless you have accepted these Terms as a representative of a business entity, in which case AAA\u2019s Commercial Arbitration Rules shall govern (as applicable), in each case as modified by this Arbitration Agreement. \u00a0The AAA's rules and forms to commence arbitration are available at www.adr.org. A party who intends to seek arbitration must first send the other party, if to Databricks, by certified mail, a completed Demand for Arbitration. You should send this notice to Databricks at: Databricks, Inc., Attn: Legal Department, Re: Demand for Arbitration, 160 Spear St., Ste. 1300, San Francisco, CA 94105 USA (with a copy to [email\u00a0protected]). \u00a0Databricks will send any notice to you to the address we have on file associated with your Databricks account (which may solely be at your account email address); it is your responsibility to keep your address up to date. All information called for in the notice must be provided including a description of the nature and basis of the claims the party is asserting and the relief sought. The arbitration shall be held in the county in which you reside or at another mutually agreed location. \u00a0If the value of the relief sought is $10,000 or less, you or Databricks may elect to have the arbitration conducted by telephone or based solely on written submissions, which election shall be binding on you and Databricks subject to the discretion of the arbitrator(s) to require an in-person hearing, if the circumstances warrant. In cases where an in-person hearing is held, you and\/or Databricks may attend by telephone, unless the arbitrator(s) require otherwise. Any settlement offer made by you or Databricks shall not be disclosed to the arbitrator(s). The arbitrator(s) will decide the substance of all claims in accordance with applicable law, including recognized principles of equity, and will honor all claims of privilege recognized by law. \u00a0The arbitrator(s) shall not be bound by rulings in prior arbitrations involving different Databricks customers, but is\/are bound by rulings in prior arbitrations involving the same Databricks customer to the extent required by applicable law. The award of the arbitrator(s) shall be final and binding, and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof. Costs of Arbitration. Payment of all filing, administration, and arbitrator fees will be governed by the AAA's rules (either Consumer or Commercial, as applicable), unless otherwise stated in this Arbitration Agreement. \u00a0If the value of the relief sought by an individual is $10,000 or less, at your request, Databricks will pay all filing, administration, and arbitrator fees associated with the arbitration. Any request for payment of fees by Databricks should be submitted by mail to the AAA along with your Demand for Arbitration and Databricks will make arrangements to pay all necessary fees directly to the AAA. \u00a0If the value of the relief sought by an individual is more than $10,000 and you are able to demonstrate that the costs of accessing arbitration will be prohibitive as compared to the costs of accessing a court for purposes of pursuing litigation on an individual basis, Databricks will pay as much of the filing, administration, and arbitrator fees as the arbitrator(s) deem necessary to prevent the cost of accessing the arbitration from being prohibitive. \u00a0In the event the arbitrator(s) determine the claim(s) you assert in the arbitration to be frivolous, you agree to reimburse Databricks for all fees associated with the arbitration paid by Databricks on your behalf that you otherwise would be obligated to pay under the AAA's rules. Severability. With the exception of any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above, if a court decides that any part of this Arbitration Agreement is invalid or unenforceable, the other parts of this Arbitration Agreement shall still apply. If a court decides that any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above is invalid or unenforceable because it would prevent the exercise of a non-waivable right to pursue public injunctive relief, then any dispute regarding the entitlement to such relief (and only that relief) must be severed from arbitration and may be litigated in court; in such case you irrevocably consent to the personal jurisdiction of the state and federal courts in the Northern District of California and such dispute shall be governed by the laws of the state of California, without regard to choice or conflicts of law principles. All other disputes subject to arbitration under the terms of the Arbitration Agreement shall be arbitrated under its terms. Amendments to Arbitration Agreement. Notwithstanding any provision in the Terms to the contrary, you and we agree that if we make any amendment to this Arbitration Agreement (other than an amendment to any notice address or website link provided herein) in the future, that amendment shall not apply to any claim that was filed in a legal proceeding against Databricks prior to the effective date of the amendment. \u00a0The amendment shall apply to all other disputes or claims governed by this Arbitration Agreement that have arisen or may arise between you and Databricks. We will notify you of amendments to this Arbitration Agreement by posting the amended terms on https:\/\/www.databricks.com\/ce-termsofuse at least 30 days before the effective date of the amendments and by providing notice through email where possible. \u00a0If you do not agree to these amended terms, you may close Your Account within the 30-day period and you will not be bound by the amended terms. \u00a0 Last Updated April 9, 2019ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/technology","text":"Partner tecnologici di Databricks - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPartner tecnologici di DatabricksEntra in contatto con i Databricks Technology Partner per integrare funzionalit\u00e0 di acquisizione dati, business intelligence e governance con Databricks Lakehouse Platform.\u201cCon Databricks e Fivetran, in futuro saremo in grado di migliorare notevolmente le informazioni di marketing. Dal punto di vista tecnico, i due strumenti interagiscono in modo armonico e l'integrazione \u00e8 molto stretta\u201d.\u2014 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP di Paul HewittI Databricks Technology Partner integrano le loro soluzioni con Databricks per offrire funzionalit\u00e0 complementari per ETL, acquisizione di dati, business intelligence, machine learning e governance.Queste integrazioni consentono ai clienti di sfruttare l'affidabilit\u00e0 e la scalabilit\u00e0 della Databricks Lakehouse Platform per fare innovazione pi\u00f9 velocemente, ottenendo al tempo stesso informazioni preziose dai dati.Partner ConnectRiunisci tutti gli strumenti di gestione e analisi dei dati e di AI su un'unica piattaforma aperta. Con Partner Connect, Databricks offre un modo semplice e veloce per collegare gli strumenti esistenti al lakehouse utilizzando integrazioni validate, e aiuta a individuare e provare nuove soluzioni.Diventa partnerMaggiori informazioniLoading...ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/glossary\/spark-api","text":"What is a Spark API?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark APIAll>Spark APITry Databricks for freeGet StartedIf you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDsWhat are Resilient Distributed Datasets?RDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are fault tolerant, immutable in nature. They can be operated on in parallel with low-level APIs, while their lazy feature makes the spark operation to work at an improved speed. RDDs support two types of operations:Transformations - lazy operations that return another RDD, this RDD doesn\u2019t compute unless action is performed on it. Some examples of transformations are map(), flatmap(), filter() Actions - operations that trigger computation and return values. Some examples of actions are count, top(), savetofile() Disadvantages of RDDsIf you choose to work with RDD you will have to optimize each and every RDD. In addition, unlike Datasets and DataFrames, RDDs don\u2019t infer the schema of the data ingested therefore you will have to specify it.What are DataFrames?DataFrames is a distributed collection of rows under named columns. In simple terms, it looks like an Excel sheet with Column headers, or you can think of it as the equivalent to a table in a relational database or a DataFrame in R or Python. It has three main common characteristics with RDD:Immutable in nature: You will be able to create a DataFrame but you will not be able to change it. A DataFrame just like an RDD can be transformedLazy Evaluations: \u00a0a task is not executed until an action is performed.Distributed: \u00a0DataFrames just like RDDs are both distributed in nature.Ways to Create a DataFrameIn Spark DataFrames can be created in several ways:Using different data formats. Such as loading the data from JSON, CSV, RDBMS, XML or ParquetLoading the data from an already existing RDD.Programmatically specifying schemaDisadvantages of DataFramesThe main drawback of DataFrame API is that it does not support compile time safely, as a result, the user is limited in case the structure of the data is not known.What are Datasets?A Dataset is a strongly-typed, immutable collection of objects that are mapped to a relational schema. A Dataset can be created using JVM objects and manipulated using complex functional transformations. Datasets can be created in two ways:DynamicallyReading from a JSON file using SparkSession.Disadvantages of DataSetsThe main disadvantage of datasets is that they require typecasting into strings.Additional Resources8 Steps for a Developer to Learn Apache Spark with Delta Lake eBookThe Data Engineer's Guide to Apache Spark and Delta Lake eBookComparing Apache Spark and DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\u30d7\u30ed\u30b0\u30e9\u30e0\u306b\u30a2\u30af\u30bb\u30b9\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/satya-nadella\/#","text":"Satya Nadella - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSatya NadellaChairman and CEO at Microsoft, Live Virtual GuestBack to speakersSatya Nadella is Chairman and Chief Executive Officer of Microsoft. Before being named CEO in February 2014, Nadella held leadership roles in both enterprise and consumer businesses across the company. Joining Microsoft in 1992, he quickly became known as a leader who could span a breadth of technologies and businesses to transform some of Microsoft\u2019s biggest product offerings. Most recently, Nadella was executive vice president of Microsoft\u2019s Cloud and Enterprise group. In this role he led the transformation to the cloud infrastructure and services business, which outperformed the market and took share from competition. Previously, Nadella led R&D for the Online Services Division and was vice president of the Microsoft Business Division. Before joining Microsoft, Nadella was a member of the technology staff at Sun Microsystems. Originally from Hyderabad, India, Nadella lives in Bellevue, Washington, with his family. He earned a bachelor\u2019s degree in electrical engineering from Mangalore University, a master\u2019s degree in computer science from the University of Wisconsin \u2013 Milwaukee and a master\u2019s degree in business administration from the University of Chicago. Nadella serves on the board of trustees to his alma mater the University of Chicago, as well as the Starbucks board of directors.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/learn-apache-spark-with-delta-lake","text":"Learn Apache Spark\u2122 with Delta Lake - DatabrickseBookUnlock the potential of your dataLearn how Apache Spark\u2122 and Delta Lake unify all your data \u2014 big data and business data \u2014 on one platform for BI and ML.Apache Spark 3.x is a monumental shift in ease of use, higher performance and smarter unification of APIs across Spark components. And for the data being processed, Delta Lake brings data reliability and performance to data lakes, with capabilities like ACID transactions, schema enforcement, DML commands and time travel.In this eBook, we offer a step-by-step guide to technical content and related assets that will lead you to learn Apache Spark and Delta Lake. Whether you\u2019re just getting started or you\u2019re already an accomplished developer, explore the benefits of these open source projects.Here are the 8 steps we\u2019ll cover:Why Apache Spark and Delta LakeApache Spark concepts, key terms and keywordsAdvanced Apache Spark internals and coreDataFrames, data sets and Spark SQL essentialsGraph processing with GraphFramesContinuous applications with structured streamingMachine learning for humansReliable data lakes and data pipelinesGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/media-and-entertainment","text":"Soluzioni per media e intrattenimento - Databricks Lakehouse - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks per media e intrattenimentoProiettare il settore dei media in un futuro guidato da dati, analisi e AICominciaProgramma una demoQuattro sfide per la gestione dei dati nel settore di media e intrattenimentoCreare un profilo unificato del pubblico\nDati acquisiti, conservati e gestiti con diversi sistemi impediscono alle organizzazioni di avere una visione completa dei dati del pubblico e degli inserzionisti.Offrire un'esperienza utente eccezionale\nI consumatori si aspettano esperienze 1:1 personalizzate e fluide in qualsiasi momento su tutti i loro dispositivi. La sfida \u00e8 offrire queste esperienze in tempo reale e su larga scala.Massimizzare il patrimonio di dati\nI data warehouse esistenti non sono in grado di gestire dati non strutturati come video, immagini e file audio, impedendo alle organizzazioni di sfruttare pienamente il potenziale delle loro risorse pi\u00f9 preziose.Passare dall'aggregazione alle analisi avanzate\nCasi complessi di utilizzo dell'AI per il ciclo di vita della pubblicit\u00e0 e dei consumatori comportano attualmente costi elevati per l'acquisizione e l'armonizzazione di set massicci di dati.Scopri il Data Lakehouse: il meglio di due mondi su un'unica piattaformaUn data lakehouse unisce il meglio dei data warehouse e dei data lake in un'unica piattaforma semplice per gestire tutti i casi di utilizzo di dati, analisi e AI. \u00c8 costruito su una piattaforma aperta e affidabile che gestisce in maniera efficiente tutti i tipi di dati e applica un unico approccio comune alla sicurezza e alla governance, per tutti i dati e le piattaforme cloud.Maggiori informazioniIl lakehouse in azioneScopri come Databricks Lakehouse supporta il tuo settore specificoTecnologie per pubblicit\u00e0 e marketingGestisci i margini e le attivit\u00e0 operative con un approccio rigoroso incentrato sui dati, migliora le prestazioni dei media e ottimizza la creativit\u00e0 per snellire il lavoro dei team.Maggiori informazioniBroadcasting e streamingCrea esperienze personalizzate 1:1 su larga scala, migliora i risultati e l'ottimizzazione della pubblicit\u00e0 e genera pi\u00f9 valore dall'intero portafoglio di contenuti.Maggiori informazioniVideogameSfrutta dati e AI per migliorare la progettazione di giochi, aumentare l'acquisizione e il coinvolgimento dei giocatori e incrementare la monetizzazione e la fidelizzazione dei giocatori.Maggiori informazioniPerch\u00e9 Databricks per media e intrattenimentoTutti i dati, le analisi e l'AI su un'unica piattaforma\nEstrapola tutto il valore dai tuoi dati per ottenere risultati eccezionali in termini di coinvolgimento del pubblico, monetizzazione e ottimizzazione della pubblicit\u00e0.Ottimizzato per il tempo reale\nScopri informazioni fruibili, promuovi la personalizzazione 1:1 e migliora l'esperienza del tuo pubblico mettendo al centro il machine learning.Risultati in tempi pi\u00f9 rapidi\nSfrutta una serie di acceleratori che semplificano l'acquisizione di dati dei consumatori (ad esempio il flusso di clic per misurare il coinvolgimento) e la creazione di casi d'uso come motori di raccomandazioni e attribuzione multitouch.Affidabilit\u00e0 e prestazioni ai massimi livelli\nDatabricks Lakehouse offre scalabilit\u00e0, velocit\u00e0 e risparmi senza precedenti. Non c'\u00e8 da meravigliarsi che il miglior data warehouse sia un lakehouse.Trasformare il settore di media e intrattenimento con il lakehouse\n\u201cCon Databricks Lakehouse Platform su AWS, Warner Bros. Discovery \u00e8 pronta per affrontare il futuro della scoperta di contenuti e delle esperienze per il pubblico. Sfruttando i dati per prevedere meglio il comportamento del consumatore e fornire consigli mirati sui contenuti in tempo reale, riusciamo a personalizzare l'esperienza dello spettatore e ad aumentare il coinvolgimento complessivo dei nostri clienti\u201d.\u2014 Martin Ma, GVP, Engineering di Warner Bros. DiscoveryApprofondimenti dei dirigenti su dati, analisi e AIScopri che cosa stanno facendo altri dirigenti nel settore di media e intrattenimento per potenziare la loro strategia di gestione dei datiMaggiori informazioniChe cosa si pu\u00f2 fare con il lakehouse?\nAccelerare il conseguimento di risultati per pubblico e inserzionisti su una piattaforma collaborativa aperta per dati, analisi e AIVista a 360\u00b0 del pubblico\nRaccogli tutti i dati strutturati e non strutturati (flusso di clic, demografici, sociali) su un'unica piattaforma per analisi e AI. Grazie a una visione a 360 gradi del percorso del consumatore, le organizzazioni possono individuare le preferenze di contenuti per offrire esperienze pi\u00f9 personalizzate, proporre annunci pubblicitari pi\u00f9 mirati e aumentare il coinvolgimento.Riduzione delle disdette e incremento del ricavo medio per unit\u00e0 (ARPU)\nGrazie a una piattaforma agile in cloud, le organizzazioni possono elaborare in modo veloce e affidabile enormi quantit\u00e0 di dati e inviarli a sistemi a valle per offrire un'esperienza personalizzata su qualsiasi canale in qualsiasi momento. I consumatori si aspettano sempre di pi\u00f9 di ricevere consigli in tempo reale e le societ\u00e0 di media competono per attirare l'attenzione del pubblico: in questo contesto, la personalizzazione in tempo reale diventa un requisito essenziale per molte organizzazioni.Generare ricavi da una libreria di contenuti\nLe societ\u00e0 di media basano la loro attivit\u00e0 su dati non strutturati come video, immagini e file audio, pertanto la capacit\u00e0 di analizzare dati non strutturati \u00e8 fondamentale per un'efficace gestione del patrimonio di media. La soluzione Lakehouse per il settore media e intrattenimento consente agli addetti al marketing di sfruttare i contenuti archiviati per le campagne, ai team di produzione di cercare contenuti esistenti da inserire in nuove produzioni e ai team di vendita di trovare propriet\u00e0 intellettuale da vendere ad altre societ\u00e0.Sfrutta modelli precostruiti per ML\/AI. La tecnologia ML al centro del business\nSfruttando la potenza del machine learning si possono capire meglio le esigenze di consumatori, dipendenti e inserzionisti. Quando tutti i dati sono centralizzati e strettamente collegati da una suite completa di strumenti collaborativi per analisi e machine learning, i team di gestione dei dati possono lavorare insieme per costruire potenti modelli predittivi che favoriscono l'innovazione negli ambiti della personalizzazione, della monetizzazione dei contenuti e dei risultati per gli inserzionisti.Scarica l'eBookPartner e soluzioni\nComincia a operare con una gamma di soluzioni di gestione e analisi dei dati e di template specifici per il settore dei media e dell'intrattenimento\nVisita il nostro Portale dei PartnerAttribuzione multitouchMisura l'efficacia degli annunci pubblicitari e ottimizza le spese di marketing con una migliore attribuzione dei canaliCominciaTossicit\u00e0 di giocatori\/utentiCrea comunit\u00e0 di utenti pi\u00f9 sane rilevando in tempo reale linguaggi e comportamenti tossiciCominciaAnalisi della sopravvivenza\/LTVIndividua i consumatori a rischio di disdetta e i fattori chiave per prolungare il ciclo di vita di ogni consumatoreCominciaPropensione all'abbandonoGestisci efficacemente la ritenzione dei clienti, analizza il ciclo di vita e riduci il tasso di abbandono (disdette)CominciaSegmentazione comportamentaleCrea una segmentazione pi\u00f9 avanzata dei clienti per migliorare le previsioni di acquisto in base ai comportamentiCominciaPrevisioni di vendita e attribuzioneMigliora i risultati degli annunci pubblicitari concentrando l'attenzione sui canali che offrono i risultati miglioriCominciaRaccomandatiAumenta le conversioni e il coinvolgimento con consigli personalizzati su tutti i canaliCominciaComputer vision\/LabelboxAnnota immagini e video per contestualizzare gli annunci pubblicitari nel lakehouse\n\u00a0\nProssimamenteQualit\u00e0 di esperienza videoAnalizza i dati in batch e in streaming per garantire un'esperienza di qualit\u00e0 nella fruizione di contenuti in streamingCominciaOfferte in tempo reale (RTB)Scopri come prevedere la visibilit\u00e0 degli annunci pubblicitari in tempo reale per migliorare la strategia RTBCominciaVedi tutte le soluzioniLakehouse for Media & Entertainment in azioneRisorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video su dati, analisi e AI per il settore media e intrattenimento\nEsplora risorseeBookSCARICAWebinarMaggiori informazioniBlogMaggiori informazioniPronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProgramma una demoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/spark\/about ","text":"About Spark \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache Spark\u2122Apache Spark is a lightning-fast\u00a0unified analytics engine\u00a0for big data and machine learning. It was originally developed at UC Berkeley in 2009.The largest open source project in data processing.Since its release,\u00a0Apache Spark, the unified analytics engine, has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. It has quickly become the largest open source community in big data, with over 1000 contributors from 250+ organizations.The team that started the Spark research project at UC Berkeley founded Databricks in 2013.Apache Spark is 100% open source, hosted at the vendor-independent Apache Software Foundation. At Databricks, we are fully committed to maintaining this open development model. Together with the Spark community, Databricks continues to contribute heavily to the Apache Spark project, through both development and community evangelism.Watch the videoWhat is Apache Spark - Benefits of Apache SparkSpeed\nEngineered from the bottom-up for performance, Spark can be\u00a0100x faster than Hadoop for large scale data processing\u00a0by exploiting in memory computing and other optimizations. Spark is also fast when data is stored on disk, and currently holds the world record for large-scale on-disk sorting.\nEase of Use\nSpark has easy-to-use APIs for operating on large datasets. This includes a collection of over 100 operators for transforming data and familiar data frame APIs for manipulating semi-structured data.A Unified Engine\nSpark comes packaged with higher-level libraries, including support for SQL queries, streaming data, machine learning and graph processing. These standard libraries increase developer productivity and can be seamlessly combined to create complex workflows.Try Apache Spark on the Databricks cloud for freeThe Databricks Unified Analytics Platform offers 5x performance over open source Spark, collaborative notebooks, integrated workflows, and enterprise security \u2014 all in a fully managed cloud platform.Try DatabricksThe open source Apache Spark project can be\u00a0downloaded hereProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/product\/unity-catalog","text":"Unity Catalog | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWUnity CatalogVereinheitlichung von Governance und Teilen f\u00fcr Daten, Analytics und KI\n\u00a0Erste SchritteDemo ansehen\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowUnity Catalog ist eine einheitliche Governance-L\u00f6sung f\u00fcr alle Daten- und KI-Assets einschlie\u00dflich Dateien, Tabellen und Machine-Learning-Modellen in Ihrem Lakehouse in jeder Cloud.Zentralisierte Governance f\u00fcr Daten und KIMit einem gemeinsamen Governance-Modell, das auf ANSI SQL basiert, k\u00f6nnen Sie Dateien, Tabellen, Dashboards und ML-Modelle in jeder Cloud zentral verwalten.Integrierte Datensuche und -erkennungFinden, verstehen und referenzieren Sie schnell Daten aus Ihrem gesamten Datenbestand und steigern Sie so die Produktivit\u00e4t.Leistung und SkalierbarkeitProfitieren Sie von einer verbesserten Abfrageleistung mit Metadaten mit geringer Latenz, die die Tabellen bereitstellen und automatisch abstimmen.Automatisierte Herkunftsbestimmung f\u00fcr alle WorkloadsErstellen Sie eine einheitliche, transparente Ansicht Ihres gesamten Daten\u00f6kosystems mit automatisierter und granularer Herkunftsbestimmung f\u00fcr alle Workloads in SQL, R, Python, Scala und \u00fcber alle Asset-Typen hinweg \u2013 Tabellen, Notebooks, Workflows und Dashboards.In vorhandene Tools integrierbarMachen Sie Ihre Daten- und KI-Governance zukunftssicher mit der Flexibilit\u00e4t, Ihre vorhandenen Datenkataloge und Governance-L\u00f6sungen zu nutzen.Wie es funktioniertAlle Daten-Assets zentral verwalten und kontrollierenMit einem g\u00e4ngigen Governance-Modell basierend auf offenem Standard ANSI SQL vereinfachen Sie die Governance f\u00fcr Dateien, Tabellen, Dashboards und ML-Modelle in jeder Cloud. Definieren Sie Zugriffsrichtlinien einmal auf Kontoebene und setzen Sie sie f\u00fcr alle Workloads und Arbeitsbereiche durch. Unity Catalog bietet au\u00dferdem zentralisiertes, fein abgestimmtes Auditing, indem er ein Auditprotokoll der f\u00fcr die Daten durchgef\u00fchrten Aktionen erfasst und Ihnen hilft, Ihre Compliance- und Audit-Anforderungen zu erf\u00fcllen.\u00a0Feingepr\u00fcfte Zugriffskontrollen verwaltenVerwenden Sie Standard-SQL-Funktionen, um Zeilenfilter und Spaltenmasken zu definieren, die detaillierte Zugriffskontrollen f\u00fcr Zeilen und Spalten erm\u00f6glichen. Da Databricks weiterhin Funktionen zur Verbesserung der Skalierbarkeit und Integration ausbaut, werden Sie mit den kommenden attributbasierten Zugriffssteuerungen Zugriffsrichtlinien basierend auf benutzerdefinierten Tags (Attributen) definieren k\u00f6nnen.Einheitliches und sicheres DatensucherlebnisFinden, verstehen und referenzieren Sie schnell relevante Daten aus Ihrem gesamten Datenbestand mit einer einheitlichen Datensuche f\u00fcr Datenanalysten, Data Engineers und Data Scientists. Die Datensuche in Unity Catalog ist standardm\u00e4\u00dfig sicher, indem sie die Suchergebnisse auf der Grundlage der Zugriffsrechte der Benutzer einschr\u00e4nkt und eine zus\u00e4tzliche Sicherheitsebene aus Datenschutzgr\u00fcnden hinzuf\u00fcgt.Verbesserte Abfrageleistung in jeder Gr\u00f6\u00dfenordnungUnity Catalog bietet eine verbesserte Abfrageleistung mit Metadaten mit geringer Latenz und automatischer Tabellenabstimmung, was zu einer schnelleren Ausf\u00fchrung von Abfragen in jeder Gr\u00f6\u00dfenordnung f\u00fchrt. Asynchrone automatische Datenverdichtung optimiert Dateigr\u00f6\u00dfen und reduziert die E\/A-Latenz (Eingang\/Ausgang) automatisch im Hintergrund.Automatisierte Datenherkunftsbestimmung in EchtzeitVerschaffen Sie sich einen umfassenden \u00dcberblick \u00fcber den Datenfluss in Ihrem Lakehouse mit automatisierter und Echtzeit-Datenherkunftsbestimmung \u00fcber alle Workloads in SQL, Python, Scala und R hinweg. F\u00fchren Sie schnell Datenqualit\u00e4tspr\u00fcfungen durch, f\u00fchren Sie eine umfassende Analyse der Auswirkungen von Daten\u00e4nderungen durch und beheben Sie Fehler in Ihren Datenpipelines. Profitieren Sie von Herkunftsbestimmung \u00fcber Tabellen, Spalten, Notebooks, Workflows und Dashboards hinweg. Herkunftsdiagramme in Unity Catalog sind berechtigungsbewusst und beschr\u00e4nken den Zugriff basierend auf den Zugriffsberechtigungen der Benutzer. Die Herkunft kann auch \u00fcber die REST-API abgerufen werden, um die Integration mit anderen Katalogen zu unterst\u00fctzen.Sicherer Datenaustausch zwischen OrganisationenUnity Catalog unterst\u00fctzt nativ Delta Sharing, das weltweit erste offene Protokoll f\u00fcr die sichere Datenfreigabe, mit dem Sie vorhandene Daten problemlos in Delta Lake- und Apache Parquet-Formaten f\u00fcr jede beliebige Computerplattform freigeben k\u00f6nnen. Verbraucher m\u00fcssen sich nicht auf der Databricks-Plattform, in derselben Cloud oder \u00fcberhaupt in einer Cloud befinden. Sie k\u00f6nnen Live-Daten freigeben, ohne sie zu replizieren oder auf ein anderes System zu kopieren. Native Integrationen mit Power BI, Tableau, Spark, Pandas und Java erm\u00f6glichen es Empf\u00e4ngern, freigegebene Daten direkt aus den Tools ihrer Wahl zu nutzen. Verwalten, kontrollieren, pr\u00fcfen und verfolgen Sie die Nutzung der freigegebenen Daten zentral auf einer Plattform.Nahtlose Integration in Ihre vorhandenen ToolsUnity Catalog arbeitet mit Ihren vorhandenen Datenkatalogen, Datenspeichersystemen und Governance-L\u00f6sungen zusammen, sodass Sie Ihre vorhandenen Investitionen nutzen und ein zukunftssicheres Governance-Modell ohne teure Migrationskosten aufbauen k\u00f6nnen.Daten- und Cloud-SpeicherData Governance- und KatalogpartnerKundschaft\"Unity Catalog half uns, das Datenmanagement und die Zugriffskontrollen im gesamten Unternehmen zu vereinfachen. Das Compass-Datenteam hat mehr als 100 Datenquellen sicher eingebunden, alle Arbeitsbereiche zu Unity Catalog migriert und eine Goldschicht geschaffen, auf die wichtige Stakeholder zugreifen k\u00f6nnen, um Einblicke in Bereiche wie Kunden, Produkte, Nutzung, Umsatz und mehr zu erhalten \u2013 und so eine Single Source of Truth mit vollst\u00e4ndiger Zugriffskontrolle im gesamten Unternehmen.\u201c\u2014 Rajesh Nagpal, Leitender Direktor f\u00fcr Datentechnik\u201eUnity Catalog hat unsere Implementierung der rollenbasierten Zugriffskontrolle erheblich vereinfacht, sodass wir Daten auf Katalog-, Datenbank-, Tabellen- und Spaltenebene sichern konnten. Wir stellen den entsprechenden Zugriff nahtlos f\u00fcr alle Benutzer bereit und k\u00f6nnen den Datenzugriff zuverl\u00e4ssig verwalten und sichern, um unsere strengen Compliance- und Datenschutzrichtlinien zu erf\u00fcllen.\u201c\u2013 Chris Locklin, Engineering Manager of Data Platforms, Grammarly\u201eUnity Catalog hat es Milliman erm\u00f6glicht, seine umfangreichen Datenbest\u00e4nde direkt an seine Benutzer zu binden, was das Zugriffsmanagement vereinfacht und die Speicherkomplexit\u00e4t reduziert. Unity Catalog erm\u00f6glicht es Milliman, strenge Gesundheitsversorgungsstandards zu erf\u00fcllen, kollaborative Datenexploration zu erm\u00f6glichen und die Speicherkomplexit\u00e4t zu reduzieren. Mit Unity Catalog k\u00f6nnen wir schnell skalieren, um die Bed\u00fcrfnisse unserer Kunden zu erf\u00fcllen.\u201c\u2013 Dan McCurley, Cloud Solutions Architect, Milliman\u201eUnity Catalog erm\u00f6glicht es uns, eine Plattform der n\u00e4chsten Generation aufzubauen, die das volle Potenzial von softwaredefinierten Fahrzeugen erschlie\u00dft, die sich weiterentwickeln und verbessern, w\u00e4hrend sie Kilometer zur\u00fccklegen \u2013 das Fahrerlebnis f\u00fcr Kunden verbessern und die Umweltvorteile des elektrifizierten Transports maximieren. Wir haben jetzt einen zentralisierten Datenkatalog und eine Zugriffsverwaltung f\u00fcr verschiedene Teams und Arbeitsbereiche, was beispiellose M\u00f6glichkeiten f\u00fcr Zusammenarbeit und Innovation er\u00f6ffnet hat.\u201c\u2014 Venkat Sivasubramanian, Leitender Direktor, Big Data\u201eUnity Catalog hat f\u00fcr uns das Spiel ver\u00e4ndert. Unsere Analysten k\u00f6nnen in Databricks Workspaces in Echtzeit auf externe AWS-Tabellen zugreifen und sie mit Delta Lake-Tabellen verbinden. Es bietet uns die Leistungsvorteile von Databricks SQL, ohne Glue-Tabellen zu migrieren. Mit Unity Catalog k\u00f6nnen verschiedene Teams zusammenarbeiten, ohne die Daten von einem Ort an einen anderen zu verschieben.\u201c\u2013 Rajat Gupta, Engineering Manager, Warner Bros. DiscoveryRessourcenKeynote und Webinar[Keynote]Data Governance and sharing on the lakehouse beim Data + AI Summit 2022[On-Demand-Webinar]So vereinfachen Sie die Daten- und KI-GovernanceeBooks und Blogs[eBook] Daten, Analysen und KI-GovernanceAnk\u00fcndigung der allgemeinen Verf\u00fcgbarkeit der Datenherkunft im Unity-KatalogAnk\u00fcndigung der Verf\u00fcgbarkeit von Data Lineage mit Unity CatalogEinf\u00fchrung des Databricks Unity-Katalogs: Feink\u00f6rnige Governance f\u00fcr Daten und KI im LakehouseDokumentationAWS-DokumentationAzure-DokumentationM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mahesh-prakriya\/#","text":"Mahesh Prakriya - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMahesh PrakriyaDirector in Intelligence Platform at MicrosoftBack to speakersMahesh Prakriya is a Director in Azure Data focused on ISVs and partnerships. Over 20+ years at Microsoft and industry, Mahesh shipped some of the key data and app platforms customer depend on including Power BI, Data Integration components, SQL Server, .NET Framework, Windows & Bing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/todd-greenstein\/#","text":"Todd Greenstein - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTodd GreensteinProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rakesh-singh","text":"Rakesh Singh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRakesh SinghLead Architect at ABN AMRO Bank N.VBack to speakersLead Solution Architect and responsible for designing a future-proof data platform for ABN AMRO BankLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deylo-woo","text":"Deylo Woo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeylo WooData Engineer Architect at Providence Health ServicesBack to speakersDeylo Woo attended University of Alaska Anchorage (Computer Science) and is an experienced IT professional with 22 years of experience and 12 years with Providence Health Services. He specializes in Software and Data Engineering, and has worked with various technologies such as Java, .Net (C#), Javascript, Python, SQL, Data Warehouses, ETL development, and cloud architectures. Deylo is originally from Brazil but grew up in the US (Alaska) where his favorite past time is camping and fishing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ruifeng-zheng","text":"Ruifeng Zheng - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRuifeng ZhengSenior Software Engineer at DatabricksBack to speakersRuifeng is currently a Databricks software engineer, Apache Spark committer, working on several different modules in Apache Spark including Spark Connect, Pandas API on Spark, PySpark, MLlib, Spark SQL, SparkR, etc. Prior to Databricks, he worked on applied machine learning for 10+ years. He holds a Master degree in Electronics Engineering from Peking University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/risha-ravindranath\/#","text":"Risha Ravindranath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRisha RavindranathSr Manager, Data Governance at Comcast AdvertisingBack to speakersRisha Ravindranath brings 10+ years of experience in Data Governance and Business Analysis. She is a highly involved business analyst who expertly brings solutions together to drive end-to-end data governance programs integrated with technical solutions. Risha currently is a Senior Manager of Data Governance at Comcast Effectv.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-mlops?itm_data=home-promocard3-bigbookmlops","text":"The Big Book of MLOps | DatabrickseBookA new data-centric approach to building robust MLOps practicesDiscover the fastest path to get machine learning models to production. The Big Book of MLOps will show you how data engineers, data scientists, and machine learning engineers can build and collaborate on a common platform, using powerful and open frameworks such as Delta Lake for data pipelines, MLflow for model management and Databricks Workflows for automation.In this eBook, you\u2019ll learn:The essential components of an MLOps reference architectureThe key stakeholders to involve as you build and deploy machine learning applicationsHow to leverage the same platform for data and models and get to production fasterHow to monitor data and models through the complete ML lifecycle with end-to-end lineageBest practices to guide your MLOps planning and decision-makingDownload your copyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/digital-pathology","text":"Digital Pathology Image Analysis | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorDigital Pathology Image AnalysisPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedImprove the efficiency of diagnostic teams with deep learningHelp augment diagnostic workflows with this Databricks Solution Accelerator for pathology image analysis. Now you can rapidly process thousands of whole slide images in minutes and use machine learning to automate the detection of metastasis. Findings are visualized with a metastasis probability heat map that can be shared with diagnostic teams.Accelerate image analysis at scaleAutomate the detection of cancer metastasisEnable clinical reproducibilityDownload notebookResourcesSelf guided tourLearn moreWebinarLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/12\/15\/announcing-general-availability-of-databricks-sql.html","text":"Announcing General Availability of Databricks SQL - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing General Availability of Databricks SQLby Bilal Aslam, Can Efeoglu, Erika Ehrli, Shant Hovsepian, Paul Leventis, Cyrielle Simeone and Reynold XinDecember 15, 2021 in Platform BlogShare this postToday, we are thrilled to announce that Databricks SQL is Generally Available (GA)! This follows our earlier announcements about Databricks SQL\u2019s world record-setting performance for data warehousing workloads, and adoption of standard ANSI SQL. With GA, you can expect the highest level of stability, support and enterprise-readiness from Databricks for mission-critical workloads on the Databricks Lakehouse Platform. In this blog post, we explore how Databricks SQL is powering a new generation of analytics and data applications, running directly on the data lake, at the world\u2019s leading companies.Customers win with the open lakehouseHistorically, data teams had to resort to a bifurcated architecture to run traditional BI and analytics workloads, copying subsets of the data already stored in their data lake to a legacy data warehouse. Unfortunately, this led to the lock-in, high costs and complex governance inherent in proprietary architectures.Our customers asked us to simplify their data architecture. We introduced Databricks SQL to provide data warehousing capabilities and first class support for SQL on the Databricks Lakehouse Platform. Using open standards, Databricks SQL provides up to 12x better price\/performance for data warehousing and analytics workloads on existing data lakes. And it works seamlessly with popular tools like Tableau, PowerBI, Looker, and dbt without sacrificing concurrency, latency and scale, all the while maintaining a single source of truth for your data.Databricks SQL is already powering production use cases at leading companies around the globe. From startups to enterprises, over 1,000 companies are using Databricks SQL to power the next generation of self-served analytics and data applications:Atlassian is building on the Lakehouse Platform one of the most ambitious data applications on the planet, providing nearly 190K external users with the ability to generate insights and analytics on the freshest data. Databricks SQL is also enabling data democratization internally across over 3K users, and more BI workloads are moving to Databricks SQL with PowerBI.Punchh has accelerated ETL pipelines, democratized data and analytics, and improved BI and reporting\u2014increasing customer retention and loyalty. Databricks SQL allows Punchh\u2019s data team to query their data directly within Databricks and then share insights through rich visualizations and fast reporting via Tableau.SEGA Europe has moved away from a costly data warehouse-centric architecture to the Databricks Lakehouse Platform. And in doing so, successfully unified massive amounts of structured and unstructured data. This enables their data teams to derive insights needed to deliver personalized experiences to 30 million gamers across the globe. SEGA Europe\u2019s existing BI tools, Tableau and PowerBI, work seamlessly with Databricks SQL.Powering modern analytics on the lakehouseDatabricks SQL offers all the capabilities you need to run data warehousing and analytics workloads on the Databricks Lakehouse Platform:Instant, elastic SQL-optimized compute for low-latency, high-concurrency queries that are typical in analytics workloads. Compute is separated from storage so you can scale with confidence.Integration with your existing tools such as Tableau, PowerBI, dbt and Fivetran, so you can get value from your data without having to learn new solutions.Simplified administration and data governance, so you can quickly and confidently enable self-serve analytics.A first-class, built-in analytics experience with a SQL query editor, visualizations and interactive dashboards. Analysts can go from zero-to-aha! in moments.We can\u2019t wait to see what you buildWatch the demo below to discover the ease of use of Databricks SQL for analysts and administrators alike:To play this video, click here and accept cookiesIf you already are a Databricks customer, follow the guide to get started (AWS | Azure). Read the release notes to learn more about what's included in this GA release. If you are not an existing Databricks customer, sign up for a free trial with a Premium or Enterprise workspace.Watch Delivering Analytics on the Lakehouse with Reynold Xin to learn more, and don\u2019t miss our free virtual training on January 13, 2022 to dive in!Try Databricks for freeGet StartedRelated postsAnnouncing General Availability of Databricks SQLDecember 15, 2021 by Bilal Aslam, Can Efeoglu, Erika Ehrli, Shant Hovsepian, Paul Leventis, Cyrielle Simeone and Reynold Xin in Platform Blog\nToday, we are thrilled to announce that Databricks SQL is Generally Available (GA)! This follows our earlier announcements about Databricks SQL\u2019s world record-setting p...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shawn-gilleran","text":"Shawn Gilleran - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShawn GilleranPrincipal Cloud Solutions Lead at LiveRampBack to speakersShawn Gilleran leads cloud solutions at LiveRamp, helping clients leverage identity for safe and effective data use in the cloud. With over 30 years in IT, he's an expert in managed infrastructure, specializing in identity resolution for marketing, compliance, and modeling. Prior to LiveRamp, he spent 25 years at Acxiom and founded Vortex, a company focused on data monetization. Shawn holds a BS in computer science and is a patent holder for marketing technologies. He resides in Little Rock, AR.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/financial-services-resources\/video-lakehouse-for-financial-services","text":"\n\n\n\n\n\n\n\nVideo: Lakehouse for Financial Services\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-marsh\/#","text":"Paul Marsh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MarshSenior Director Application Development at New York JetsBack to speakersPaul Marsh is the Sr. Director of Application Development at the New York Jets. In his current role, Paul is responsible for the development and management of the Jets data infrastructure including its Databricks installation and the other technologies that make up the organization's data stack. Paul has been with the Jets organization for 19 years, including 14 years overseeing application development at the organization. Paul holds an BA in History from Binghampton University as well as a Masters of Science in E-Commerce from Fairleigh Dickinson University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/slava-frid","text":"Slava Frid - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSlava FridCTO at WorldQuant PredictiveBack to speakersSlava is a 20+ year technology industry veteran who has led award-winning teams in finance, media, & non-profit sectors & enjoys pushing the envelope of what is considered possible. He is currently embracing the challenge of helping to build a new way to enable Quantitative Researchers to answer toughest questions businesses & organizations have. He received his degree in Econ from Wharton and a Computer Science degree from UPenn\u2019s School of Engineering. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=sales","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueDatabricks 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{"source":"https:\/\/www.databricks.com\/legal\/applicant-privacy-notice","text":"Applicant Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesApplicant Privacy NoticeEffective Date: January 3, 2023This Applicant Privacy Notice describes how Databricks, Inc., its affiliates and subsidiaries (collectively, \u201cDatabricks,\u201d \u201cwe,\u201d \u201cus,\u201d and \u201cour\u201d) collect, use and share personal information during the application and recruitment process. It also contains information about your choices and privacy rightsInformation We Collect About YouWe may collect the following personal information during the applicant recruitment process:Contact Information. We will collect basic contact information such as your full name, email address, and phone number.Work History. As part of the application process we may collect a resume, CV, cover letter, and\/or job application which may include information about your education, experiences, and job history.Educational Information. We may collect information including degrees awarded, transcripts, and other information in support of the job application.Online Resources. We may collect publicly available information from online sites, such as information contained within your LinkedIn profile, Facebook page, or other personal websites.Diversity and Inclusion. Where allowed or required by law we may ask you to provide information such as ethnicity, gender identity, veteran status, or any disability or accommodation request during the recruitment process.Candidate Assessments and Presentations. For certain roles, we may collect information from an assessment of your skills. You may also be asked to perform a technical exercise or do a presentation during the recruitment process, which may be recorded and shared with the Databricks internal teams responsible for the hiring decision.Reference Information. We may collect reference information where applicable, including information provided by third parties.Information from Third Parties. We may collect information about you from recruitment agencies who presented you, recruiting sites, Databricks employees who referred you, referees, and background checking companies that are used to verify the information you have provided during the application and recruitment process. We may combine such information with the information we receive or collect from you.Background Check. We may, as permitted by law, choose to conduct a background check, which may include verification of your education, job history, references, and criminal records history.Other information. We also collect any additional information that you choose to include in your application materials or share with us during the application and recruitment process including information collected during phone screens, email\/messaging exchanges and interviews.Purposes of Collection and UseWe may process your personal information for the following legitimate business purposes:We collect and use your contact information to keep in contact with you during the recruitment process, including through our applicant tracking system, and to contact you about other open roles that may be of interest to you.We review your resume\/CV and any information collected from online resources to assess your skills and experience against the position for which you have applied.If you are asked to complete an assessment or provide a presentation during the recruitment process, we will use that information to match your skills against the position for which you applied.If you are successfully moved forward in the recruitment process, we may use your information to perform background checks, education verification, and reference checks, as permitted by local law.If you are hired by Databricks your personal information will be transferred to your employee file.If you are not successful in the recruitment process, we may hold onto the information collected during the recruitment process, including your personal information, so we can reach out to you if other roles become available that match your skill set. If you would prefer that we remove your information from our systems, please let us know by emailing [email\u00a0protected].Any data you submit to a Third Party Service will be subject to the terms of service and privacy policy of such Third Party Service. We may also link to co-branded websites or products that are maintained by Databricks and one or more of our business partners. Please note that these co-branded websites and products may have their own privacy policy, which we encourage you to read and understand. When you click a link to a third-party site, you will leave our site.We may process personal information to comply with our legal, regulatory, or other corporate government requirements.We may also process your personal information to analyze and improve our application and recruitment process.How We Share Your InformationWe may share your personal information with the following types of third parties:Within the Databricks group of affiliated companies. We may share your personal information within the Databricks group of affiliated companies to facilitate the application and recruitment process.Service Providers. We may engage service providers to perform certain functions related to the application and recruitment process, including companies that help us run our internal applicant tracking system, perform background checks, or perform audits. All third parties that act on our behalf in the application and recruitment process are subject to confidentiality provisions and the requirements that they will only use your personal information to provide the services.Legal Requirements. We may disclose your personal information when authorized by law or as necessary to comply with a legal process.Protection of Rights. We may disclose your personal information when required to protect and defend the rights and property of Databricks and its group of affiliated companies, our third-party vendors, and other users of any websites used in the applicant and recruitment process.\u00a0Legal basis for processingConsent. In certain cases, we ask you for your consent to process your personal information. You can withdraw your consent at any time by emailing [email\u00a0protected].Performance of a Contract. We collect and use your personal information where it is necessary to take steps, at your request, prior to making a job offer, completing a contract of employment with you, or to perform our obligations under an agreement we have with you. For example, we use your personal information to make you a job offer or complete a contract of employment with you.Legitimate Interest. We may process your personal information for legitimate interests including, for example, to conduct our recruitment processes efficiently or to manage applicants effectively.Other Legal Bases. In some cases, we may have a legal obligation to process your personal information. We also may need to process your personal information to protect vital interests, or to exercise, establish, or defend legal claims.International Transfers\u00a0Databricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Where necessary, we also make use of supplementary measures to ensure your information is adequately protected.\u00a0Data RetentionWe will retain your personal information for as long as necessary to fulfill the purposes for which it was collected, resolve disputes, enforce our agreements, and comply with any laws or regulations. Databricks may retain your personal information longer with your consent or for a legitimate business interest where we have assessed the business benefit and confirmed that such business benefit is not outweighed by your personal rights and freedoms.Your Privacy RightsDepending upon your residence, you may have certain rights in relation to your personal information. Depending on applicable data protection laws, these may include your right to request access to or to update your information, request that it be deleted, or object to Databricks using it for certain purposes. If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. Depending on your location, you may also raise any concerns you have regarding our collection and use of your personal information with your local data protection authority. California residents, please see below under \u201cAdditional Information for California Residents\u201d for information about rights that may be applicable to you.Security\u00a0We use technical and organizational measures that provide a level of security appropriate to the risk of processing your personal information. Please be aware, however, that no method of transmitting information over the Internet or storing information is completely secure.Changes to this Privacy NoticeWe may update this policy from time to time by posting a new version on this page. We encourage you to periodically review this page for the latest information on our privacy practices.How to contact usIf you have any questions about this Applicant Privacy Notice or wish to exercise your rights in your personal information, please contact us at [email\u00a0protected] or at the mailing addresses below. We will respond to your request within a reasonable time or as otherwise required by law.Databricks Inc.\nAttn: Privacy\n160 Spear Street\nSuite 1300\nSan Francisco, California 94105\nUnited StatesAdditional Information for California ResidentsWe provide the following information to our applicants or candidates who are California residents, pursuant to the California Consumer Privacy Act, as amended by the California Privacy Rights Act (\u201cCCPA\u201d). For a description of all of our data collection, use and disclosure practices, please read this Privacy Notice in its entirety.Categories of Personal InformationBelow, we describe the categories of Personal Information (as defined in the CCPA) that we have collected within the preceding 12 months and may collect about applicants or candidates on a going-forward basis:IdentifiersPersonal information categories listed in the California Customer Records statute (Cal. Civ. Code \u00a7 1798.80(e)) (e.g., name, address, email address)Characteristics of protected classifications under California or federal lawInternet or other similar network activityGeolocation data (e.g., general location derived from an IP address)Sensory data (e.g., audio, electronic, visual or similar information including candidate assessments and presentations)Professional or employment-related informationEducation informationInferences drawn from the preceding categories of Personal InformationWithin these categories of Personal Information, we may also collect the following categories of Sensitive Personal Information \u00a0(as defined in the CCPA):\u00a0Account log-in in combination with any required security or access codes, password, or credentials allowing access to the accountSocial security, driver\u2019s license, state identification card, or passport numberRacial or ethnic origin, for diversity purposes and consistent with applicable lawHealth-related information, to the extent necessary to provide necessary accommodationsCategories of Recipients of Personal InformationFor each category of Personal Information (including Sensitive Personal Information) listed above, we disclose this information as described above in the \u201cHow we share your information\u201d section of the Applicant Privacy Notice.Sources of Personal InformationWe obtain the categories of Personal Information listed above directly from you or from devices on which you use our Sites, as well as described above in the \u201cInformation we Collect About You\u201d section of the Applicant Privacy Notice.Purposes for Which We Use Personal InformationWe use Personal Information for a variety of business and commercial purposes, as described above in the \u201cPurposes of Collection and Use\u201c section of our Applicant Privacy Notice.Retention Period CriteriaDatabricks retains the personal information as described above in the \u201cData Retention\u201c section of this Applicant Privacy Notice.CCPA Rights and Requests\u00a0To the extent provided by the CCPA, you may make the following types of requests under the CCPA with respect to Personal Information that we process on our own behalf.Requests to Know, Correct, and Delete: You may request:\u00a0Access to a copy of the specific pieces of Personal Information that we have collected about you;Correction of Personal Information that we maintain about you, if it is inaccurate; and\/orDeletion of Personal Information that we maintain about you, subject to certain exceptionsYou may submit such requests by completing the request form here or emailing us at [email\u00a0protected]. We will respond to your request consistent with the CCPA, and subject to any exceptions that may apply under the CCPA. We may need to request additional Personal Information from you, such as email address, state of residency, or mailing address, in order to verify your identity and protect against fraudulent requests.Authorized AgentsIf you wish to use an authorized agent to make a CCPA request on your behalf, please direct the authorized agent to use the submission methods noted above. As part of our verification process, we may request that the authorized agent provides, as applicable, proof concerning status as an authorized agent. We may also require you to verify your own identity directly with us; or directly confirm with us that you provided permission to submit the request on your behalf.NondiscriminationYou have the right to be free from unlawful discriminatory treatment for exercising any of your CCPA rights.Please contact us at [email\u00a0protected] if you have any additional questions.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/07\/23\/augment-your-siem-for-cybersecurity-at-cloud-scale.html","text":"How to Augment Your SIEM for Cybersecurity at Cloud Scale - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAugment Your SIEM for Cybersecurity at Cloud Scaleby Michael Ortega and Monzy MerzaJuly 23, 2021 in Platform BlogShare this postOver the last decade, security incident and event management tools (SIEMs) have become a standard in enterprise security operations. SIEMs have always had their detractors. But the explosion of cloud footprints is prompting the question, are SIEMs the right strategy in the cloud-scale world? Security leaders from HSBC don\u2019t think so. In a recent talk, Empower Splunk and Other SIEMs with the Databricks Lakehouse for Cybersecurity, HSBC highlighted the limitations of legacy SIEMs and how the Databricks Lakehouse Platform is transforming cyberdefense. With $3 trillion in assets, HSBC\u2019s talk warrants some exploration.In this blog post, we will discuss the changing IT and cyber-attack threat landscape, the benefits of SIEMs, the merits of the Databricks Lakehouse and why SIEM + Lakehouse is becoming the new strategy for security operations teams. Of course, we will talk about my favorite SIEM! But I warn you, this isn\u2019t a post about critiquing \u201clegacy technologies built for an on-prem world.\u201d This post is about how security operations teams can arm themselves to best defend their enterprises against advanced persistent threats.The enterprise tech footprintSome call it cloud-first and others call it cloud-smart. Either way, it is generally accepted that every organization is involved in some sort of cloud transformation or evaluation -- even in the public sector, where onboarding technology isn\u2019t a light decision. As a result, the main US cloud service providers all rank within the top 5\u00a0 largest market cap companies in the world. As tech footprints are migrating to the cloud, so are the requirements for cybersecurity teams. Detection, investigation and threat hunting practices are all challenged by the complexity of the new footprints, as well as the massive volumes of data. According to IBM, it takes 280 days on average to detect and contain a security breach. According to HSBC\u2019s talk at Data + AI Summit, 280 days would mean over a petabyte of data -- just for network and EDR (endpoint threat detection and response) data sources.When an organization needs this much data for detection and response, what are they to do?\u00a0 Many enterprises want to keep the cloud data in the cloud. But what about from one cloud to the other? I spoke to one large financial services institution this week who said, \u201cWe pay over a $1 million in egress cost to our cloud provider.\u201d Why? Because their current SIEM tool is on one cloud service and their largest data producers are on another.\u00a0 Their SIEM isn\u2019t multi-cloud. And over the years, they have built complicated transport pipelines to get data from one cloud provider to the other. Complications like this have warped their expectations from technology. For example, they consider 5-minute delays in data to be real time. I present this here as a reality of what modern enterprises are confronted with -- I am sure the group I spoke with is not the only one with this complication.Security analytics in the cloud worldThe cloud terrain is really messing with every security operations team\u2019s m.o. What was called big data 10 years ago is puny data by today\u2019s cloud standards. With the scale of today\u2019s network traffic, gigabytes are now petabytes, and what used to take months to generate now happens in hours. The stacks are new and security teams are having to learn them. Mundane tasks like, \u201chave we seen these IPs before\u201d are turning into hours or days-long searches in SIEM and logging tools. Slightly more sophisticated contextualization tasks, like adding the user\u2019s name to network events, are turning into near impossible ordeals. And if one wants to do streaming enrichments of external threat intelligence at terabytes of data per day -- good luck -- hope you have a small army and a deep pocket. And we haven\u2019t even gotten to anomaly detection or threat hunting use cases. This is by no means a jab at SEIMs. In reality, the terrain has changed and it\u2019s time to adapt. Security teams need the best tools for the job.What capabilities do security teams need in the cloud world? First and foremost, an open platform that can be integrated with the IT and security tool chains and does not require you to provide your data to a proprietary data store. Another critical factor is a multi-cloud platform, so it can run on the clouds (plural) of your choice. Additionally, a scalable and highly-performant analytics platform, where compute and storage are decoupled that can support end-to-end streaming AND batch processing. And finally, a unified platform to empower data scientists, data engineers, SOC analysts and business analysts -- all data people. These are the capabilities of the Databricks Lakehouse Platform.The SaaS and auto-scaling capabilities of Databricks simplify the use of these sophisticated capabilities. Databricks security customers are crunching across petabytes of data in sub ten minutes. One customer is able to collect from 15+ million endpoints and analyze the threat indicators in under an hour. A global oil and gas producer, paranoid about ransomware, runs multiple analytics and contextualizes every single powershell execution in their environment -- analysts only see high confidence alerts.Lakehouse + SIEM : The pattern for cloud-scale security operationsGeorge Webster, Head of Cybersecurity Sciences and Analytics at HSBC, describes\u00a0 the Lakehouse + SIEM is THE pattern for security operations. It leverages the strengths of the two components: a lakehouse architecture for multicloud-native storage and analytics, and SIEM for security operations workflows. For Databricks customers, there are two general patterns for this integration. But they are both underpinned by what Webster calls, The Cybersecurity Data Lake with Lakehouse.The first pattern: The lakehouse stores all the data for the maximum retention period. A subset of the data is sent to the SIEM and stored for a fraction of the time.\u00a0 This pattern has the advantage that analysts can query near-term data using the SIEM while having the ability to do historical analysis and more sophisticated analytics in Databricks. And manage any licensing or storage costs for the SIEM deployment.The second pattern is to send the highest volume data sources to Databricks, (e.g. cloud native logs, endpoint threat detection and response logs, DNS data and network events). Comparatively low volume data sources go to the SIEM, (e.g. alerts, email logs and vulnerability scan data). This pattern enables Tier 1 analysts to quickly handle high-priority alerts in the SIEM. Threat hunt teams and investigators can leverage the advanced analytical capabilities of Databricks. This pattern has a cost benefit of offloading processing, ingestion and storage off of the SIEM.Integrating the Lakehouse with SplunkWhat would a working example look like? Because of customer demand, the Databricks Cybersecurity SME team created the Databricks add-on for Splunk. The add-on allows security analysts to run Databricks queries and notebooks from Splunk and receive the results back into Splunk. A companion Databricks notebook enables Databricks to query Splunk, get Splunk results and forward events and results to Splunk from Databricks.With these two capabilities, analysts on the Splunk search bar can interact with Databricks without leaving the Splunk UI. And Splunk search builders or dashboards can include Databricks as part of their searches. But what's most exciting is that security teams can create bi-directional, analytical automation pipelines between Splunk and Databricks.\u00a0 For example, if there is an alert in Splunk, Splunk can automatically search Databricks for related events, and then add the results to an alerts index or a dashboard or a subsequent search. Or conversely, a Databricks notebook code block can query Splunk and use the results as inputs to subsequent code blocks.With this reference architecture, organizations can maintain their current processes and procedures, while modernizing their infrastructure, and become multi-cloud native to meet the cybersecurity risks of their expanding digital footprints.Achieving scale, speed, security and collaborationSince partnering with Databricks, HSBC has reduced costs, accelerated threat detection and response, and improved their security posture. Not only can the financial institution process all of their required data, but they've increased online query retention from just days to many months at the PB scale. The gap between an attacker's speed and HSBC's ability to detect malicious activity and conduct an investigation is closing. By performing advanced analytics at the pace and speed of adversaries, HSBC is closer to their goal of moving faster than bad actors.As a result of data retention capabilities, the scope of HSBC threat hunts has expanded considerably. HSBC is now able to execute 2-3x more threat hunts per analyst, without the limitations of hardware. Through Databricks notebooks, hunts are reusable and self-documenting, which keeps historical data intact for future hunts. This information, as well as investigation and threat hunting life cycles, can now be shared between HSBC teams to iterate and automate threat detection. With efficiency, speed and machine learning\/artificial intelligence innovation now available, HSBC is able to streamline costs, reallocate resources, and better protect their business-critical data.What's nextWatch Empower Splunk and Other SIEMs with the Databricks Lakehouse for Cybersecurity to hear directly from HSBC and Databricks about how they are addressing their cybersecurity requirements.Learn more about the Databricks add-on for Splunk.References\u00a0Market caps: https:\/\/www.visualcapitalist.com\/the-biggest-companies-in-the-world-in-2021\/Breach lifecycle: https:\/\/www.ibm.com\/security\/digital-assets\/cost-data-breach-report\/#\/Try Databricks for freeGet StartedSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pieter-noordhuis","text":"Pieter Noordhuis - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPieter NoordhuisSr. Staff Software Engineer at DatabricksBack to speakersSoftware Engineer at Databricks working on developer toolingLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/delta-lake","text":"Delta Lake Demo: Reliable Data Lakes at Scale | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta Lake on Databricks DemoGet started for freeDownload Demo NotebookWith\u00a0Delta Lake on Databricks, you can build a\u00a0lakehouse architecture\u00a0that combines the best parts of data lakes and data warehouses on a simple and open platform that stores and manages all of your data and supports all of your analytics and AI use cases.In this demo, we cover the main features of Delta Lake, including unified batch and streaming data processing, schema enforcement and evolution, time travel, and support for UPDATEs\/MERGEs\/DELETEs, as well as touching on some of the performance enhancements available with Delta Lake on Databricks.See full list of demosDive deeper into Delta LakeLearn moreLearn moreLean moreVideo transcriptDelta Lake Demo: Introduction\nThe lakehouse is a simple and open data platform for storing and managing all of your data, that supports all of your analytics and AI use cases. Delta Lake provides the open, reliable, performant and secure foundation for the lakehouse.\nIt\u2019s an open-source data format and transactional data management system, based on Parquet, that makes your data lake reliable by implementing ACID transactions on top of cloud object storage. Delta Lake tables unify batch and streaming data processing right out of the box. And finally, Delta Lake is designed to be 100% compatible with Apache SparkTM. So it\u2019s easy to convert your existing data pipelines to begin using Delta Lake with minimal changes to your code.Collapse full transcriptExpand full transcriptCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/building-machine-learning-platforms?itm_data=lakehouse-link-buildingmlplatforms","text":"Building Machine Learning Platforms | DatabricksBuilding Machine Learning PlatformsHear Matei Zaharia\u2019s keynote on MLOps and ML Platforms State of the Industry \u2014 now available on-demand. Learn about managing the end-to-end ML lifecycle at scale from Databricks\u2019 chief technology officer and co-founder. Topics covered:Product demos: How to operationalize data science and ML on Databricks with MLflowReal-world use cases: Analytics experts at Blue Cross, Atlassian, Quby and OutreachQ&A panel: Hosted by Ben Lorica, Chief Data Scientist, DatabricksFeatured SpeakersMatei ZahariaCo-founder and Chief Technology OfficerDatabricksBen LoricaChief Data ScientistDatabricksClemens MewaldDirector, Product Management, Data Science and MLDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform(GCP) | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWGoogle Cloud \uae30\ubc18 Databricks\uac1c\ubc29\ud615 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uacfc \uac1c\ubc29\ud615 \ud074\ub77c\uc6b0\ub4dc\ub97c \uacb0\ud569\ud558\uc5ec \ud1b5\ud569 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubc0f \ubd84\uc11d \ud1b5\ud569\uc2dc\uc791\ud558\uae30Google Cloud \uae30\ubc18 Databricks\ub294 \uacf5\ub3d9 \uac1c\ubc1c\ub41c \uc11c\ube44\uc2a4\ub85c, \uc774\ub97c \uc0ac\uc6a9\ud558\uba74 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc640 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uc7a5\uc810\uc744 \uacb0\ud569\ud55c \uac04\ub2e8\ud55c \uac1c\ubc29\ud615 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \uc800\uc7a5\ud558\uc5ec \uad00\ub9ac\ud558\uace0, \ubaa8\ub4e0 \ubd84\uc11d \ubc0f AI \uc6cc\ud06c\ub85c\ub4dc\ub97c \ud1b5\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks\ub294 Google Cloud Storage, BigQuery \ubc0f Google Cloud AI Platform\uacfc \uae34\ubc00\ud788 \ud1b5\ud569\ub418\uc5b4 Google Cloud\uc5d0\uc11c \ub370\uc774\ud130\uc640 AI \uc11c\ube44\uc2a4\ub85c \ub9e4\ub044\ub7fd\uac8c \uc791\uc5c5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ubaa8\ub4e0 \ub370\uc774\ud130\uc5d0\uc11c SQL \ubd84\uc11d \uc2e4\ud589\ud611\uc5c5\ud615 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\ud504\ub85c\ub355\uc158 \uba38\uc2e0 \ub7ec\ub2dd\nGoogle Cloud \uae30\ubc18 Databricks\ub97c \uc0ac\uc6a9\ud574\uc57c \ud558\ub294 \uc774\uc720\uc624\ud508\uac1c\ubc29\ud615 \ud45c\uc900, \uac1c\ubc29\ud615 API \ubc0f \uac1c\ubc29\ud615 \uc778\ud504\ub77c\uc5d0 \uae30\ubc18\ud558\uc5ec \uc6d0\ud558\ub294 \ub300\ub85c \ub370\uc774\ud130\uc5d0 \uc561\uc138\uc2a4\ud558\uace0, \uc774\ub97c \ucc98\ub9ac \ubc0f \ubd84\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ucd5c\uc801\ud654Google Kubernetes Engine\uc5d0 Databricks\ub97c \ubc30\ud3ec\ud558\uba74 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uc2e4\ud589\ub418\ub294 \ucd5c\ucd08\uc758 Kubernetes \uae30\ubc18 Databricks \ub7f0\ud0c0\uc784\uc73c\ub85c\uc368, \ub354\uc6b1 \ube60\ub974\uac8c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ud1b5\ud569Google Cloud Console\uc5d0\uc11c \ud074\ub9ad \ud55c \ubc88\uc73c\ub85c Databricks\uc5d0 \uc561\uc138\uc2a4\ud558\uace0, \ud1b5\ud569 \ubcf4\uc548, \uccad\uad6c \ubc0f \uad00\ub9ac\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uace0\uac1d \uc0ac\ub840 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30\n\"Google Cloud \uae30\ubc18 Databricks\ub294 \ud655\uc7a5 \uac00\ub2a5\ud55c \ucef4\ud4e8\ud305 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub2e4\uc591\ud55c \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc801\uc6a9\ud558\ub294 \uacfc\uc815\uc744 \ub2e8\uc21c\ud654\ud558\uc5ec, Databricks\uc5d0\uc11c \uc0ac\uc6a9\ud558\ub294 \uac01 \ube44\uc988\ub2c8\uc2a4 \uc9c8\ubb38\uc774\u0000\u0000\ub098 \ubb38\uc81c \uc124\uc815\uc5d0 \ub300\ud55c \uc194\ub8e8\uc158\uc744 \uc81c\uacf5\ud558\ub294 \ub370 \ud544\uc694\ud55c \uacc4\ud68d \uc0ac\uc774\ud074\uc744 \ub2e8\ucd95\ud569\ub2c8\ub2e4.\"\u2014Harish Kumar, Reckitt \uae00\ub85c\ubc8c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \uc774\uc0acGoogle Cloud\uc640\uc758 \uac04\uc18c\ud654\ub41c \ud1b5\ud569Google Cloud StorageGoogle Cloud StorageGoogle Cloud Storage(GCS)\uc758 \ub370\uc774\ud130\uc5d0 \ub9e4\ub044\ub7ec\uc6b4 \uc77d\uae30\/\uc4f0\uae30 \uc561\uc138\uc2a4\ub97c \uc9c0\uc6d0\ud558\uba70, Databricks \ub0b4\uc5d0\uc11c Delta Lake \uc624\ud508 \ud615\uc2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uac15\ub825\ud55c \uc548\uc815\uc131 \ubc0f \uc131\ub2a5 \uae30\ub2a5\uc744 \ucd94\uac00\ud569\ub2c8\ub2e4.Google Kubernetes EngineBigQueryBig Cloud IdentityGoogle Cloud AI PlatformGoogle Cloud BillingLooker\ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\ub9ac\uc18c\uc2a4\uac00\uc0c1 \uc774\ubca4\ud2b8\uac00\uc0c1 \uc6cc\ud06c\uc20d: \uac1c\ubc29\ud615 \ub370\uc774\ud130 \ub808\uc774\ud06c\ub274\uc2a4Databricks, Google Cloud\uc640 \ud611\ub825\ud558\uc5ec \uae00\ub85c\ubc8c \uae30\uc5c5\uc5d0 \ud50c\ub7ab\ud3fc \uc81c\uacf5\ube14\ub85c\uadf8 \ubc0f \ubcf4\uace0\uc11cGoogle Cloud \uae30\ubc18 Databricks \ucd9c\uc2dc \uacf5\uc9c0Google Cloud \uae30\ubc18 Databricks \uc18c\uac1c \u2013 \ucd5c\uc2e0 \uacf5\uac1c \ubbf8\ub9ac \ubcf4\uae30Google Cloud \uae30\ubc18 Databricks \ub370\uc774\ud130\uc2dc\ud2b8Google Cloud \uae30\ubc18 Databricks \uc815\uc2dd \ucd9c\uc2dcGoogle Cloud \uae30\ubc18 Databricks\ub97c \uc0ac\uc6a9\ud55c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubc0f \ubd84\uc11d\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks 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\ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/natalia-demidova\/#","text":"Natalia Demidova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North America at Hitachi Solutions America Ltd.Back to speakersNatalia has a Ph.D. in Mechanical Engineering. She is serving as a Director \u2013 Solution Principal in Data, Data Science and AI with Hitachi Solutions. Natalia led the design of the Real-time AI platforms with MLOps and LLMOps, and Machine Learning pipelines in alignment with Client\u2019s strategic business goals and KPIs. Some examples of Natalia's solutions with Azure Databricks involve the Intelligent Knowledge Management platform, AEC Construction Cloud with AI, IoT-based predictive maintenance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/lovelytics-health","text":"Lovelytics Health | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionHealth Data Interoperability by LovelyticsIndustry-specific solution developed by Lovelytics and powered by the Databricks Lakehouse Platform\nGet startedQuick and meaningful analytics for health dataThe healthcare industry has a legacy of highly structured data models and complex analytics pipelines for a variety of use cases such as clinical trial analytics, therapeutics, operational reporting, and governance and compliance. The Lovelytics Health Data Interoperability accelerator automates the ingestion of streaming FHIR bundles into the lakehouse for downstream patient analytics at scale. Now you can:Democratize technology and analytics to prototype health data dashboards quickerSimplify the exchange of health data models and reuse data assets for a variety of new use casesEstablish the right foundation for your analytics roadmapGet startedProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/healthcare-and-life-sciences","text":"Lakehouse pour la sant\u00e9 et les sciences de la vie - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLakehouse pour la sant\u00e9 et les sciences de la vieOffrir de meilleurs r\u00e9sultats aux patients gr\u00e2ce aux donn\u00e9es et \u00e0 l'IAD\u00e9marrerPlanifier une d\u00e9moQuatre d\u00e9fis li\u00e9s aux donn\u00e9es dans le domaine de la sant\u00e9 et des sciences de la vieFragmentation des donn\u00e9es des patients\nLes silos de donn\u00e9es et la prise en charge limit\u00e9e des donn\u00e9es non structur\u00e9es emp\u00eachent les organisations de comprendre le parcours du patient.Croissance rapide des donn\u00e9es de sant\u00e9\nLes anciennes architectures de donn\u00e9es on-premise sont complexes \u00e0 g\u00e9rer et co\u00fbteuses \u00e0 faire \u00e9voluer pour r\u00e9pondre aux volumes massifs de donn\u00e9es de sant\u00e9 actuelles, dus notamment \u00e0 la croissance de l'imagerie et de la g\u00e9nomique.Soins et op\u00e9rations en temps r\u00e9el\nLes data warehouses et les outils disjoints emp\u00eachent de fournir en temps r\u00e9el les insights n\u00e9cessaires \u00e0 la prise de d\u00e9cisions cruciales en mati\u00e8re de soins, ainsi qu'\u00e0 la fabrication et \u00e0 l'administration en toute s\u00e9curit\u00e9 de produits th\u00e9rapeutiques importants.Complexit\u00e9 de l'analytique avanc\u00e9e de la sant\u00e9\nLes capacit\u00e9s l\u00e9g\u00e8res de ML emp\u00eachent les organisations de s'attaquer \u00e0 un large spectre, des mod\u00e8les de soins aux patients de nouvelle g\u00e9n\u00e9ration \u00e0 l'analytique pr\u00e9dictive pour la R&D de m\u00e9dicaments.Lakehouse pour la sant\u00e9 et les sciences de la vieUne plateforme unifi\u00e9e d'IA et de donn\u00e9es\nUne plateforme unique qui rassemble toutes vos charges de travail de donn\u00e9es et d'analytique afin de permettre de profondes innovations pour les soins aux patients et la R&D m\u00e9dicamenteuse.\nSolutions partenaires\nLes principaux fournisseurs mondiaux de solutions pour le secteur de la sant\u00e9 et des sciences de la vie, tels que Deloitte, Accenture et ZS Associates, d\u00e9veloppent le lakehouse. Profitez d'offres pr\u00e9d\u00e9finies qui acc\u00e9l\u00e8rent la transformation data-driven dans le domaine de la R&D m\u00e9dicamenteuse et des soins aux patients.\nDes outils pour acc\u00e9l\u00e9rer\nDatabricks et ses partenaires ont mis au point une s\u00e9rie d'acc\u00e9l\u00e9rateurs de solutions qui facilitent l'int\u00e9gration des donn\u00e9es relatives aux soins de sant\u00e9, telles que les messages\u00a0HL7, et la r\u00e9alisation de cas d'usage tels que l'analytique de textes m\u00e9dicaux et le monitoring de la s\u00e9curit\u00e9 des m\u00e9dicaments.\nCollaboration dans le secteur\nActiver le partage de donn\u00e9es s\u00e9curis\u00e9es et ouvertes et la collaboration avec des organisations de l'ensemble de l'\u00e9cosyst\u00e8me de la sant\u00e9, afin d'acc\u00e9l\u00e9rer la recherche pour sauver des vies et am\u00e9liorer la prestation de soins.\nProposer des soins d'avenir avec Lakehouse\n\u00a0\n\u00ab\u00a0Le Lakehouse de Databricks pour les soins de sant\u00e9 et les sciences de la vie fournit \u00e0 GE\u00a0Healthcare une plateforme moderne, ouverte et collaborative pour \u00e9laborer une vision des patients \u00e0 travers leur parcours de soins. Gr\u00e2ce \u00e0 ces fonctionnalit\u00e9s, nous avons r\u00e9duit les co\u00fbteux silos de donn\u00e9es h\u00e9rit\u00e9es et \u00e9quip\u00e9 nos \u00e9quipes d'insights pr\u00e9cis et opportuns.\u00a0\u00bb\u2014 Joji George, directeur de la technologie, LCS Digital, GE HealthcarePourquoi un lakehouse pour la sant\u00e9 et les sciences de la vie\u00a0?\nAcc\u00e9l\u00e9rer la recherche et am\u00e9liorer les r\u00e9sultats des patients sur une plateforme ouverte et collaborative pour les donn\u00e9es et l'IAVue \u00e0 360\u00b0 du patient\nRegroupez toutes vos donn\u00e9es structur\u00e9es et non structur\u00e9es (patient, R&D et op\u00e9rations) sur une plateforme unique d\u00e9di\u00e9e \u00e0 l'analytique et \u00e0 l'IA. Gr\u00e2ce \u00e0 une vision globale du parcours du patient, les organisations peuvent proposer des traitements plus personnalis\u00e9s.Une \u00e9volutivit\u00e9 infinie pour les \u00e9tudes au niveau de la population\nAnalysez rapidement et de mani\u00e8re fiable les donn\u00e9es de millions de patients gr\u00e2ce \u00e0 une plateforme \u00e9volutive dans le cloud. Gr\u00e2ce \u00e0 ces insights \u00e0 l'\u00e9chelle de la population, les organisations b\u00e9n\u00e9ficient d'une vision plus compl\u00e8te des tendances en mati\u00e8re de sant\u00e9, ce qui leur permet de mettre au point de meilleures th\u00e9rapies.Analytique en temps r\u00e9el, op\u00e9rations en temps r\u00e9el\nInt\u00e9grez et traitez rapidement des donn\u00e9es en streaming, o\u00f9 qu'elles se trouvent, pour alimenter l'analytique en temps r\u00e9el, avec des applications allant de la gestion de la capacit\u00e9 des lits d'h\u00f4pitaux \u00e0 l'optimisation de la fabrication et de la distribution de produits pharmaceutiques.D\u00e9couverte de m\u00e9dicaments et soins aux patients gr\u00e2ce au ML\nLib\u00e9rez tout le potentiel du machine learning pour mieux comprendre les maladies et pr\u00e9voir les besoins en termes de sant\u00e9. Toutes vos donn\u00e9es sont connect\u00e9es de mani\u00e8re transparente avec une suite compl\u00e8te d'outils collaboratifs pour de l'analytique avanc\u00e9.T\u00e9l\u00e9charger l'ebookPartenaires et solutionsD\u00e9marrez avec une vari\u00e9t\u00e9 de solutions et de mod\u00e8les de donn\u00e9es et d'analytique sp\u00e9cifiques aux soins de sant\u00e9 et aux sciences de la vie.Sant\u00e9 connect\u00e9eAm\u00e9liorez l'exp\u00e9rience des patients, ainsi que vos performances, en personnalisant le parcours de soins et l'acc\u00e8s aux services.D\u00e9marrerPrecisionView\u2122\u00c9largir les capacit\u00e9s, augmenter les moyens et enrichir la collaboration interne dans le secteur de la sant\u00e9 et des sciences de la vie.D\u00e9marrerInterop\u00e9rabilit\u00e9 des donn\u00e9es de sant\u00e9Automatisez l'int\u00e9gration de bundles FHIR en streaming dans votre lakehouse pour analyser les donn\u00e9es patients en aval \u00e0 grande \u00e9chelle.D\u00e9marrerD\u00e9marrerGestion intelligente des donn\u00e9es pour la recherche biom\u00e9dicaleTransformez les donn\u00e9es scientifiques en un actif pour votre entreprise afin de cr\u00e9er une cha\u00eene de valeur de bout en bout.D\u00e9marrerD\u00e9couvrez toutes les solutions partenairesMod\u00e8les de donn\u00e9es et mise en place de cohortes\u00a0: concordance OMOP et score de propensionInt\u00e9grez et standardisez facilement des donn\u00e9es du monde r\u00e9el dans votre lakehouse pour une analyse d'observation \u00e0 l'\u00e9chelle.D\u00e9marrerInterop\u00e9rabilit\u00e9\u00a0: ing\u00e9rez des messages\u00a0HL7V2Automatisez l'ingestion de messages\u00a0HL7V2 en streaming dans votre lakehouse pour l'analytique en temps r\u00e9el.D\u00e9marrerInterop\u00e9rabilit\u00e9\u00a0: ing\u00e9rer des bundles FHIRAutomatisez l'ingestion de bundles FHIR en streaming dans votre lakehouse pour l'analytique des patients en avalD\u00e9marrerImage\u00a0: classification de pathologie digitaleAugmentez les workflows de diagnostic gr\u00e2ce au deep learning en d\u00e9tectant les m\u00e9tastases sur les diapositives de pathologie digitales.D\u00e9marrerR&D\u00a0: identification des cibles m\u00e9dicamenteusesAnalysez les associations g\u00e9n\u00e9tiques \u00e0 grande \u00e9chelle pour aider les \u00e9quipes de R&D \u00e0 identifier de nouvelles cibles m\u00e9dicamenteuses.D\u00e9marrerSant\u00e9 de la population\u00a0: pr\u00e9diction du risque de maladieCr\u00e9ez des mod\u00e8les pr\u00e9dictifs des risques de maladie afin d'am\u00e9liorer les programmes de gestion des soins.D\u00e9marrerNLP\u00a0: d\u00e9tecter les \u00e9v\u00e9nements ind\u00e9sirablesAm\u00e9liorez le monitoring de la s\u00e9curit\u00e9 des m\u00e9dicaments en d\u00e9tectant les effets ind\u00e9sirables gr\u00e2ce \u00e0 notre solution NLP d\u00e9velopp\u00e9e en commun avec John Snow Labs.D\u00e9marrerNLP\u00a0: extraire des donn\u00e9es r\u00e9elles d'oncologieTransformez les notes oncologiques non structur\u00e9es en insights in\u00e9dits sur les patients \u00e0 l'aide de notre solution NLP d\u00e9velopp\u00e9e en commun avec John Snow Labs.D\u00e9marrerNLP\u00a0: automatiser la suppression des PHIAutomatisez la suppression des informations sensibles des patients par les donn\u00e9es textuelles gr\u00e2ce \u00e0 notre solution NLP d\u00e9velopp\u00e9e en commun avec John Snow LabsD\u00e9marrerVoir toutes les solutionsLakehouse pour la sant\u00e9 et les sciences de la vie en actionPour en savoir plus,Sant\u00e9\nOffrir des soins centr\u00e9s sur le patient gr\u00e2ce aux donn\u00e9es et \u00e0 l'IASciences de la vie\nApporter de nouveaux traitements aux patients qui en ont besoin gr\u00e2ce \u00e0 l'analytique de donn\u0000\u00e9es et \u00e0 l'IAAm\u00e9liorer les r\u00e9sultats de sant\u00e9 gr\u00e2ce aux donn\u00e9es et \u00e0 l'IAT\u00e9l\u00e9charger l'ebook \u2192Ressources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez la biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les donn\u00e9es et l'IA pour le secteur de la sant\u00e9 et des sciences de la vie.\nExplorer les ressourcesEbooksAm\u00e9liorer les r\u00e9sultats avec un lakehouse pour la sant\u00e9 et les sciences de la vieD\u00e9couvrez de nouveaux insights patients gr\u00e2ce au Natural Language Processing \u00e0 grande \u00e9chelleLakehouse\u00a0: concr\u00e9tiser le potentiel des donn\u00e9es r\u00e9ellesFiche solution\u00a0: le lakehouse pour la sant\u00e9 et les sciences de la vieWebinairesAtelier\u00a0: FHIR et analytique patient en temps r\u00e9el avec un lakehouseWebinaire\u00a0: le syst\u00e8me d'information r\u00e9gional de Chesapeake, un moteur d'innovations sant\u00e9 pour les patientsAtelier\u00a0: standardiser des donn\u00e9es avec OMOP et pr\u00e9dire le risque de maladie avec le MLAtelier\u00a0: extraire des donn\u00e9es r\u00e9elles avec le NLPAtelier\u00a0: acc\u00e9l\u00e9rer la R&D avec des donn\u00e9es r\u00e9elles et l'IABlogsAmgen acc\u00e9l\u00e8re le d\u00e9veloppement et la commercialisation des m\u00e9dicaments avec un lakehouse d\u00e9di\u00e9 \u00e0 la sant\u00e9 et aux sciences de la vieLe lakehouse pour la sant\u00e9 et les sciences de la vieAm\u00e9lioration de la s\u00e9curit\u00e9 des m\u00e9dicaments gr\u00e2ce \u00e0 la d\u00e9tection des \u00e9v\u00e9nements ind\u00e9sirables via le NLPLa bo\u00eete \u00e0 outils g\u00e9nomiques en open source de Databricks surpasse les principaux proc\u00e9d\u00e9s.Extraction des informations oncologiques \u00e0 partir de donn\u00e9es cliniques r\u00e9elles avec le NLPPr\u00eat \u00e0 vous lancer\u00a0?Nous serions ravis de conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.ESSAYER GRATUITEMENT DATABRICKSPlanifier une d\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/glossary\/pyspark","text":"What is PySpark?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPySparkAll>PySparkTry Databricks for freeGet StartedWhat is PySpark?Apache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface with Resilient Distributed Datasets (RDDs) in Apache Spark and Python programming language. This has been achieved by taking advantage of the Py4j library.Py4J is a popular library which is integrated within PySpark and allows python to dynamically interface with JVM objects. PySpark features quite a few libraries for writing efficient programs. Furthermore, there are various external libraries that are also compatible. Here are some of them:PySparkSQLA PySpark library to apply SQL-like analysis on a huge amount of structured or semi-structured data. We can also use SQL queries with PySparkSQL. It can also be connected to Apache Hive. HiveQL can be also be applied. PySparkSQL is a wrapper over the PySpark core. PySparkSQL introduced the DataFrame, a tabular representation of structured data that is similar to that of a table from a relational database management system.MLlibMLlib is a wrapper over the PySpark and it is Spark\u2019s machine learning (ML) library. This library uses the data parallelism technique to store and work with data. The machine-learning API provided by the MLlib library is quite easy to use. MLlib supports many machine-learning algorithms for classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives.GraphFramesThe GraphFrames is a purpose graph processing library that provides a set of APIs for performing graph analysis efficiently, using the PySpark core and PySparkSQL. It is optimized for fast distributed computing. Advantages of using PySpark: \u2022 Python is very easy to learn and implement. \u2022 It provides simple and comprehensive API. \u2022 With Python, the readability of code, maintenance, and familiarity is far better. \u2022 It features various options for data visualization, which is difficult using Scala or Java. \u00a0Additional ResourcesGetting Started with Python on Apache SparkGetting The Best Performance With PySparkFrom Python to PySpark and Back Again \u2013 Unifying Single-host and Distributed Deep Learning with MaggyDemocratizing PySpark for Mobile Game PublishingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dawn-song","text":"Dawn Song - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDawn SongProfessor, Department of Electrical Engineering and Computer Science at UC BerkeleyBack to speakersDawn Song is a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley and co-Director of Berkeley Center on Responsible Decentralized Intelligence. Her research interest lies in AI and deep learning, security and privacy, and blockchain. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, ACM SIGSAC Outstanding Innovation Award, and numerous Test-of-Time Awards and Best Paper Awards from top conferences in Computer Security and Deep Learning. She is an ACM Fellow and an IEEE Fellow. She is ranked the most cited scholar in computer security (AMiner Award). She obtained her Ph.D. degree from UC Berkeley. She is also a serial entrepreneur and has been named on the Female Founder 100 List by Inc. and Wired25 List of Innovators.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-armbrust","text":"Michael Armbrust - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael ArmbrustDistinguished Engineer at DatabricksBack to speakersMichael Armbrust is committer and PMC member of Apache Spark\u2122 and the original creator of Spark SQL. He currently leads the Delta Live Tables team at Databricks and is the original creator of Spark SQL, Structured Streaming and Delta. He received his PhD from UC Berkeley in 2013, and was advised by Michael Franklin, David Patterson, and Armando Fox. His thesis focused on building systems that allow developers to rapidly build scalable interactive applications, and specifically defined the notion of scale independence. His interests broadly include distributed systems, large-scale structured storage and query optimization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/will-girten","text":"Will Girten - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWill GirtenSr. Specialist Solutions Architect at DatabricksBack to speakersAs a Lead SSA at Databricks and author of the Node.js connector for Delta Sharing, Will is driven by his passion for open-source technologies and creating a more connected, data-driven world. He has over a decade of experience in big data, data warehousing, and performance optimizations. Will is committed to pushing the limits of what's possible and delivering transformative results. Contributing to the Delta Sharing project is just one way he's working to make a difference.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lorenzo-de-tomasi","text":"Lorenzo De Tomasi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLorenzo De TomasiData Architect, Data Platforms Lead at Barilla at Barilla G. e R. Fratelli S.p.A.Back to speakersLorenzo De Tomasi is a skilled AI and Data Engineering manager. Holding a Computer Science Engineering degree, he worked as a Data Scientist at Luxottica Group, developing computer vision algorithms for quality processes. Now, he leads Advanced Analytics technology at Barilla Group, implementing complex Machine Learning, Deep Learning, and Advanced Analytics solutions in Marketing, Finance, RDQ, Sales, and more.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kylie-taylor\/#","text":"Kylie Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKylie TaylorData Scientist at Mars PetcareBack to speakersKylie Taylor is a Data Scientist at Mars Petcare. Her current work focuses on deploying machine learning models at scale and modeling the impacts of price inflation on shopper behavior. She holds a Masters in Economics with a focus in Statistics from the University of Texas at Austin. Previous to her role as a Data Scientist, she served as a Senior Statistician in the Global R&D division of Mars Petcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/reynold-xin\/#","text":"Reynold Xin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingReynold XinCo-founder and Chief Architect at DatabricksBack to speakersReynold is an Apache Spark\u2122 PMC member and the top contributor to the project. He initiated and led efforts such as DataFrames and Project Tungsten. He is also a co-founder and Chief Architect at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lewis-mbae\/#","text":"Lewis Mbae - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLewis MbaeHead of Customer Engineering at RudderStackBack to speakersLewis leads Customer Engineering at RudderStack. His team's core focus is to be the trusted technical advisor for all RudderStack customers throughout their journey on the platform. Prior to RudderStack he spent 7 years at Fastly where he held senior roles in Sales Engineering. On the personal side, he grew up in Kenya and moved to the United States to attend college. He has a MS in Computer Science from Columbia as well as a BS in Electrical Engineering from StanfordLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nihar-sheth\/#","text":"Nihar Sheth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNihar ShethSenior Product Manager at AWS - AmazonBack to speakersNihar Sheth is a Senior Product Manager on the Amazon Kinesis Data Streams team at Amazon Web Services. He is passionate about developing intuitive product experiences that solve complex customer problems and enables customers to achieve their business goals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/willy-lulciuc","text":"Willy Lulciuc - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWilly LulciucSr. Software Engineer at AstronomerBack to speakersWilly Lulciuc is a Software Engineer at Astronomer working on observability and lineage. He makes datasets discoverable and meaningful with metadata. He co-created Marquez and is now involved in the OpenLineage initiative. Previously, he was the Founder Engineering of Datakin, a data lineage startup. When he's not reviewing code and creating indirections, he can be found experimenting with analog synthesizers.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rahil-bhatnagar\/#","text":"Rahil Bhatnagar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRahil BhatnagarDevelopment Lead, LOLA at Anheuser BuschBack to speakersRahil Bhatnagar has experience leading cross-functional teams to build scalable products, taking them from ideas to production. Applying his distributed systems and game development background to create sustainable dynamic solutions on time. Currently, leading and scaling Anheuser-Busch's Machine Learning Platform, LOLA to solve the growing demand for machine learning insights in a tech-first FMCPG.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/digital-twin","text":"Digital TwinPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDigital TwinAll>Digital TwinTry Databricks for freeGet StartedWhat is a Digital Twin?The classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers system and processes state data with help of various IoT sensors (operational technology data (OT)) and enterprise data (informational technology (IT)) to forms a virtual model which is then used to run simulations, study performance issues, and generate possible insights.The concept of Digital Twins is not new. In fact, it is reported that the first application was over twenty five years ago, during the early phases of foundation and cofferdam construction for the London Heathrow Express facilities, to monitor and predict foundation borehole grouting. In the years since this first application, edge computing, AI, data connectivity, 5G connectivity, and the improvements of the Internet of Things (IoT) have enabled digital twins to become cost-effective and are now an imperative in today's data-driven businesses.Digital twins are now so ingrained in Manufacturing that the global industry market is forecasted to reach $48Bn dollars in 2026. This figure is up from $3.1 Bn in 2020 at a CAGR of 58%, riding on the wave of Industry 4.0.Today's manufacturing industries are expected to streamline and optimize all the processes in their value chain from product development and design, through operations and supply chain optimization to obtaining customer feedback to reflect and respond to rapidly growing demands swiftly. The digital twins category is broad and is addressing a multitude of challenges within manufacturing, logistics and transportation.The most common challenges faced by the manufacturing industry that digital twins are addressing are:Product designs are more complex, resulting in higher cost, and increasingly longer development timesThe supply chain is opaqueProduction lines are not optimized \u2013 performance variations, unknown defects and projection of operating cost is obscurePoor quality management \u2013 over reliance on theory, managed by individual departments,Reactive maintenance costs are too high resulting in excessive downtime or process disruptionsIncongruous collaborations between the departmentsInvisibility of customer demand for gathering real time feedbackWhy is this important?Industry 4.0 and the subsequent Intelligent Supply Chain efforts have made significant strides in improving operations and building agile supply chains - but these efforts would have come at significant costs without digital twin technology. Can you imagine the cost to change an oil refinery's crude distillation unit process conditions to improve the output of diesel one week and gasoline the next to address changes in demand and insure maximum economic value? Can you imagine how to replicate an even simple supply chain to model risk? It is financially and physically impossible to build a physical twin of a supply chain.Let's look at the benefits that digital twins deliver to the manufacturing sector:Product design and development is performed with less cost and is completed in less time as iterative simulations, using multiple constraints deliver the best or most optimized design - all commercial aircraft are designed using digital twinsDigital twins provide us with the awareness of how long inventory will last, when to replenish, and how to minimize the supply chains disruptions - the oil and gas industry uses supply chain oriented digital twins to reduce supply chain bottlenecks in storage and mid-stream delivery, schedule tanker off-loads and model demand with externalities.Continuous quality checks on produced items with ML\/AI generated feedbacks pre-emptively assures improved product quality - automotive final paint inspection is performed with computer vision built on top of digital twin technologyStriking the sweet spot between when to replace a part before the process degrades or breaks down and utilizing the components to its fullest, digital twin provides with a real time feedback - digital twins are the backbone of building an asset performance management suiteDigital twins create the opportunity to have multiple departments in sync by providing necessary instructions modularly to attain a required throughput - digital twins are the backbone of kaizen events that optimizes manufacturing process flowCustomer feedback loops can be modeled through inputs, from point of sale customer behavior, buying preferences, or product performance and then integrated into the product development process, forming a closed loop providing an improved product designWhat are Databricks' differentiated capabilities?Databricks' Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader and Photon to enable customers to make data available for real-time decisions.Lakehouse for MFG supports the largest data jobs at near real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.A Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for real-time stream ingestion of data and analytics on streaming data. Data warehouses require the extraction, transformation, loading, and additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest of data sets to power real-time decisions in BI tools.Additional ResourcesFour Forces Driving Intelligent ManufacturingManufacturing Leaders ForumDatabricks solutions for ManufacturingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sean-owen\/#","text":"Sean Owen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSean OwenPrincipal Product Specialist at DatabricksBack to speakersSean is a Principal Product Specialist for Data Science and Machine Learning at Databricks. He is an Apache Spark committer and PMC member, and co-author Advanced Analytics with Spark. Previously, he was director of Data Science at Cloudera and an engineer at Google, and worked in early-stage technology venture investing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/02\/15\/lakehouse-for-financial-services-paving-the-way-for-data-driven-innovation-in-fsis.html","text":"Lakehouse for Financial Services: Paving the Way for Data-Driven Innovation in FSIs - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorLakehouse for Financial Services: Paving the Way for Data-Driven Innovation in FSIsby Antoine Amend and Junta NakaiFebruary 15, 2022 in NewsShare this postWhen it comes to \u201cdata-driven innovation,\u201d financial service institutions (FSI) aren\u2019t what typically come to mind. But with massive amounts of data at their potential disposal, this isn\u2019t for lack of imagination. FSIs want to innovate but are continually slowed down by complex legacy architectures and vendor lock-in that prevent data and AI from becoming material business drivers.\nLargely as a result of these challenges, the financial services industry has arguably seen little innovation in recent decades \u2013 even as other regulated sectors such as healthcare and education continue to break barriers. Even for the most established incumbents, a lack of innovation can quickly lead to being taken over by a new, digital-native company \u2013 a move some of us at Databricks call Tesla-fication. This is where one disruptive, data and AI-driven innovator becomes disproportionately more successful than the incumbents who previously dominated the space. One indication of this success can be found in the stock market. Today, Tesla boasts a $900+ billion market capitalization, making it worth more than the next 10 leading automotive competitors combined. Incumbency is no longer a moat.\nIn fact, we\u2019re already starting to see Tesla-fication happening in financial services. Nubank, a Brazilian fintech launched in 2014, has quickly changed the competitive dynamics in its home country and beyond. Early on, Nubank disrupted the credit card market, by enabling online applications, as well as by extending credit to those with no credit history. Today, it uses bleeding-edge technology, data and AI to develop new products and services. Data science plays an essential role in every aspect of their business \u2013 from customer support to credit lines. Seven years after their launch, in December of 2021, Nubank became one of the largest IPOs in Latin America and briefly eclipsed the market capitalization of Brazil\u2019s largest bank. Signs of Tesla-fication are emerging across all segments of financial services, from banking to insurance to capital markets. For FSIs, this means that the traditional sources of competitive advantage \u2013 capital and scale \u2013 no longer cut it. Today, transformation requires leaders to focus their investments on two modern sources of competitive advantage: data and people.\nIntroducing Lakehouse for Financial ServicesToday, we\u2019re thrilled to introduce Lakehouse for Financial Services\u00a0to help bring data and people together for every FSI. Lakehouse for Financial Services addresses the unique requirements of FSIs via industry-focused capabilities, such as pre-built solutions accelerators, data sharing capabilities, open standards and certified implementation partners. With this platform, organizations across the banking, insurance and capital market sectors can increase the impact and time-to-value of their data assets, ultimately enabling data and AI to become central to every part of their business \u2013 from lending to insuring.\nSo, why is Lakehouse for Financial Services critical for success? When speaking with our customers, we identified the biggest challenges around transforming into a data-driven organization (and how Lakehouse addresses them):\nRisk of vendor lock-in: FSIs are particularly vulnerable to being stuck with proprietary data formats and technologies that stifle collaboration and innovation. Lakehouse is powered by open source and open standards, meaning that data teams can leverage the tools of their choice.No multi-cloud: Increasingly, regulators are asking FSIs to consider systemic risk arising from overreliance on a single vendor. Lakehouse solves this by offering full support for all major cloud vendors.Real-time data access for BI: The most recent data is typically the most valuable, but traditional architectures often make it a hurdle for data analysts to access it. With Lakehouse, data teams across functions always can access the most up-to-date, reliable data.Lack of support for all data sets: The fastest-growing data in FSIs is unstructured data sets (text, images, etc), which makes data warehouses less than ideal for critical use cases. Lakehouse handles all types of data - structured, semi-structured and unstructured - and even offers data sharing capabilities with leading providers such as Factset.Driving AI use cases. Although the regulated aspect of financial services makes it difficult to embrace and scale AI, the main hurdles are internal policies around risk adversity coupled with siloed infrastructures and legacy processes. Lakehouse makes AI accessible and transparent via MLflow; coupled with Delta Lake time travel capability, AI has been adopted as a next generation of model risk management for independent validation.What makes Lakehouse for Financial Services Equipped to Tackle These Challenges?We built Lakehouse for Financial Services specifically to tackle these challenges and empower organizations to find new ways to gain a competitive edge, innovate risk management and more, even within highly-regulated environments. Here\u2019s how we\u2019re doing just that:\nPre-built Solution Accelerators for Financial Services Use CasesLakehouse for Financial Services aligns with our 14 financial services solution accelerators, fully functional and freely available notebooks that tackle the most common and high-impact use cases that our customers are facing. These use cases include:\nPost-Trade Analysis and Market Surveillance: Using an efficient time series processing engine for market data, this library combines core market data and disparate alternative data sources, enabling asset managers to backtest investing strategies at scale and efficiently report on transaction cost analysis.Transaction Enrichment: This scalable geospatial data library enables hyper-personalization in retail banking to better understand customer transaction behavior required for next-gen customer segmentation and modern fraud prevention strategies.Regulatory Reporting: This accelerator streamlines the acquisition, processing and transmission of regulatory data following open data standards and open data sharing protocols.GDPR Compliance: Simplify the technical challenges around compliance to the \u201cright to be forgotten\u201d requirement while ensuring strict audit capabilities.Common Data Models: A set of frameworks and accelerators for common data models to address the challenges FSIs have in standardizing data across the organization.Industry Open Source ProjectsAs part of this launch, we\u2019re thrilled to announce that we have joined FINOS (FinTech Open Source Foundation) to foster innovation and collaboration in financial services. FINOS includes the world\u2019s leading FSIs such as Goldman Sachs, Morgan Stanley, UBS and JP Morgan as members. Open Source has become a core strategic initiative for data strategies in financial services as organizations look to avoid complex, costly vendor lock-in and proprietary data formats. As part of FINOS, Databricks is helping to facilitate the processing and exchange of financial data throughout the entire banking ecosystem. This is executed via our Delta Lake and Delta Sharing integrations with recent open source initiatives led by major FSIs.\nDatabricks is working to help empower the standardization of data by significantly democratizing data accessibility and insights. Ultimately, we want to bring data to the masses. That\u2019s why we recently integrated the LEGEND ecosystem with Delta Lake functionalities such as Delta Live Tables. Developed by leading financial services institutions and subsequently open-sourced through the LINUX Foundation, the LEGEND ecosystem allows domain experts and financial analysts to map business logic, taxonomy and financial calculations to data. Now integrated into the Lakehouse for Financial Services, those same business processes can be directly translated into core data pipelines to enforce high-quality standards with minimum operation overhead. Coupled with the Lakehouse query layer, this integration provides financial analysts with massive amounts of real-time data directly through the comfort of their business applications and core enterprise services.\nSimple deployment of the Lakehouse environmentWith Lakehouse for Financial Services, customers can easily automate security standards. More specifically, the utility libraries and scripts we\u2019ve created for financial services deliver automated setup for notebooks and are tailored to help solve security and governance issues important to the financial services industry based on best practices and patterns from our 600+ customers.\nA data model framework for standardizing dataIn addition to solution accelerators, Lakehouse provides a framework for common data models to address the challenges FSIs have in standardizing data across the organization. For example, one solution accelerator is designed to easily integrate the Financial Regulation (FIRE) Data model to drive the standardization of data, serve data to downstream tools, enable AI quality checks and govern the data using Unity Catalog.\nOpen data sharingLast year, we launched Delta Sharing, the world\u2019s first open protocol for securely sharing data across organizations in real-time, independent of the platform on which the data resides. This is largely powered by our incredible ecosystem of partners, which we\u2019re continuing to scale and grow. We are thrilled to announce that we have recently invested in Ticksmith, a leading SaaS platform that simplifies the online data shopping experience and was one of the first platforms to implement Delta Sharing. With the TickSmith and Databricks integration, FSIs can now easily create, package and deliver data products in a unified environment.\nImplementation PartnersDatabricks is working with consulting and SI partner Avanade to deliver risk management solutions to financial institutions. Built on Azure Databricks, our joint solution makes it easier for customers to rapidly deploy data into value-at-risk models to keep up with emerging risks and threats. By migrating to the cloud and modernizing data-driven risk models, financial institutions are able to reduce regulatory, operational compliance risks related and scale to meet increased throughput.\nDatabricks is also partnering with the Deloitte FinServ Governed Data Platform, a cloud-based, curated data platform meeting regulatory requirements that builds a single source of truth for financial institutions to intelligently organize data domains and approved provisioning points, enabling activation of business intelligence, visualization, predictive analytics, AI\/ML, NLP and RPA.\nConclusionTesla-fication is starting to happen all around us. Lakehouse for Financial Services is designed to help our customers make a leapfrog advancement in their data and AI journey with pre-built solution accelerators, data sharing capabilities, open standards and certified implementation partners. We are on the mission to help every FSI become the Tesla of their industry.\nWant to learn more? Check out this overview and see how you can easily get started or schedule a demo.Try Databricks for freeGet StartedRelated postsLakehouse for Financial Services: Paving the Way for Data-Driven Innovation in FSIsFebruary 15, 2022 by Antoine Amend and Junta Nakai in News\nWhen it comes to \u201cdata-driven innovation,\u201d financial service institutions (FSI) aren\u2019t what typically come to mind. But with massive amounts of data at their...\nSee all News postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pouya-barrach-yousefi","text":"Pouya Barrach-Yousefi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPouya Barrach-YousefiData Pro and Director Strategic Accounts at ProphecyBack to speakersIn the 6 years at IQVIA prior to joining Prophecy, Pouya was a Data Science Developer and tech lead for the Analytics Center of Excellence, then joined the global Data Science & Advanced Analytics team as an Associate Data Science Director to focus on delivering commercial AIML solutions for pharma clients, and finally as Director of Enterprise AIML Strategy he led data, data science, and machine learning improvements across IQVIA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fcWEBINAR May 18 \/ 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack.\n\u3054\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c\u30d0\u30a4\u30aa\u533b\u85ac\u54c1\u4f01\u696d\u306e\u7d4c\u55b6\u9663\u3092\u5bfe\u8c61\u306b\u884c\u3063\u305f\u65b0\u305f\u306a\u8abf\u67fb\u306b\u3088\u308a\u3001\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u30a8\u30d3\u30c7\u30f3\u30b9\uff08RWE\uff09\u306e\u6d3b\u7528\u306b\u3088\u308b\u6210\u679c\u304c\u660e\u3089\u304b\u306b\u306a\u308a\u307e\u3057\u305f\u3002\n\u30a2\u30f3\u30b1\u30fc\u30c8\u306e\u7d50\u679c\u3092\u898b\u308b\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeaconsJoin Generation AI in San Francisco June 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessions\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29\u3054\u767b\u9332Databricks MarketplaceOpen marketplace for data, analytics and AI\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebTo play this video, click here and accept cookiesWhat is Databricks Marketplace?\nDatabricks Marketplace is an open marketplace for all your data, analytics and AI, powered by open source Delta Sharing standard. The Databricks Marketplace expands your opportunity to deliver innovation, and advance all your analytics and AI initiatives.\u00a0\nObtain data sets as well as AI and analytics assets \u2014 such as ML models, notebooks, applications and dashboards \u2014 without proprietary platform dependencies, complicated ETL or expensive replication. This open approach allows you to put data to work more quickly in every cloud with your tools of choice.Discover more than just dataUnlock innovation and advance your organization\u2019s AI, ML and analytics initiatives. Access more than just data sets, including ML models, notebooks, applications and solutions.Evaluate data products fasterPrebuilt notebooks and sample data help you quickly evaluate and have much greater confidence that a data product is right for your AI, ML or analytics initiatives.Avoid vendor lock-inSubstantially reduce the time to deliver insights and avoid lock-in with open and seamless sharing and collaboration across clouds, regions or platforms. Directly integrate with your tools of choice and right where you work.Featured data providers on Databricks MarketplaceBecome a data provider on the marketplace\n\u95a2\u9023\u30ea\u30bd\u30fc\u30b9EventRegister now for Data + AI Summit 2023\u3054\u767b\u9332eBookA New Approach to Data Sharing\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9eBookData, Analytics and AI Governance\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u57fa\u8abf\u8b1b\u6f14Data Governance and Sharing on the Lakehouse at Data + AI Summit 2022 \u30d6\u30ed\u30b0Marketplace Public Preview AnnouncementDatabricks Marketplace Announcement at Data + AI Summit 2022\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8AWSAzureGCP\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-data-science-use-cases-nurture","text":"The Big Book of Data Science Use Cases \u2013 2nd Edition | DatabrickseBookThe Big Book of Data Science Use Cases \u2013 2nd EditionSee top use cases for applying data science in businesses across industriesThe world of data science is evolving so fast that it\u2019s not easy to find real-world use cases that are relevant to what you\u2019re working on. That\u2019s why we\u2019ve collected these blogs from industry thought leaders with practical use cases you can put to work right now. This how-to reference guide provides everything you need \u2014 including code samples \u2014 so you can get your hands dirty working with the Databricks platform.In this eBook, you will learn:Top ways to apply data science so it has an impact on your businessHow-to walk-throughs using code samples to recreate data science use casesCustomer stories where users are seeing success from using DatabricksComplete the formProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/databricks-onboarding-sessions?utm_source=databricks&utm_medium=website&utm_campaign=7013f000000LkrvAAC&utm_content=learn-page","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/events","text":"Veranstaltungen von Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWVeranstaltungen von DatabricksInformieren Sie sich \u00fcber anstehende Meetups, Webinare, Konferenzen und mehr von und zu Databricks.Data+AI Summit 202326.\u201329.\u00a0JuniSie haben die Wahl: Nehmen Sie pers\u00f6nlich teil oder verfolgen Sie Keynotes und ausgew\u00e4hlte Sessions im Livestream.Jetzt registrierenLoading...Browse All Upcoming EventsProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lin-qiao\/#","text":"Lin Qiao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLin QiaoCo-creator of PyTorch, Co-founder and CEO at FireworksBack to speakersLin Qiao is the co-founder and CEO of Fireworks, which is on a mission to accelerate the transition to AI-powered business via interactive experimentation and a production platform centered around PyTorch technologies and state-of-the-art models built using PyTorch. She led the development of PyTorch, AI compilers and on-device AI platforms at Meta for the past half-decade. She drove AI research to production innovations across hardware acceleration, enabling model exploration and large and complex model scaling, building production ecosystems and platforms for all Meta\u2019s AI use cases. She received a Ph.D. in computer science, started her career as a researcher in Almaden Research Lab, and later moved to the industry as an engineer. Prior to Meta, she worked on a broad range of distributed and data processing domains, from high-performance columnar databases, OLTP systems, streaming processing systems, data warehouse systems, and logging and metrics platforms.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/healthcare-and-life-sciences","text":"Lakehouse for Healthcare and Life Sciences - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLakehouse for Healthcare and Life SciencesOffrire esiti migliori ai pazienti con la potenza dei dati e dell'AICominciaProgramma una demoQuattro sfide per la gestione dei dati nella sanit\u00e0 e nelle bioscienzeFrammentazione dei dati dei pazienti\nSilos di dati e supporto limitato per dati non strutturati impediscono alle organizzazioni di seguire il percorso del paziente.Crescita rapida dei dati sanitari\nLe architetture on-premise esistenti sono complesse da gestire e costose da espandere per l'enorme volume di dati sanitari attuale, alimentato anche dalla crescita di immagini e genomica.Cure e operazioni in tempo reale\nData warehouse e strumenti scollegati impediscono di fornire le informazioni in tempo reale necessarie per prendere decisioni terapeutiche critiche e per produrre e somministrare in modo sicuro terapie importanti.Analisi sanitaria avanzata complessa\nFunzionalit\u00e0 di ML leggere impediscono alle organizzazioni di gestire tutti gli aspetti, dai modelli di nuova generazione per la cura dei pazienti, all'analisi predittiva nella ricerca e sviluppo di farmaci.Lakehouse for Healthcare and Life SciencesPiattaforma unificata per dati e AI\nUn'unica piattaforma che raccoglie tutti i dati e i carichi di lavoro di analisi per favorire innovazioni trasformative nella cura dei pazienti e nella R&D di farmaci.\nSoluzioni dei partner\nI principali fornitori mondiali di soluzioni per la sanit\u00e0 e le bioscienze, come Deloitte, Accenture e ZS Associates, sviluppano per il lakehouse. Sfrutta i vantaggi di offerte preconfezionate che accelerano la trasformazione guidata dai dati nella ricerca farmaceutica e nella cura dei pazienti.\nAcceleratori\nDatabricks e i suoi partner hanno realizzato una serie di Acceleratori che facilitano l'acquisizione di dati sanitari, ad esempio messaggi HL7, e consentono di realizzare casi d'uso come l'analisi di testi medici e il monitoraggio della sicurezza dei farmaci.\nCollaborazione con il settore\nLa condivisione di dati sicura e aperta e la collaborazione con organizzazioni dell'ecosistema sanitario aiutano ad accelerare la ricerca di farmaci salvavita e migliorare la somministrazione di cure.\nEntrare nel futuro delle cure con il lakehouse\n\u00a0\n\u201cDatabricks Lakehouse for Healthcare and Life Sciences mette a disposizione di GE Healthcare una piattaforma moderna, aperta e collaborativa per avere una vista completa del paziente lungo tutto il percorso di cura. Grazie a queste funzionalit\u00e0 abbiamo ridotto i costosi silos di dati esistenti e dotato i nostri team di informazioni approfondite, tempestive e precise\u201d.\u2014 Joji George, Chief Technology Officer, LCS Digital, GE HealthcarePerch\u00e9 Lakehouse for Healthcare and Life Sciences?\nAccelerare la ricerca e migliorare gli esiti per i pazienti su una piattaforma collaborativa aperta per dati e AIVista del paziente a 360\u00b0\nRaccogli tutti i dati strutturati e non strutturati (pazienti, R&D e operazioni) su un'unica piattaforma per analisi e AI. Con una vista completa del percorso del paziente, le organizzazioni possono fornire terapie pi\u00f9 personalizzate.Scala infinita per studi a livello di popolazione\nCon una piattaforma scalabile in cloud si possono analizzare i dati di milioni di pazienti in modo veloce e affidabile. Acquisendo dati che riguardano tutta la popolazione, le organizzazioni possono avere una vista pi\u00f9 completa delle evoluzioni sanitarie e, di conseguenza, sviluppare terapie migliori.Analisi in tempo reale, operativit\u00e0 in tempo reale\nI dati in streaming possono essere acquisiti da qualsiasi sorgente ed elaborati per alimentare analisi in tempo reale, con applicazioni che vanno dalla gestione della capacit\u00e0 di posti letto negli ospedali all'ottimizzazione della produzione e della distribuzione di farmaci.Scoperta di farmaci e cura dei pazienti supportate da ML\nSfrutta la potenza del machine learning per conoscere meglio le malattie e prevedere le esigenze sanitarie. Tutti i dati sono connessi direttamente a una suite completa di strumenti di collaborazione per analisi avanzate.Scarica l'eBookPartner e soluzioniComincia a operare con una gamma di soluzioni di gestione e analisi dei dati e di template specifici per il settore della sanit\u00e0 e delle bioscienzeSanit\u00e0 intelligenteMigliorare l'esperienza dei pazienti e gli esiti clinici personalizzando il percorso del paziente e l'accesso alle cure.CominciaPrecisionView\u2122Ampliare le funzionalit\u00e0, aumentare la capacit\u00e0 e arricchire la collaborazione interna nel settore della sanit\u00e0 e delle bioscienze.CominciaInteroperabilit\u00e0 dei dati sanitariAutomatizzare l'acquisizione di bundle FHIR in streaming all'interno del lakehouse per le analisi dei pazienti a valle su larga scala.CominciaCominciaGestione intelligente dei dati per la ricerca biomedicaleTrasformare i dati scientifici in un patrimonio aziendale creando una catena del valore completa.CominciaScopri tutte le soluzioni dei partnerModelli di dati e costruzione di coorti: OMOP e Propensity Score MatchingAcquisisci e standardizza facilmente dati reali nel lakehouse per analisi osservazionale su larga scalaCominciaInteroperabilit\u00e0: Acquisizione di messaggi HL7V2Automatizza l'acquisizione di messaggi HL7V2 in streaming all'interno del lakehouse per analisi in tempo realeCominciaInteroperabilit\u00e0: Acquisizione di bundle FHIRAutomatizza l'acquisizione di bundle FHIR in streaming all'interno del lakehouse per le analisi dei pazienti a valleCominciaImmagini: Classificazione digitale delle patologiePotenziare i flussi di lavoro diagnostici con il deep learning individuando metastasi in immagini digitaliCominciaR&D: Identificazione di bersagli farmacologiciAnalizzare le associazioni genetiche su larga scala per aiutare i team di R&D a individuare nuovi bersagli farmacologiciCominciaSalute della popolazione: Previsione del rischio di malattieCostruzione di modelli predittivi del rischio di malattie per migliorare i programmi di gestione delle cureCominciaNLP: Rilevazione di eventi avversiMigliora il monitoraggio della sicurezza dei farmaci attraverso il rilevamento di eventi avversi utilizzando la nostra soluzione NLP sviluppata congiuntamente con John Snow LabsCominciaNLP: Estrarre dati oncologici dal mondo realeTrasformare note oncologiche non strutturate in nuove informazioni sui pazienti utilizzando la nostra soluzione NLP sviluppata congiuntamente con John Snow LabsCominciaNLP: Automatizzare la rimozione di dati sanitari protetti (PHI)La rimozione di dati sensibili dei pazienti dai dati testuali pu\u00f2 essere automatizzata con la soluzione NLP sviluppata insieme a John Snow LabsCominciaVedi tutte le soluzioniLakehouse for Healthcare and Life Sciences in azioneVuoi saperne di pi\u00f9?Sanit\u00e0\nFornire cure mirate al paziente con l'efficacia dei dati e dell'AIBioscienze\nPortare nuove cure ai pazienti con analisi dei dati e AIMigliorare gli esiti in sanit\u00e0 con dati e AIScarica l'eBook \u2192Risorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video su dati e AI per sanit\u00e0 e bioscienze.\nEsplora risorseeBookMigliorare gli esiti con Lakehouse for Healthcare and Life SciencesScoprire nuove informazioni sui pazienti applicando l'elaborazione del linguaggio naturale (NLP) su larga scalaMantenere la promessa di dati raccolti dal mondo reale con il lakehouseScheda tecnica: Presentazione del lakehouse per sanit\u00e0 e bioscienzeWebinarWorkshop: FHIR migliora l'analisi dei pazienti in tempo reale con il lakehouseWebinar: Promuovere le innovazioni in sanit\u00e0 con il sistema informatico regionale di Chesapeake per i nostri pazientiWorkshop: Standardizzare i dati con OMOP e prevedere il rischio di malattie con il MLWorkshop: Estrarre dati reali con NLPWorkshop: Accelerare la ricerca e sviluppo con dati reali e AIBlogAmgen accelera lo sviluppo e la fornitura di farmaci con il lakehouse per sanit\u00e0 e bioscienzePresentazione del lakehouse per sanit\u00e0 e bioscienzeAumentare la sicurezza dei farmaci individuando gli eventi avversi con la tecnologia NLP (elaborazione del linguaggio naturale)Il toolkit open-source di genomica di Databricks supera le prestazioni degli strumenti pi\u00f9 diffusiEstrazione di insight oncologici da dati clinici reali con NLPPronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProgramma una demoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erin-boelkens\/#","text":"Erin Boelkens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErin BoelkensVP of Product at LiveRampBack to speakersErin Boelkens is Vice President of Product at LiveRamp (NYSE: RAMP). In this role, she oversees LiveRamp solutions that enable clients to manage data assets in a safe and secure way across identity, business development, addressability, healthcare, and data management. Previously, Erin was LiveRamp\u2019s VP of Engineering and Head of Global Identity Engineering, where she led a team of creative and innovative engineers providing industry-leading identity products across offline and online channels. Erin joined the company in 2018 after spending 13 years in engineering, product and data science at Acxiom (Nasdaq: ACXM). Erin holds a bachelor\u2019s degree in computer information systems and a master\u2019s of science in management information systems from Arkansas State University. She is also certified as a Scrum Product Owner and a Scrum Master from the Scrum Alliance, as well as Marketing certification from Pragmatic Marketing. She resides in Little Rock, Arkansas.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pakshal-kumar-h-dhelaria\/#","text":"Pakshal Kumar H Dhelaria - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPakshal Kumar H DhelariaSenior Software Engineer 1 at CitrixBack to speakersA strong leader with an overall experience of 6+ years solving critical problems in the industry and passionate about innovative architecture\/solutions. Expertise in Kafka, Apache Spark, Streaming, Spring, Spring Boot Framework Interested in Machine learning and NLP. Worked on RDBMS (MySQL, Postgres,), Time-Series DB(Druid). Extensively using Functional\/Reactive Programming, Java, NodeJS.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/glossary","text":"Glossaries Archive | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGlossaryA-ZsearchACID Transactions What is a transaction?\nIn the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a cons{...}AdaGrad Gradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.\nTypes of Gradient Descent\nThere are three primary types of gradient descent {...}Alternative Data What is Alternative Data?\nAlternative data is information gathered by using alternative sources of data that others are not using; &nbsp;non-traditional information sources. Analysis of alternative data can provide insights beyond that which an in{...}Anomaly Detection Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like{...}Apache Hive What is Apache Hive?\nApache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.\nWith exten{...}Apache Kudu What is Apache Kudu?\nApache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows to{...}Apache Kylin What is Apache Kylin?\nApache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/S{...}Apache Spark What Is Apache Spark?\nApache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.&nbsp;Apache Spark started in 2009 as a research project at {...}Apache Spark as a Service What is Apache Spark as a Service?\nApache Spark is an open source cluster computing framework for fast real-time large-scale data processing.&nbsp;Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently ra{...}Artificial Neural Network What is an Artificial Neural Network?\nAn artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.\nHow Do Artificial Neural Networks Work?\nArtificial Neural Networks can be best viewed{...}Automation Bias What is Automation Bias?\nAutomation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, {...}Bayesian Neural Network What Are Bayesian Neural Networks?\nBayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology {...}Big Data Analytics The Difference Between Data and Big Data Analytics\nPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relat{...}Bioinformatics Bioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.\nBioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data.{...}Catalyst Optimizer At the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional program{...}Complex Event Processing What is Complex Event Processing [CEP]?\nComplex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being s{...}Continuous Applications Continuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate{...}Convolutional Layer In deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language {...}Data Analysis Platform What is a Data Analysis Platform?\nA data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visua{...}Data Governance What is Data Governance?\nData governance is the oversight to ensure data brings value and supports the business strategy. Data governance is more than just a tool or a process. It aligns data-related requirements to the business strategy using a f{...}Data Lakehouse What is a Data Lakehouse?\nA data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business int{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Data Sharing What is data sharing?\nData sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or external{...}Data Vault What is a data vault?\nA data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.\nHubs represent core business concepts, {...}Data Warehouse What is a data warehouse?\nA data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business i{...}Databricks Runtime Databricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of {...}DataFrames What is a DataFrame?\nA DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are {...}Datasets Datasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recal{...}Deep Learning What is Deep Learning?\nDeep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referre{...}Demand Forecasting What is demand forecasting?\nDemand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.\nRet{...}Dense Tensor Dense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software prod{...}Digital Twin What is a Digital Twin?\nThe classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers {...}DNA Sequence What is a DNA Sequence?\nThe DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). &nbsp;Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine {...}Extract Transform Load (ETL) What is ETL?\nAs the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to pr{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Genomics Genomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DN{...}Hadoop Cluster What Is a Hadoop Cluster?\nApache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by{...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hadoop Ecosystem What is the Hadoop Ecosystem?\nApache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of{...}Hash Buckets In computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from whic{...}Hive Date Function What is a Hive Date Function?\nHive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditi{...}Hosted Spark What is Hosted Spark?\nApache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Py{...}Jupyter Notebook What is a Jupyter Notebook?\nA Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.\nWhat are Jupyter Notebooks used fo{...}Keras Model What is a Keras Model?\nKeras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.&nbsp;Keras has become one of {...}Lakehouse for Retail What is Lakehouse for Retail?\nLakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.\nLakehouse fo{...}Lambda Architecture What is Lambda Architecture?\nLambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solv{...}Machine Learning Library (MLlib) Apache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and mod{...}Machine Learning Models What is a machine learning Model?\nA machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recogni{...}Managed Spark What is Managed Spark?\nA managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, m{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}Materialized views Delta Pipelines \/ Materialized Views in Databricks Delta\nIntro\nDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve dat{...}Medallion Architecture What is a medallion architecture?\nA medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through ea{...}ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and c{...}MLOps What is MLOps?\nMLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. M{...}Model Risk Management Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and{...}Neural Network What is a Neural Network?\nA neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an outpu{...}Open Banking What is Open Banking?\nOpen banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of custo{...}Orchestration What is Orchestration?\nOrchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of {...}Overall Equipment Effectiveness What is Overall Equipment Effectiveness?\nOverall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to{...}pandas DataFrame \nWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as ef{...}Parquet What is Parquet?\nApache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in {...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}Predictive Analytics What is Predictive Analytics?\nPredictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.\nHow Does Predictive Analytics Work?\nPredictive analytics {...}Predictive Maintenance What is predictive maintenance?\nPredictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rath{...}PyCharm PyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to crea{...}PySpark What is PySpark?\nApache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface wi{...}Real-Time Retail What is real-time data for Retail?\nReal-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. {...}Resilient Distributed Dataset (RDD) \nRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API {...}Snowflake Schema What is a snowflake schema?\nA snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and re{...}Spark API If you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDs\nWhat are Resilient Distributed Datasets?\nRDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are {...}Spark Applications Spark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; res{...}Spark Elasticsearch What is Spark Elasticsearch?\nSpark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and r{...}Spark SQL Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can al{...}Spark Streaming Apache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Stre{...}Spark Tuning What is Spark Performance Tuning?\nSpark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also preven{...}Sparklyr What is Sparklyr?\nSparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little l{...}SparkR SparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follow{...}Sparse Tensor Python offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library. Sptensor is a class that represents the sparse tensor. A spa{...}Star Schema What is a star schema?\nA star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The st{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a stre{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API What is the Tensorflow Estimator API?\nEstimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow {...}Transformations What Are Transformations?\nIn Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d {...}Tungsten What is the Tungsten Project?\nTungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance{...}Unified AI Framework Unified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute r{...}Unified Data Analytics Unified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it e{...}Unified Data Analytics Platform Databricks' Unified Data Analytics Platform&nbsp;helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at mass{...}Unified Data Warehouse What is a Unified Data Warehouse?\nA unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in {...}What Is Hadoop? Apache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them{...}ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacob-renn","text":"Jacob Renn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacob RennChief Technologist at AI Squared, IncBack to speakersDr. Jacob Renn is co-founder and Chief Technologist of AI Squared, a seed-stage startup located in the Washington, DC area. At AI Squared, Jacob leads the company\u2019s R&D efforts. Jacob is the lead developer of DLite, a family of large language models developed by AI Squared, and he is also the creator of the BeyondML project. Jacob also serves as adjunct faculty at Capitol Technology University, where he completed his PhD in Technology with a focus in Explainable Artificial Intelligence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jaison-dominic","text":"Jaison Dominic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJaison DominicSenior Manager Information Systems at AmgenBack to speakersJaison Dominic is a Transformational Data & Analytics leader passionate about driving value for patients and businesses through Data Engineering, Advanced Analytics, and Enterprise Data Fabric. He enjoys driving discussions on Data Strategy alignment with business objectives, leading teams, and building effective partnerships within and outside the organization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-announces-lakehouse-manufacturing-empowering-worlds","text":"Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their Data - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataApril 4, 2023Share this postLakehouse for Manufacturing offers pre-built solutions, partner-designed Brickbuilder offerings and integrated AI capabilities tailored to customers across the manufacturing, logistics, transportation, energy and utilities industries\nSAN FRANCISCO \u2013\u00a0April 4, 2023 \u2013 Databricks, the lakehouse company, today announced the Databricks Lakehouse for Manufacturing, the first open, enterprise-scale lakehouse platform tailored to manufacturers that unifies data and AI and delivers record-breaking performance for any analytics use case. The sheer volume of tools, systems and architectures required to run a modern manufacturing environment makes secure data sharing and collaboration a challenge at scale, with over 70 percent of data projects stalling at the proof of concept (PoC) stage. Available today, Databricks\u2019 Lakehouse for Manufacturing breaks down these silos and is uniquely designed for manufacturers to access all of their data and make decisions in real-time. Databricks\u2019 Lakehouse for Manufacturing has been adopted by industry-leading organizations like DuPont, Honeywell, Rolls-Royce, Shell and Tata Steel.\u00a0\nDatabricks\u2019 newest industry-specific lakehouse goes beyond the limitations of traditional data warehouses by offering integrated AI capabilities and pre-built solutions that accelerate time to value for manufacturers and their partners. These include powerful solutions for predictive maintenance, digital twins, supply chain optimization, demand forecasting, real-time IoT analytics and more. A robust partner ecosystem and custom, partner-built Brickbuilder Solutions offer customers even greater choice in delivering real-time insights and impact across the entire value chain, and at a lower total cost of ownership (TCO) than complex legacy technologies\n\u201cWe employed Databricks to optimize inventory planning using data and analytics, positioning parts where they need to be based on the insight we gain from our connected engines in real time and usage patterns we see in our service network,\u201d said Stuart Hughes, Chief Information and Digital Officer at Rolls-Royce Civil Aerospace. \u201cThis has helped us minimize risks to engine availability, reduce lead times for spare parts and drive more efficiency in stock turns - all of this enables us to deliver TotalCare, the aviation industry\u2019s leading Power-by-the-Hour (PBH) maintenance program.\u201d\u00a0\nWith Databricks, organizations can unlock the value of their existing investments and achieve AI at scale by unifying all of their data \u2013 regardless of type, source, frequency or workload \u2013 on a single platform. The Lakehouse for Manufacturing has robust data governance and sharing built-in, and enables organizations to deliver real-time insights for agile manufacturing and logistics, across their entire ecosystem.\nPowerful industry solutions tailored for the lakehouse\nThe Lakehouse for Manufacturing includes access to packaged use case accelerators that are designed to jumpstart the analytics process and offer a blueprint to help organizations tackle critical, high-value industry challenges. Popular data solutions for Databricks\u2019 Lakehouse for Manufacturing customers include:\u00a0\n\nDigital Twins: Created from data derived from sensors, digital twins enable engineers to monitor and model systems in real-time. With digital twins, manufacturers can process real-world data in real-time and deliver insights to multiple downstream applications, including process optimization modeling, risk assessments, condition monitoring, and optimized design.\nPredictive Maintenance: By leveraging predictive maintenance, manufacturers can ingest real-time industrial Internet of Things (IIoT) data from field devices and perform complex time-series processing to maximize uptime and minimize maintenance costs.\u00a0\nPart-Level Forecasting: To avoid inventory stockouts, shorten lead times and maximize sales, manufacturers can perform demand forecasting at the part level rather than the aggregate level.\nOverall Equipment Effectiveness: By incrementally ingesting and processing data from sensor\/IoT devices in a variety of formats, organizations can provide a consistent approach to KPI reporting across a global manufacturing network.\nComputer Vision: The development and implementation of computer vision applications enabled manufacturers to automate critical manufacturing processes, improving quality, reducing waste and rework costs, and optimizing flow.\n\n\u201cShell has been undergoing a digital transformation as part of our ambition to deliver more and cleaner energy solutions. Databricks\u2019 Lakehouse is central to the Shell.ai Platform and the ability to execute rapid queries on massive datasets,\u201d said Dan Jeavons, VP Computational Science and Digital Innovation at Shell. \u201cWith the help of Databricks, Shell is better able to use its full historic data set to run 10,000+ inventory simulations across all its parts and facilities. Shell\u2019s inventory prediction models now run in a few hours rather than days, significantly improving stocking practices and driving significant savings annually.\u201d\nDatabricks Partners deliver an ecosystem of powerful, purpose-built solutions for manufacturers\nCustomers across the manufacturing industry also benefit from vetted data solutions from leading partners like Avanade, Celebal Technologies, DataSentics, Deloitte and Tredence, which are tailor-made to combine the power of Databricks\u2019 Lakehouse Platform with proven industry expertise. Partner Brickbuilder Solutions and popular use cases for the Lakehouse for Manufacturing include:\u00a0\n\nAvanade Intelligent Manufacturing: Avanade enables manufacturers to harness all types of data, drive interoperability and realize more value throughout the manufacturing lifecycle with a comprehensive look at connected production facilities and assets.\nCelebal Technologies Migrate to Databricks: A suite of proven tools from Celebal Technologies empowers organizations to easily migrate legacy on-premises\/cloud environments to the Lakehouse Platform and addresses the key scalability, performance and cost challenges of legacy systems.\nDataSentics Quality Inspector: With DataSentics, manufacturers can leverage computer vision to automate quality control and easily detect defects, foreign objects and anomalies throughout the manufacturing process, from classification and detection to product segmentation and tracking.\u00a0\u00a0\nDeloitte Smart Factory: Deloitte offers automated Monthly Management Reporting to deliver dynamic insights and enable a digital organization supported by an enterprise data lake and advanced analytics.\nTredence Predictive Supply Risk Management: Tredence unifies siloed data and drives end-to-end visibility into order flows and supplier performance with a holistic view of the entire supply chain, coupled with real-time data to assess risk factors and prescriptive, AI-powered recommendations across all supply chain functions.\n\n\u201cAvanade is delighted to partner with industry innovators like Databricks. As the leading Microsoft Partner for Manufacturing, we see manufacturers getting smarter about how they use digital technologies \u2013 because they have to. Times are tough and innovations today must deliver more value more quickly across more of the organization than ever before. The potential of lakehouse is truly exciting and will play a significant part in our Industry X and Smart Digital Manufacturing services,\u201d said Thomas Nall, Avanade Manufacturing Lead.\n\u201cUsing the Lakehouse for Manufacturing, a business can utilize all data sources in their value chain so that the power of predictive AI and ML insights can be realized to identify inefficiencies in production processes, improve productivity, enhance quality control, and reduce supply chain costs. This data-driven manufacturing is where we see the industry going as companies seek to accelerate their Smart Factory transformations,\u201d said Anthony Abbattista, Principal and Smart Factory Analytics Offering Leader at Deloitte Consulting LLP.\n\u201cWith rising costs, plateauing industrial productivity, and talent gaps, manufacturing companies are facing unprecedented operational challenges. At the same time, autonomy, connectivity and electrification are shaping an entirely new approach of software-defined products that require a transformation of the business and operating model to be competitive and innovative. In the next 5 years, the companies that outperform in this industry will be the ones that not only manage data but effectively operationalize the value from data, analytics and AI at scale,\u201d said Shiv Trisal, Global Industry Leader for Manufacturing at Databricks. \u201cWe are very excited to launch tailored accelerators that target the industry\u2019s biggest pain points, and collaborate with leading partners to introduce Lakehouse for Manufacturing, enabling data teams to boost industrial productivity, gain nth-tier supply chain visibility and deliver smarter products and services at an accelerated pace.\u201d\nThe introduction of the Lakehouse for Manufacturing comes on the heels of the recent release of Databricks Model Serving, for fully managed production ML and a new, native integration with VS Code. For more information, visit Databricks\u2019 Lakehouse for Manufacturing homepage.\u00a0\nFor those attending Hannover Messe, register to join Databricks on April 18th for An Evening at the Lakehouse at Insel Beach Club and learn more about Databricks\u2019 platform and work with customers throughout the industry.\u00a0\n\u00a0\nAbout Databricks\nDatabricks is the lakehouse company. More than 9,000 organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, and over 50% of the Fortune 500 \u2014 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\nContact: [email\u00a0protected]\u00a0\n\u00a0\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/tackle-data-transformation","text":"Tackle Data Transformation With Delta Live Tables - DatabricksOn-DemandDelta Live Tables: Modern software engineering and management for ETLAvailable on-demandTo drive data analysis, data science and machine learning, data engineers have the difficult and laborious task of cleansing complex, diverse data and transforming it into a usable source. To do so, they need to know the ins and outs of the data infrastructure platform, and it requires the building of complex queries in various languages, stitching them together for production. For many organizations, this complexity limits their ability to utilize these critical downstream use cases.Watch this webinar to learn how Delta Live Tables simplifies the complexity of data transformation and ETL. Delta Live Tables (DLT) is the first ETL framework to use modern software engineering practices to deliver reliable and trusted data pipelines at any scale.In this webinar, you will learn how Delta Live Tables enables:Analysts and data engineers to innovate rapidly with simple pipeline development and maintenanceData teams to remove operational complexity by automating administrative tasks and gaining broader visibility into pipeline operationsTrust your data with built-in quality controls and quality monitoring to ensure accurate and useful BI, data science, and MLSimplified batch and streaming with self-optimization and auto-scaling data pipelinesSpeakersMichael ArmbrustDistinguished Software EngineerDatabricksAbhay PrajapatiPrincipal Data Solutions ArchitectJLLWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/code-of-conduct\/#","text":"Code of Conduct - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCode of ConductData + AI Summit Event , Organized by DatabricksSummit Organizers are committed to creating a safe and inclusive experience for our conference attendees, regardless of gender, sexual orientation, disability, physical appearance, body size, race, or religion. We do not tolerate harassment in any form. All communication \u2014 including at the event and various associated venues, as well as online \u2014 should be appropriate for a professional audience, including people of many different backgrounds and experiences. Be kind to others. Do not insult or put down other attendees. Act professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate at any time at any event organized by Databricks.\nInteraction Guidelines for AttendeesFor all interactions during the Data + AI Summit Event, we expect participants to abide by the event\u2019s Code of Conduct to ensure the environment remains productive and respectful. The following guidelines will further help ensure we maintain an inclusive experience throughout our event:\n\nBe respectful of others.\nAvoid conflicts and arguments.\nUse common sense, kindness, and consideration together with the guidelines outlined above.\nIf you intend to participate in the event, please make sure to dress appropriately.\n\nEnforcementIf a participant engages in behavior that doesn\u2019t comply with these expectations, Summit Organizers may take any action that we deem appropriate, including warning the participant, excluding the participant from certain activities, prohibiting the participant from attending future events organized by Databricks, expelling the participant from the event without a refund, banning the participant from online forums, and other similar type experiences. Participants asked to stop any harassing or other unacceptable behaviors are expected to comply immediately. Anyone violating these rules may be asked to leave the experience without a refund at the sole discretion of Summit Organizers.\n\nPlease note, while we take all concerns raised seriously, we will use our discretion to determine when and how to follow up on reported incidents, and may decline to take any further action and\/or may direct the participant to other resources to address the concern.\nReporting an IssueIf you are being harassed, notice that someone else is, or have any concerns, please contact Summit Organizers at [email\u00a0protected] and provide your name, phone number, email, and a description of the situation. Summit Organizers can only address complaints about behavior at the Event.\nThe reporting mechanisms under this Code of Conduct are not intended to address criminal activity or emergency situations. If you have been the victim of a crime or there is an emergency, please contact the appropriate municipal authorities, such as the police, fire, medical, or other emergency responders.\nThank you for helping make Databricks Data + AI Summit a welcoming, friendly place for all to share new ideas, learn, and connect.\n\nInformation for Presenters: Presenters who are unsure whether their presentations or other materials and communications are consistent with these expectations, please contact Toby Malina at\u00a0 [email\u00a0protected] in advance of the experience.\n\u00a0\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zachary-huang\/#","text":"Zachary Huang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZachary HuangPhD at Columbia UniversityBack to speakersZachary Huang is a PhD student at Columbia University. His research interests are in novel data management systems over large join graphs. His research works have been applied to data exploration, machine learning, and data market.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zoe-durand\/#","text":"Zoe Durand - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZoe DurandSenior Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rob-saker\/#","text":"Rob Saker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRob SakerGlobal VP, Retail and Manufacturing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/session_na20\/automating-federal-aviation-administrations-faa-system-wide-information-management-swim-data-ingestion-and-analysis","text":"AboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLCDatabricks - YouTube"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steven-yu","text":"Steven Yu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteven YuPrincipal Solutions Architect at DatabricksBack to speakersTBDLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/lakehouse-for-retail","text":"What is Lakehouse for Retail?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLakehouse for RetailAll>Lakehouse for RetailTry Databricks for freeGet StartedWhat is Lakehouse for Retail?Lakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.Lakehouse for Retail is the culmination of technologies, partners, tools, and industry initiatives to drive stronger collaboration around data + AI. It is made up of four fundamental building blocks:\nUnified Data + AI Platform: Delivers critical capabilities required to run modern retail on a single platform:\nMake data-informed decisions in real-timeDeliver more accurate analysis with powerful AILeverage a variety of data types on one unified platformPartner Solutions: Customers can confidently adopt Lakehouse for Retail by adopting partner-built use case solutions created on Lakehouse for Retail.Driving Industry Data Sharing & Collaboration: Drive secure and open data sharing as well as collaboration to unlock innovation with partners.Tools to Accelerate: Databricks and its partners have invested in a variety of retail solution accelerators to help customers quickly adopt and drive results with Lakehouse.Why are retailers turning to Lakehouse for Retail?Over the last two years, retailers have struggled with the massive shift to e-commerce and with shifting consumers' preferences and needs. To address these challenges, retailers have built the following solutions into their strategy:Operate in real-time: Companies must be able to rapidly ingest data at scale and make insights available across the value chain in real-time.Eliminate technical roadblocks: Allows organizations to perform fine-grained analysis for all products within their tight service level agreements.Use multimodal data quickly and efficiently for analysis: Only 5-10% of a company\u2019s data is structured. Tapping into the other 90% of data helps businesses better understand the environment around them and make better decisions.Gain an inexpensive and open method of collaboration: For data and analysis, collaboration is critical to ensure open interaction and innovation for all partners in the value chain. Enhanced collaboration also improves the speed of operations, builds richer analytics, and reduces the cost of alignment across the value chain.What are the benefits to retailers?Immediate benefits:\u00a0Real-time access to data. Moving from batch-oriented access, analysis, and compute will allow data to be \u201calways-on\u201d, which drives real-time decisions and business intelligence. Real-time use cases, such as demand forecasting, personalization, on-shelf availability, arrival time prediction, and order picking & consolidation, provide value to the organization through improved supply chain agility, reduced cost to serve, optimized product availability, and stocking replenishment.Long-term benefits:Retail has always been about collaboration - but most of that collaboration didn\u2019t involve data sharing or data collaboration. Lakehouse for Retail is changing this. Data sharing between retailers, suppliers, agencies, and distributors, in an open and secure environment, opens up additional fine-grained use cases, therefore promoting additional consumption.Learn more about Lakehouse for Retail solutions.Additional ResourcesIntroduction to Lakehouse for Retail VideoCollaborating Across the Retail Value Chain with Data and AIThe Retail Lakehouse: Build Resiliency and Agility in the Age of DisruptionReimagining the future of retail with data + AI blogBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-debrabant\/#","text":"Justin DeBrabant - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin DeBrabantSVP of Product at ActionIQBack to speakersJustin is Senior Vice President of Product at ActionIQ. He spent his formative years building large distributed systems to support data science and analytics and holds a Ph.D. in Databases from Brown University where he researched the forefront of modern data systems. For the last 10+ years, he has been passionate about building data-driven products that help realize the value of customer data by delivering truly customer-centric experiences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/technology-and-software","text":"Data Analytics, Machine Learning and AI for the Technology Industry | Databricks \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Analytics and Machine Learning for the Technology and Software IndustryBring new technologies to market faster with big data analytics and machine learning.Develop Next Generation Technology Solutions with Data Analytics and AIEnabling technology and software companies to tap into the potential of data and machine learning to develop new technologies and applications that customers crave \u2014 powered by the Databricks Unified Data Analytics Platform.Product development and supportAnalyze customer and market data to identify new product features and predict customer support needs for early intervention and remediation.Security MonitoringAnalyze product and network data in real-time to detect anomalies and respond to threats before they impact application and system performance.Predictive maintenanceFrom the factory floor to products in the field, analyze streaming IoT data to predict maintenance needs before they occur.Customer TalkAutomating Support Ticket Forecasting with Databricks, Delta Lake and MLflowLearn how Atlassian built a robust, fault-tolerant, auditable, and reproducible ML pipeline for predicting support tickets at a granular level.Watch nowCustomer TalkHow Salesforce Uses Apache Spark and Databricks to Power Intelligent ServicesWatch this Spark + AI Summit talk to learn how Salesforce uses Apache Spark and Databricks to discover new insights, power smarter decision making, and automate development workflows.Watch nowCustomer KeynoteThreat Detection at Petabyte-scaleWatch this Spark + AI Summit keynote to learn how one of the largest tech companies in the world uses Databricks to monitor cyber threats in real-time.Watch nowCase StudyUsing AI to Uncover Revenue OpportunitiesRead how People.ai uses machine learning to help enterprise customers drive actionable insights that uncover revenue opportunities.Read more\u201cDatabricks Unified Analytics Platform has helped foster collaboration across our data science and engineering teams which has impacted innovation and productivity.\u201d \u2014John Landry, Distinguished Technologist, HP, Inc.Read the case studyReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/customers","text":"Clienti di Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWClienti di DatabricksScopri come aziende innovative in tutti i settori utilizzano Databricks Lakehouse Platform per operare con successoStorie in evidenza\n\n\nCustomer Story\n\nAT&T democratizes data to prevent fraud, reduce churn and increase CLV\nDatabricks Lakehouse has helped AT&T accelerate AI across operations, including decreasing fraud by 70%\u201380%\n\nRead more\n\n\nREFERENZA\n\nShell innova con soluzioni energetiche per un mondo pi\u00f9 pulito\nDatabricks Lakehouse aiuta a democratizzare i dati e modernizzare le operazioni a livello globale\n\nPer saperne di pi\u00f9\n\n\nCustomer Story\n\nBurberry adopts data-driven content creation\nBurberry sees a 70% improvement in time savings for generating image insights with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nABN AMRO transforms banking on a global scale\nABN AMRO puts data and Al into action with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nRolls-Royce delivers a greener future for air travel\nRolls-Royce decreases carbon through real-time data collection with Databricks Lakehouse\n\nWatch video\n\n\nCustomer Story\n\nSEGA drives the future of gaming with data and Al\nSEGA uses Databricks Lakehouse to democratize data and deliver gaming experiences at scale\n\nWatch videoScopri tutti i clientiL'effetto team di datiI team di gestione dei dati sono la forza coesa che risolve i problemi pi\u00f9 complessi del mondo.Scopri come \u2192La tua pu\u00f2 essere la prossima storia di successoContattiRisorseREFERENZAScopri come Databricks aiuta Cond\u00e9 Nast a proporre contenuti personalizzati ai propri clienti.Maggiori informazioniWebinarScopri come Apple e Disney+ hanno unificato con successo analisi e AIGuardaPodcastIl ruolo dei dati e dell'IA nell'equit\u00e0 dell'assistenza sanitaria \u00e8 stato illustrato dal CDAO di HumanaGuardaPronto per cominciare?Prova gratuitaContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/julie-ferris","text":"Julie Ferris - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJulie FerrisVice President, Commercial Optimization at Definitive HealthcareBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-mantz\/#","text":"Chris Mantz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris MantzData Architect at SlalomBack to speakersA consultant, as well as a data architect and data engineer by training, Chris has 4 years of experience architecting Databricks solutions across a variety of industries including healthcare, transportation, and retail.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/technology","text":"Databricks Technology Partners - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Technology PartnersConnect with Databricks Technology Partners to integrate data ingestion, business intelligence and governance capabilities with the Databricks Lakehouse Platform.\u201cWith Databricks and Fivetran, we will be able to significantly improve marketing insights in the future. From a technical standpoint, the two tools interact harmoniously together and the integration feels very native.\u201d\u2014 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP at Paul HewittDatabricks Technology Partners integrate their solutions with Databricks to provide complementary capabilities for ETL, data ingestion, business intelligence, machine learning and governance.These integrations enable customers to leverage the Databricks Lakehouse Platform\u2019s reliability and scalability to innovate faster while deriving valuable data insights.Partner ConnectBring together all your data, analytics and AI tools on one open platform. With Partner Connect, Databricks provides a fast and easy way to connect your existing tools to your lakehouse using validated integrations, and helps you discover and try new solutions.Become a partnerLearn moreLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/product\/machine-learning","text":"Databricks Machine Learning | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWMachine LearningAcelere seus projetos de IA com uma abordagem baseada em dados para machine learningExperimente gratuitamenteAgendar uma demonstra\u00e7\u00e3o\nCrie seu pr\u00f3prio modelo de linguagem grande como Dolly\n25 de abril de 2023 | 8h PT\nParticipeMergulhe no machine learning com a DatabricksMLflow gerenciadoRegistro de modelosRuntime para MLNotebooks colaborativosFeature StoreAutoMLIA explic\u00e1velReposit\u00f3riosMonitoramento de modelosServindo modeloCom base em uma arquitetura aberta de\u00a0lakehouse,\u00a0o Databricks Machine Learning permite que as equipes de ML preparem e processem dados, simplifiquem a colabora\u00e7\u00e3o em toda a empresa e padronizem todo o ciclo de vida, dos testes \u00e0 produ\u00e7\u00e3o.Mais de US$ 6 milh\u00f5es em economiaCONA Services usa Databricks para um ciclo de vida completo de ML com o intuito de otimizar a cadeia de suprimentos de centenas de milhares de lojas.Saiba maisR$ 3,9 milh\u00f5es em economiaVia aproveita o machine learning para prever a demanda com precis\u00e3o, reduzindo os custos de computa\u00e7\u00e3o em 25%.Saiba maisMais de US$ 50 milh\u00f5es em redu\u00e7\u00e3o de custosAmgen est\u00e1 melhorando a colabora\u00e7\u00e3o de data science para acelerar a descoberta de medicamentos e reduzir os custos operacionais.Saiba maisSimplifique todos os aspectos de dados para MLDesenvolvido em uma base aberta de lakehouse gra\u00e7as ao Delta Lake, o Databricks ML permite que suas equipes de machine learning acessem, explorem e preparem qualquer tipo de dados em qualquer escala. Transforme recursos em pipelines de produ\u00e7\u00e3o de autoatendimento sem depender do suporte de data engineering.Automatize o rastreamento e a governan\u00e7a de experimentosO MLflow Gerenciado rastreia automaticamente seus par\u00e2metros de experimentos e logs, m\u00e9tricas, controles de vers\u00e3o de dados e c\u00f3digo, bem como artefatos de modelo a cada execu\u00e7\u00e3o de treinamento. Voc\u00ea pode ver rapidamente execu\u00e7\u00f5es anteriores, comparar resultados e reproduzir um resultado de execu\u00e7\u00e3o anterior, conforme necess\u00e1rio. Depois de identificar a melhor vers\u00e3o de um modelo para produ\u00e7\u00e3o, registre-a no Registro de Modelos para simplificar as transfer\u00eancias ao longo do ciclo de implanta\u00e7\u00e3o.Gerencie todo o ciclo de vida do modelo, dos dados \u00e0 produ\u00e7\u00e3o \u2014 e vice-versaDepois que os modelos treinados forem registrados, voc\u00ea poder\u00e1 gerenci\u00e1-los de forma colaborativa durante todo o ciclo de vida usando o Registro de Modelos. Os modelos podem ser versionados e passar por diferentes etapas, como teste, prepara\u00e7\u00e3o, produ\u00e7\u00e3o e arquivamento. A gest\u00e3o do ciclo de vida se integra aos fluxos de trabalho de aprova\u00e7\u00e3o e governan\u00e7a de acordo com os controles de acesso baseados em fun\u00e7\u00f5es. Coment\u00e1rios e notifica\u00e7\u00f5es por e-mail fornecem um ambiente colaborativo rico para equipes de dados.Implante modelos de ML de baixa lat\u00eancia e grande escalaImplante modelos com um \u00fanico clique, sem se preocupar com gerenciamento de servidor ou restri\u00e7\u00f5es de escala. Com a Databricks, voc\u00ea pode implantar seus modelos como endpoints API REST em qualquer lugar com disponibilidade de n\u00edvel empresarial.Componentes do produtoNotebooks colaborativosOs notebooks da Databricks s\u00e3o compat\u00edveis nativamente com Python, R, SQL e Scala. Os usu\u00e1rios podem trabalhar com as linguagens e bibliotecas de sua escolha para descobrir, visualizar e compartilhar insights.Saiba maisRuntime para machine learningAcesso com um clique a clusters de ML pr\u00e9-configurados e otimizados com base em uma distribui\u00e7\u00e3o escal\u00e1vel e confi\u00e1vel das estruturas de ML mais populares (como PyTorch, TensorFlow e scikit-learn), com otimiza\u00e7\u00f5es integradas para desempenho inigual\u00e1vel em toda a empresa.Saiba maisFeature StoreFacilite a reutiliza\u00e7\u00e3o de recursos com busca baseada em linhagem de dados que aproveita fontes registradas automaticamente. Disponibilize seus recursos para treinamento com implanta\u00e7\u00e3o de modelos simplificados que n\u00e3o requerem altera\u00e7\u00f5es na aplica\u00e7\u00e3o cliente.Saiba maisAutoMLEmpodere todos, de especialistas em ML a citizen data scientists, com uma abordagem \u201ccaixa de vidro\u201d para AutoML, que n\u00e3o apenas fornece o modelo de melhor desempenho, mas tamb\u00e9m gera c\u00f3digo para refinamento adicional por especialistas.Saiba maisMLflow gerenciadoDesenvolvido em MLflow \u2014 a principal plataforma de c\u00f3digo aberto do mundo para o ciclo de vida de ML \u2014 o MLflow Gerenciado ajuda os modelos de ML a passar rapidamente dos testes para a produ\u00e7\u00e3o, com um alto n\u00edvel de seguran\u00e7a, confiabilidade e escalabilidade em toda a empresa.Saiba maisDisponibiliza\u00e7\u00e3o de modelos de n\u00edvel de produ\u00e7\u00e3oDisponibilize modelos em qualquer escala com um clique, com a op\u00e7\u00e3o de computa\u00e7\u00e3o serverless.Saiba maisMonitoramento de modelosMonitore o desempenho do modelo e seu impacto nas m\u00e9tricas de neg\u00f3cios em tempo real. A Databricks oferece visibilidade e linhagem de ponta a ponta, desde modelos de produ\u00e7\u00e3o at\u00e9 sistemas de dados de origem. A plataforma permite analisar o modelo e a qualidade dos dados durante todo o ciclo de vida do ML e, portanto, identifica problemas antes que tenham impacto prejudicial.Saiba maisReposit\u00f3riosOs reposit\u00f3rios permitem que os engenheiros rastreiem os fluxos de trabalho do Git na Databricks. Assim, as equipes de dados podem aproveitar fluxos de trabalho de CI\/CD automatizados e portabilidade de c\u00f3digo.Saiba maisMigre para a DatabricksN\u00e3o aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA.Migre para a DatabricksRecursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre data science e machine learning.\nExplorar recursose-bookse-book: The Big Book of MLOpsExplore a nova solu\u00e7\u00e3o de Delta SharingGuia de migra\u00e7\u00e3o: Do Hadoop para DatabricksDemonstra\u00e7\u00f5es e blogsMergulhe nas solu\u00e7\u00f5es de machine learning com a DatabricksCinco etapas principais para uma migra\u00e7\u00e3o bem-sucedida do Hadoop para a arquitetura de lakehouseEventos virtuaisAutoML: Machine learning r\u00e1pido e simplificado para todosEvento virtual do MLOps: Padroniza\u00e7\u00e3o do MLOps em escalaAutomatiza\u00e7\u00e3o do ciclo de vida de ML com Machine Learning DatabricksEvento virtual MLOps: Operacionaliza\u00e7\u00e3o do machine learning em grande escalaCria\u00e7\u00e3o de plataformas de machine learningDelta Lake: A base do seu lakehouseGuia passo a passo para migra\u00e7\u00e3o do HadoopTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/try-databricks-azure?itm_data=AzurePage-HeroTrialButton-AzureTrial","text":"Try Databricks on Azure \u2013 DatabricksTry Databricks on AzureDiscover how easy it is to simplify your data architecture by unifying all of your analytics and AI workloads on a simple open lakehouse platform.Azure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Power BI and many more Azure services.Join thousands of customers who already use this game-changing platform for their data teams.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/neil-patel","text":"Neil Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNeil PatelLead Specialist Solutions Architect at DatabricksBack to speakersNeil Patel is an SSA at Databricks. He has worked on a variety of use cases and problems across different customers.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/test1-testcfp1102\/#","text":"Test1 TestCFP1102 - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTest1 TestCFP1102 testBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vincent-chen","text":"Vincent Chen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVincent ChenDirect of Product \/ Founding Engineer at Snorkel AIBack to speakersVincent Chen leads product for machine learning experiences in Snorkel Flow. Before that, he led Snorkel's ML Engineering team and performed research at the Stanford AI Lab, where he worked on the foundations of data-centric machine learning systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rahil-bhatnagar","text":"Rahil Bhatnagar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRahil BhatnagarDevelopment Lead, LOLA at Anheuser BuschBack to speakersRahil Bhatnagar has experience leading cross-functional teams to build scalable products, taking them from ideas to production. Applying his distributed systems and game development background to create sustainable dynamic solutions on time. Currently, leading and scaling Anheuser-Busch's Machine Learning Platform, LOLA to solve the growing demand for machine learning insights in a tech-first FMCPG.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/legal\/privacynotice","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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Databricks\ub294 \uace0\uac1d\uc758 \uc131\uacf5\uc744 \uc704\ud574 \uad11\ubc94\uc704\ud55c \uc790\uc0ac \ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud65c\uc6a9\ud558\uc5ec \ud544\uc694\uc5d0 \ub530\ub77c \ud568\uaed8 \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.Databricks \ubc0f Spark \uc804\ubb38\uac0010\ub144 \uac04 \ucd95\uc801\ub41c \uacbd\ud5d8\n\ube45\ub370\uc774\ud130\uc5d0 \ub300\ud55c \ud48d\ubd80\ud55c \uc9c0\uc2dd\n\uc2e4\uc81c \uad6c\ud604 \uae30\uc220\n\ud504\ub85c\uc81d\ud2b8 \uacc4\ud68d \ubc0f \uc2e4\ud589\uc124\uacc4 \ubc0f \uc544\ud0a4\ud14d\ucc98 \uc9c0\uc6d0\n\ud504\ub85c\uc81d\ud2b8\ub97c \ud50c\ub7ab\ud3fc \uae30\ub2a5\uc5d0 \ub9de\ub3c4\ub85d \uc9c0\uc6d0\n\ud504\ub85c\uc81d\ud2b8 \uc77c\uc815\uacfc \ub9ac\uc18c\uc2a4 \uc694\uad6c \uc0ac\ud56d\uc5d0 \ub300\ud55c \uc870\uc5b8 \uc81c\uacf5\n\uad6c\ud604 \ubc0f \ud504\ub85c\ub355\uc158 \uacc4\ud68d\ud655\uc7a5\uc131\uc744 \uc704\ud55c \uc544\ud0a4\ud14d\ud2b8 \uc194\ub8e8\uc158\n\ud504\ub85c\ud1a0\ud0c0\uc785 \uac1c\ubc1c \uc9c0\uc6d0\nDevOps \ud1b5\ud569 \uc694\uad6c \uc0ac\ud56d \ud574\uacb0\nCOE \uad6c\ud604 \uc9c0\uc6d0\uacf5\ud1b5\uc801 \ud45c\uc900 \ubc0f \ud504\ub808\uc784\uc6cc\ud06c \uac1c\ubc1c\n\uc5ec\ub7ec \ud300\uc744 \uc704\ud55c \ub9ac\uc18c\uc2a4\ub85c \uc81c\uacf5\n\ub2e4\ub978 Databricks \ud300\uacfc\uc758 \uc0c1\ud638\uc791\uc6a9 \uc9c0\uc6d0\n\ub9ac\uc18c\uc2a4\uc131\uacf5 \ud06c\ub808\ub527 \ud504\ub85c\uadf8\ub7a8 \uac1c\uc694\uad50\ud658 \uc694\uccad \uc591\uc2ddDatabricks Academy\ub97c \uc120\ud0dd\ud558\ub294 \uc774\uc720\uace0\uac1d \uc131\uacf5\uc758 \uc911\uc2ec\uc5d0 \uc120 \uc0ac\ub78c\ub4e4\uc740 Databricks Academy\ub97c \ud1b5\ud55c \uad50\uc721\uacfc \uc778\uc99d\uc744 \ubc1b\uc73c\uba74 UC Berkeley\uc5d0\uc11c Spark \uc5f0\uad6c \ud504\ub85c\uc81d\ud2b8\ub97c \uc2dc\uc791\ud55c \ud300\uc5d0\uac8c \ub370\uc774\ud130 \ubd84\uc11d\uc744 \ubc30\uc6cc \ub9c8\uc2a4\ud130\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks Academy\ub97c \ud1b5\ud574 \ube60\ub974\uac8c \uc2e4\ub825\uc744 \ud0a4\uc6b0\uc138\uc694.\uc9c0\uae08 \uae30\uc220\uc744 \uc5c5\uadf8\ub808\uc774\ub4dc\ud558\uc138\uc694\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb38\uc758\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/milos-colic","text":"Milos Colic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMilos ColicTech Lead EMEA Public Sector - Sr. Solutions Architect at DatabricksBack to speakersMilos Colic is Tech Lead for Public Sector UK&I at Databricks. He is passionate about big data processing and has been working with Apache Spark for more than 5 years. Milos has co-authored Mosaic framework built on top of Spark to process geospatial data efficiently at large scales. He has been very active on the Databricks blog writing about Data Products, FAIR Standards, Geospatial, Data Linking, Personalization in Retail Banking, GDPR, data sharing and more.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/menglei-sun\/#","text":"Menglei Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMenglei SunSenior Software Engineer at DatabricksBack to speakersMenglei Sun is a senior software engineer at Databricks working on data lineage and data discovery related projects. Previously, Menglei worked at Houzz, BlackRock on data infrastructure, data engineering and platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dael-williamson\/#","text":"Dael Williamson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDael WilliamsonField CTO at DatabricksBack to speakersAs the EMEA CTO for Databricks, Dael provides thought leadership and guidance for the C-level executives at major customers. Prior to joining Databricks, Dael was the Global Data Technology Lead at Avanade\/Accenture. An entrepreneurial CTO and Business Platform Economist focussed on digital, data & AI led business transformations across different industries. A published data scientist in the field of protein molecular modelling, with extensive experience working in start-ups and enterprises.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anup-segu\/#","text":"Anup Segu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnup SeguCo-Head of Data Engineering at YipitDataBack to speakersAnup is the Co-Head of Data Engineering at YipitData, a leader in the alternative data industry that provides data insights for investment firms and corporations. At YipitData, Anup helped found its Data Engineering department, architected its petabyte-scale data platform, and drove adoption of data analytics and spark across the company. Previously, Anup worked in investment banking at Citigroup and studied at Indiana University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/on-shelf-availability","text":"Improve On-Shelf Availability- 2021 | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorImprove On-Shelf AvailabilityPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedUse AI out-of-stock modeling to improve on-shelf availabilityOut of stock (OOS) is one of the biggest problems in retail. This Solution Accelerator shows how OOS can be solved with real-time data and analytics by using the Databricks Lakehouse Platform to solve on-shelf availability in real time to increase retail sales. The accelerator can also be used for supply chain solutions.Use real-time insights to rapidly respond to demandDrive more sales with on-shelf availabilityScale-out your solution to accommodate any size operationDownload notebooksResourcesWebinarLearn moreeBookLearn moreBlogRead nowDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions","text":"Databricks \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130 - Databricks \uc0ac\uc6a9 \uc0ac\ub840Skip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 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Try adjusting the filters or start a new search.reset the list\uc0b0\uc5c5 \uc194\ub8e8\uc1582\uc8fc \uc774\ub0b4\uc5d0 \uad6c\uc0c1\uc5d0\uc11c \uac1c\ub150 \uc99d\uba85 \ub2e8\uacc4\uae4c\uc9c0 \uc644\ub8ccDatabricks \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130\ub294 \ubaa8\ub4e0 \uae30\ub2a5\uc744 \uac16\ucd98 \ub178\ud2b8\ubd81\uacfc \ubaa8\ubc94 \uc0ac\ub840\ub97c \ud3ec\ud568\ud55c \uc804\uc6a9 \uac00\uc774\ub4dc\ub97c \ud1b5\ud574 \ube60\ub978 \uc131\uacfc\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. 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{"source":"https:\/\/www.databricks.com\/blog\/2021\/05\/10\/improving-customer-experience-with-transaction-enrichment.html","text":"Improving Customer Experience With Transaction Enrichment - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorImproving Customer Experience With Transaction Enrichmentby Milos ColicMay 10, 2021 in Engineering BlogShare this postThe retail banking landscape has dramatically changed over the past five years with the accessibility of open banking applications, mainstream adoption of Neobanks and the recent introduction of tech giants into the financial services industry. According to a recent Forbes article, millennials now represent 75% of the global workforce, and \"71% claim they'd \"rather go to the dentist than to take advice from their banks\". The competition has shifted from a 9 to 5 pm brick-and-mortar branch network to winning over digitally savvy consumers who are becoming more and more obsessed with the notions of simplicity, efficiency, and transparency. Newer generations are no longer interested to hear generic financial advice from a branch manager but want to be back in control of their finances with personalized insights, in real time, through the comfort of their mobile banking applications. To remain competitive, banks have to offer an engaging mobile banking experience that goes beyond traditional banking via personalized insights, recommendations, setting financial goals and reporting capabilities \u2013 all powered by advanced analytics like geospatial or natural language processing (NLP).These capabilities can be especially profound given the sheer amount of data banks have at their fingertips. According to 2020 research from the Nilson Report, roughly 1 billion card transactions occur every day around the world (100 million transactions in the US alone). That is 1 billion data points that can be exploited every day to benefit the end consumers, rewarding them for their loyalty (and for the use of their data) with more personalized insights. On the flip side, that is 1 billion data points that must be acquired, curated, processed, categorized and contextualized, requiring an analytic environment that supports both data and AI and facilitates collaboration between engineers, scientists and business analysts. SQL does not improve customer experience. AI does.In this new solution accelerator (publicly accessible notebooks are reported at the end of this blog), we demonstrate how the lakehouse architecture enables banks, open banking aggregators and payment processors to address the core challenge of retail banking: merchant classification. Through the use of notebooks and industry best practices, we empower our customers with the ability to enrich transactions with contextual information (brand, category) that can be leveraged for downstream use cases such as customer segmentation or fraud prevention.Understanding card transactionsThe dynamics of a card transaction are complex. Each action involves a point of sales terminal, a merchant, a payment processor gateway, an acquiring bank, a card processor network, an issuer bank and a consumer account. With many entities involved in the authorization and settlement of a card transaction, the contextual information carried forward from a merchant to a retail bank is complicated, sometimes misleading and oftentimes counter-intuitive for end consumers and requires the use of advanced analytics techniques to extract clear Brand and Merchant information. For starters, any merchant needs to agree on a merchant category code (MCC), a 4 digit number used to classify a business by the types of goods or services it provides (see list). MCC by itself is usually not good enough to understand the real nature of any business (e.g. large retailers selling different goods) as it is often too broad or too specific.Merchant Category Codes (Source: https:\/\/instabill.com\/merchant-category-code-mcc-basics\/)In addition to a complex taxonomy, the MCC is sometimes different from one point of sales terminal to another, even given the same merchant. Relying only on MCC code is not sufficient enough to drive a superior customer experience and must be combined with additional context, such as transaction narrative and merchant description to fully understand the brand, location, and nature of goods purchased. But here is the conundrum. The transaction narrative and merchant description is a free form text filled in by a merchant without common guidelines or industry standards, hence requiring a data science approach to this data inconsistency problem. In this solution accelerator, we demonstrate how text classification techniques such as fasttext can help organizations better understand the brand hidden in any transaction narrative given a reference data set of merchants. How close is the transaction description \"STARBUCKS LONDON 1233-242-43 2021\" to the company \"Starbucks\"?An important aspect to understand is how much data do we have at our disposal to learn text patterns from. When it comes to transactional data, it is very common to come across a large disparity in available data for different merchants. This is perfectly normal and it is driven by the shopping patterns of the customer base. For example, it is to be expected that we will have easier access to Amazon transactions than to corner shop transactions simply due to the frequency of transactions happening at these respective merchants. Naturally, transaction data will follow a power law distribution (as represented below) in which a large portion of the data comes from a few merchants.Our approach to fuzzy string matchingThe challenge of approaching this problem from fuzzy string matching is that simple, larger parts of the description and merchant strings do not match. Any string-type distance would be very high and, in effect, any similarity very low. What if we changed our angle? Is there a better way to model this problem? We believe that the problem outlined above would better be modeled by document (free text) classification rather than string similarity. In this solution accelerator, we demonstrate how fasttext helps us efficiently solve the description-to-merchant translation and unlock advanced analytics use cases.A popular approach in recent times is to represent text data as numerical vectors, making two prominent concepts appear: word2vec and doc2vec (see blog). Fasttext comes with its own built-in logic that converts this text into vector representations based on two approaches, cbow and skipgrams (see documentation), and depending on the nature of your data, one representation would perform better than the other. Our focus is not on dissecting the internals of the logic used for vectorization of text, but rather on the practical usage of the model to solve text classification problems when we are faced with thousands of classes (merchants) that text can be classified into.Generalizing approach to card transactionsTo maximize the benefits of the model, data sanitization and stratification are key! Machine learning (ML) simply scales and performs better with cleaner data. With that in mind, we will ensure our data is stratified with respect to merchants. We want to ensure we can provide a similar amount of data per merchant for the model to learn from. This will avoid the situation in which the model would bias towards certain merchants just because of the frequency at which shoppers are spending with them. For this purpose we are using the following line of code:\nresult = data.sampleBy(self.target_column, sample_rates)\nStratification is ensured by Spark sampleBy method, which requires a column over whose values stratification will occur, as well as a dictionary of strata label to sample size mappings. In our solution, we have ensured that any merchant with more than 100 rows of available labeled data is kept in the training corpus. We have also ensured that zero class (unrecognized merchant) is over-represented in the 10:1 ratio due to higher in-text perplexity in the space of transactions that our model cannot learn from. We are keeping zero class as a valid classification option to avoid inflation of false positives. Another equally valid approach is to calibrate each class with a threshold probability of the class at which we no longer trust the model-produced label and default to the \"Unknown Merchant\" label. This is a more involved process, therefore, we opted for a simpler approach. You should only introduced complexity in ML and AI if it brings obvious value.From the cleaning perspective, we want to ensure our model is not stifled by time spent learning from insignificant data. One such example is dates and amounts that may be included in the transaction narrative. We can't extract merchant-level information based on the date that transaction happened. If we add to this consideration that merchants do not follow the same standard of representation when it comes to dates, we immediately conclude that dates can safely be removed from the descriptions and that this action will help the model learn more efficiently. For this purpose, we have based our cleaning strategy on the information presented in the Kaggle blog. As a data cleaning reference, we present the full logical diagram of how we have cleaned and standardized our data. This being a logical pipeline the end-user of this solution can easily modify and\/or extend the behavior of any one of these steps and achieve a bespoke experience.After getting the data into the right representation, we have leveraged the power of MLflow, Hyperopt and Apache Spark\u2122 to train fasttext models with different parameters. MLflow enabled us to track many different model runs and compare them. Critical functionality of MLflow is its rich UI, which makes it possible to compare hundreds of different ML model runs across many parameters and metrics:For a reference on how to parameterize and optimize a fasttext model, please refer to the documentation. In our solution, we have used the train_unsupervised training method. Given the volumes of merchants we had at our disposal (1000+), we've realized that we cannot properly compare the models based on one metric value. Generating a confusion matrix with 1000+ classes might not bring desired simplicity of interpretation of performance. We have opted for an accuracy per percentile approach. We have compared our models based on performance on median accuracy, worst 25th percentile and worst 5th percentile. This gave us an understanding of how our model's performance is distributed across our merchant space.As a part of our solution we have implemented integration of fasttext model with MLflow and are able to load model via MLflow APIs and apply the best model at scale via prepackaged Spark udfs as in code below:\nlogged_model = f'runs:\/{run_id}\/model'\nloaded_model = mlflow.pyfunc.load_model(logged_model)\nloaded_model_udf = mlflow.pyfunc.spark_udf(\n   spark, model_uri=logged_model, result_type=\"string\"\n)\n\nspark_results = (\n   validation_data \n      .withColumn('predictions', loaded_model_udf(\"clean_description\"))\n)\nThis level of simplicity in applying a solution is critical. One can rescore historical transactional data with several lines of code once the model has been trained and calibrated. These few lines of code unlock customer data analytics like never before. Analysts can finally focus on delivering complex advanced data analytics use cases in both streaming or batch, such as customer lifetime value, pricing, customer segmentation, customer retention and many other analytics solutions.Performance, performance, performance!The reason behind all this effort is simple: obtain a system that can automate the task of transaction enrichment. And for a solution to be trusted in automated running mode, performance has to be on a high level per merchant. We have trained several hundred different configurations and compared these models with a focus on low performer merchants. Our 5th lowest percentile accuracy achieved was at around 93% accuracy; our median accuracy achieved was at 99%. These results give us the confidence to propose automated merchant categorization with minimal human supervision.These results are great, but a question comes to mind. Have we overfitted? Overfitting is only a problem when we expect a lot of generalization from our model, meaning when our training data is only representing a very small sample of reality and new arriving data wildly differs from the training data. In our case, we have very short documents with grammars of each merchant that are reasonably simple. On the other hand, fasttext generates ngrams and skipgrams, and in transaction descriptions, this approach can extract all useful knowledge. These two considerations combined indicate that even if we overfit these vectors, which are by nature excluding some tokens from knowledge representation, we will generalize nevertheless. Simply put, the model is robust enough against overfitting given the context of our application. It is worth mentioning that all the metrics produced for model evaluation are computed over a set of 400,000 transactions, and this dataset is disjoint from the training data.Is this useful if we don't have a labeled datasetThis is a difficult question to answer with yes or no. However, as a part of our experimentation, we have formulated a point of view. With our framework in place, the answer is yes. We have performed several ML model training campaigns with different amounts of labeled rows per merchant. We have leveraged MLflow, Hyperopt and Spark to both train different models with different parameters and train different models with different parameters over different data sizes and cross-reference them and compare them over a common set of metrics.This approach has enabled us to answer the question: What is the smallest number of labeled rows per merchant that I need to train the proposed model and score my historical transactional data? The answer is: as low as 50, yes, five-zero!With only 50 records per merchant, we have maintained 99% median accuracy and the 5th lowest percentile has decreased performance by only a few percentage points to 85%. On the other hand, the results obtained for 100 records per merchant dataset were 91% accuracy for the lowest 5th percentile. This only indicates that certain brands do have a more perplexed syntax of descriptions and might need a bit more data. The bottom line is that the system is operational at great median performance and reasonable performance in edge cases with as few as 50 rows per merchant. This makes the entry barrier to merchant classification very low.Transaction enrichment to drive superior engagementWhile retail banking is in the midst of transformation based on heightened consumer expectations around personalization and user experience, banks and financial institutions can learn a significant amount from other industries that have moved from wholesale to retail in their consumer engagement strategies. In the media industry, companies like Netflix, Amazon and Google have set the table for both new entrants and legacy players around having a frictionless, personalized experience across all channels at all times. The industry has fully moved from \"content is king\" to experiences that are specialized based on user preference and granular segment information. Building a personalized experience where a consumer gets value builds trust and ensures that you remain a platform of choice in a market where consumers have endless amounts of vendors and choices.Learning from the vanguards of the media industry, retail banking companies that focus on banking experience rather than transactional data would not only be able to attract the hearts and minds of a younger generation but would create a mobile banking experience people like and want to get back to. In this model centered on the individual customer, any new card transaction would generate additional data points that can be further exploited to benefit the end consumer, drive more personalization, more customer engagement, more transactions, etc. -- all while reducing churn and dissatisfaction.\nAlthough the merchant classification technique discussed here does not address the full picture of personalized finance, we believe that the technical capabilities outlined in this blog are paramount to achieving that goal. A simple UI providing customers with contextual information (like the one in the picture above) rather than a simple \"SQL dump\" on a mobile device would be the catalyst towards that transformation.In a future solution accelerator, we plan to take advantage of this capability to drive further personalization and actionable insights, such as customer segmentation, spending goals, and behavioral spending patterns (detecting life events), learning more from our end-consumers as they become more and more engaged and ensuring the value-added from these new insights benefit them.\nIn this accelerator, we demonstrated the need for retail banks to dramatically shift their approach to transaction data, from an OLTP pattern on a data warehouse to an OLAP approach on a data lake, and the need for a lakehouse architecture to apply ML at an industry scale. We have also addressed the very important considerations of the entry barrier to implementation of this solution concerning training data volumes. With our approach, the entry barrier has never been lower (50 transactions by a merchant).Try the below notebooks on Databricks to accelerate your digital banking strategy today and contact us to learn more about how we assist customers with similar use cases.\u00a0GET THE NOTEBOOKTry Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/the-best-data-warehouse-is-a-lakehouse","text":"The best data warehouse is a lakehouse | DatabricksOn DemandThe best data warehouse is a lakehouseTalks. Demos. Success stories. Q&A.Available on demandMany enterprises today are running a hybrid architecture \u2014 data warehouses for business analytics and data lakes for machine learning. But with the advent of the data lakehouse, you can now unify both on one platform.Join us to learn why the best data warehouse is a lakehouse. You\u2019ll see how Databricks SQL and Unity Catalog provide data warehousing capabilities, fine-grained governance and first-class support for SQL \u2014 delivering the best of data lakes and data warehouses.Hear from Databricks Chief Technologist Matei Zaharia and our team of experts on how to:Ingest, store and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIUse automated and real-time lineage to monitor end-to-end data flowReduce costs and get started in seconds with on-demand, elastic SQL serverless computeHelp every analyst and analytics engineer to ingest, transform and query using their favorite tools, like Fivetran, dbt, Tableau and Power BIThis presentation will come to life with demos, success stories and best practices learned from the field, while interactive Q&As will help you get all your questions answered from the experts.SpeakersMatei ZahariaCo-founder and Chief TechnologistDatabricksShant HovsepianPrincipal Software EngineerDatabricksMiranda LunaStaff Product ManagerDatabricksFranco PatanoLead Product SpecialistDatabricksTranscript\u2013 [Shant Hovsepian] Hello, everyone. Thank you so much for taking time out of your busy days to join us today. We're going to talk about the best data warehouse is a lakehouse. We'll be joined by Haley Creech, who's a product director for Enterprise Data and Analytics Platforms at GSK. Me, I'm Shant Hovsepian, software engineer at Databricks. We'll be joined by a few of my colleagues from Databricks, Miranda Luna, senior staff product manager, Franco Patano, lead product specialist, and Matei Zaharia, CTO and one of the co-founders of Databricks.So for the agenda today, we're going to do an introduction to the Lakehouse, Unity Catalog, and Databricks SQL. I have an amazing demo, show you how to get started, and tips and tricks. Talk a little bit about how GSK is leveraging Databricks SQL and the Lakehouse. And we'll talk through some of the lessons that we've learned from our users out there.A few housekeeping items. We will share the webinar recording after the event. Don't worry if you need to step away for something and come back. You'll have the recording handy later. You can use the Q&A box either down here or here to ask questions while I'm talking. We have a bunch of subject matter experts on standby, waiting to answer your questions. And at the end, we'll also take some time to answer any questions anyone may have.So let's get started by talking a little bit about how data and AI is disrupting entire industries. If you look at the companies here, tech companies, Amazon, Google, Apple, the FAANGS, as we call them, they're all using data and AI in strategic ways in how they run their businesses.Netflix, for example, started as a video rental mail order system, and went into streaming. They used data and AI to make recommendations of what other shows or movies people are interested in. They even took it one step further and they're a movie studio today, and they use the data and insights from which parts of films and shows their customers like to help produce better movies. So if it weren't for data and AI, Netflix probably wouldn't exist today. We'd all still be getting videos from Blockbuster.And it's not just the tech companies. There are traditional larger enterprises, like AT&T, that are leveraging data and AI. For example, AT&T got a lot of their customer data that used to live in a data warehouse, and put it together with real-time streaming events from transactions and phone subscribers to build over a hundred machine learning models that were used to help 182 million subscribers stay safe from fraud throughout the usage of the platform.So how is it that these companies are able to leverage data and AI? Well, we use what we call the data maturity curve here to kind of understand. This is if you look at the x-axis, it shows you a company's point in their data maturity. And the y-axis, the value, the competitive advantage they're getting from their data.Most companies start all the way down here from the left, where they just get some data into the system, they clean it, they build some basic reports, ad hoc queries. Then as you move further to the right, you get into more predictive modeling or prescriptive and automated decision-making systems within the platform. So the left side kind of asks questions about the past, and the right, you sort of use a crystal ball to try to predict the future.But most companies today are still stuck on the left of that curve. They struggle to really find success at scale. And they all want to go to the right. They all want to use predictions in AI to make their businesses more efficient.Their main reason for that is most people when they start from the left, easiest way to get started, traditional way is get a data warehouse, pull your data in it, put a BI tool on top, and ask them basic questions. However, when you need to do AI and machine learning, you need a data lake. You need to get your various different datasets. Some of them may be images, video, unstructured content. And put them on a platform that can scale and let you ask different types of questions around different types of processing on it. That always runs on a data lake. These are two separate systems, and there's a giant gap between them.Really, it manifests itself in a weird way. So for example, here, we have the data lake on the right-hand side, and this is where data typically lands first in just about every organization. Raw data, raw files come in a data lake, maybe some basic processing happens, and then they have to get summarized and copied over into the data warehouse. Once they're in the data warehouse, there are modeled and structured tables, governance rules, and your traditional tools are on top.These two systems, though, painful to manage, they're very separated, and it really just... It creates a disjointed, duplicative set of data silos. And what's worse is on top of the copies of the data, you end up having incompatible, different security models where data in the data lake might be encrypted, but once it goes into the data warehouse and someone's built a table out of it, you may not have kept that encryption in there. You may have changed the format. Someone may have access to it when they shouldn't have access to it. Vice versa. Always gets complicated when you have to maintain multiple different security models.And then of course, there are the use cases. You can't just get your high performance, high concurrency BI workloads and stick it on a data lake and expect it to perform just as well. You sort of need to change something. You need to do things differently. Just like how you can't do data streaming in a data warehouse because the data lake's where that data lands, and just even by the time you get it into the data warehouse, you've already lost a lot of that opportunity to get real-time insights.But does it have to be two disparate platforms? Let's say we've got the best of the data lake. We've got the open, reliable data storage that can efficiently handle data of various types. On top of it, layered a new way to do governance, an approach that works across all your data assets and all your clouds. And integrated engine is built for today to be able to do both machine learning and BI workloads efficiently and scale as needed.This is what we call the lakehouse paradigm. And at Databricks, we use Delta Lake as the core secret sauce technology as that first layer on the system, where you can bring reliability and consistency to what was once an unreliable set of files living in cloud storage. Then we have Unity Catalog, which is the central place to do all of your governance, whether they're tables, files, blobs, machine learning models. And Databricks SQL is that engine that's built for the modern processing needs, high performance, and scalability.So this is the Databricks Lakehouse Platform. When we talk to our customers and ask them why they like it so much, one of the first things they say is that it's simple. See, when there's only one platform they need to worry about, it's one set of technology and tools they need to train everyone on, one place to put all of your use cases, it really simplifies the whole system.And multicloud. About 80% of our customers use more than one cloud today. Having one consistent interface across the various clouds, not having to learn the idiosyncrasies of the various different cloud platforms is a tremendous benefit.The last is open. All of the technology here in the lakehouse and Databricks are built on open source and open standards. This is hugely valuable to a lot of our customers who traditionally when using data platforms that come from proprietary locked in systems controlled by single vendors.And when moving to the lakehouse, everyone's always a little apprehensive. Do I have to retool everything? Do I have to change everything? That's where the openness helps even more, because the entire lakehouse architecture is built on open standards. So all of the tools that you're used to for your data governance, your data pipelines, even data ingestion, the whole modern data stack actually already works in the lakehouse paradigm because it's so easy for these ecosystem partners to integrate using the open standards and open APIs. So you get all of the tools and functionality, even your traditional BI tools, machine learning, and user-facing data science platforms working on the system and free from integration hassles.So it's not just Databricks. The rest of the industry's really taken notice about the lakehouse. You can see the various other cloud vendors have talked about their new lakehouses. Google announced a lakehouse-like offering. AWS, even Oracle. And your traditional data warehouse companies are talking about lakehouse.But how do these lakehouse offerings really stand up? Well, we wanted to test that, and so we created what's called the lakehouse benchmark. This is essentially a modification of TPC-DS, traditional data warehouse and benchmark, but we ran it on data that's living in an open format Parquet. So this is data that exists in the cloud in an open format that all of these other vendors said they now support because they're a lakehouse.When you ran this workload across these different systems, you can see here Databricks SQL came in at just $8 to run the entire three terabyte workload. Some of the other vendors, well, those in some cases, up to 30 times more expensive to run on those systems.So while they say that they're a lakehouse and they support these open formats, were they really optimized? Do they expect their users to use it? It seems unclear if there's such a huge gap.And you might say, \"Well, it's not fair. These systems, while they claim to be lakehouses, weren't designed to be lakehouses from the start. So you're benchmarking them on something that they were never really built to do.\" That's true, so we also went one step further and got the traditional TPC-DS 10 terabyte benchmark. And this time, we ran it, but we didn't put it in an open format. We loaded the data directly to the proprietary data warehouse format that those vendors use and didn't keep it in an open storage format and open access. And even in that case, while the difference may not be 30X, you can see that Databricks came in at about $76, and this includes the time to load the data, do any optimizations, and run the queries. While some of the enterprise offerings or even the standard offering from other vendors still came in to over 3X the cost to run the same workload.What's more is even if the data is going into the proprietary database format, it probably is sitting in a data lake today. So the fact that you don't even have to load it with Databricks is a huge potential savings as well, where in these other systems, you're always going to have to be loading that data in.But let's talk a little bit beyond the benchmarks, right? Performance is really important in the cloud because it's usage-based, it's a consumption model. So the faster something runs, at the end of the day, you save money. So that performance and efficiency does deliver a lot of business impact.For example, there's a global media company we all know about. When they moved to the lakehouse, they were able to unify their subscriber data and their streaming data and build better machine learning models for personalization and recommendations. And what's even nice about this is they had a $30 million reduction in costs. And on top of that, almost $40 million in increased revenue from accelerated offerings, right? So this helped on both the bottom line of the business and top-line growth.Another Fortune 50 retailer, one of the largest in the world, was able to use their supply chain data with the streaming IoT sensors from within all of their stores to detect when food was being spoiled, when there was too much surplus, and optimize their whole supply chain end to end. This switch to the lakehouse and integrating the real-time data gave them 10X faster time to insight and saved around $100 million annually through reduced food waste.And one of my favorite examples is Atlassian. It's a product I use every day as a developer. They completely migrated all of their internal data systems over to lakehouse and stopped using data warehouses. For them, it was really about democratizing access to their entire enterprise and lowering the operational costs so that every single Atlassian employee can use the data to make informed and better decisions. This really reduced their analytics infrastructure costs by 60%, and led to a 30% better delivery time on their analysis.So at Databricks, our mission is to democratize data and AI, and our destination is the lakehouse.Now I want to introduce Matei Zaharia to talk about how to do fine-grained access control, as well as data sharing in the lakehouse. Thank you, everyone.\u2013 [Matei Zaharia] Thanks, Shant. I'm excited to talk about data governance and sharing on the lakehouse and what we're doing for those.First of all, let's start with governance. I think as anyone who's tried to work on this knows, governance for data and AI workloads today is very complex. It's mostly because you've got different kinds of systems that you have to manage. You've got data lakes, you might have a metadata system like Apache Hive, and you probably also have your data warehouse and different systems for machine learning. And then you have to figure out how to give all your users the right permissions in each system and how to audit all of it.The problem is that each system has different ways of managing governance. For example, on your data lake, you can set permissions on the level of files and directories, but it actually has some limitations. You can't set row and column level permissions, for instance.In contrast, once you start defining a table, in systems like Hive, you can set permissions on tables and views. But just turning that over a data lake doesn't guarantee that all the permissions of the underlying files match. So the permissions on the metadata can be out of sync with the data.And then when you put data in the data warehouse, that has its own permission model involving tables, columns, and rows and so on, which is great, but it's just different from what you have elsewhere in your data systems. And of course, for machine learning, all the different systems in the machine learning space have their own way of doing governance.So at Databricks, to make governance significantly simpler in the lakehouse, we've designed Unity Catalog, a single catalog and a single governance layer over all the data and AI assets in the lakehouse. The design is very simple. All the access to your storage system, whether it's data lake files, tables, machine learning models and so on, is policed by Unity Catalog. And there's a single permission model you can set up once that determines who has access to what.And to make it very easy to configure, the permissions are all set using SQL GRANT statements. So anyone who knows how to administer a data warehouse or just a SQL database can go and set permissions and actually administer the whole lakehouse, including files and machine learning.And everything is also centrally audited across these workloads. We've instrumented all of them so you can see who is doing what. And you also get fine-grained lineage across all of them to see what items are derived from other ones. That's a very powerful feature for understanding how your data is being used.So how do you use Unity Catalog? The simplest part of it is just setting up the access controls. You can just do that using SQL. So for example, you can set permissions on tables using a GRANT statement for select, but you can also set permissions on files, which is something unique with Unity Catalog. And you can also see all the activity that's happening in the system as a system table across all these things, and then see how people are using the data.Beyond that, you've got a powerful search interface where people can search across all the datasets in the whole company and can discover them and can set up comments and additional metadata about each one.And finally, you've got a very powerful lineage feature that tracks column level lineage feature through all the workloads that run on the Databricks Lakehouse Platform. So you can see, for example, for every table, what tables upstream it's derived from. But the lineage even extends to notebooks and dashboards. So you can see, for example, which dashboards are using this table, or which scheduled jobs, which data science notebooks, and so on.And because we are doing all this in the Databricks Runtime engine, we can understand the lineage at the level of individual fields. Not just datasets, but you can see which columns are derived from which ones, which is very useful for both managing just the data in your organization and also tracking any possible security problems if someone creates a derived dataset based on a sensitive column.So Unity Catalog is also designed to integrate with the best of breed products in many areas of data governance. This includes products to set advanced policies, like Immuta or Privacera, the best data ingestion products, BI and dashboarding tools, and tools for data pipelines. So you can use that with everything in the modern data stack together.And we're very excited to announce that just earlier this summer, Unity Catalog became GA. So now anyone with a Databricks account can try it out. And we've been seeing a lot of customers greatly simplify the way they manage their data with this.So Unity Catalog is one piece of the equation in making the lakehouse very easy to govern, but the other piece is collaborating across organizations or across just different groups in the same organization. For this purpose, we've also built some very powerful features for data sharing.Data sharing, if you haven't looked into it, it's often considered one of the most important aspects of a modern data platform. Many organizations are saying this is becoming increasingly important. For example, Gartner is saying that it may improve economic performance of organization by 3X, and they expect data ecosystems to grow significantly.Now, traditionally, it's been possible to do data sharing in some data warehouse platforms, but only within the context of a single platform. So for example, if you have lots of users on, say, BigQuery, these users can share data with each other, but only with other instances of BigQuery. And if someone else has lots of users on, say, Amazon Redshift, they can share data with each other across instances of Redshift, but not with other platforms.And for many organizations, this is very limiting because you do end up with different systems deployed in the organization or with partner organizations, and they aren't able to share data with each other. So this leads to vendor lock-in. And it also means that in practice, if you need to share a dataset broadly, you probably need to replicate it into many systems, many different cloud regions, and get it into all of them, which is just expensive to do.So at Databricks, we took a very different approach, sticking to the lakehouse philosophy of openness, and we designed an open protocol for data sharing that's called Delta Sharing, which means that it can work across computing platforms. You don't have to be sharing with someone on Databricks. Anyone who can run open source systems like Spark, Pandas, Power BI or just applications in Java can actually consume the data.The way it works is very straightforward. The data provider can simply set up tables to be shared using SQL commands, but then the data consumer can connect to them from many different platforms, not just from Databricks, and can actually read the data in there. And it's all based on the open source Delta lake file format. So basically, any tool that includes that library can start receiving data. So it enables cross-platform sharing, and you can just do it on your existing tables.Delta Sharing's rapidly being embraced throughout the industry. We're already seeing petabytes of data shared per day, even though the product only started preview less than a year ago.Just as an example, Nasdaq has been using it to streamline delivery of some very large datasets they have in the cloud that they just couldn't share through other means. It was just too expensive to replicate it into other platforms or share it through FDP or things like that.And Shell has also been using it to share datasets with other companies it collaborates with to streamline production and make it more efficient. Again, massive datasets that now any platform that can run Spark or one of these other tools can immediately access.Delta Sharing has also been evolving rapidly. There are a whole bunch of new connectors that launched this year. The support for tables that change over time and sharing a changed data feed where you can see just which rows changed. And also within Databricks, it's very easy to set up sharing with someone else on Databricks, say, just through a couple of clicks.So Delta Sharing is also a growing piece of the lakehouse. We're working on some powerful features that we're also incorporating in the open source project, including sharing views that can filter down the data, and also sharing streams so that a streaming client can consume the changes in real-time and react to data that's being shared.Delta Sharing is also GA as of this summer, so we invite you to check it out. And together with Delta Sharing and with Unity Catalog, you end up having very powerful control of governance, both within an organization and across organizations that collaborate.So that's it for the governance and sharing features. Now back to Shant to talk about some of the powerful warehousing and BI features in the lakehouse.\u2013 [Shant Hovsepian] Thanks, Matei. Hi, everyone. It's me, Shan't, again. I'm going to spend some time now talking to you about how we can do data warehousing and analytics on the Lakehouse.Of course, all of that's possible with Databricks SQL. It's our SQL warehouse offering on top of the lakehouse. You can think of it as the house in lakehouse. I'm going to spend some time talking about how you can connect your data stack up, how we combine the best of data lakes and data warehouses, and of course, how we obsess over bringing the most value possible through performance.So let's talk about connecting your data stack. When we set out to build Databricks SQL, we wanted a first-class SQL experience. So all of your existing data warehouse tools that are built around the whole SQL ecosystem can just work out of the box in the lakehouse. So whether it's ingestion from business critical applications, transformation of that data using standard transformation toolkits, or just consumption and querying of that in your business applications, we've got you covered with Databricks SQL.First, let's talk a little bit about data ingestion. Basically, the ability to work with your data no matter where it is. We've gone and done tons of work with Fivetran to make sure that their traditional data warehouse integration work just as well on the lakehouse, making it easy to ingest business critical data from Marketo, Salesforce, Google Analytics. Whatever your source may be, it works seamlessly out of the box.When it comes to data transformation, we've done similar integrations with dbt. Open source connector that you can use with Databricks and run all of your dbt pipelines, your transformations, and collaboratively explore and transform your dbt projects on the lakehouse.And then data consumption, of course. What good is the data that you just load into the system if you can't give it to your users to get insights and build new business value from it? So we've worked with a ton of the existing BI vendors out there to make sure that all of their connectors are lakehouse certified, so you can get the best out of the box experience possible.But of course, BI tools aren't just it. When it comes to business applications, sometimes you need to write code and integrate the data right where it's going to be consumed, which is why we're excited now to support our ability to run SQL from anywhere. Build custom data applications directly using a REST API to run SQL queries, or use one of our new open source connectors from your favorite programming language. Everything from Go, Node.js, and of course, Python, basic command line connectivity, and traditional Java JDBC stack are all available to connect to directly today.So how are we combining some of the best of data warehousing and data lakes together? Well, we've come out with Python user-defined functions. Databricks had always made Python a first-class citizen when it comes to your data science, AI, and engineering workloads. But now you have the power and flexibility of Python when you need it, calling it directly from your SQL. So it's available in the preview today. You can check out the link here, use it for your machine learning models, your data transformation pipelines, directly from your favorite SQL tools.Query federation. Now, the lakehouse is home to all your data sources, no matter where they are. And with query federation functionality, now you can directly connect to multiple different data sources no matter where they live. You can connect to remote databases without having to worry about ingesting and moving data. You can combine multiple data sources across these things, or even treat some data sources as a reference dataset or a dimension table while your full dataset is in the data lake. And all of this is seamless, and our query optimization engine automatically pushes down the parts of the query that are relevant to each of the different data sources.Materialized views, of course. Materialized views are essential for speeding up queries when you want to use pre-computed results. And while materialized views have been around data warehouses for a while, what's new and interesting is we've taken some of the best technology Databricks has for streaming workloads, and we've built our materialized views on top of that. So you don't have to worry about picking refresh intervals or measuring the trade-off between data latency and correctness. With our materialized views, you can choose. You can have your data in view to be always up to date as needed, or dial that back and simplify your ETL and data transformation pipelines.We've added new support for data modeling with constraints. This is very familiar in traditional data warehouse techniques. You can have your primary and foreign key constraints defined to understand and visualize the relationships between your tables, support IDENTITY columns, which automatically generate unique integer values for all the new rows added to your tables, and most importantly, enforced CHECK constraints so you never have to worry about data correctness or quality issues. As the data is loaded, we'll check those constraints and give an error if the system doesn't meet the criteria you've defined in your constraint. This is very unique-\u2013 [Shant Hovsepian] .... meet the criteria you've defined in your constraint. This is very unique and no other cloud data warehouse provides this functionality today.We recently added geospatial support, so now you can supercharge your geospatial processing. We're using a unique engine based on H3, so you have very efficient storage of your spatial data, whether it's large or small. You get high performance spatial joins. And by having a direct SQL interface now to the geospatial engine, you can combine your AI, your advanced GPU data visualization and your simple SQL analytics together in the same platform, without having to switch between tools anymore.We also added information schema support. So now, all of your metadata is simply a query away. And what's even more interesting, with Unity Catalog, you can have an information schema table that defines relationships between your catalogs, your schemas, your columns, even your unstructured data sources, like locations for files and cloud storage, as well as machine learning models.So, let's talk a little bit about some of the world-class performance features we've incorporated in Databricks SQL to make it a competitive and performing engine on the lake house.So, Photon is our next generation query execution engine, that we built from the ground up. You can see in this chart over here, with every release of the Databricks runtime, we're constantly getting better and better performance. But eventually, things start to flatten out. We sort of hit a plateau. And it was at that point that we knew we needed to do a whole new paradigm shift to get to the next level of performance. And that's Photon. Here it is. Huge performance improvement from the release of this technology.So, what is Photon? It's essentially an MPP Execution model, written in native code, leveraging vectorized CPU primitives. It's a lot of technical language for saying, it was built from scratch to be really fast. So far, it's processed exabytes of data, billions of queries, and it's not just about performance. Our customers are getting faster interactive workloads, they've seen their ETL jobs run at one fifth the cost, and they're seeing on average about a 30% savings in TCO. Sometimes as high as 80%, some of their workloads.And if you are interested in learning more about Photon, we published a paper recently at the SIGMOD conference. We're very humbled and fortunate enough to win the Best Industry Paper Award, and it really details all the inner workings and details of how Photon works. Feel free to check it out and get more information.And so, when we talk about performance and we talk about Photon and all of the things we've done in the system, we really wanted to go back to build things from the ground up, so we can have amazing performance on both the data warehousing workloads and a lot of the AI\/ML workloads that you would normally get on the data lake.And so over here on the left-hand side, we have the 100 terabyte TPC-DS price\/performance benchmark. So this was something where Databricks set the official data warehousing performance record. You can read more about it over here. This was a fully audited benchmark, where Databricks ran 100 terabytes, a large intensive, designed for data warehousing workloads, benchmark. And we essentially looked at the price\/performance. How much did it cost to run this benchmark? And with Databricks SQL, it was done at about one twelfth what some of the highest competitors were able to do. So a lot of work is done into making these stressful, difficult data warehouse workloads fast.But I also want to draw your attention to this chart over here on the right side, where here, it's a much smaller data set. It's 10 gigabytes, not 100 terabytes. So traditionally, you wouldn't think of data lakes as a platform that made sense for small data sets, but when it comes to data warehousing and BI, many cases, you have a mix of small data and large data sets, and we wanted to make sure our performance was awesome regardless of the data set size. So here, you can see that while we started out running this concurrent query benchmarks, we're running a bunch of queries concurrently, measuring how many of them can complete in an hour on a small data set. When we started, it wasn't too great, around 4,000 queries an hour. But since then, we've seen a 3x improvement. Now, not just meeting the other data warehouse competitors results, but exceeding them in many cases.And one of the ways that we've been able to get such great performance for concurrency is having an elastic infrastructure that can scale with query and workload demand. And that's possible with Databricks Serverless. So, Databricks SQL runs best with Serverless. It gives improved agility at a lower cost for our users. It's instant, elastic compute. You get fast query execution, you can scale nearly instantly. For the admins, it's zero management. You don't have to worry about pools and reserving instances and dealing with a lot of the cloud compute complexities that can happen when there are demand and supply issues. And overall, for IT budget, it means lower TCO. You don't have to over-provision anymore, and you can automatically shut everything down when things are idle.But of course, we had to spend a lot of time and effort making sure that we're optimizing away that idle time. Because when you have a serverless environment, if there's nothing running, no queries, no user interacting with it, we want to shut those machines down so you don't have to get charged for it. So we've done a lot of work then to make sure once they're shut down, the next query that comes in doesn't have to pay any warmup costs, to read data from cloud storage or to recompute certain results. So a lot of the concurrency benefits in the elasticity of scaling with Serverless were made possible because as soon as you need more resources, as soon as you get a lot of concurrency, we can spin them up and they can execute queries immediately.When we first started, that first query that you would bring in on a new instance would still take about 40 to 50 seconds because of warmup and caching effects. Today with Serverless SQL, now that first query can get up and running within 10 seconds of a new instance starting up. And pretty soon, we're working on a new persistent caching feature where you can have your new compute resources added to your warehouse immediately, within three seconds, to handle the new workloads.And so with that, I want to conclude that the best data warehouse is a lake house. I'm going to stop talking about why, and benchmark results and all of these things, and let Miranda show you exactly why we think the best data warehouse is a lake house. Thank you.\u2013 [Miranda] Hi, everybody. My name's Miranda and I'm a product manager on the Databricks SQL team. As you've heard today, the best way to warehouse is in fact a lake house, because it marries the speed of the data warehouse with the scale and flexibility of the data lake. So today, I'm going to walk you through DB SQL top to bottom. We'll start by creating a serverless SQL warehouse and then explore some of our data, it's lineage, it's governance. We'll then analyze that data and DB SQL's built-in SQL Editor and take a look at new features like query history, materialized views and Python UDFs. We'll wrap by switching over to our favorite BI tools and interacting with our lake house data live from those environments, all powered by serverless warehouses. We've got a lot of fun ahead of us, so let's get started.I'm going to start by creating a serverless warehouse. Serverless warehouses come online in seconds and are optimized for high concurrency BI workloads. That's exactly what we're doing today, so I'm going to create one. We'll go ahead and make a new one called Acme. And as soon as I get that confirmation, I'm going to go ahead and switch over to the data tab. Now, why don't we pick Acme from here? Let's see what's going on. As I... Oh, already started. Great. And as you'll see here, I have a number of different catalogs, each with different schemas and tables within. This is all governed by Unity Catalog in a central manner, and today we're going to show exactly how, by creating a new one ourselves. So I'm going to go ahead and start by creating a new catalog. Let's call it, oh, acme_avo, since we've got some avocado data. We'll go ahead and hit create.And you'll notice a couple things have happened here. First, default schema has been created, there's no data there. Why don't we go ahead and start by giving Shant and Matei permissions on this. Let's see, Shant. And I forget if I have a second user on here. Okay, great. Let's just give it all on this particular schema. You'll also notice that I have an information schema that contains a number of different views on all of the changes that have happened in my catalog. So for example, if I go to schema privileges, I'll be able to see those changes I just made to grant permission on the default schema to Matei and Shant. And while we're at it, why don't we just make sure that they have at least usage on the entire catalog? Just thinking ahead, I want to make sure that they've got everything they need and they're not going to need me to intervene anymore. So let's go ahead and give them usage.Great. Now again, if I go and look at my catalog privileges information schema view, I should be able to see that that would just execute it successfully. All the information I need to really audit changes and permissions and data are going to be captured right here. Now, it's not just easy to see the changes in permissions, it's actually easy to bring data into Databricks as well. So certainly, one option is I can always ingest from a partner. Another option would be to use a technology like Delta Live Tables. But today, let's do something simple. Let's create a table from a local CSV that I have here on my machine, that has avocado prices. I'm going to go ahead and select Acme and make sure we're in the default schema. Great.Excellent. And now you can see that the table UI gives me a few helpers. One, I can see the type, that's kind of auto-assigned to each of those columns. It's going to be coming in from the CSV. Everything looks good to me, so I'm going to go ahead and I'm going to hit create, and we will have a new table in our default schema. As soon as that's done creating, it drops me right back into that new table in the data explorer. Now I'm going to do a couple things, so we can take a look at lineage.Great, so this opens it in a new query and I can go ahead and hit run. What that's going to do is it's going to go ahead and just give me a preview of that table if I want to. I'm going to just save this and say, avocado test. I'm going to let that continue and then I'm going to pop back to the data explorer.And the other action I can take is I can create a quick dashboard. So I can pick a couple different fields of interest, and I'll go ahead and hit create there. By default, that's going to create a new dashboard for me that shows me a couple interesting stats about my data. But the reason I wanted to do all that is so I could show you a little bit more about the lineage of this exact table. So, one, if I come down to dashboards, you'll see downstream lineage, the quick dashboard, I can go ahead and open it directly from in here. That's the same dashboard we were just on. The other thing that I can do is I can come and click on this table insights button, to understand a little bit more about who the frequent users are. No surprise, there I am, we just created this table. As well as some of the frequent queries, and I can open any one of those in the SQL editor with just a click of a button.Now that we've got a good handle on the compute, data and governance side of the lake house, why don't we actually spend a little time here in this SQL Editor and learn a bit more about what we can do in terms of analyzing our data? If I want to use a third party SQL workbench, I can do that via ODBC, JDBC connection. But today, let's take a closer look at the experience right within Databricks, side by side with your data. One thing that I really like about the editor here is that it's super trivial for me to just pick a few columns of interest and go ahead and expand those. If I want to format the query, I can do that with a click of a button. Also, definitely realize that not everybody loves buttons, so we have a number of different keyboard shortcuts available. Super easy to review the entire list of them.And then I can go ahead, and just like most other SQL editors, I can go ahead and add a visualization if I'm interested in that. And when I have a few columns, we actually suggest one out of the box for you. I can toggle through a few different views, if I'm interested in that.Now, all these executions that we've been running today, I can review in past execution. So anything that's in the current query or in all queries across all the work I've been doing, which is a really nice way to go ahead and take a look at anything. If I did something silly like put a number of extra commas first, it's going to kind of give me a little bit of a warning there. But then if I try to run it, I'm going to get that sort of syntax error highlighting that I'm used to. I'm going to see that this is the issue, row two is the row with the syntax error. And I can even see it's this first duplicate comma that's the issue. So I go ahead, and if I didn't want to just modify this, I could actually go ahead and click here and open up a past execution. If I wanted to resume editing this, I would go back to my original one. But it's pretty trivial to go back in time and see what were the versions that were working.Now, I'm going to go ahead and open up another query that I have, and this one is going to be for national revenue trends. So let's go ahead and pull that up. This is on TPC-DH data. And let's go ahead and add another country, just so we know that this is not going to be coming from cache or anything like that. I'm going to go ahead and remove the limit 1000 I had when I was working earlier, and let's just run that. Now, you'll notice as this starts to execute, I can pull up a little bit more information about what's actually happening with my query. And then as it completes, I'm going to actually be able to access a lot more of a detailed breakdown.Now, I pulled this up while the query was executing, but as it completes, I can always get it back that way. And I can go ahead and I can pull up the query profile, and very quickly, I can see where time is being spent, whether I prefer the graph view, the tree view. And I can kind of understand exactly what the different elements of my query performance are. Obviously, this is a pretty quick query, we're not too concerned with what we see here. But if I did have a longer running one or somebody else in my organization was running into some trouble, I could zoom in and kind of really understand exactly what was going on, and help them correct any sort of inefficiency that they might have in their query.Now, this is kind of the profile for one single query, but certainly as an administrator, it's helpful to have an understanding of what's going on across your entire workspace. So we also offer this query history area, where at a glance, I can see everything that's happening. And I'm an admin on this workspace, but I can see everything that's happening across all the different warehouses. Or I could drill down into just one. I can look at myself or all users. I've been the most active recently, so I would expect to... Yep, there I am. See myself.But really helpfully, the other thing that we can do is also filter by status. So if I want to see all the queries that failed, I can really easily drill down to those. You can imagine too, that if I wanted to understand any sort of queue or queries that haven't finished running, I could go ahead and pull up all the queries that are running and sort by the duration that they've been out and open. That's going to help me, as an administrator, really identify anywhere where I might want to engage a particular user and make sure that they're not blocked.Now let's go back to the SQL Editor, because we're going to dig into a couple new really exciting features, Python UDFs and materialized views. So let's get started. Starting with Python UDFs, I'm going to pull up a quick example that I've already created and let's walk through that together. Now, UDFs, or user-defined functions, are ways to kind of extend Vanilla Spark with custom business logic. And to date, we've supported SQL UDFs, right? So I'm going to run through a quick example of that, and then we'll get to the fun stuff in Python. But the idea here is again, in the lake house, we want you to be able to use whatever makes the most sense for your use case. Whether that is super simple, to express logic in SQL, being able to reuse that, whether that's something a little bit more complex that requires Python or that might already exist, it would just be great to use instead of kind of rewriting in a SQL format. We want to give you the tools that you need to do whatever you need to do.So let's go ahead and start by just taking a look at this table. We're going to start with a SQL UDF example. So you can see here, I just have a country, email and name fields. This SQL UDF, let's kind of do a simple example first, let's just do a little bit of masking. Let's insert some ellipses. And you could imagine, this might be a source table in the bronze layer that I have access to as a data admin, but I want to do a little bit of transformation at the silver layer before I expose that to the broader organization. I certainly want analysts in my organization to be able to understand, you know, unique number of users by email across each country, but they probably don't need the specific email themselves in order to do that.So the first thing I'm going to do is I'm going to go ahead and run this, create this function. So all this is going to do is kind of take a look at where the @ from the email is, and then insert some ellipses on either side. This is going to be SQL UDF, so you can see that our language here is SQL. And let's just take a look and... Oh, let's make sure that it's doing exactly what we expect it to. So I'm going to just take a look at the country, and then I'm going to mask the email field from emails demo. You can envision this being a super easy function to call anytime you have any sort of data in the bronze layer where you want to apply some simple masking.So we can see here, yep, I've been able to kind of mask, it'd be pretty good to get an idea of distinct users per country with this sort of masking. Again, it's not going to be as unique as an ID field, but it's helpful to at least be able to do an eyeball check. Now, this is where the fun kind of starts. This is where the new and exciting pieces come in. So here, what we're going to do is we're actually going to create a Python UDF. And all we're going to do is, if you remember that name field, we're going to go ahead and just say hi. Right? Very, very simple. Certainly know that much more common use cases are redacting PII from Nested JSON fields or calling forecasts.But today, again, we want to kind of look at everything very, very simple here in the SQL editors. So let's go ahead and do that. We're unselected. We've now created that in the email catalog default schema, and here's where I'm going to bring it all together. So you remember that mask email SQL UDF, greet Python UDF. And we're going to go ahead and we're going to call both of those UDFs in the exact same SQL query. So we're going to stick to the country, then we're going to mask the email, then we're going to add a little greeting in front of the name. So let's go ahead and run that.And just like that, we are able to get country, a masked email address again via SQL UDF, and then add a little greeting to the name field via a Python UDF. That's the power of the lake house coming together. Now, let's talk about materialized views. Another really critical feature in a data warehouse.To take a look at materialized views, let's switch over into another environment where I've loaded up an example. Materialized views reduce costs, and improve query latency by pre-computing slow queries and frequently used computations. They also enable easy to use transformations by cleaning, enriching and [inaudible 00:51:12] normalization of base tables. Overall, MVs reduce costs while providing a simplified end user experience, because they're incrementally computing changes from the base tables.And today, we're going to look at a very simple example. So first, if you recall, even though we're in a new environment, same data we're used to. So the acme_avo catalog, the default schema and the avocado table, we're going to go ahead and run that. Great. And we'll see here, that was a confirmation that was successfully executed. And we're going to do a quick check, but all I'm doing here is essentially picking a subset of my columns from that original avocado table. We're going to do the quick validation that we are actually kind of just seeing the date, total bags and region. And then what we're going to do is we're going to take this as our base table for the materialized view, and we're just going to set the table properties to kind of enable the data feed that we need. We're going to run that.Perfect, successfully executed. And now, this is where we're actually going to create the materialized view. So you see here, I'm going to create a replace that materialized view. We're going to call it avocado_mv. We're leaving avocado_mv base as a separate table, that's what we're going to build off of. And we're just going to go ahead and group by regions. We're going to end up with bags sold by region. And let's just double check. We'll first create the materialized view, then we'll double check, spot check one of our regions.Awesome, so we got the confirmation, but let's just take a look and see, for example, what the value is for Boston, all right? Boston's a big Celtics town, we're looking at avocados, avocados are green. Celtics going far in the playoffs this year, I'm sure. So let's see what comes back for that particular region. Awesome. So it looks like we are at about 21.49 million avocados, love to see it. Now, again, if you remember our data, it was over a few years. And what we're going to do now is, we have a materialized view that is computing the total bag sold per region. We took a look at what it was for Boston, but now we're going to actually show the power of the materialized view itself, and whether it's incrementally updating based on just the inserted new values.So here, all I'm going to do is insert one more row of data. What we're going to do is we're going to... And this is, again, into the base table. We're going to insert one more row, we're going to say that there was a crazy sale in September of 2022, there were an extra 5 million bags sold. So we should see this go up by about 5 million. So let's go ahead and first insert this. And then the next thing we're going to do is refresh the view. Now that view's only going to compute on this one inserted value. Cool. One inserted row, one affected row, fantastic.And now if we refresh this materialized view and we take a look at that same, look at that materialized view where the region is Boston, we should see that number go up by 5 million. Excellent. So we've refreshed our view. And now, let's take a look. Moment of truth. Do we have 5 million more bags in Boston? Yes, we do. We were at 21.495 and now we're at 26.495. Just like that, our materialized view automatically refreshed and took into account that additional row of data inserted into the base table. And we were able to quickly see how I can recompute.Now, we've done a lot of analysis and exploration of our data in the lake house, right from within the Databricks SQL UI. But of course, we know that it's just as important to work within our favorite third party BI tools. And we also understand that's where a lot of analysts are spending most of their day. So, why don't we go ahead and switch over to Tableau?Now that I'm over here in Tableau and I've established a connection using my personal access token and some details on that serverless warehouse. You can see here that I'm able to view data from that exact same lake house data we've been interacting with to date. So I can take a look at the acme_avo catalog, the default database, and if I want to take a look at what tables are going to come back, I can go ahead and drag avocado over here, one we're super familiar with. And immediately, I'll be able to take a look and confirm the fields are what I expect, as well as get a quick preview of some of the data. You'll notice that this is a live connection, but of course, extract is also always an option.You know, what I'm now going to be able to do is go ahead and let's just ask and answer a question of our data, like we would in Tableau any day. I might want to know the total number of bags sold each year, broken out by region. So with a few clicks and drags, I can do that. And I can see, of course, US total is going to be very large, but I'm also seeing quite a bit of sales in California, Great Lakes, Mid-South. If I wanted to understand if that held true just kind of overall, it's really trivial to remove that kind of date metric from the columns field. And you can see here that yes, California, Great Lakes, Los Angeles, Mid-South - Mid-South, more of a region - all stay very popular in terms of total number of bags sold overall. And also if I bring back, broken out by different year.Well, thank you all for joining me today. I really appreciate you giving me the opportunity to show you a little bit of what's new in Databricks SQL, and why the best data warehouse is in fact a lake house. Now, I'm going to actually hand the reins over to one of our customers so that we can hear a real life story. This is going to be how GSK uses Databricks SQL and Unity Catalog to scale data analysis through a harmonized mesh ecosystem. Take it away.\u2013 [Haley] Thanks so much. I'm so happy to be with all of you here today. At GSK, we treat and prevent disease with our vaccines, specialty medicines and general medicines. We focus on the science of the immune system, human genetics and advanced technologies in four core therapeutic areas, to have major impact of health at scale. We're ambitious for our patients, we're accountable for impact, and we do the right thing, because 2.5 billion people around the world count on us to get it right.So it's important to note that the advanced analytics journey at GSK did not start with the enterprise data and analytics platform. There are some amazing data experts all around the company. We have folks in vaccines developing end-to-end in the vaccine space, machine learning algorithms. In commercial, they're developing insights for the commercial line of business. In the supply chain, they're optimizing the manufacturing chains and the supply chains to decrease cost.And each one of these groups, if you dive into these, they're even more siloed. Which, it's great that they're creating insights, but as I mentioned, they're silos. There's opportunity for data redundancy. And most importantly, from my perspective, there's this amazing story to tell about a treatment going from the research and development phase, through the supply chain, actually getting manufactured, all the way to commercial and being sold to customers. And with these different groups operating in silos, that story gets lost.Additionally, there are inconsistent governance patterns. Chargeback is different between groups. They may not be using the right tools for the problem. And all of this together inspired the enterprise data and analytics platform at GSK, which is called Code Orange. We have a fit for purpose ingestion tool catalog. We have an enterprise data lake that is a harmonized mesh architecture, which we'll be getting into shortly, that has a complex and audit-ready security model. We have core and common data tools that are easy for different customers to use for things like data modeling, data cataloging, and data preparation. And we also have analytics suites for advanced and traditional data and analytics, with things like, in the future, data science workbenches and analytics workbenches as well.So how did we do this? We built Code Orange, as I mentioned, the brand name for our data platform, on a harmonized mesh ecosystem, where we see the respective business units, before, as different nodes.\u2013 [Haley] ... see the respective business units before, as different nodes. I really scaled down this image so I wasn't overloading you with each component on the node, but it is much more robust than this and I'm totally willing to discuss this with you guys after the session if you have some more questions. So, you guys can see we leverage Databricks on the mesh core, which is where our common services are, and then on each node as well, as well as our ADLS Gen Two storage, which provides a lake on each business unit's node or business function's node. Note that we have connections both networking and virtualization between each of the nodes to enable that data sharing, which I'm going to get into that a bit more as we get to the end of this session. During this talk though, because of the scope of this session, I really want to focus on how we're leveraging Databricks SQL.Additionally, it's important to note that we're also using Databricks as a key component in our Fit for Purpose Ingestion catalog, and as part of our data analytics workbench in all of those tools. Focusing on Databricks SQL, I really want to focus on three key problems that it solved for us as we released it to the supply chain business unit last quarter. The first one is the ease of use. I know this may seem silly to some of you, especially in startups or smaller organizations, but in a 90,000-person company, it is so difficult to download software. Some people don't have the right permissions to download any query-type tools that they need from the internet, and they have to go through a complex governance process just to be able to hit download. But, since this is browser-based, it really increases time to insight by making it accessible to anyone who already has the right access.Additionally, our super users who are using Databricks as part of that Fit for Purpose catalog or is part of our analytics suite, have everything they need in one place so they can easily go back and forth between their Python notebooks and then query whatever they just transformed and make sure it looks accurate using these query capabilities, which is really easy to use for those power users. Next, I want to talk about cost. This is not Databricks. The screenshot is actually a cloud help, which is how we do fin-ops at GSK. We have saved a lot of money by using Databricks. In the first iteration of the platform. One of our major spend was actually on traditional data warehouses because as you guys know, they're always running, always incurring cost. And one thing that Databricks SQL did for my customers is it put financial power into their hands as a user of the platform. They're able to optimize when the queries run. They can make it so it's basically an on-demand system that they can actually control rather than something that's just always incurring cost.And finally, connectivity. I know this is going to be mentioned a lot earlier today and a lot more, but there are many, many, many different ways to connect to downstream analytics tools. Just by going to Power BI, for instance, you can click a couple buttons and you can figure out 20 different ways to connect from ADLS to a visualization tool. But, whenever you get into complex security models, some of these ways just don't work, and in a big organization, this leads to lots of support tickets, customer complaints, and similar problems. Databricks provides that easy connection to the downstream applications for traditional reporting insights and most importantly to me as someone who ends up writing a lot of documentation for the customers, it's self-documenting. People can read and understand how to do it without any jumping through hoops.What we used to do before this was an option, we used personal access tokens from the data science and engineering workspace, and we have some pretty complex documentation in place to allow them to connect to Power BI using personal access tokens, and so this is a game changer as was demoed in a supply chain demo at the end of Q2 last year. My customers are demoing this to their customers because it's so powerful. I want to take a second to look at the future. As we all heard, Unity Catalog is GA, which is so exciting to me, and let me tell you why. Looking at the architecture diagram from before, we see that each of these nodes are connected. Well, also notice that we have workspaces in each environment as well. Each of these different business functions have an analytics and ETL workspace per environment. But what happens whenever you're trying to access data in each one?Today we have two options. One, the customer, so the person in the business has to open up, let's say the supply chain's workspace, but then also the enterprise's workspace and actually not see their data in a unified view. We also have another approach where we use service principles, but what that does is it triggers a secondary governance process. So, whenever someone has already been granted access to the data because this isn't user-based, it's still another process of them having to go through and jump through hoops to get access to that data. What Unity Catalog is going to do for us is it will allow in a single workspace, the customers to have access to all of the data they have access to, and it will actually allow that sharing experience to greatly improve across the company.Whenever I started talking to you all today, I mentioned the story of the treatment all throughout the process and how it touches every single business function to get that global view of what it means to bring a treatment to market, and with Unity Catalog, I think that we're really going to be able to accomplish this. Thank you all for the time. Next up, I would like to introduce Franco who's going to be going through some best practices with you all.\u2013 [Franco Patano] Thanks, Haley. It's always great hearing from our customers. Hey, everyone, my name is Franco Patano and I am a Product Specialist at Databricks. I focus on Databricks SQL and I'm here to give you some tips from the field. First off, let's talk about cloud data warehouses. We often see in the field how organizations are using cloud data warehouses, and unfortunately, they're trying to use it as a modern data platform, but they're kind of stuck in this situation where they're realizing it's not a modern data platform and they're trying to look for an alternate solution. Often what we find is they're doing ELT on a cloud data warehouse because we used to do that on-prem. You had the choice, but there were these tools, ETL tools like Informatica, Talend, and Ab Initio where you would build your ETL outside of the warehouse because the warehouse was considered premium compute.You didn't want to waste your premium compute on ETL tasks, but you could still do it because you bought the servers, you bought the software, you already licensed it, and you owned the network and you had your data center. Why couldn't you just do it? You were able to, so some people did, and what we find is that on-prem, this was fine, but when you lift and shift that into the cloud, all of a sudden costs get out of control because in the cloud you're metered on everything. Those workloads while inefficient, but they did what they were supposed to do on-prem, they end up costing a lot of money in the cloud because they're built up of really complex multi-stage processes to get that data to be able to fit into a table, from a file into a table. And most data warehouses, by the way, they might have things called streams, they don't have real streaming because they measure streaming in minutes. Real streaming is measured in seconds and that's a big difference.And then also you can't really load crucial data for data science into a data warehouse. Things like images or video or audio, they don't fit. Often they might have some support for semi-structured data with things called a variant type where you could just shove anything in there. Often this is not very efficient and it's very complex because it involves you making numerous copies of the data before you can actually do something with it. We often find that these things are not optimized for data engineering, but the one thing that they're great at is doing BI and reporting through typical tools like Power BI, Tableau, Looker, DBT, and they have a really good system there. But the thing that it isn't good for was data science. And normally what we find with organizations that try to do this is they have to copy data back out of the warehouse, back onto a data lake in order to use these ML or data science tools, and that is very expensive to do. And often these tooling that they're all disparate and disconnected from the main data stack, and this is fraught with friction.Often customers come to us and they're like, \"Can't we just have one system to do everything from BI to AI? And that's what we think Databricks is, and I'm going to tell you, you could do modern data warehousing on Databricks and then you can enable all the other use cases for data science and machine learning. There is a real stream processing engine and Databricks called Spark Structured Streaming that can read directly from these event buses and process streams at the speed of thought. We also have a large amount of partners that have real-time CDC tools that connect to on-prem systems or cloud systems to transport or ETL that data out onto your data lake. And essentially, the foundation of the Lakehouse is Delta Lake because Delta is really just an open protocol. It's an open-source protocol to deal with your tables on a data lake, and we'll talk a little bit more about the benefits of that. But essentially, Delta is what enables you to have a table on a data lake, and that's how you can do modern data warehousing on Lakehouse.And then once you have one construct that can be read as a table or files, you can service your BI or analytics needs with Databricks SQL with those tables or your data science and machine learning can be leveraged using the files because it's all the same construct on your data lake in the open source format, Delta Lake. Now, often people come to us and they're like, \"Well, how do you actually process the data?\" Data warehousing, they had this concept of raw staging presentation layer, and really it's the same concept in Delta or Lakehouse. It's bronze, silver, and gold. These are very similar terms. Essentially, bronze or raw is where you land your data that you got from the source and you want this for lineage purposes, and often this could be considered right optimized, just get the data and land it there. If you're getting data from a vendor, this is where it lands on a cloud Object Store. If you're getting data from streams, this is where you would land it from your streaming source onto Object Store.And then just like what was made popular with Bill Inman and data warehousing, you want an integration layer, you want a layer that all of your data can be integrated together, but the data needs to be cleaned up and there needs to be data enrichment, you need to take care of bad dates or nulls or maybe common business logic. And you organize this data by key domains, and this is the silver, the staging layer. You can employ normal forms here. We'll talk about data modeling a little bit, but this could also be considered like an ODS or an operational data store. And then you need to actually deliver solutions to your business and this is where you're going to lead the gold layer of the presentation layer, and this is where solutions are built, and here you can build your data models. We recommend Star Schema, but this is your read-optimized layer. This is where your BI tools and your analytics are going to connect to in order to get that data to serve it up to your users.And you can build all types of things here like sandboxes or data meshes and even feature stores or data science areas. So, let's talk about dimensional modeling. People often ask, \"Can you do dimensional modeling on Lakehouse?\" Absolutely. Delta Lake as a table format on a data lake. Essentially you can do all those same things, but we often get asked, \"What do you recommend?\" Typically, all of the common benchmarks that exist today are something of a Star Schema like the data warehousing benchmarks. That's what we know works really, really well because it's what we benchmark. That doesn't mean that other modeling techniques don't work or they're not performant. This is the one that we know it is. And some best practices are don't over normalize. Use conform dimensions. Definitely use surrogate keys for your joins and your optimizations. You can do solely changing dimensions for time tracking. Delta Live Tables has a great API called Apply Changes Into which makes this really simple, and then you can use materialized views to scale out your analytics MBI so that you have great performance at runtime.What are some common things or some steps to success for dimensional modeling on Databricks or Lakehouse? Essentially, you should leverage Delta Live Tables if you don't have another choice for ETL on Databricks and Databricks SQL together. Essentially you get efficient ETL and ELT with query serving. We'll talk a little bit about how we benchmark this in a couple slides, but essentially you have three things to remember, Optimize, Z-order, and Analyze. Delta Live Tables currently handles optimizing Z-order for you. It scheduled jobs for it so that the tables are kept in sync. And then Analyze collects statistics for the cost-based optimizer to pick the right plan and to do other optimizations during runtime. We're trying to make these tools as simple as possible for our users, but those are just some things you can do just to stay ahead of the game.Sometimes people ask, \"What about me that data mesh architecture, can you do data mesh on Lakehouse?\" Absolutely. What we find is that data mesh is more of a practice and less of a technology or a tool set, and you can essentially use the bronze layer to put your source systems where you get your sources from. In your integration layer, your silver layer, you can build your product domains. And then in your gold layer you can build all of your derived data products, and this is where you can enable your self-service layer so that you could have all of your data workers leveraging your derived data products so that they can provide value to your business.And then let's talk about a Lakehouse mesh governance model. If you have a self-service layer, you need a way in order to govern that, and like we learned about Unity, this is how we can enable that on the Lakehouse. When you have enterprise data sources where maybe only a few people have modify access, but everyone can have read, you can enable access controls in order to do that. Or if you want to give business units or departments the ability to manage their own data, you can set different permissions on that database itself. And then if you want to enable users to bring their own data sets to enrich the data even further, you can apply different access controls to that layer as well, and this keeps everyone in their well gardens in order to manage proper data governance on the Lakehouse.Next, people often ask, \"How can I get good workload management out of Databricks SQL? How do I know I'm getting the best cost optimizations over the day? Databricks SQL warehouses on the backend just kind of manages for you, and I'll just explain how that works. Essentially, the first thing you have to decide is a size. If you don't know, I often recommend medium and it works out great. This is the first level with most cloud instances where you get a full network bandwidth and you really want that in order to have fast performance. And then what you want to do is set your scaling. You can set scale min one, 10 max. Don't get concerned with looking at the price tag on 10.Basically, as you see here over the course of the business day, as users are coming in the morning, Databricks SQL warehouse is scaling up to handle all of those users' demands, and then as they leave for lunch, it scales down to make sure you're not paying for idle compute, and then when those users come back in the afternoon, it slowly scales up to make sure it's handling their demand appropriately. Behind the scenes, Databricks SQL is looking out for your costs to make sure you're getting the best price-performance in the cloud. And that's not all because I'm here to tell you the best warehouse is a Lakehouse and we run a ton of benchmarks to prove it. But I want to talk to you today about two. You've probably already heard of TPCDS.We made a big splash in the news about this last year, but to me, that's only one half of the story because TPCDS is the industry-standard benchmark for data warehouses, for query serving. How fast can you do these 99 queries and report on the price performance of that? But how does the data get into a warehouse? It has to be ETL or ETL teed. And that's a completely other half of the equation. So, there's another industry-standard benchmark for warehouses for ETL, which is called TPCDI or data integration. And while this benchmark is very old, and we haven't submitted an official submission yet because the price performance metric accounts for buying hardware and software and the depreciation over three years, we just don't do that stuff in the cloud anymore. But, generally, every data researcher agrees on two things, what matters most in benchmarking, your throughput, and your price performance.We're here to tell you that we ran those benchmarks too, and what we found is that with Lakehouse on Delta Lake and Delta Live Tables, we can process 23 million rows per second. That's amazing performance. Not only that, but we are able to process a billion rows for less than a dollar. That's just unheard of in the cloud today. And this is the value that we're trying to provide to you, a great data platform that does everything like data warehousing, ETL, and query serving, and everything machine learning and AI, and you can get great price performance on all of that. And you can see here that our weekly active users is growing very, very fast because our users and their administrators and the people that pay the bill all agree that Lakehouse is the best warehouse.You might be thinking, this sounds great, but why do people typically choose Lakehouse? Essentially, it breaks down to the economics of Lakehouse architecture because you don't have to make multiple copies of the data. It's one copy in Delta Lake. There's no need to have those copies, and so your costs for data storage go down, and this is great. Most people agree we don't want redundant copies of our data sitting around for data security reasons and cost reasons. And then because you have a single platform for all of your data and AI needs, you can reduce some of your redundancy in the cloud. Because with migrations, we often find customers have on-prem tools and cloud tools, and there are a whole lot of overlap between these things. And then since all of your data is in one place and all of your tooling is on one platform, it simplifies your path to production and it has never been clearer than with the lakehouse.And we generally take a technical approach to migrations where we do an architecture infrastructure assessment. Definitely reach out to our Databricks, we have a field team that is excellent at this. And then we help you plan your migration, moving your data from wherever it sits to Delta Lake. And then we migrate your pipelines. If you want to use DLT or if you want to use one of our partners like Fivetran, Rivery, or any others, and then we migrate your pipelines. And then once we've migrated the data on the pipelines, we can point all of your analytics and BI tools to the new Lakehouse in the cloud, and now you're free to explore all those new use cases with data science and machine learning on Lakehouse. If you need help accelerating your migration, whether you need tools like Arcion, Fivetran, or Click, or you need system integrators to help you accelerate your migration, there's partners like Accenture, Deloitte, and Cognizant ready to help you out across all three clouds, and we even have Databricks' migration specialists to help you package up different solutions that you need.When you meet with Databricks, we can help you with our solutions accelerators, which are pre-packaged solutions that you can copy and deploy in your organization. We also have professional services and personalized workshops to help you accelerate your success. And let's take a look at Databricks Academy. This is a great resource for all of your data workers across your organization to be able to get the training they need to be effective in their role. We have an array of academy plan learning plans to help all of the different types of workers that you have working with your data in your organization from a Lakehouse fundamental learning plan to data analysis or even an advanced SQL for Databricks SQL. There's all different types of learning plans for everyone to learn how to deliver value to their business.And there's even different types of courses. There's free self-paced courses. We have workshops and instructor-led, even certifications if you want to get certified. And here's a look at some of our tracks we have for the data analyst, the data engineer, machine learning practitioner, or the Apache Spark developer, platform administrator, and the architect. Thank you for joining us today. Have a great day.\u2013 [Jillian] All right, Franco, fantastic. Thank you very much to all of our presenters and all of our speakers and attendees for joining us today. It was an awesome session. We had so many questions coming through, so it's now time to kick off our live Q and A with all of our presenters. My name is Jillian [inaudible 01:23:39]. I am going to be your moderator for today. First off, we had lots of questions about how to qualify for the voucher. Just to recap, you will need to answer the feedback survey and take the fundamental course, which is about two hours. The links are in the resources section of this webinar platform. We will also send them to you via email after this webinar, and you will get links to the presentation, the recording as well, of course. We hope you enjoyed it so far. Let's just start with a few questions, starting with some intro basic questions about that. Just to recap, what can Databricks provide that others cannot?\u2013 [Franco Patano] Is it open to anyone to take that?\u2013 [Jillian] Go ahead, Franco.\u2013 [Franco Patano] Hello, everyone. That's a great question. Most customers, they have a lot of choice in the cloud today, and you have cloud providers providing the solutions that are built for their cloud, and you have some vendors that are providing solutions that are built among the clouds. And typically, when I think of this type of question, it's about the confusion of choice. You have all of these different choices that are thrown at you as a consumer of these cloud products, and most of the time, you just need to get your work done. You need to build something, you need to build a platform, and you need to enable all of your users. What I think is something that Databricks provides that no one else does is essentially a unified analytics platform. Where can I build one solution that can service all of my users in my organization? And that's what I think Databricks provides that no one else does.\u2013 [Jillian] Absolutely. We're a unified platform. Does that mean we provide all components required for batch processing, training, data warehousing, all that data science, machine learning?\u2013 [Franco Patano] Yes. Yeah, that means when we say that we were looking at the architecture earlier that Sean was showing that all of those use cases are supported.\u2013 [Jillian] Fantastic.\u2013 [Franco Patano] You can have one platform to do your ETL, data engineering, machine learning, business intelligence with warehouse-serving all on one copy of your data at Delta Lake.\u2013 [Jillian] Right. And that's how the Lakehouse is better than either the traditional data lake on one side or the traditional data warehouse on the other. Is Databricks available for on-prem deployment?\u2013 [Franco Patano] That is a great question. Databricks is only available on the public clouds, so AWS, Azure, and GCP. But, that doesn't mean that we don't work in a hybrid type of architecture. We have a lot of customers that still have pockets of things on-prem, or they're going through their cloud migration journey. And with some of the features that were announced today, especially Unity and Query Federation, you essentially can connect to your on-prem networks to catalog all your data, and if you want to federate, you have that option. Or if you want to ETL that data into the cloud, you have that option as well.\u2013 [Jillian] That's awesome. Databricks is more like a SaaS model, but do customers have to manage the infrastructure? Do we do it? How much work is needed?\u2013 [Franco Patano] That is another great question. Databricks offers options in this category. Traditionally how Databricks works is we have a SaaS product that can be considered the UI, the notebooks, the cluster managers, the warehouse managers, but you can actually deploy the infrastructure in your account. It's similar to IAS, but not really, but it's really more of a SaaS product. And then we have our service offering, which is completely managed for you.\u2013 [Jillian] Awesome. We have some questions also about how to get started. Some of the attendees ask, do we have any advice about skills that somebody needs to get started on its journey with Databricks? Is it mandatory to know Python or any other language specifically for Databricks? What's your advice on that?\u2013 [Franco Patano] Yeah, I have organizations asking all the time and it usually comes out of, \"We don't know Spark, how can we use Databricks? Or I don't know Scala, how can we use Databricks?\" Or something along that effect. And actually, you don't have to know Spark to use Databricks, you don't even have to know Scala. Actually, the most popular languages on our platform are SQL and Python. SQL is considered lingua franca of the data professionals all over the world. It's the most common language out there. Python is a close second, but we even offer low-code tools on Databricks now. We just announced Bamboolib that basically is kind of like an Excel macro recorder for Databricks, or essentially for Python. Even if you don't know coding, you don't have to in Databricks, you can use Bamboolib and learn on your own, and you can even go to academy.databricks.com to help you on your journey.\u2013 [Jillian] Yeah. Awesome. Thanks, Franco. I see we have Mate and Sean on the line as well. I hope the audio is functioning now. I just want to go back a little bit to the origins of the Lakehouse and maybe perhaps talk a little bit about Delta as well. We had lots of questions around Delta. Can somebody just summarize how a data lake is different from Delta Lake?\u2013 [Matei Zaharia] Yeah. I can take that.\u2013 [Jillian] Yeah.\u2013 [Matei Zaharia] Oh.\u2013 [Jillian] Go for it, Mate.\u2013 [Matei Zaharia] Okay. Yeah. Traditionally a data lake was basically just a low-cost file-based storage where you could store large amounts of data as they're being produced. You don't have to throw anything away, and then you can query them and organize them later, and then extract more valuable curated data sets...\u2013 [Matei Zaharia] ... Stacked, more valuable, curated data sets from them. Delta Lake and Lakehouse are trying to take the same type of infrastructure, but just make it also good for actually working with the curated data for data warehousing. Basically, you get the same kind of low cost, large scalability and easy ingest that you have with the data lake, but then you can have tables that get really good performance. You can have different sort of statistics and indexes about them, and you can also have transactions and version control and other management features right on there, so basically eliminating the need for a second system to do those advanced data management things.\u2013 [Jillian] Very cool. So is that fair to say that, essentially, we can think about a lake house as your existing data lake with Delta Lake on top to help manage the data? Then all of the tools that we provide for ETL, data warehousing, streaming, DSML, et cetera, et cetera, and cataloging?\u2013 [Matei Zaharia] Yeah. And basically just a additional kind functionality on top of the data lake. A key part of that is Delta as the data management and storage layer that supports all those management features.\u2013 [Jillian] Awesome. So we're hearing about other formats available. So could you compare Delta with other open source table formats like Iceberg and Murphy?\u2013 [Matei Zaharia] Yeah, so definitely this Lakehouse model is becoming quite popular and there are other projects that do similar things, that update your data lake to make it easier to manage.Out of the ones today, I think Delta is the one that's been used the most widely. It's used at basically thousands of companies already, partly because Databricks and Azure and other vendors have built products based on it.These formats are quickly evolving. But at least today, I think in Delta you'll find a lot more emphasis on scale. It works very well with very large tables and on performance for queries of any size basically. We've tried to really optimize performance because we wanted to take on the data warehousing use case head on. Some of the other projects started more in just the data lake world and these kind of batch workloads. But the formats are all evolving over time.\u2013 [Jillian] Yeah. Awesome. Okay, so that's for Delta.By the way, as we go through questions, I'll ask attendee, feel free to keep asking questions. We're watching as the Q&A panel, they're coming very fast, but we'll do our best to see what's coming and maybe take some additional as we go.So about Unity Catalog, let say, we've heard from many customers that it truly is a game changer. So could you just recap why customers should adopt Unity Catalog for their data governance needs on the Databricks platform and what they love about it the most?\u2013 [Matei Zaharia] Yeah, I mean, I think it just makes it a lot easier to manage your data, to manage who has access to it, to audit it, and to set up advanced governance around it. We've seen a lot of people adopted just to simplify that process. Once you do that, the interface is very similar to managing permissions in a SQL database, so just anyone who has the knowledge of how to do that from a system like, say, BigQuery or Edge, Shift or anything like that, can now manage the entire lake house and all the data sets they already have in there and give people fine grain access to pieces of it.But it is also something where that we're building a lot of great new functionality in. For example, the Lineage feature is one of the favorite features among early users. It just simplifies a lot of operations when working with data, just to know who's using this data set, when did they last use it, and make sure you don't break anything as you change stuff in there. And we have quite a few other great features just coming on top of that, as well.\u2013 [Jillian] Anything you'd like to share?\u2013 [Matei Zaharia] I'm excited about the tags and attribute-based access control based on those. Basically, instead of having to set permissions on individual resources, like individual tables, you can set a tag. You can create a tag, for example, this is, say, credit card data and apply that to lots of columns and then just create a rule that applies to all of them that's based on the tag. Then you can just have your data stewards who just figure out which data to tag, or you can do it automatically using background scanning. Then everything has those tags and all the rules apply to them.\u2013 [Jillian] Yeah, that's very cool.We had some questions about integration to Unity Catalog. I know you touched on this in your presentation. But again, just to recap, there was so much content today. Unity Catalog works across multiple workspaces. It works with your active directory, for example, works with listing solutions like Collibra, Informatica, correct?\u2013 [Matei Zaharia] Yep. Yeah, we've been working with all the major product vendors in the data space to make it work well. So all the BI tools, all the ETL products, and also catalogs like Collibra and Elation that let you catalog everything in your enterprise.\u2013 [Jillian] Very cool.You also talked about data sharing. So could you talk about some of the key benefits that customers would realize from using Delta sharing on Databricks?\u2013 [Matei Zaharia] Yeah. I mean, it basically makes it easy to share data in your organization with other groups, either in your company or in others. One of the key things with it is the other groups don't need to be running the same platform as you. For example, they don't need to be on database. You can share data with someone who is just doing analysis, say, on a VM, doing data science and Python, they can just directly connect from Python to it. You can share it with someone who's using Power BI; they can just connect in the Power BI user interface. They don't need to set up a data warehouse or anything like that to put the data into. You can share it with anyone that's running Spark in any form or Databricks SQL or other tools.When we talk to users who need to exchange data a lot, the top problem was how hard it is to share to different platforms than what you have, because every platform is trying to use it as a lock-in mechanism to encourage more people to use the same platform because of the convenient sharing. We think in most organizations, you're never going to just replace all that you have in every corner of it and have a single computing engine deployed everywhere. So we'd rather work with everything that's already out there and just make it very convenient for people.\u2013 [Jillian] All right, Franco, fantastic. Thank you very much to all of our presenters and all of our speakers and attendees for joining us today. It was an awesome session. We had so many questions coming through, so it's now time to kick off our live Q and A with all of our presenters. My name is Jillian [inaudible 01:23:39]. I am going to be your moderator for today. First off, we had lots of questions about how to qualify for the voucher. Just to recap, you will need to answer the feedback survey and take the fundamental course, which is about two hours. The links are in the resources section of this webinar platform. We will also send them to you via email after this webinar, and you will get links to the presentation, the recording as well, of course. We hope you enjoyed it so far. Let's just start with a few questions, starting with some intro basic questions about that. Just to recap, what can Databricks provide that others cannot?\u2013 [Franco Patano] Is it open to anyone to take that?\u2013 [Jillian] Go ahead, Franco.\u2013 [Franco Patano] Hello, everyone. That's a great question. Most customers, they have a lot of choice in the cloud today, and you have cloud providers providing the solutions that are built for their cloud, and you have some vendors that are providing solutions that are built among the clouds. And typically, when I think of this type of question, it's about the confusion of choice. You have all of these different choices that are thrown at you as a consumer of these cloud products, and most of the time, you just need to get your work done. You need to build something, you need to build a platform, and you need to enable all of your users. What I think is something that Databricks provides that no one else does is essentially a unified analytics platform. Where can I build one solution that can service all of my users in my organization? And that's what I think Databricks provides that no one else does.\u2013 [Jillian] Absolutely. We're a unified platform. Does that mean we provide all components required for batch processing, training, data warehousing, all that data science, machine learning?\u2013 [Franco Patano] Yes. Yeah, that means when we say that we were looking at the architecture earlier that Sean was showing that all of those use cases are supported.\u2013 [Jillian] Fantastic.\u2013 [Franco Patano] You can have one platform to do your ETL, data engineering, machine learning, business intelligence with warehouse-serving all on one copy of your data at Delta Lake.\u2013 [Jillian] Right. And that's how the Lakehouse is better than either the traditional data lake on one side or the traditional data warehouse on the other. Is Databricks available for on-prem deployment?\u2013 [Franco Patano] That is a great question. Databricks is only available on the public clouds, so AWS, Azure, and GCP. But, that doesn't mean that we don't work in a hybrid type of architecture. We have a lot of customers that still have pockets of things on-prem, or they're going through their cloud migration journey. And with some of the features that were announced today, especially Unity and Query Federation, you essentially can connect to your on-prem networks to catalog all your data, and if you want to federate, you have that option. Or if you want to ETL that data into the cloud, you have that option as well.\u2013 [Jillian] That's awesome. Databricks is more like a SaaS model, but do customers have to manage the infrastructure? Do we do it? How much work is needed?\u2013 [Franco Patano] That is another great question. Databricks offers options in this category. Traditionally how Databricks works is we have a SaaS product that can be considered the UI, the notebooks, the cluster managers, the warehouse managers, but you can actually deploy the infrastructure in your account. It's similar to IAS, but not really, but it's really more of a SaaS product. And then we have our service offering, which is completely managed for you.\u2013 [Jillian] Awesome. We have some questions also about how to get started. Some of the attendees ask, do we have any advice about skills that somebody needs to get started on its journey with Databricks? Is it mandatory to know Python or any other language specifically for Databricks? What's your advice on that?\u2013 [Franco Patano] Yeah, I have organizations asking all the time and it usually comes out of, \"We don't know Spark, how can we use Databricks? Or I don't know Scala, how can we use Databricks?\" Or something along that effect. And actually, you don't have to know Spark to use Databricks, you don't even have to know Scala. Actually, the most popular languages on our platform are SQL and Python. SQL is considered lingua franca of the data professionals all over the world. It's the most common language out there. Python is a close second, but we even offer low-code tools on Databricks now. We just announced Bamboolib that basically is kind of like an Excel macro recorder for Databricks, or essentially for Python. Even if you don't know coding, you don't have to in Databricks, you can use Bamboolib and learn on your own, and you can even go to academy.databricks.com to help you on your journey.\u2013 [Jillian] Yeah. Awesome. Thanks, Franco. I see we have Mate and Sean on the line as well. I hope the audio is functioning now. I just want to go back a little bit to the origins of the Lakehouse and maybe perhaps talk a little bit about Delta as well. We had lots of questions around Delta. Can somebody just summarize how a data lake is different from Delta Lake?\u2013 [Matei Zaharia] Yeah. I can take that.\u2013 [Jillian] Yeah.\u2013 [Matei Zaharia] Oh.\u2013 [Jillian] Go for it, Mate.\u2013 [Matei Zaharia] Okay. Yeah. Traditionally a data lake was basically just a low-cost file-based storage where you could store large amounts of data as they're being produced. You don't have to throw anything away, and then you can query them and organize them later, and then extract more valuable curated data sets...\u2013 [Matei Zaharia] ... Stacked, more valuable, curated data sets from them. Delta Lake and Lakehouse are trying to take the same type of infrastructure, but just make it also good for actually working with the curated data for data warehousing. Basically, you get the same kind of low cost, large scalability and easy ingest that you have with the data lake, but then you can have tables that get really good performance. You can have different sort of statistics and indexes about them, and you can also have transactions and version control and other management features right on there, so basically eliminating the need for a second system to do those advanced data management things.\u2013 [Jillian] Very cool. So is that fair to say that, essentially, we can think about a lake house as your existing data lake with Delta Lake on top to help manage the data? Then all of the tools that we provide for ETL, data warehousing, streaming, DSML, et cetera, et cetera, and cataloging?\u2013 [Matei Zaharia] Yeah. And basically just a additional kind functionality on top of the data lake. A key part of that is Delta as the data management and storage layer that supports all those management features.\u2013 [Jillian] Awesome. So we're hearing about other formats available. So could you compare Delta with other open source table formats like Iceberg and Murphy?\u2013 [Matei Zaharia] Yeah, so definitely this Lakehouse model is becoming quite popular and there are other projects that do similar things, that update your data lake to make it easier to manage.Out of the ones today, I think Delta is the one that's been used the most widely. It's used at basically thousands of companies already, partly because Databricks and Azure and other vendors have built products based on it.These formats are quickly evolving. But at least today, I think in Delta you'll find a lot more emphasis on scale. It works very well with very large tables and on performance for queries of any size basically. We've tried to really optimize performance because we wanted to take on the data warehousing use case head on. Some of the other projects started more in just the data lake world and these kind of batch workloads. But the formats are all evolving over time.\u2013 [Jillian] Yeah. Awesome. Okay, so that's for Delta.By the way, as we go through questions, I'll ask attendee, feel free to keep asking questions. We're watching as the Q&A panel, they're coming very fast, but we'll do our best to see what's coming and maybe take some additional as we go.So about Unity Catalog, let say, we've heard from many customers that it truly is a game changer. So could you just recap why customers should adopt Unity Catalog for their data governance needs on the Databricks platform and what they love about it the most?\u2013 [Matei Zaharia] Yeah, I mean, I think it just makes it a lot easier to manage your data, to manage who has access to it, to audit it, and to set up advanced governance around it. We've seen a lot of people adopted just to simplify that process. Once you do that, the interface is very similar to managing permissions in a SQL database, so just anyone who has the knowledge of how to do that from a system like, say, BigQuery or Edge, Shift or anything like that, can now manage the entire lake house and all the data sets they already have in there and give people fine grain access to pieces of it.But it is also something where that we're building a lot of great new functionality in. For example, the Lineage feature is one of the favorite features among early users. It just simplifies a lot of operations when working with data, just to know who's using this data set, when did they last use it, and make sure you don't break anything as you change stuff in there. And we have quite a few other great features just coming on top of that, as well.\u2013 [Jillian] Anything you'd like to share?\u2013 [Matei Zaharia] I'm excited about the tags and attribute-based access control based on those. Basically, instead of having to set permissions on individual resources, like individual tables, you can set a tag. You can create a tag, for example, this is, say, credit card data and apply that to lots of columns and then just create a rule that applies to all of them that's based on the tag. Then you can just have your data stewards who just figure out which data to tag, or you can do it automatically using background scanning. Then everything has those tags and all the rules apply to them.\u2013 [Jillian] Yeah, that's very cool.We had some questions about integration to Unity Catalog. I know you touched on this in your presentation. But again, just to recap, there was so much content today. Unity Catalog works across multiple workspaces. It works with your active directory, for example, works with listing solutions like Collibra, Informatica, correct?\u2013 [Matei Zaharia] Yep. Yeah, we've been working with all the major product vendors in the data space to make it work well. So all the BI tools, all the ETL products, and also catalogs like Collibra and Elation that let you catalog everything in your enterprise.\u2013 [Jillian] Very cool.You also talked about data sharing. So could you talk about some of the key benefits that customers would realize from using Delta sharing on Databricks?\u2013 [Matei Zaharia] Yeah. I mean, it basically makes it easy to share data in your organization with other groups, either in your company or in others. One of the key things with it is the other groups don't need to be running the same platform as you. For example, they don't need to be on database. You can share data with someone who is just doing analysis, say, on a VM, doing data science and Python, they can just directly connect from Python to it. You can share it with someone who's using Power BI; they can just connect in the Power BI user interface. They don't need to set up a data warehouse or anything like that to put the data into. You can share it with anyone that's running Spark in any form or Databricks SQL or other tools.When we talk to users who need to exchange data a lot, the top problem was how hard it is to share to different platforms than what you have, because every platform is trying to use it as a lock-in mechanism to encourage more people to use the same platform because of the convenient sharing. We think in most organizations, you're never going to just replace all that you have in every corner of it and have a single computing engine deployed everywhere. So we'd rather work with everything that's already out there and just make it very convenient for people.\u2013 [Jillian] Right. Plus, now based on this technology Delta sharing, we also provide solutions like marketplace and clean rooms. Correct?\u2013 [Matei Zaharia] Yeah, and these will have the same benefits, basically, that you can connect to them from any computing platform and you can actually exchange and collaborate on data that way.\u2013 [Jillian] Yeah, yeah. Very cool.Is there anything else you would like to on Unity Catalog and Delta sharing? I have more questions on ingest, DTL, DB SQL, things like that.\u2013 [Matei Zaharia] Yeah, they're both generally available, as I said in the webinar. So yeah, we're very excited to see people try them out and hear feedback.\u2013 [Jillian] Absolutely.So switching here a little bit. So we've talked about Delta, we've talked about Unity Catalog and data governance and data sharing.We had lots of questions around ingest in ETL as we went through this webinar as well. One of the question was, \"For data ingestion, should I have to use other ETL tools such as Fivetran, Data Factory, et cetera, or do we have any components provided on Databricks itself?\"\u2013 [Shant Hovsepian] I can take that. Hey, everyone, it's Sean.\u2013 [Jillian] Hey, Sean.\u2013 [Shant Hovsepian] Yeah. So Fivetran and Azure Data Factory are very frequently used ingestion tools with Databricks. Fivetran works great when you have various different data sources that you want to bring in. If you're in the Azure stack, ADF is also connected to just about anything. So we have tons of users that use those together with the rest of the Databricks platform.Out of the box directly in Databricks with the workflows product and DLT, there are various different types of ingestion pipelines you can build and data sources you can choose from. Really, it's the beauty of the Lakehouse, have the flexibility to choose the tools and system that you're familiar with and that works with you. It's compatible with just about all the leading methods out there.\u2013 [Jillian] So we had some specific questions like, \"Is ingestion from block storage supported, for example?\"\u2013 [Shant Hovsepian] Yeah, of course. If that's Azure blob storage, yes. Then generally talking about blob storage, wherever the data is stored, yeah, it's always available in the Lakehouse.\u2013 [Jillian] Yep. \"Can I import data from Kafka, like auto streaming services?\"\u2013 [Shant Hovsepian] Yes. So you can use Auto Loader or the general streaming infrastructure to bring in data directly from Kafka topics. That's one of the nice things, you can have the realtime data in the Lakehouse directly with all of your data warehousing type workloads. So you don't ever have to worry about data being too old or stale. You can basically get that realtime feed right in.\u2013 [Jillian] And can we implement CDC using Auto Loader?\u2013 [Shant Hovsepian] Technically, you can. Auto Loader out of the box doesn't have CDC integration. with various data sources unless it was added recently. Franco, maybe you would know better than I would on that one?Yeah, I think it's compatible. You can, essentially, for the source that you're reading from, whether it's Postgres or some other database, if you can get the stream to come in with a wall log CDC format, then we can have Auto Loader to that.\u2013 [Jillian] Okay. So as we have this data coming in and all of these data pipelines, how do we handle the quality in Databricks?\u2013 [Shant Hovsepian] Oh, yeah. So if you've heard about Delta Live Tables, DLT, which was something that we made generally available recently during the Data AI summit this summer, that's got an amazing feature. It's called expectations, where you can essentially define what you expect your data to look like. When those expectations aren't met, as the data's going through the pipeline and transformations, you can redirect those results to an error table or an exceptions table, get an alert and get a notification onto the system. So it's automatically maintained, you just need to define your constraints.\u2013 [Jillian] Very cool. So DLT is our solution for managing your data pipeline's quality, stream data, et cetera, et cetera?\u2013 [Shant Hovsepian] Yeah. Specifically. It's expectations. It's a cool feature if look it up online on the docs, it makes it very easy to constantly monitor your data quality and then deal with anything that doesn't meet your requirements.\u2013 [Jillian] Yeah. We had a question around small, I guess, extensibility. So all these data is coming in into Delta Life Tables, Delta tables creating Databricks. Can they be consumed through APIs?\u2013 [Shant Hovsepian] Oh, yeah. So especially with the Lakehouse, the value in many times is you can get this realtime, ingested data and make it accessible to everybody in your organization. We've done a lot of work, I talked about some of the new connectors that are available, but there's essentially rest APIs that you can use to get through your data and tables and query them as well as native SDKs, everything from Java, C#, traditional data sources, Python, Go, and Node where you can actually get to the data pretty...\u2013 [Jillian] Very cool. Okay, so let's talk about Databricks SQL a little more. So we touched on serverless compute in the presentation and in the demo for Databricks SQL. So can you clarify, is it using the AWS plus Azure resources or Databricks compute itself? How does the infrastructure work?\u2013 [Shant Hovsepian] Oh, yeah. That question came up a couple of times. So Databricks SQL works in two modes.There's essentially a managed serverless version where all of the infrastructure is managed by Databricks on your behalf, so nothing spins up in your VPC in your accounts and the compute is instantly available and can scale nearly elastically based on your demand.Then there's what we call DB SQL Classic, which is something where it's essentially a set of special built VMs that Databricks deploys into your VPC, your network, and your cloud account. So it's not fully managed infrastructure, there are some systems and resources that you'll see show up in your cloud console when using Databricks, but you get the flexibility to choose from both, depending on what your use case requirements are.\u2013 [Jillian] Right. Awesome.So in one of the examples we saw in the demo with the Tableau, with the live connection, if the data doesn't change, does it still query the data every time you change the visualization or will there it be a persistent cache on the serverless connection?\u2013 [Shant Hovsepian] Oh, yeah. No, for sure. There's a lot of intelligence, and this is the beauty of Delta, is added logical, reliable ability to reason about the data in the Delta Lake so that we have what is traditionally a transaction snapshot ID equivalent... But when someone queries the same data, especially it's very 80\/20, 80% of users tend to run the same queries over and over again. So caching is a huge benefit.Behind the scenes we use Delta's snapshot transaction isolation to see, \"Oh, the last time this query ran, we have those results, they're saved, we can just reuse them again and not run this query all over again if we know for a fact that Unity Catalog tells us that nothing has changed with the security permissions on the data and user and that Delta tells us that underlying data hasn't been updated, so the transaction snapshot hasn't changed.\" In those cases, it'll immediately serve the data from the cache. It'll be super snappy.\u2013 [Jillian] Yeah, yeah. Thanks, Sean.So Miranda, it was an amazing demo. Thank you so much for putting all of this together. You showed us some very cool existing and upcoming capabilities on Databricks SQL. Python UDF and Materialized View specifically are still in private preview. Can you comment on one that'll be publicly available, maybe or what's coming next?\u2013 [Miranda] Sure. Yep, you are correct that both Python UDFs and Materialized Views are in private preview. The exact timing of a public preview availability will depend on just how we hit some of our exit criteria and the feedback we get during that private preview. So highly encourage anyone interested to sign up so that we can go ahead and get you early access and you can kind of help shape exactly what that experience looks like.Next on deck is going to be Query Federation. So that private preview has not kicked off yet, but that's coming. If there's any interest there, again expressing, letting us know now so we can get you on the list and reach out when we're closer.\u2013 [Jillian] Very cool. Thanks. Can you clarify how the DB SQL, Databricks SQL, refers from stock SQL?\u2013 [Shant Hovsepian] Oh, I can take that. First and foremost, Databricks SQL is a whole service. It's a platform for your data warehousing needs. Databricks SQL is ANSI standard SQL compliance and it's built as a modern MPP architecture.Spark's SQL is a part of the Apache Spark project and it's essentially the expression layer that you use to define SQL transformations, SQL expressions while you're working with Spark. You can embed it in your Python, you can use it with the rest of the Spark API. It's not quite ANSI SQL compliance at all, and it's not a full hosted, managed service to run all of your workloads. It's really just one of the parts of the general Spark project.\u2013 [Jillian] Yeah, they're very, very different. But we had a few questions about this, so wanted to clarify.I loved one of the comment we had throughout the presentation. So Nathalie said, \"Okay, so I can see you have priority with other cloud data warehousing, right? Data masking, materialized views, [inaudible 01:49:18], time travel. So how is Databricks SQL different from a data warehouse? How's Breakout different from a data warehouse?\" Could you clarify that again?\u2013 [Shant Hovsepian] Oh, this is a good one. Who wants to take this? I could do it, too.\u2013 [Jillian] Well, Franco, I know that this is a question a lot of your customers are asking you, as well. He was put on mute.\u2013 [Shant Hovsepian] Well, okay. So I'll take first pass, that's it. But the most important thing is, and of the biggest ahas we've seen with Databricks SQL, yes, you can do your ETL, you can do your warehousing, you can your BI. It's very flexible. It's extremely cost-effective. That's the beauty of being built on the open standards and open technology of the Lakehouse. There's a huge value there that you get from a TCO perspective.But the aha moments that we've really seen is when people can do simple AI and realtime stream processing trivially with that data in the data warehouse. That's in DB SQL, you don't have to move to data to another system, you don't need to copy it. You can kind of get those predictive insights almost instantly from the exact same data. So if we go back to that data AI maturity curve that I was talking about, because you don't need to switch systems, you don't need to reload the data, you don't need to change your tooling set, you don't need to get it retrained on it. You can go from basic BI to AI aha with just a couple commands. So it's very simple to go along that whole journey.\u2013 [Jillian] Yeah, yeah. So I think to summarize, Databricks SQL is a serverless data warehouse on the Lakehouse, but it's part of a broader platform that does ETL, streaming, data sense, machine learning, so all in one. That's, I guess, one of the key differentiator.Actually I see one question that's coming through the screen that's a great segue in the next section because they wanted to talk about Photon a little bit. So can you elaborate on the difference between Photon and Databricks SQL?\u2013 [Shant Hovsepian] Oh, yeah. So Photon is a general purpose compute engine. Essentially, it's a technology and it's like the engine behind the scenes that crunches numbers. So if you take a car, let's say a pickup truck, and you look at it from the outside, it's a pickup truck, but it may have a V8 engine and may have a V4 engine. In the case of Photon, it's like a V12 superpower engine. DB SQL is the truck, right? DB SQL is a data warehouse product for your Lakehouse architecture. It's got SQL, it integrates with Unity Catalog, [inaudible 01:52:06] governance and all those things. The Photon is really just that new MPP built for modern new CPUs. Most data warehouses out there were designed 30, 40 years ago, probably before I was born, and they were built for the type of hardware that existed back in the day. Photon is really optimized for the new set of modern CPU and data center technologies that exists.\u2013 [Jillian] Okay, thanks, Sean. So can you elaborate on how does it compare with stock? What was the journey between stock and Photon and what difference between both?\u2013 [Shant Hovsepian] Yeah. First of all, if people are interested in this topic, we published a great paper, it's academic paper, a few months ago at SIGMOD Conference. If you just Google for Photon paper, SIGMOD paper, we can provide some links. It's got way more details and information there.But yeah, the beauty of Photon is, it's essentially 100% Spark API compatible. Spark is a much bigger distributed compute system. It's not just an execution engine, but it also has different APIs like the RDD API. Photon is really specifically focused on the data frame API. It has task schedulers, has job management, it has a lot of the things that you need for distributed AI processing, broadcast variables, scheduling. So Spark is a bigger system. Photon is more just like the expression evaluation engine. They're both level with each other.\u2013 [Jillian] Absolutely. Down the line, Photon is Databricks proprietary, right? So it's compatible with the Spark APIs like to mention, but that's becoming our default engine over time on the Lakehouse platform. Whereas Spark will remain open source, we're still committed to Spark. Photon is curating Spark in our platform, is that right?\u2013 [Shant Hovsepian] Yes. Apache Spark and Databricks, it's called the Databricks Runtime. So that's essentially our version of Spark. It has a bunch of enhancements and features. Mind you, Databricks loves open source and we're 100% committed to it. We make the most contributions, enhancements, Apache Spark. So we do a lot of work with Apache Spark. Just our version of Apaches Spark is the Databricks Runtime called the DBR for short. And Photon is just like an acceleration piece for DBR, the Databricks Runtime.\u2013 [Jillian] Yeah. Is there anything special that customers need to do to use Photon on the platform?\u2013 [Shant Hovsepian] Absolutely not. They just need to make sure they're using... I tend to recommend a very recent version of Databricks Runtime. So when you use a data science, data engineering workspace cluster, you want to go with a DBR version... The most recent one you can find is 11.2 right now. Once you pick that DBR version, there'll be an option that says, \"Enable Photon.\" You just check that box and you'll get the awesome features and functionality.\u2013 [Jillian] Yeah. And on Databricks SQL, it's just on by default, so there's really nothing to worry about.\u2013 [Shant Hovsepian] With the Databricks SQL, Photon... There's all sorts of things buried inside Databricks SQL that makes it awesome, but very much a self-contained data warehouse product where Photon is like a feature in your Spark.\u2013 [Jillian] Right. We're almost on top of the hour, so this is my last question for you.This is a pricing question because we had a few and think it's important to address. \"Is Unity Catalog available on standard Databricks or premium? How about Databricks SQL Are there any extra cost enabling Photon acceleration on the cluster as well?\"If you could talk to that, it would be fantastic and then we'll be ready to wrap up.\u2013 [Shant Hovsepian] Cool. So right now Unity Catalog is available in premium and enterprise SKUs, available in the standard SKU. The Databricks standard SKU in general doesn't have table access controls for various features like that. So a lot of the governance features that are important for many types of data warehousing workloads aren't available in the standard SKU. So Databricks SQL also isn't available in the standard SKU, it's available in premium and enterprise SKUs. Nobody else on the call is correcting me so I believe that is still true and it hasn't changed. But suffice it to say, we want data to be secure and governed everywhere. So I think... we find better ways of unlocking the unity and Unity Catalog for every workload and every... I think the second question you asked was about-\u2013 [Jillian] Yeah, and for Photon, as well. Do you want to speak about that?\u2013 [Shant Hovsepian] Yeah, yeah. When you enable photon, I showed some of it in the slides, we've seen customers on average get like a 30% savings in overall TCO. So not only do things run faster, but they cost less money because you don't need to keep your compute resources up longer. So overall, TCO, we've seen tremendous savings. So at the end of the day, it won't cost you any more money to use Photon, it ends up costing less money total. But that said, in Databricks, when you do enable Photon, it's a different TPU billing rate. So it's charged at a different rate, but you will not keep your compute resources up longer because everything's so much faster. So you always end up saving money in the long run.\u2013 [Jillian] Yes, absolutely. Thank you, Sean.We're now on top of the hour, so that conclude our event for today. I just want to say thank you again to all of our attendees for your time and sitting with us today, our presenters for creating all of this amazing content. We hope it was helpful and we-Join usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brad-corwin\/#","text":"Brad Corwin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrad CorwinChief Data Scientist at Booz Allen HamiltonBack to speakersBrad Corwin is a Chief Data Scientist at Booz Allen Hamilton with over a decade of professional experience in software engineering, data engineering and data science. He has a focus on innovative techniques and operationalizing data science solutions. He provides thought leadership to maximize the outcome and has a passion for building data-driven solutions in a rapid Agile environment. He currently leads Advana\u2019s Data Science and Data Engineering team to accelerate data and AI delivery.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-roome","text":"Paul Roome - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul RoomeStaff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/data-management-101","text":"\n\n\n\n\n\n\n\nData Management 101\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/james-demmel","text":"James Demmel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJames DemmelDr. Richard Carl Dehmel Distinguished Professor at University of California, BerkeleyBack to speakersProf. James Demmel is a Distinguished Professor of Mathematics and Computer Science at the University of California, Berkeley. He is the former chair of the Computer Science Division and EECS Department of UC Berkeley. Demmel is known for his work on numerical linear algebra libraries, including LAPACK, ScaLAPACK and SuperLU. Demmel\u2019s work on high-performance computing, such as communication-avoiding algorithms, has been recognized by many honors and awards. He is a member of the National Academy of Sciences, National Academy of Engineering, American Academy of Arts and Sciences; Fellow of the AAAS, ACM, AMS, IEEE, and SIAM; ACM Paris Kanellakis Theory and Practice Award, IPDPS Charles Babbage Award, IEEE Sidney Fernbach Award, 13 best paper prizes. Demmel was one of just two scientists honored the Leslie Fox Prize for Numerical Analysis in 1986 and he was the winner of the J.H. Wilkinson Prize in Numerical Analysis and Scientific Computing, the IEEE's Sidney Fernbach Award \"for computational science leadership in creating adaptive, innovative, high-performance linear algebra software\", and the IEEE Computer Society Charles Babbage Award.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hannes-muhleisen","text":"Hannes M\u00fchleisen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHannes M\u00fchleisenCo-Founder and CEO at DuckDB LabsBack to speakersProfessor Dr. Hannes M\u00fchleisen is a creator of the DuckDB database management system and the co-founder and CEO of DuckDB Labs, a consulting company providing services for DuckDB. He is also a senior researcher of the Database Architectures group at the Centrum Wiskunde & Informatica (CWI) in Amsterdam and a Professor of Data Engineering at Radboud University. Hannes\u2019 main interest is analytical data management systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions","text":"Databricks Solution Accelerators - Databricks Use CasesSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for IndustryNo compromise data analytics and AI solutions purpose-built for your industryGet startedSchedule a demoDiscover the Lakehouse for your industryCommunications, Media & EntertainmentEarn more attention, capture more imaginationsLearn howFinancial ServicesBuild more trust, ensure peace of mindLearn howHealthcare and Life SciencesDiscover and deliver better careLearn howRetail and Consumer GoodsLead customers on their journey and champion your brandLearn howBrowse all industriessearchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listIndustry SolutionsFrom idea to proof of concept in as little as two weeksDatabricks Solution Accelerators are purpose-built guides \u2014 fully functional notebooks and best practices \u2014 that speed up results. Databricks customers are saving hours of discovery, design, development and testing, with many going from idea to proof of concept (PoC) in as little as two weeks.Explore AcceleratorsReady to start?Explore what Databricks can do for you by starting of with a free trial.Start your trialProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/derek-slager\/#","text":"Derek Slager - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDerek SlagerCTO at AmperityBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/contact","text":"Contattaci - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWContattiHai bisogno di aiuto per la formazione o l'assistenza? Consulta queste risorse aggiuntive.DocumentazioneLeggi la documentazione tecnica per Databricks su AWS, Azure o Google CloudCommunity di DatabricksDiscuti, condividi e interagisci con utenti ed esperti di DatabricksTrainingPadroneggia la Databricks Lakehouse Platform con corsi di formazione autogestiti o con istruttore, oppure diventa sviluppatore certificatoSupportoSei gi\u00e0 cliente? Clicca qui se hai un problema tecnico o di pagamentoLe nostre sediScopri tutte le nostre sedi nel mondo ed entra in contattoKnowledge baseTrova rapidamente le risposte alle domande pi\u00f9 frequenti sui prodotti e servizi DatabricksProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/11\/17\/databricks-open-source-genomics-toolkit-outperforms-leading-tools.html","text":"How Glow Performs Genetic Association Studies 10x More Efficiently Than Hail - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDatabricks\u2019 Open Source Genomics Toolkit Outperforms Leading Toolsby William BrandlerNovember 17, 2021 in Engineering BlogShare this postCheck out the\u00a0solution accelerator\u00a0to download the notebooks referred throughout this blog.\u00a0Genomic technologies are driving the creation of new therapeutics, from RNA vaccines to gene editing and diagnostics. Progress in these areas motivated us to build Glow, an open-source toolkit for genomics machine learning and data analytics. The toolkit is natively built on Apache Spark\u2122, the leading engine for big data processing, enabling population-scale genomics.The project started as an industry collaboration between Databricks and the Regeneron Genetics Center. The goal is to advance research by building the next generation of genomics data analysis tools for the community. We took inspiration from bioinformatics libraries such as Hail, Plink and bedtools, married with best-in-class techniques for large-scale data processing. Glow is now 10x more computationally efficient than industry leading tools for genetic association studies.The vision for Glow and genomic analysis at scaleThe primary bottleneck slowing the growth in genomics is the complexity of data management and analytics. Our goal is to make it simple for data engineers and data scientists who are not trained in bioinformatics to contribute to genomics data processing in distributed cloud computing environments. Easing this bottleneck will in turn drive up the demand for more sequencing data in a positive feedback loop.When to use GlowGlow\u2019s domain of applicability falls in aggregation and mining of genetic variant data. Particularly for data analyses that are run many times iteratively or that take more than a few hours to complete, such as:Annotation pipelinesGenetic association studiesGPU-based deep learning algorithmsTransforming data into and out of bioinformatics tools.As an example, Glow includes a distributed implementation of the Regenie method. You can run Regenie on a single node, which is recommended for academic scientists. But for industrial applications, Glow is the world\u2019s most cost effective and scalable method of running thousands of association tests. Let\u2019s walk through how this works.Benchmarking Glow against HailWe focused on genetic association studies for benchmarks because they are the most computationally intensive steps in any analytics pipeline. Glow is >10x more performant for Firth regression relative to Hail without trading off accuracy (Figure 1). We were able to achieve this performance because we apply an approximate method first, restricting the full method to variants with a suggestive association with disease (P Glow documentation.to set up the environment.Glow on the Databricks Lakehouse PlatformWe had a small team of engineers working on a tight schedule to develop Glow. So how were we able to catch up with the world\u2019s leading biomedical research institute, the brain power behind Hail? We did it by developing Glow on the Databricks Lakehouse Platform in collaboration with industry partners. Databricks provides infrastructure that makes you productive with genomics data analytics. For example, you can use Databricks Jobs to build complex pipelines with multiple dependencies (Figure 2).Furthermore, Databricks is a secure platform trusted by both Fortune 100 and healthcare organizations with their most sensitive data, adhering to principles of data governance (FAIR), security and compliance (HIPAA and GDPR).Figure 2: Glow on the Databricks Lakehouse PlatformWhat lies in store for the future?Glow is now at a v1 level of maturity, and we are looking to the community to help contribute to build and extend it. There\u2019s lots of exciting things in store.Genomics datasets are so large that batch processing with Apache Spark can hit capacity limits of certain cloud regions. This problem will be solved by the open Delta Lake format, which unifies batch and stream processing. By leveraging streaming, Delta Lake enables incremental processing of new samples or variants, with edge cases quarantined for further analysis. Combining Glow with Delta Lake will solve the \u201cn+1 problem\u201d in genomics.A further problem in genomics research is data explosion. There are over 50 copies of the Cancer Genome Atlas on Amazon Web Services alone. The solution proposed today is a walled garden, managing datasets inside genomics domain platforms. This solves data duplication, but then locks data into platforms.This friction will be eased through Delta Sharing, an open protocol for secure real-time exchange of large datasets, which will enable secure data sharing between organizations, clouds and domain platforms. Unity Catalog will then make it easy to discover, audit and govern these data assets.We\u2019re just at the beginning of the industrialization of genomics data analytics. To learn more, please see the Glow documentation, tech talks on YouTube,  and workshops.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ben-coppersmith\/#","text":"Ben Coppersmith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBen CoppersmithSr. Manager, Data Platform at Disney StreamingBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ioannis-papadopoulos","text":"Ioannis Papadopoulos - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIoannis PapadopoulosCloud Technologist at DatabricksBack to speakersIoannis is a Cloud Technologist at Databricks, working in collaboration with the technical fields of AWS, Azure, and GCP.\nHe started his career at CERN as a research physicist and then moved to Apple to lead the business development of the research markets in EMEA.\nBefore joining Databricks, Ioannis had co-founded 3 startups, where he championed the development of serverless architectures on the cloud. \nIoannis holds a Ph.D. in Physics, an MBA, and an Executive Master in digital transformation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/databricks-named-leader-by-gartner","text":"Databricks Named a Leader | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks Named a LeaderCloud Database Management SystemsDatabricks named a Leader in 2022 Gartner\u00ae Magic Quadrant\u2122 CDBMSDatabricks is proud to announce that Gartner has named us a Leader in the 2022 Magic Quadrant for Cloud Database Management Systems for the second consecutive year.We believe this recognition validates our vision for the lakehouse as a single, unified platform for data management and engineering \u2014 as well as, analytics and AI.Download the report to learn why Gartner named Databricks a Leader and gain additional insight into the benefits that a lakehouse platform can bring to your organization.Access the Report Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ori-zohar","text":"Ori Zohar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOri ZoharPrincipal Product Marketing Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lior-gavish\/#","text":"Lior Gavish - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLior GavishCTO and Co-founder at Monte Carlo DataBack to speakersLior Gavish is CTO and Co-Founder of Monte Carlo, a data reliability company backed by Accel, Redpoint Ventures, GGV, ICONIQ Growth, Salesforce Ventures, and IVP. Prior to Monte Carlo, Lior co-founded cybersecurity startup Sookasa, which was acquired by Barracuda in 2016. At Barracuda, Lior was SVP of Engineering, launching award-winning ML products for fraud prevention. Lior holds an MBA from Stanford and an MSC in Computer Science from Tel-Aviv University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gaurav-saraf","text":"Gaurav Saraf - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGaurav SarafProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/company\/diversity","text":"\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3 |DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u3068\u63d0\u643a\u3057\u3001\u3088\u308a\u591a\u304f\u306e\u5973\u6027\u3084\u9ed2\u4eba\u3001\u30e9\u30c6\u30f3\u30a2\u30e1\u30ea\u30ab\u7cfb\u5b66\u751f\u304c\u6280\u8853\u5206\u91ce\u306e\u30ad\u30e3\u30ea\u30a2\u3092\u8ffd\u6c42\u3067\u304d\u308b\u3088\u3046\u652f\u63f4\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u8aad\u3080\u30ec\u30dd\u30fc\u30c8Women in Tech \u30e1\u30f3\u30bf\u30fc\u30b7\u30c3\u30d7\u30d7\u30ed\u30b0\u30e9\u30e0Databricks \u3067\u306f\u3001\u6b74\u53f2\u7684\u306b\u4ee3\u8868\u7684\u306a\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u306b\u5bfe\u3057\u3066\u3001\u5c02\u9580\u7684\u306a\u6210\u9577\u3068\u6607\u9032\u306e\u6a5f\u4f1a\u3092\u63d0\u4f9b\u3059\u308b\u3053\u3068\u306e\u91cd\u8981\u6027\u3092\u8a8d\u8b58\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u8aad\u3080\u30ec\u30dd\u30fc\u30c82021 InHerSight AwardDatabricks \u306f\u3001\u5973\u6027\u306b\u3068\u3063\u3066\u6700\u9ad8\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u8077\u5834\u306e 1 \u3064\u306b\u5973\u6027\u304b\u3089\u9078\u3070\u308c\u305f\u3053\u3068\u3092\u5b09\u3057\u304f\u601d\u3044\u307e\u3059\u3002\u8a73\u3057\u304f\u306f\u3001InHerSight\u3000\u306e\u30d7\u30ed\u30d5\u30a3\u30fc\u30eb\u3067\u3054\u89a7\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u3082\u3063\u3068\u8aad\u3080\u30c7\u30fc\u30bf\u306e\u672a\u6765\u3092\u3001\u4e00\u7dd2\u306b\u4f5c\u308a\u307e\u305b\u3093\u304b\uff1f\u30c7\u30fc\u30bf\u3068 AI 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/glossary\/personalized-banking","text":"Personalized FinancePlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPersonalized FinanceAll>Personalized FinanceTry Databricks for freeGet StartedWhat is Personalized Finance?Financial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remain competitive, banks have to offer an engaging banking experience that goes beyond traditional banking via personalized insights, recommendations, setting financial goals and reporting capabilities \u2013 all powered by advanced analytics like geospatial or natural language processing (NLP). Personalized finance, also known as open finance, is based on data-sharing principles that can empower banks to offer a broader range of possibilities to their clients that are suited specifically to their needs. Personalized finance is made possible through open banking (refer to next section) standards and evolving regulations across the world.What does Personalized Finance look like in practice?In today's on-demand culture, personalized finance means that customers want their banks, insurance carrier or wealth manager to meet them where they are\u2014in the products and channels that they use. For example, real-time installment lending, also called Buy Now Pay Later (BNPL) is automatically added on to your retail shopping experience. Perhaps you've recently opened your banking app and noticed some new features to add accounts from other banks to help you monitor all your accounts at once, or you added your bank account to your investing app to see how much you can invest this month. These are examples of personalized finance that gives consumers more control over their financial well-being. Another example, Spanish bank BBVA's recent blog1 describes in detail how the bank \"uses data science to identify the characteristics that define them (always with their prior consent) and therefore offer recommendations on how to manage their everyday finances, lower their debt, save or plan for the future.\"Why is Personalized Finance important?Customers want more choice, control and a seamless customer experience. Beyond their account or credit card balances, customers increasingly want access to information about their finances that can help them make more informed decisions about their money and financial goals. At the same time, they expect to be presented with personalized offers that best fit their investment posture and preferences.\n> 72% of customers rate personalization as \"Highly Important\" in today's financial services landscape\n> 60% of consumers say they are likely to become repeat buyers after a personalized shopping experienceFor the financial services institution (FSI), personalized finance benefits are:Foster customer loyalty and retention by providing an enhanced customer experience that is targeted to their needs and behavior.Increase in engagement and conversion rates, resulting in a greater share of wallet\/ higher customer lifetime value.Stronger marketing ROI through targeted marketing campaigns and consistent messaging across channels.What are the challenges in implementing Personalized Finance?Legacy Infrastructure. Legacy technologies can't harness insights from fast-growing unstructured and alternative data sets \u2014 and don't offer open data sharing capabilities to fuel collaboration.Strict data and privacy regulations. A number of high profile instances of data theft and breaches have made many consumers more cautious about sharing their personal data.Access to third party data. Vendor lock-in and disjointed tools hinder the ability to do real-time analytics that drives and democratizes smarter financial decisions.Data silos. Highly complex workflows, disparate technologies, and spreadsheet-culture makes collaboration difficult and keeps data trapped in silos across multiple business units.How does Databricks help financial institutions with Personalized Finance?Databricks Lakehouse for Financial Services provides banking, insurance and capital markets companies with the ability to unify data and AI on an open and collaborative platform to deliver personalized customer experiences, minimize risk, and accelerate innovation. It eliminates the technical limitations of legacy systems, and enables FSIs to leverage all of their data to minimize risk while accelerating transformative innovation. It allows FSIs to aggregate different types of data \u2014 from market to alternative data \u2014 enabling hyper-personalized experiences that drive cross-selling opportunities, customer satisfaction and share of wallet. By unifying data and AI, FSIs are also able to simplify the complexity of regulatory reporting, risk management and compliance by securely streamlining the acquisition, processing and transmission of data to empower better data governance practices.1 How BBVA uses data to look after its customers' financial healthAdditional ResourcesBig Book of Use Cases in Financial ServicesGartner\u00ae Hype Cycle\u2122 for Financial Data and Analytics Governance, 2022Hyper Personalization Accelerator for Banks and FintechsReshaping Retail Banking with Personalization workshop with DeloitteLakehouse for Financial Services solutionsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/franco-patano\/#","text":"Franco Patano - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFranco PatanoProduct Specialist at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/antonio-castelo\/#","text":"Antonio Castelo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAntonio Castelo CollibraBack to speakersAntonio built the first partner integration with Unity Catalog, and has been instrumental in building customer momentum around the partnership with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/202107-amer-industry-healthcare-and-life-sciences-workshop-extract-real-world-da","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/hosted-spark","text":"What is Hosted Spark?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHosted SparkAll>Hosted SparkTry Databricks for freeGet StartedWhat is Hosted Spark?Apache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. In addition, it also supports several other tools such as Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.Spark Provides Two Modes for Data Exploration:InteractiveBatch For a simplified end-user interaction, Spark is also provided to organizations in a unified hosted data platform.\u00a0In the absence of direct access to Spark resources by remote applications, the user had to face a longer route to production. In order to overcome this obstacle, there have been created services that enable remote apps to efficiently connect to a Spark cluster over a REST API from anywhere. These interfaces support the execution of snippets of code or programs in a Spark context that runs locally or in Apache Hadoop YARN. Hosted Spark interfaces proved to be turnkey solutions as they facilitate the interaction between Spark and application servers, streamlining the architecture required by interactive web and mobile apps.Hosted Spark Services Provide These Features:Interactive Scala, Python, and R coveringsBatch submissions in Scala, Java, PythonMultiple users are able to share the same serverAllows users to submit jobs from anywhere through RESTNo code change is required do be done to your programsOrganizations can now easily overcome the existing bottlenecks that impede their ability to operationalize Spark, and instead, focus on capturing the value promised by big data. \u00a0Additional ResourcesAbout Apache SparkAzure Databricks\u2014Apache Spark as a ServiceLearning Apache Spark 2nd Edition eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/data-science-machine-learning\/dsml-demo?itm_data=DSproduct-pf-dsml","text":"\n\n\n\n\n\n\n\nData Science and Machine Learning | Databricks Demo\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/de\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/legal\/privacynotice#dbadditionalinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nic-jansma","text":"Nic Jansma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNic JansmaSenior Principal Lead Engineer at AkamaiBack to speakersNic is a software developer at Akamai building high-performance websites, apps and open-source tools, and co-chair of W3C Web Performance Working Group.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/sponsors","text":"Sponsors - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricing2023 SponsorsBecome a sponsorIf you are interested in sponsoring Data + AI Summit 2023, please contact our Sponsorship Management Team.\nOrganizing SponsorPrivacyPlatinum SponsorPrivacyPrivacyPrivacyDiamond SponsorsPrivacyPrivacyPrivacyPrivacyGold + SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyGold SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacySilver SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyBronze SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/unitycatalog","text":"Unity Catalog Demo - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnity Catalog DemosGet started for freeDatabricks Unity Catalog is a unified governance solution for all data and AI assets, including files, tables and machine learning models in your lakehouse on any cloud.Unity Catalog simplifies governance of data and AI assets on the Databricks Lakehouse Platform by providing fine-grained governance via a single standard interface based on ANSI SQL that works across clouds. With Unity Catalog, data teams benefit from a companywide catalog with centralized access permissions, audit controls, automated lineage, and built-in data search and discovery. Unity Catalog also natively supports Delta Sharing, an open standard for securely sharing live data from your lakehouse to any computing platform.Unity Catalog Overview Demo\nIn this brief demonstration, we give you a first look at Unity Catalog, a unified governance solution for all data and AI assets. Unity Catalog provides a single interface to centrally manage access permissions and audit controls for all data assets in your lakehouse, along with the capability to easily search, view lineage and share data.\nAutomated Data Lineage With Unity Catalog\nUnity Catalog automatically tracks data lineage for all workloads in SQL, R, Python and Scala. Data lineage is captured down to the table and column levels and displayed in real time with just a few clicks. Unity Catalog also captures lineage for other data assets such as notebooks, workflows and dashboards. Lineage can be retrieved via REST API to support integrations with other data catalogs and governance tools.\nDive deeper into the Unity CatalogLearn moreLearn moreCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet StartedReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/data-partner-program","text":"Programme Partenaire de donn\u00e9es | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWProgramme de partenariat avec les fournisseurs de donn\u00e9esAvec Databricks, acc\u00e9dez au vaste \u00e9cosyst\u00e8me ouvert des consommateurs de donn\u00e9esInscrivez-vous maintenant\u00c0 partir d'une plateforme unique, Databricks aide ses partenaires fournisseurs de donn\u00e9es \u00e0 mon\u00e9tiser leurs assets de donn\u00e9es aupr\u00e8s d'un vaste \u00e9cosyst\u00e8me ouvert de consommateurs de donn\u00e9es. Nos partenaires peuvent tirer parti de la plateforme Lakehouse de Databricks pour cibler davantage de clients, r\u00e9duire les co\u00fbts et offrir une exp\u00e9rience de premier plan pour tous leurs besoins de partage de donn\u00e9es.Avantages d\u2019un partenariat avec les fournisseurs de donn\u00e9esAtteindre plus de consommateursUne couverture \u00e9largie \u00e0 davantage de consommateurs de donn\u00e9es \u0000\u00e0 partir d'une plateforme ouverte et s\u00e9curis\u00e9eUne meilleure exp\u00e9rience clientTemps de configuration et d'activation r\u00e9duit pour les consommateurs de donn\u00e9esSupport marketingUne exposition accrue gr\u00e2ce au soutien marketing de DatabricksTechnologie au service des produits de donn\u00e9esExploitation de la plateforme Lakehouse, leader sur le march\u00e9, pour les donn\u00e9es, l'analytique et l'IAAcc\u00e8s aux produits et \u00e0 l'\u00e9quipe de R&DAcc\u00e8s aux \u00e9quipes en charge des produits, du Data Engineering et de l'assistance de DatabricksSolutions pour l'industrieRencontrez nos \u00e9quipes sectorielles pour \u00e9laborer des solutions adapt\u00e9es \u00e0 votre secteur d'activit\u00e9 et con\u00e7ues sp\u00e9cialement pour les cas d'usage des clientsDelta\u00a0Sharing pour les fournisseurs de donn\u00e9esDatabricks s'int\u00e8gre en mode natif \u00e0 Delta\u00a0Sharing, le premier protocole ouvert au monde pour partager des donn\u00e9es en toute s\u00e9curit\u00e9 entre les organisations, en temps r\u00e9el et ind\u00e9pendamment de la plateforme sur laquelle elles se trouvent.Delta\u00a0Sharing est approuv\u00e9 par un large \u00e9cosyst\u00e8meClients open sourceClients commerciauxBusiness IntelligenceAnalytiqueGouvernanceFournisseurs de donn\u00e9esPr\u00eat \u00e0 vous lancer\u00a0?Inscrivez-vous maintenantTrouver un partenaireProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c31da9bde0850\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/karthik-ramasamy\/#","text":"Karthik Ramasamy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKarthik RamasamyHead of Streaming at DatabricksBack to speakersKarthik Ramasamy is the Head of Streaming at Databricks. Before joining Databricks, he was a Senior Director of Engineering, managing the Pulsar team at Splunk. Before Splunk, he was the co-founder and CEO of Streamlio that focused on building next-generation event processing infrastructure using Apache Pulsar and led the acquisition of Streamlio by Splunk. Before Streamlio, he was the engineering manager and technical lead for real-time infrastructure at Twitter where he co-created Twitter Heron, which was open sourced and used by several companies. He has two decades of experience working with companies such as Teradata, Greenplum and Juniper in their rapid growth stages building parallel databases, big data infrastructure and networking. He co-founded Locomatix, a company that specializes in real-time streaming processing on Hadoop and Cassandra using SQL, which was acquired by Twitter. Karthik has a Ph.D. in computer science from the University of Wisconsin, Madison, with a focus on big data and databases. During his college tenure, several of the research projects he participated in were later spun off as a company acquired by Teradata. Karthik is the author of several publications, patents and a popular book, Network Routing: Algorithms, Protocols and Architectures.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-harris\/#","text":"Ryan Harris - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan HarrisPrincipal Cybersecurity Engineer at HSBCBack to speakersRyan Harris is a Principal Cybersecurity Engineer on the Global Cybersecurity Science & Analytics Team at HSBC, focusing on transforming cybersecurity into a data-driven organization by designing and building a secure cloud-native environment to analyze petabytes of security data. For over 20 years he has leveraged data to disrupt financial services threat actors, preventing $100M+ in fraud. He served as a Captain in the USAF, and has a degree in Cognitive Science & Computer Science from UVa.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/dataaisummit\/?itm_data=menu-learn-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sidharth-kunnath\/#","text":"Sidharth Kunnath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSidharth KunnathPrincipal Architect at American Airlines, IncBack to speakersOver 18 years of IT experience exclusively in designing and building enterprise data analytical solutions deployed over enterprise data warehouses and data lakes, both within on-premises and cloud (Azure)\nOver 4 years of experience implementing data analytics projects within Azure data analytical ecosystem, leveraging Azure services like Event Hub (AEH), Stream Analytics (ASA), Azure Functions (AF), Databricks (ADB) and Azure Datalake Storage (ADLS)\nExperience in defining enterprise data strategy and its physical implementation across the organization\nExperience in Application, Solution and Data Architecture, working both with technology and the business, translating between the two\nExperience in implementation of real-time data streaming layer using Azure streaming architecture as well as real-time data serving layer using APIs installed over NoSQL databases like Cassandra\nExtensive experience implementing data warehousing projects based on Teradata\nDomain knowledge of airline business including subject areas like revenue management & performance, customer loyalty, flight operations, inventory, maintenance & engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lee-yang\/#","text":"Lee Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLee YangSr. Principal SW Engineer at NVIDIABack to speakersLee Yang is a Sr. Principal Software Engineer at NVIDIA, working on integrating deep learning with Apache Spark. Before that, at Yahoo, he created and open-sourced TensorFlowOnSpark, a framework for large-scale, distributed TensorFlow training and inference using Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/customers","text":"Databricks Customer Stories | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks CustomersDiscover how innovative companies across every industry are leveraging the Databricks Lakehouse Platform for successSee all customersExplore the Burberry storyFeatured Stories\n\n\nCustomer Story\n\nAT&T democratizes data to prevent fraud, reduce churn and increase CLV\nDatabricks Lakehouse has helped AT&T accelerate AI across operations, including decreasing fraud by 70%\u201380%\n\nRead more\n\n\nCustomer Story\n\nShell innovates with energy solutions for a cleaner world\nDatabricks Lakehouse helps to democratize data and modernize operations globally\n\nRead more\n\n\nCustomer Story\n\nABN AMRO transforms banking on a global scale\nABN AMRO puts data and Al into action with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nRolls-Royce delivers a greener future for air travel\nRolls-Royce decreases carbon through real-time data collection with Databricks Lakehouse\n\nWatch video\n\n\nCustomer Story\n\nDelivering integrity and efficiency for the U.S. Postal Service\nUSPS OIG supports efficient postal service to millions with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nWalgreens personalizes pharmacy care to improve patient outcomes\nDatabricks Lakehouse helps Walgreens personalize patient experiences for over 825 million prescriptions filled annually\n\nRead moreExplore all customersThe Data Team EffectData teams are the united force that are solving the world\u2019s toughest problems.Be the next success storyContact usResourcesCustomer StoryLearn how Databricks enables Cond\u00e9 Nast to deliver personalized content to its customers.Learn moreWebinarLearn how Apple and Disney+ unified analytics and AI for successWatch nowPodcastHear about the role of data and AI in healthcare equity from the CDAO at HumanaWatch nowReady to get started?Try for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/retail-industry-solutions","text":"A solu\u00e7\u00e3o de Data Lakehouse para o setor de varejo e CPG - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWExplorar as solu\u00e7\u00f5es lakehouse para o setor de varejoOs dados unificados, as an\u00e1lises e a plataforma de IA que os varejistas usam para fornecer mais em cada fase da jornada do clienteInscrever-seEntre em contatoMelhor desempenho, maior escala, TCO mais baixoLakehouse para o setor de varejoIntegre dados e cargas de trabalho de IA com recursos de compartilhamento integrados e governan\u00e7a para garantir que as equipes internas e externas tenham acesso aos dados de que precisam, no momento certoImpacto em toda a cadeia de valorEngajamento do clienteMais relevante e altamente personaliz\u00e1vel em todos os pontos de contatoAo obter uma vis\u00e3o precisa e abrangente de seus clientes em tempo real, os varejistas t\u00eam tudo de que precisam para criar relacionamentos personalizados, incluindo entender o sentimento nos canais e personalizar recomenda\u00e7\u00f5es. O resultado \u00e9 maior lucratividade e fidelidade.Efici\u00eancia operacionalProdutividade dos funcion\u00e1riosDesempenho do produtoParceiros e solu\u00e7\u00f5es para o setor de varejoSolu\u00e7\u00f5es de an\u00e1lises de dados e IA sem compromisso criadas especificamente para o seu setorOs aceleradores de solu\u00e7\u00f5es da Databricks s\u00e3o guias criados especificamente para acelerar os resultados usando notebooks totalmente funcionais e pr\u00e1ticas recomendadas. Economize tempo de descoberta, design, desenvolvimento e testes em casos de uso, como classifica\u00e7\u00e3o de propens\u00e3o, valor do tempo de vida do cliente, otimiza\u00e7\u00e3o da separa\u00e7\u00e3o de pedidos e muito mais.Previs\u00e3o refinadaGere previs\u00f5es em grande escala em menos tempo\nAproveite o poder computacional distribu\u00eddo da Plataforma Databricks Lakehouse para fazer previs\u00f5es granulares de maneira mais eficiente no n\u00edvel de estoque da loja.Comece agoraSegmenta\u00e7\u00e3o de clientesMelhore a segmenta\u00e7\u00e3o de clientes\nGere previs\u00f5es de compra mais precisas com base no comportamento por meio da segmenta\u00e7\u00e3o avan\u00e7ada de clientes usando dados de vendas, campanhas, sistemas de promo\u00e7\u00e3o e muito mais.Comece agoraAn\u00e1lises de ponto de venda em tempo realCalcule estoques em tempo real em v\u00e1rios locais de loja para melhorar as margens de varejo\nIngira rapidamente todas as fontes e tipos de dados do ponto de venda em escala para obter insights em tempo real que atendam \u00e0s necessidades urgentes de informa\u00e7\u00f5es na loja.Comece agoraExplorar aceleradores para o setor de varejoTemos parceria com as principais empresas de consultoria para oferecer solu\u00e7\u00f5es inovadoras e dedicadas a cada setor de neg\u00f3cios. As solu\u00e7\u00f5es Databricks Brickbuilder ajudam a reduzir custos e maximizar o valor dos seus dados. Elas s\u00e3o apoiadas por d\u00e9cadas de experi\u00eancia no setor e projetadas para a Plataforma Databricks Lakehouse para atender \u00e0s suas necessidades.Vis\u00e3o unificada da demandaMaximize a precis\u00e3o, granularidade e pontualidade com um plano de demanda baseado em uma \u00fanica fonte confi\u00e1vel.Saiba maisGerenciamento de crescimento de receitaAcelere a an\u00e1lise de dados de faturamento, dados externos de mercado, not\u00edcias e dados extra\u00eddos da internet para explorar as tend\u00eancias do varejo.Saiba maisTrellisResolva desafios relacionados a previs\u00f5es de demanda, reabastecimento, compras, pre\u00e7os e servi\u00e7os de promo\u00e7\u00e3o.Saiba maisExplorar todas as solu\u00e7\u00f5es Brickbuilder\u201cAgora, no n\u00edvel do cliente, podemos combinar informa\u00e7\u00f5es de compra online e offline, o que antes era uma tarefa dif\u00edcil. Essa vis\u00e3o omnicanal nos permite construir um mecanismo de recomenda\u00e7\u00e3o online mais abrangente, que gera um engajamento tremendo.\u201d\n\u2014 Wendell Kuling, gerente de data science e an\u00e1lises da Jumbo\n\u201cA Databricks nos permite oferecer a melhor experi\u00eancia aos clientes em todos os mercados. Com base na Plataforma Lakehouse, nossos stakeholders e desenvolvedores podem colaborar melhor e obter tend\u00eancias e insights importantes necess\u00e1rios para atender nossos 180 milh\u00f5es de clientes.\u201c\n\u2014 Sergiy Tkachuk, diretor de data science da Reckitt\n\u201cCada vez mais unidades de neg\u00f3cios est\u00e3o usando a plataforma de maneira self-service, o que antes era imposs\u00edvel. Estou extremamente impressionada com o impacto positivo que o Databricks teve na Columbia.\u201d\n\u2014 Lara Minor, gerente s\u00eanior de dados empresariais, Columbia Sportswear\nRecursosTour autoguiadoTodos os recursos de que voc\u00ea precisa para explorar o lakehouse para o setor de varejoWebinarsAcelera\u00e7\u00e3o da tomada de decis\u00f5es em tempo real no setor de varejoe-booksBig Book of Retail Use CasesProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/tensile-ai-accelerated-sas-migration","text":"SAS Migration Accelerator by Tensile AI and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionSAS Migration Accelerator by Tensile AIMigration solution developed by Tensile AI and powered by the Databricks Lakehouse Platform\nGet startedEnsure a rapid and sound migration processAs organizations continue to modernize data and analytic capabilities with the Databricks Lakehouse Platform, mission-critical SAS applications are often a barrier to realizing the maximum benefits of the cloud. Tensile AI has deep SAS and Databricks expertise with extensive experience leading large-scale data and analytic migrations. Tensile AI\u2019s SAS Migration Accelerator enables the rapid migration of SAS processes with minimal disruption and risk to internal teams, allowing organizations the flexibility to move single, critical workloads or the entire enterprise, according to defined modernization goals. This results in superior performance and cost reduction. With Tensile AI\u2019s solution, you can:Quickly and safely move complex SAS workloads to the cloudAchieve significant savings through product rationalization and licensing costs \u2014 the average savings is 35%Increase value through system performance \u2014 with an average performance gain of 85%Get startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/24\/data-warehousing-modeling-techniques-and-their-implementation-on-the-databricks-lakehouse-platform.html","text":"Different Data Warehousing Modeling Techniques and How to Implement them on the Databricks Lakehouse Platform - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorData Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse PlatformUsing Data Vaults and Star Schemas on the Lakehouseby Soham Bhatt and Deepak SekarJune 24, 2022 in Platform BlogShare this postThe lakehouse is a new data platform paradigm that combines the best features of data lakes and data warehouses. It is designed as a large-scale enterprise-level data platform that can house many use cases and data products. It can serve as a single unified enterprise data repository for all of your:data domains,real-time streaming use cases,data marts,disparate data warehouses,data science feature stores and data science sandboxes, anddepartmental self-service analytics sandboxes.Given the variety of the use cases \u2014 different data organizing principles and modeling techniques may apply to different projects on a lakehouse. Technically, the Databricks Lakehouse Platform can support many different data modeling styles. In this article, we aim to explain the implementation of the Bronze\/Silver\/Gold data organizing principles of the lakehouse and how different data modeling techniques fit in each layer.What is a Data Vault?A Data Vault is a more recent data modeling design pattern used to build data warehouses for enterprise-scale analytics compared to Kimball and Inmon methods.Data Vaults organize data into three different types: hubs, links, and satellites. Hubs represent core business entities, links represent relationships between hubs, and satellites store attributes about hubs or links.Data Vault focuses on agile data warehouse development where scalability, data integration\/ETL and development speed are important. Most customers have a landing zone, Vault zone and a data mart zone which correspond to the Databricks organizational paradigms of Bronze, Silver and Gold layers. The Data Vault modeling style of hub, link and satellite tables typically fits well in the Silver layer of the Databricks Lakehouse.Learn more about Data Vault modeling at Data Vault Alliance.A diagram showing how Data Vault modeling works, with hubs, links, and satellites connecting to one another.What is Dimensional Modeling?Dimensional modeling is a bottom-up approach to designing data warehouses in order to optimize them for analytics. Dimensional models are used to denormalize business data into dimensions (like time and product) and facts (like transactions in amounts and quantities), and different subject areas are connected via conformed dimensions to navigate to different fact tables.The most common form of dimensional modeling is the star schema. A star schema is a multi-dimensional data model used to organize data so that it is easy to understand and analyze, and very easy and intuitive to run reports on. Kimball-style star schemas or dimensional models are pretty much the gold standard for the presentation layer in data warehouses and data marts, and even semantic and reporting layers. The star schema design is optimized for querying large data sets.A star schema exampleBoth normalized Data Vault (write-optimized) and denormalized dimensional models (read-optimized) data modeling styles have a place in the Databricks Lakehouse. The Data Vault\u2019s hubs and satellites in the Silver layer are used to load the dimensions in the star schema, and the Data Vault\u2019s link tables become the key driving tables to load the fact tables in the dimension model. Learn more about dimensional modeling from the Kimball Group.Data organization principles in each layer of the LakehouseA modern lakehouse is an all-encompassing enterprise-level data platform. It is highly scalable and performant for all kinds of different use cases such as ETL, BI, data science and streaming that may require different data modeling approaches. Let's see how a typical lakehouse is organized:A diagram showing characteristics of the Bronze, Silver, and Gold layers of the Data Lakehouse Architecture.Bronze layer \u2014 the Landing ZoneThe Bronze layer is where we land all the data from source systems. The table structures in this layer correspond to the source system table structures \u201cas-is,\u201d aside from optional metadata columns that can be added to capture the load date\/time, process ID, etc. The focus in this layer is on change data capture (CDC), and the ability to provide an historical archive of source data (cold storage), data lineage, auditability, and reprocessing if needed \u2014 without rereading the data from the source system.In most cases, it's a good idea to keep the data in the Bronze layer in Delta format, so that subsequent reads from the Bronze layer for ETL are performant \u2014 and so that you can do updates in Bronze to write CDC changes. Sometimes, when data arrives in JSON or XML formats, we do see customers landing it in the original source data format and then stage it by changing it to Delta format. So sometimes, we see customers manifest the logical Bronze layer into a physical landing and staging zone.Storing raw data in the original source data format in a landing zone also helps with consistency wherein you ingest data via ingestion tools that don\u2019t support Delta as a native sink or where source systems dump data onto object stores directly. This pattern also aligns well with the autoloader ingestion framework wherein sources land the data in landing zone for raw files and then Databricks AutoLoader converts the data to Staging layer in Delta format.Silver layer \u2014 the Enterprise Central RepositoryIn the Silver layer of the Lakehouse, the data from the Bronze layer is matched, merged, conformed and cleaned (\u201cjust-enough\u201d) so that the Silver layer can provide an \u201centerprise view\u201d of all its key business entities, concepts and transactions. This is akin to an Enterprise Operational Data Store (ODS) or a Central Repository or Data domains of a Data Mesh (e.g. master customers, products, non-duplicated transactions and cross-reference tables). This enterprise view brings the data from different sources together, and enables self-service analytics for ad-hoc reporting, advanced analytics and ML. It also serves as a source for departmental analysts, data engineers and data scientists to further create data projects and analysis to answer business problems via enterprise and departmental data projects in the Gold layer.In the Lakehouse Data Engineering paradigm, typically the (Extract-Load-Transform) ELT methodology is followed vs. traditional Extract-Transform-Load(ETL). ELT approach means only minimal or \u201cjust-enough\u201d transformations and data cleansing rules are applied while loading the Silver layer. All the \u201centerprise level\u201d rules are applied in the Silver layer vs. project-specific transformational rules, which are applied in the Gold layer. Speed and agility to ingest and deliver the data in Lakehouse is prioritized here.From a data modeling perspective, the Silver Layer has more 3rd-Normal Form like data models. Data Vault-like write-performant data architectures and data models can be used in this layer. If using a Data Vault methodology, both the raw Data Vault and Business Vault will fit in the logical Silver layer of the lake \u2014 and the Point-In-Time (PIT) presentation views or materialized views will be presented in the Gold Layer.Gold layer \u2014 the Presentation LayerIn the Gold layer, multiple data marts or warehouses can be built as per dimensional modeling\/Kimball methodology. As discussed earlier, the Gold layer is for reporting and uses more denormalized and read-optimized data models with fewer joins compared to the Silver layer. Sometimes tables in the Gold Layer can be completely denormalized, typically if the data scientists want it that way to feed their algorithms for feature engineering.ETL and data quality rules that are \u201cproject-specific\u201d are applied when transforming data from the Silver layer to Gold layer. Final presentation layers such as data warehouses, data marts or data products like customer analytics, product\/quality analytics, inventory analytics, customer segmentation, product recommendations, marketing\/sales analytics etc. are delivered in this layer. Kimball style star-schema based data models or Inmon style Data marts fit in this Gold Layer of the Lakehouse. Data Science Laboratories and Departmental Sandboxes for self-service analytics also belong in the Gold Layer.The Lakehouse Data Organization ParadigmTo summarize, data is curated as it moves through the different layers of a Lakehouse.The Bronze layer uses the data models of source systems. If data is landed in raw formats, it is converted to DeltaLake format within this layer.The Silver layer for the first time brings the data from different sources together and conforms it to create an Enterprise view of the data \u2014 typically using a more normalized, write-optimized data models that are typically 3rd-Normal Form-like or Data Vault-like.The Gold layer is the presentation layer with more denormalized or flattened data models than the Silver layer, typically using Kimball-style dimensional models or star schemas. The Gold layer also houses departmental and data science sandboxes to enable self-service analytics and data science across the enterprise. Providing these sandboxes and their own separate compute clusters prevents the Business teams from creating their own copies of data outside of the Lakehouse.This Lakehouse data organization approach is meant to break data silos, bring teams together, and empower them to do ETL, streaming, and BI and AI on one platform with proper governance. Central data teams should be the enablers of innovation in the organization, speeding up the onboarding of new self-service users, as well as the development of many data projects in parallel \u2014 rather than the data modeling process becoming the bottleneck. The Databricks Unity Catalog provides search & discovery, governance and lineage on the Lakehouse to ensure good data governance cadence.Build your Data Vaults and star schema data warehouses with Databricks SQL today.How data is curated as it moves through the various Lakehouse layers.Further reading:Five Simple Steps for Implementing a Star Schema in Databricks With Delta LakeBest practices to implement a Data Vault model in Databricks LakehouseDimensional Modeling Best practice & Implementation on Modern LakehouseIdentity Columns to Generate Surrogate Keys Are Now Available in a Lakehouse Near You!Load an EDW Dimensional Model in Real Time With Databricks LakehouseTry Databricks for freeGet StartedRelated postsFive Simple Steps for Implementing a Star Schema in Databricks With Delta LakeMay 20, 2022 by Cary Moore, Lucas Bilbro and Brenner Heintz in Product\nMost data warehouse developers are very familiar with the ever-present star schema. Introduced by Ralph Kimball in the 1990s, a star schema is...\nPrescriptive Guidance for Implementing a Data Vault Model on the Databricks Lakehouse PlatformJune 24, 2022 by Soham Bhatt, Tanveer Shaikh and Glenn Wiebe in Solutions\nThere are many different data models that you can use when designing an analytical system, such as industry-specific domain models, Kimball, Inmon, and...\nData Modeling Best Practices & Implementation on a Modern LakehouseOctober 20, 2022 by Leo Mao, Abhishek Dey, Justin Breese and Soham Bhatt in Platform Blog\nA Large number of our customers are migrating their legacy data warehouses to Databricks Lakehouse as it enables them to modernize not only...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/automating-the-ml-lifecycle-with-databricks-machine-learning?itm_data=product-resources-automatingMLlifecycle","text":"Automating the ML Lifecycle With Databricks Machine Learning | DatabricksOn-demand webinar | Q&AAutomating the ML Lifecycle With Databricks Machine LearningCome learn about the key elements of the machine learning lifecycle and how to automate away the most time-consuming manual, repeated and error-prone processes. In this webinar, we\u2019ll discuss and demonstrate how Databricks Machine Learning can help you automate model training, tuning and the production process \u2014 saving you hours of development time.We\u2019ll also cover how data engineers, data scientists, ML engineers and DevOps can collaborate and make the MLOps lifecycle more efficient and productive. Along the way, we\u2019ll highlight the newest capabilities of Databricks Machine Learning, including AutoML, the Feature Store and Model Registry webhooks.Join us to learn how to:Ingest, prepare and featurize dataTune and train modelsManage the model lifecycleServe, monitor and retrain models in productionSpeakerRafi KurlansikSr. Solutions Architect, Machine LearningDatabricksWatch On-demandProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/manufacturing-industry-solutions","text":"Solutions pour l'industrie manufacturi\u00e8re \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWD\u00e9couvrez le lakehouse pour la fabricationR\u00e9duisez vos co\u00fbts, optimisez la productivit\u00e9 et unifiez votre \u00e9cosyst\u00e8me de donn\u00e9es sur la seule plateforme con\u00e7ue pour r\u00e9pondre aux besoins des fabricantsS'inscrireNous contacterUn TCO r\u00e9duit. De meilleures performances. Davantage d'\u00e9volutivit\u00e9.Le lakehouse pour la fabricationLorsque vous unifiez toutes vos charges de travail de donn\u00e9es, d'analytique et d'IA au sein d'une plateforme int\u00e9grant le partage et la gouvernance, les \u00e9quipes internes et externes acc\u00e8dent aux donn\u00e9es dont elles ont besoin au moment voulu.Un impact sur toute la cha\u00eene de valeurEngagement des clientsDes r\u00e9sultats pr\u00e9cis et une exp\u00e9rience sans friction pour les clientsLorsque vous avez une vue \u00e0 360\u00a0degr\u00e9s sur vos clients, vos op\u00e9rations et vos actifs, vous pouvez assurer les plus hauts niveaux de disponibilit\u00e9, de qualit\u00e9 de service et de valeur \u00e9conomique sur l'ensemble du cycle de vie des produits. Cette vue alimente l'individualisation des r\u00e9sultats clients, une approche proactive du service de terrain et l'\u00e9mergence de solutions strat\u00e9giques diff\u00e9renci\u00e9es.Efficacit\u00e9 op\u00e9rationnelleProductivit\u00e9 des collaborateursInnovation produitSolutions et partenaires pour la fabricationDes solutions d\u2019analytique et d\u2019IA sans compromis, sp\u00e9cialement pens\u00e9es pour les fabricantsLes acc\u00e9l\u00e9rateurs de solutions Databricks sont des guides sp\u00e9cialis\u00e9s con\u00e7us pour acc\u00e9l\u00e9rer les r\u00e9sultats dans la fabrication, \u00e0 l'aide de notebooks enti\u00e8rement fonctionnels et de bonnes pratiques. Gagnez du temps au moment de la d\u00e9couverte, de la conception, du d\u00e9veloppement et des tests dans des cas d'usage cl\u00e9s\u00a0: jumeau num\u00e9rique, efficacit\u00e9 globale des \u00e9quipements, pr\u00e9visions, etc.Surveillance de l'efficacit\u00e9 globale des \u00e9quipements et des KPIAssurez un monitoring performant et \u00e9volutif des \u00e9quipements, de bout en bout\nImportez et traitez de fa\u00e7on incr\u00e9mentielle diff\u00e9rents formats de donn\u00e9es provenant des capteurs et appareils IoT. Puis calculez et r\u00e9v\u00e9lez des KPI et des m\u00e9triques pour produire des insights utiles.D\u00e9marrerPr\u00e9visions \u00e0 la pi\u00e8ce pr\u00e8sAnticipez la demande \u00e0 la pi\u00e8ce pr\u00e8s pour une fabrication rationalis\u00e9e\nR\u00e9alisez des pr\u00e9visions de demande \u00e0 la pi\u00e8ce pr\u00e8s plut\u00f4t qu'au niveau global afin de minimiser les perturbations de la cha\u00eene d'approvisionnement et accro\u00eetre les ventes.D\u00e9marrerJumeaux num\u00e9riquesGagnez en efficacit\u00e9 op\u00e9rationnelle et am\u00e9liorez la prise de d\u00e9cision\nTraitez les donn\u00e9es r\u00e9elles en continu, calculez des insights \u00e0 grande \u00e9chelle pour les injecter dans diff\u00e9rentes applications en aval, et optimisez les op\u00e9rations de l'usine en prenant des d\u00e9cisions data-driven.D\u00e9marrerD\u00e9couvrez les acc\u00e9l\u00e9rateurs pour la fabricationNous nous sommes associ\u00e9s \u00e0 des cabinets de conseil de premier plan pour proposer des solutions innovantes d\u00e9di\u00e9es \u00e0 chaque secteur d'activit\u00e9. Les solutions Databricks Brickbuilder vous aident \u00e0 r\u00e9duire les co\u00fbts et \u00e0 optimiser la valeur de vos donn\u00e9es. Les solutions Brickbuilder s'appuient sur des d\u00e9cennies d\u2019expertise sectorielle et sont pens\u00e9es pour la plateforme Databricks Lakehouse, pour r\u00e9pondre \u00e0 vos besoins exacts.Fabrication intelligente Exploitez la puissance de vos donn\u00e9es, favorisez l'interop\u00e9rabilit\u00e9 et g\u00e9n\u00e9rez des insights riches \u00e0 grande \u00e9chelle avec l'analytique et l'IA.En savoir plusInspection de la qualit\u00e9Automatisez le contr\u00f4le qualit\u00e9 gr\u00e2ce \u00e0 la vision par ordinateur pour d\u00e9tecter les d\u00e9fauts, les corps \u00e9trangers, les anomalies et les erreurs de configuration.En savoir plusUne gestion pr\u00e9dictive du risque d'approvisionnementObtenez une visibilit\u00e9 granulaire sur les flux de commande et les performances des fournisseurs pour gagner en efficacit\u00e9, g\u00e9rer les exceptions et am\u00e9liorer la r\u00e9silience.En savoir plusD\u00e9couvrez toutes les solutions partenaires\u00ab\u00a0Le lakehouse Databricks nous permet de rendre les donn\u00e9es plus accessibles dans toute l'organisation, afin de construire les v\u00e9hicules \u00e9lectriques les plus innovants et les plus fiables au monde.\u00a0\u00bb\n\u2013 Wassym Bensaid, Vice President of Software Development, Rivian\n\u00ab\u00a0Au fil des ans, l\u2019utilisation de Databricks s\u2019est consid\u00e9rablement \u00e9largie. Au d\u00e9part, Databricks \u00e9tait notre plateforme d'IA et de big data, mais les fronti\u00e8res de son champ d'action ont \u00e9t\u00e9 repouss\u00e9es. Une classe enti\u00e8rement nouvelle d'ing\u00e9nieurs citoyens et de data scientists l'utilise aujourd'hui comme un outil de Business Intelligence moderne pour prendre des d\u00e9cisions commerciales plus \u00e9clair\u00e9es.\u00a0\u00bb\n\u2013 Daniel Jeavons, Directeur g\u00e9n\u00e9ral, Centre d'excellence pour les analytiques avanc\u00e9es, Shell\n\u00ab\u00a0La plateforme Databricks nous aide \u00e0 minimiser les risques pesant sur la disponibilit\u00e9 des moteurs, \u00e0 r\u00e9duire les d\u00e9lais d'obtention des pi\u00e8ces d\u00e9tach\u00e9es et \u00e0 g\u00e9rer la rotation des stocks plus efficacement. Et c'est gr\u00e2ce \u00e0 tout cela que nous d\u00e9livrons TotalCare, le programme de maintenance Power-by-the-Hour (PBH) num\u00e9ro\u00a0un du secteur de l'aviation.\u00a0\u00bb\n\u2014 Stuart Hughes, Directeur de l'informatique et du num\u00e9rique, Rolls-Royce Civil Aerospace\nRessourcese-bookExploitez la puissance de vos donn\u00e9es ERPWebinairesAm\u00e9liorer la maintenance pr\u00e9dictive dans la fabrication gr\u00e2ce aux donn\u00e9es et \u00e0 l'IAe-bookQuatre forces motrices pour la fabrication intelligentePr\u00eat \u00e0 vous lancer\u00a0?Nous serions ravis de conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.ESSAYER GRATUITEMENT DATABRICKSNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/varun-sharma\/#","text":"Varun Sharma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVarun SharmaPrincipal Data Engineer at Visa Inc.Back to speakersVarun Sharma is a Principal Data Engineer at Visa's Data and AI platform, with over a decade of Big Data experience in the finance domain. At Visa, Varun has been instrumental in building a high-performance data engineering platform to power the company's analytics and machine learning applications. Varun has a deep understanding of distributed computing like frameworks like Apache Spark and Hadoop. He's very passionate about making data accessible to everyone.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arthur-li\/#","text":"Arthur Li - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArthur LiSenior Software Engineer at InstacartBack to speakersArthur Li is a software engineer who has been working at Instacart for the past two years focusing on batch data processing infrastructure. He has contributed to the company's data platform team by implementing data collection and management strategies that have streamlined the company's data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chao-sun","text":"Chao Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChao SunSoftware Engineer at AppleBack to speakersChao is currently a software engineer working at Apple, focusing on open source Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/media-and-entertainment","text":"Solutions pour le secteur des m\u00e9dias et du divertissement \u2013 Databricks Lakehouse \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks pour le secteur des m\u00e9dias et du divertissementLes donn\u00e9es, l'analytique et l'IA au service de l'avenir des m\u00e9diasD\u00e9marrerPlanifier une d\u00e9moLes quatre d\u00e9fis li\u00e9s aux donn\u00e9es dans le secteur des m\u00e9dias et du divertissementCr\u00e9er un profil d'audience unifi\u00e9\nParce que les donn\u00e9es sont collect\u00e9es, stock\u00e9es et g\u00e9r\u00e9es dans des syst\u00e8mes disparates, les entreprises de m\u00e9dias ne parviennent pas \u00e0 obtenir une image globale de leur audience et des informations sur les annonceurs.Offrir une exp\u00e9rience utilisateur exceptionnelle\nLes consommateurs attendent en permanence des interactions individualis\u00e9es et sans friction, sur tous les supports. Le d\u00e9fi\u00a0: d\u00e9livrer ces exp\u00e9rience en temps r\u00e9el, \u00e0 grande \u00e9chelle.Exploiter l'int\u00e9gralit\u00e9 de vos donn\u00e9es m\u00e9dias\nLes data warehouses traditionnels sont incapables de traiter les donn\u00e9es non structur\u00e9es telles que les fichiers vid\u00e9o, image et audio, ce qui emp\u00eache les entreprises de lib\u00e9rer tout le potentiel de leurs assets les plus prometteurs.Au-del\u00e0 de l'agr\u00e9gation, l'analytique avanc\u00e9e\nLes cas d'usage complexes de l'IA concernant le cycle de vie de la publicit\u00e9 et des consommateurs n\u00e9cessitent actuellement l'acquisition et l'harmonisation de jeux de donn\u00e9es massifs, ce qui a un co\u00fbt consid\u00e9rable.D\u00e9couvrez Data Lakehouse\u00a0: le meilleur des deux mondes sur une seule plateformeUn data lakehouse combine le meilleur des data warehouses et des data lakes en une plateforme simple et unique afin de traiter tous vos cas d'usage de donn\u00e9es, d'analytique et d'IA. Il s'appuie sur une base de donn\u00e9es ouverte et fiable qui traite efficacement tous types de donn\u00e9es et applique une approche commune de gouvernance et de s\u00e9curit\u00e9 \u00e0 l'ensemble de vos donn\u00e9es et plateformes cloud.En savoir plusLe lakehouse en actionD\u00e9couvrez les possibilit\u00e9s du lakehouse Databricks pour votre secteur d'activit\u00e9Technologies marketing et publicit\u00e9G\u00e9rez les marges, apportez \u00e0 vos op\u00e9rations une rigueur ax\u00e9e sur les donn\u00e9es, am\u00e9liorez la performances de vos contenus et optimisez le travail cr\u00e9atif pour harmoniser les t\u00e2ches de vos \u00e9quipes.En savoir plusDiffusion et streamingCr\u00e9ez des exp\u00e9riences individualis\u00e9es \u00e0 grande \u00e9chelle, am\u00e9liorez les performances de vos campagnes et extrayez davantage de valeur de l'ensemble de votre portefeuille de contenu.En savoir plusJeux vid\u00e9osExploitez les donn\u00e9es et l'IA pour am\u00e9liorer la conception des jeux, accro\u00eetre l'acquisition et l'engagement des joueurs, et maximiser la mon\u00e9tisation et la fid\u00e9lisation.En savoir plusPourquoi Databricks pour le secteur des m\u00e9dias et du divertissement\u00a0?Toutes vos donn\u00e9es, votre analytique et votre IA r\u00e9unies sur une seule plateforme\nExploitez toute la valeur de vos donn\u00e9es pour optimiser l'engagement de vos audiences, vos campagnes et leur mon\u00e9tisation.Optimis\u00e9 pour le temps r\u00e9el\nD\u00e9couvrez des insights exploitables, r\u00e9alisez vos objectifs de personnalisation et am\u00e9liorez l'exp\u00e9rience de votre audience gr\u00e2ce au machine learning.Acc\u00e9l\u00e9rer vos r\u00e9sultats commerciaux\nPuisez dans nos Acc\u00e9l\u00e9rateurs de solutions pour ing\u00e9rer plus facilement les donn\u00e9es clients, notamment pour analyser l'engagement sur les flux de clics. D\u00e9livrez des cas d'usage puissants comme les moteurs de recommandation et l'attribution multi-contact.Une fiabilit\u00e9 et une performance de premier ordre\nLe lakehouse Databricks offre une combinaison in\u00e9gal\u00e9e de vitesse, d'\u00e9volutivit\u00e9 et de rentabilit\u00e9. Il n'est pas \u00e9tonnant que le meilleur data warehouse soit un lakehouse.Transformer le secteur des m\u00e9dias et du divertissement avec le lakehouse\n\u00ab\u00a0Avec la plateforme Databricks Lakehouse sur AWS, Warner Bros. Discovery invente le futur de la d\u00e9couverte de contenu et de l'exp\u00e9rience de ses audiences. En exploitant les donn\u00e9es pour pr\u00e9dire plus pr\u00e9cis\u00e9ment le comportement des consommateurs et proposer des recommandations de contenu individualis\u00e9es en temps r\u00e9el, nous personnalisons l'exp\u00e9rience du spectateur et am\u00e9liorons l'engagement global de nos clients\u00a0\u00bb\u2014 Martin Ma, GVP, Ing\u00e9nierie chez Warner Bros. Discovery\u00c9clairages de haut niveau sur les donn\u00e9es, l'analytique et l'IAD\u00e9couvrez les projets men\u00e9s par d'autres d\u00e9cideurs du secteur des m\u00e9dias et du divertissement pour optimiser leur strat\u00e9gie de donn\u00e9esEn savoir plusQue pouvez-vous faire avec un lakehouse\u00a0?\nAcc\u00e9l\u00e9rez vos r\u00e9sultats en termes d'audience et de publicit\u00e9 gr\u00e2ce \u00e0 une plateforme de donn\u00e9es, d'analytique et d'IA collaborative et ouverteUne vue \u00e0 360\u00b0 sur votre audience\nRassemblez toutes vos donn\u00e9es, structur\u00e9es ou non (parcours de navigation, informations d\u00e9mographiques, r\u00e9seaux sociaux, etc.) au sein d'une m\u00eame plateforme d'analytique et d'IA. Munies d'une vision holistique du parcours du consommateur, les organisations peuvent interpr\u00e9ter les pr\u00e9f\u00e9rences de contenu et ainsi affiner la personnalisation des exp\u00e9riences et le ciblage de la publicit\u00e9 et de l'engagement.R\u00e9duire l'attrition, augmenter l'ARPU\nEn exploitant une plateforme cloud agile, une entreprise peut rapidement traiter des quantit\u00e9s massives de donn\u00e9es avec un haut niveau de fiabilit\u00e9, puis les injecter dans des syst\u00e8mes en aval pour d\u00e9livrer des exp\u00e9riences personnalis\u00e9es sur tous les canaux, \u00e0 tout moment. Les consommateurs attendent toujours plus de recommandations en temps r\u00e9el, et leur attention fait l'objet d'une concurrence f\u00e9roce parmi les acteurs des m\u00e9dias. Dans ce contexte, une capacit\u00e9 de personnalisation proche du temps r\u00e9el devient un imp\u00e9ratif pour de nombreuses entreprises.Les biblioth\u00e8ques de contenus comme source de revenus\nLes entreprises du secteur des m\u00e9dias se basent sur des donn\u00e9es non structur\u00e9es (fichiers vid\u00e9o, image et audio)\u00a0: elles doivent donc imp\u00e9rativement \u00eatre en capacit\u00e9 de les analyser pour assurer une gestion efficace de leurs assets multim\u00e9dia. Le lakehouse pour le monitoring et l'\u00e9valuation permet aux responsables marketing d'exploiter les contenus archiv\u00e9s pour \u00e9laborer des campagnes. Il permet aussi aux \u00e9quipes de production de rechercher des contenus existants \u00e0 int\u00e9grer \u00e0 de nouvelles cr\u00e9ations, et aux \u00e9quipes de vente d'identifier des contenus \u00e0 vendre \u00e0 d'autres entreprises du secteur.Exploitez des mod\u00e8les d'IA \/ ML pr\u00e9d\u00e9finis. Mettre le ML au c\u0153ur de votre activit\u00e9\nLib\u00e9rez la puissance du machine learning pour mieux comprendre les besoins de vos consommateurs, de vos collaborateurs et de vos annonceurs. Une fois que toutes vos donn\u00e9es sont centralis\u00e9es et connect\u00e9es de fa\u00e7on transparente par une suite compl\u00e8te d'outils collaboratifs d'analytique et de machine learning, les \u00e9quipes de donn\u00e9es ont la possibilit\u00e9 de cr\u00e9er de puissants mod\u00e8les pr\u00e9dictifs qui favoriseront l'innovation dans les domaines de la personnalisation, de la mon\u00e9tisation des contenus et de la publicit\u00e9.T\u00e9l\u00e9charger l'ebookPartenaires et solutions\nPrenez un bon d\u00e9part en choisissant des mod\u00e8les et des solutions de donn\u00e9es et d'analytique sp\u00e9cialement pens\u00e9s pour le secteur des m\u00e9dias et du divertissement\nD\u00e9couvrez notre portail partenairesAttribution multipointMesurez l'efficacit\u00e9 des campagnes et optimisez les d\u00e9penses marketing en am\u00e9liorant l'attribution des canauxD\u00e9marrerToxicit\u00e9 des joueurs et utilisateursPr\u00e9servez une ambiance saine au sein de vos communaut\u00e9s d'utilisateurs en d\u00e9tectant en temps r\u00e9el les propos et les comportements toxiquesD\u00e9marrerAnalyse de survie \/ valeur vieIdentifiez les risques de d\u00e9sabonnement chez vos consommateurs et les facteurs qui prolongent leur cycle de vieD\u00e9marrerTendance \u00e0 l'attritionOptimisez la fid\u00e9lisation, obtenez une vision pr\u00e9cise du cycle de vie et r\u00e9duisez votre taux de d\u00e9sabonnementD\u00e9marrerSegmentation comportementaleCr\u00e9ez des segments avanc\u00e9s pour g\u00e9n\u00e9rer de meilleures pr\u00e9visions d'achat en fonction des comportementsD\u00e9marrerPr\u00e9vision des ventes et attributionOptimisez les r\u00e9sultats de la publicit\u00e9 en ciblant les canaux les plus performantsD\u00e9marrerRecommandationsAugmentez les conversions et l'engagement gr\u00e2ce \u00e0 des recommandations multicanal personnalis\u00e9esD\u00e9marrerReconnaissance d'image \/ LabelboxAnnotez des images et des vid\u00e9os dans le lakehouse pour orienter le ciblage publicitaire contextuel\n\u00a0\nBient\u00f4t disponibleQualit\u00e9 de l'exp\u00e9rience vid\u00e9oAnalysez les donn\u00e9es en batch et en streaming pour garantir les performances de l'exp\u00e9rience en streamingD\u00e9marrerEnch\u00e8res en temps r\u00e9elApprenez \u00e0 pr\u00e9dire la visibilit\u00e9 des publicit\u00e9s en temps r\u00e9el pour affiner votre strat\u00e9gie RTBD\u00e9marrerVoir toutes les solutionsLakehouse pour les m\u00e9dias et le divertissementRessources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les donn\u00e9es, l'analytique et l'IA d\u00e9di\u00e9s au secteur des m\u00e9dias et du divertissement\nExplorer les ressourcese-bookT\u00c9L\u00c9CHARGER MAINTENANTWebinairesEn savoir plusBlogsEn savoir plusPr\u00eat \u00e0 vous lancer\u00a0?Nous serions ravis de conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.ESSAYER GRATUITEMENT DATABRICKSPlanifier une d\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeremy-lewallen\/#","text":"Jeremy Lewallen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeremy LewallenProduct Manager at DatabricksBack to speakersJeremy Lewallen is a Staff Product Manager on DBSQL. He leads the the workload management, performance, control plane, API, and concurrency product direction.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/data-partner-program","text":"Programa de parceiros de dados | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPrograma de parceria com provedores de dadosAcesse o amplo e aberto ecossistema de consumidores de dados com a DatabricksInscreva-se agoraA partir de uma \u00fanica plataforma, a Databricks ajuda os parceiros provedores de dados a monetizar seus ativos de dados para um grande ecossistema aberto de consumidores de dados. Nossos parceiros podem aproveitar a Databricks Lakehouse Platform para atingir mais clientes, reduzir custos e oferecer a melhor experi\u00eancia da categoria para todas as suas necessidades de compartilhamento de dados.Benef\u00edcios da parceria com provedores de dadosAlcance mais consumidoresCobertura expandida para mais consumidores de dados a partir de uma plataforma aberta e seguraMelhor experi\u00eancia do clienteTempo reduzido de configura\u00e7\u00e3o e ativa\u00e7\u00e3o para consumidores de dadosSuporte de marketingMaior exposi\u00e7\u00e3o com o suporte de marketing da DatabricksTecnologia para produtos de dadosA\u00a0plataforma lakehouse\u00a0l\u00edder de mercado para dados, an\u00e1lises e IAAcesso \u00e0 equipe de produto e P&DAcesso \u00e0 equipe de produto, engenharia e suporte da DatabricksSolu\u00e7\u00f5es para cada setorTrabalhe com nossas equipes de cada setor para criar\u00a0solu\u00e7\u00f5es\u00a0espec\u00edficas projetadas para casos de uso de clientesDelta Sharing para provedores de dadosA Databricks se integra nativamente ao\u00a0Delta Sharing, o primeiro protocolo aberto do mundo para compartilhamento seguro de dados entre organiza\u00e7\u00f5es, em tempo real e independentemente da plataforma em que est\u00e3o.O Delta Sharing tem a aprova\u00e7\u00e3o de um grande ecossistemaClientes de c\u00f3digo abertoClientes comerciaisBusiness IntelligenceAn\u00e1lisesGovernan\u00e7aProvedores de dadosTudo pronto para come\u00e7ar?Inscreva-se agoraEncontrar uma parceriaProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/legal\/cloud-provider-directory","text":"Databricks Cloud Provider Directory | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Cloud Provider DirectoryDatabricks Unified Analytics Platform ServicesThe Databricks Unified Analytics Platform Service is available directly from Databricks on the platforms of the following Cloud Service Providers:Cloud Service ProviderApplicable DocumentationPricingAvailable Instance Types**Security Certifications and AttestationsAmazon Web ServicesDocsPricingInstance TypesSOC 2 Type II*, ISO 27001:2013, ISO 27018:2019, HIPAA\u2020, PCI-DSS\u2020Google Cloud PlatformDocsPricingInstance TypesISO 27001:2013, ISO 27018:2019\u00a0Please note that usage of Databricks Platform Services Workspaces may not count towards your Universal Commitment \/ Minimum Commitment unless we confirm otherwise in writing from [email\u00a0protected]. Please note that certain products and features may not be available on GCP. Please see here for details.Databricks Powered ServicesThe Databricks Runtime data processing engine also powers the following Databricks Powered Services:Azure Databricks (provided by Microsoft Corporation)Databricks Data Insights (provided by Alibaba Cloud)Databricks does not provide the Databricks Powered Services to Customers directly; in order to use a Databricks Powered Service, you must enter into a contract with the relevant provider listed above. Please note that usage of Databricks Powered Services may not count towards your Universal Commitment \/ Minimum Commitment unless we confirm otherwise in writing from [email\u00a0protected].Databricks may update this Directory at any time to add additional Cloud Service Providers and Databricks Powered Services.*Report available under NDA.Please note that the SOC 2 Type II Report does not yet cover Databricks on GCP. Databricks expects to add Databricks on GCP to our SOC 2 Type II Report in Q4 of 2021. **Available instance types are updated according to available instance types on an applicable Cloud Provider and may change. \u2020 Only available for certain deployment types. Please speak to a Databricks sales representative for further information.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/corey-zwart","text":"Corey Zwart - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCorey ZwartChief Technology Officer at PumpJack DataworksBack to speakersCorey is an accomplished DevOps Engineer and Cloud Architect, consistently recognized for his reliability, dependability, & integrity in achieving technical outcomes. Corey serves as the Chief Technology Officer for Pumpjack Dataworks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/xiao-li","text":"Xiao Li - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingXiao LiSenior Engineering Manager at DatabricksBack to speakersXiao Li is a senior engineering manager, Apache Spark Committer and PMC member at Databricks. His main interests are on Spark and database engine. Previously, he was an IBM master inventor and an expert on asynchronous database replication and consistency verification. He received his Ph.D. from University of Florida in 2011.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/dense-tensor","text":"What are Dense Tensors?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDense TensorAll>Dense TensorTry Databricks for freeGet StartedDense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software products that can perform tensor computations, such as the MATLAB suite that has even been enhanced by various open source third party toolboxes. MATLAB alone is capable of supporting a variety of element-wise and binary dense tensor operations A dense layer is a fully connected layer, as each and every neuron gets an input from all the neurons in the previous layer, thus being densely connected. This means that every Neuron in a Dense layer will be fully connected to every Neuron in the prior layer.  Dense is usually used towards the end of a network, and sometimes multiple times. Trying to build a layered infrastructure for high-performance dense tensor applications, one of the most used libraries is dten, which is known for storing and manipulating dense tensors. The library focuses on storing dense tensors in canonical storage formats and converting between storage formats in parallel. In addition, it supports tensor matricization in different ways. The library is general-purpose and provides a high degree of flexibility. We may regard a tensor as the multidimensional generalization of a matrix. Mathematically, matricization is merely a conceptual (or logical) restructuring of the tensor.Additional ResourcesTensorFlow\u2122 on DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/product\/pricing","text":"Tarifs de Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWProlongation de la promotion SQL \u2013 \u00c9conomisez 40\u00a0% ou plus Profitez de notre promotion de 15\u00a0mois sur Serverless SQL et le tout nouveau SQL ProEn savoir plusTarifs de DatabricksUne plateforme simple pour centraliser toutes vos charges de travail de donn\u00e9es, d'analytique et d'IA, sur l'ensemble de vos cloudsD\u00e9marrez votre essai gratuitComment fonctionnent les tarifs de Databricks\u00a0?Payez \u00e0 l'utilisationDatabricks offre une approche de paiement \u00e0 l'utilisation sans frais initiaux. Ne payez que les produits que vous utilisez, \u00e0 la seconde pr\u00e8s.\u00c9conomisez davantage avec les remises pour engagement d'utilisationDatabricks vous permet de r\u00e9duire vos co\u00fbts gr\u00e2ce \u00e0 des remises lorsque vous vous engagez \u00e0 respecter certains niveaux d'utilisation. Plus votre engagement d'utilisation est \u00e9lev\u00e9, plus la remise sera importante par rapport au paiement \u00e0 l'usage. L'utilisation des engagements de d\u00e9penses est tr\u00e8s souple\u00a0: vous pouvez les r\u00e9partir sur plusieurs clouds. Contactez-nous pour plus d'informations.D\u00e9couvrir les produitsWorkflows et StreamingT\u00e2chesStarting at $0.07 \/ DBUEx\u00e9cutez des pipelines de data engineering pour cr\u00e9er des data lakes et g\u00e9rer les donn\u00e9es \u00e0 grande \u00e9chelleEn savoir plusWorkflows et Streaming Delta\u00a0Live\u00a0tablesStarting at $0.20 \/ DBUCr\u00e9ez facilement des pipelines ETL de qualit\u00e9 en batch ou en streaming, en utilisant Python ou SQL avec l'\u00e9dition DLT qui convient le mieux \u00e0 votre charge de travailEn savoir plusEntreposage des donn\u00e9esDatabricks SQLStarting at $0.22 \/ DBUEx\u00e9cutez des requ\u00eates SQL pour produire des rapports BI, des analytiques et des visualisations, et obtenir ainsi de pr\u00e9cieux insights \u00e0 partir de vos data lakes. Disponible en deux versions\u00a0: Classic Compute et Serverless Compute (manag\u00e9).En savoir plusData Science et Machine LearningTout usageStarting at $0.40 \/ DBUEx\u00e9cutez des charges de travail interactives en data science et en machine learning. Convient \u00e9galement au data engineering, \u00e0 la BI et \u00e0 l'analytique.En savoir plusData Science et Machine LearningInf\u00e9rence serverless en temps r\u00e9elStarting at $0.07 \/ DBUFaites des pr\u00e9dictions en direct dans vos applications et vos sites web.\nEn savoir plusPlateforme Databricks et extensionsPlateforme Databricks et extensionsNiveaux de plateforme\u00a0: Des fonctionnalit\u00e9s multiplateforme qui offrent le niveau id\u00e9al de gestion, de gouvernance et de s\u00e9curit\u00e9 pour toutes les charges de travail, des plus simples aux plus strat\u00e9giques\nExtensions de plateforme\u00a0: Des am\u00e9liorations touchant tous les produits de la plateforme Databricks, pour am\u00e9liorer les capacit\u00e9s de gestion, de gouvernance et de s\u00e9curit\u00e9En savoir plusESSAYER GRATUITEMENT DATABRICKSEssayer gratuitementPlanifier une d\u00e9moFAQQue contient l'essai gratuit\u00a0?Les avantages de l'essai gratuit pendant 14\u00a0jours\u00a0:Un environnement collaboratif permettant aux \u00e9quipes data de cr\u00e9er des solutions de mani\u00e8re collaborativeDes notebooks interactifs pour utiliser Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn et bien d'autres encoreVeuillez noter que votre fournisseur de cloud vous facturera quand m\u00eame les ressources \u2013 les instances de calcul, notamment \u2013 utilis\u00e9es au sein de votre compte pendant l'essai gratuit.Que se passe-t-il \u00e0 la fin de l'essai gratuit\u00a0?\u00c0 la fin de la p\u00e9riode d'essai, vous b\u00e9n\u00e9ficierez d'un abonnement automatique au plan auquel vous avez souscrit lors de votre essai gratuit. Vous pourrez annuler votre abonnement \u00e0 tout moment.Les tarifs sont-il bas\u00e9s sur l'utilisation ou le volume de stockage\u00a0?Les tarifs de Databricks sont bas\u00e9s sur votre utilisation du calcul. Le stockage, le r\u00e9seau et les co\u00fbts associ\u00e9s varient en fonction des services que vous choisissez et de votre fournisseur cloud.Qu'est-ce qu'une DBU\u00a0?Une unit\u00e9 Databricks (DBU) est une unit\u00e9 normalis\u00e9e de puissance de traitement sur la plateforme Lakehouse de Databricks utilis\u00e9e \u00e0 des fins de mesure et de tarification. Le nombre de DBU consomm\u00e9es par une charge de travail d\u00e9pend de mesures de traitement qui peuvent inclure les ressources de calcul utilis\u00e9es et la quantit\u00e9 de donn\u00e9es trait\u00e9es. Les tarifs sont-ils les m\u00eames dans toutes les r\u00e9gions\u00a0?Les prix de Databricks et ceux de l'infrastructure cloud peuvent varier en fonction de votre r\u00e9gion et du fournisseur de services cloud. Pour plus d'informations, consultez les pages de tarification de Databricks propres \u00e0 chaque produit.Databricks est-il aussi \u00e9conomique que les autres services cloud ou solutions open source\u00a0?Le prix des produits Databricks a pour but de proposer aux clients un co\u00fbt total de possession (TCO) comp\u00e9titif pour leurs charges de travail. Pour estimer vos \u00e9conomies avec Databricks, il est essentiel de tenir compte des aspects cl\u00e9s des solutions alternatives\u00a0: taux d'ex\u00e9cution des t\u00e2ches, dur\u00e9e, effort manuel et ressources requises pour soutenir une t\u00e2che. Pour vous aider \u00e0 estimer vos \u00e9conomies avec pr\u00e9cision, nous vous recommandons de comparer les r\u00e9sultats obtenus avec un d\u00e9ploiement servant de test de faisabilit\u00e9. Par exemple, voyez le gain de temps r\u00e9alis\u00e9 par ce client et les r\u00e9sultats du comparatif de ce client. Contactez-nous pour d\u00e9marrer.En quoi consiste Databricks Community Edition\u00a0?Databricks Community Edition est une plateforme gratuite, aux fonctionnalit\u00e9s limit\u00e9es, con\u00e7ue pour quiconque souhaite s'initier \u00e0 Spark. Inscrivez-vous ici.Comment serais-je factur\u00e9\u00a0?Par d\u00e9faut, un pr\u00e9l\u00e8vement mensuel sera effectu\u00e9 sur votre carte bancaire en fonction du nombre de secondes utilis\u00e9es. Contactez-nous pour d'autres options de facturation, telles que le paiement sur facture ou sous forme de forfait annuel.Proposez-vous une assistance technique\u00a0?Nous proposons une assistance technique. Vous pouvez aussi consulter la documentation technique. Contactez-nous pour en savoir plus.ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/seth-babcock","text":"Seth Babcock - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSeth BabcockHead of Connected Aviation Tech Ops Solutions and Analytics at Collins AerospaceBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/apache-spark-under-the-hood","text":"Apache Spark\u2122 Under the Hood | DatabricksApache Spark\u2122 Under the HoodGetting started with core architecture and basic conceptsApache Spark\u2122 has seen immense growth over the past several years, becoming the de-facto data processing and AI engine in enterprises today due to its speed, ease of use, and sophisticated analytics. Spark unifies data and AI by simplifying data preparation at massive scale across various sources, providing a consistent set of APIs for both data engineering and data science workloads, as well as seamless integration with popular AI frameworks and libraries such as TensorFlow, PyTorch, R and SciKit-Learn.Databricks, founded by the team that originally created Apache Spark, is proud to share excerpts from the book, Spark: The Definitive Guide. Enjoy this free mini-ebook, courtesy of Databricks.In this eBook, we cover:The past, present, and future of Apache Spark.Basic steps to install and run Spark yourself.A summary of Spark\u2019s core architecture and concepts.Spark\u2019s powerful language APIs and how you can use them.Get the eBook to learn more.Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators","text":"Databricks Solution Accelerators - Deliver Data & AI Value Faster - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIndustry SolutionsDeliver the data and AI-driven outcomes that matter most \u2014 fasterStart your free trialDatabricks Solution AcceleratorsSave hours of discovery, design, development and testing with Databricks Solution Accelerators. Our purpose-built guides \u2014 fully functional notebooks and best practices \u2014 speed up results across your most common and high-impact use cases. Go from idea to proof of concept (PoC) in as little as two weeks.\n\u00a0\nStart using Solution Accelerators with your free Databricks trial or your existing account.\n\u00a0\nStart your free trial todayBrowse AcceleratorssearchHide filtersIndustrySortDatabricksToxicity Detection in GamingfeaturedDatabricksOn-Shelf AvailabilityfeaturedDatabricksFine-Grained Demand Forecastingfeatured\ud83d\udd25DatabricksAutomated PHI RemovalfeaturednewDatabricksAbstracting Real-World Data for OncologyDatabricksAnti-Money LaunderingDatabricksCohort Building with Knowledge GraphsDatabricksComputer Vision FoundationsDatabricksCustomer Entity ResolutionDatabricksCustomer Lifetime Value\ud83d\udd25DatabricksCustomer SegmentationSplunkCyber Analytics (Splunk Connector)DatabricksDetecting Adverse Drug EventsnewDatabricksDigital Pathology Image AnalysisDatabricksDigital TwinsDatabricksESG Performance Analytics\ud83d\udd25DatabricksFHIR Interoperability with dbigniteDatabricksFuzzy Item MatchingDatabricksGenome-Wide Association StudiesDatabricksGeospatial Analytics to Identify FraudDatabricksHL7v2 Interoperability With SmolderDatabricksMedia Mix Modeling (MMM)DatabricksMedicare Risk AdjustmentDatabricksMerchant ClassificationDatabricksModern Investment PlatformDatabricksMulti-Touch AttributionDatabricksOptimized Order PickingDatabricksOverall Equipment EffectivenessDatabricksPredictive Maintenance (IoT)DatabricksPrice TransparencynewDatabricksProduct Quality InspectionDatabricksPropensity ScoringnewDatabricksR&D Optimization with Knowledge GraphsnewDatabricksReal-Time Bidding OptimizationDatabricksReal-Time Financial Fraud PreventionDatabricksReal-Time Point-of-Sale AnalyticsnewDatabricksReal-world EvidenceDatabricksRecommendation EngineDatabricksRegulatory ReportingDatabricksReputation RiskDatabricksRetention ManagementDatabricksRisk ManagementDatabricksSafety StockDatabricksSales Forecasting & Ad Attribution\ud83d\udd25DatabricksScalable Route GenerationDatabricksSocial Determinants of HealthDatabricksSubscriber Churn PredictionDatabricksSupply Chain Distribution OptimizationDatabricksSurvival Analysis & Lifetime ValueDatabricksThreat Detection with DNSDatabricksVideo Quality of ExperienceFAQHow much do Solution Accelerators cost?Solution Accelerators are available to any Databricks customer free of charge.Do I need to be a Databricks customer to use a Solution Accelerator?You can implement Solution Accelerators with a free Databricks trial or with your existing Databricks account.What can I expect from a Solution Accelerator?Solution Accelerators are designed to help you save hours of discovery, design, development and testing. Our goal is to jump-start your data and AI use cases by providing the right resources (notebooks, proven patterns and best practices). You can expect to go from idea to proof of concept (PoC) in as little as two weeks.See how actual customers use DatabricksExplore Customer StoriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/identifying-fraud","text":"Identify credit card fraud with geospatial analytics and AI | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorIdentify Fraud With Geospatial Analytics and AIPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAnalyze geospatial behaviors at scale to identify anomalous card transactionsLearn how geospatial data, machine learning and a lakehouse architecture enable organizations to better understand customer spending behaviors, and detect abnormal credit card transaction patterns in real time. Geospatial analysis can enhance fraud prevention, mitigate losses and build customer trust.Augment analytics with geospatial data at scaleUncover \u201cnormal\u201d behavior to identify the abnormalGet real-time customer spending insightsDownload notebookResourcesCase studyLearn moreEngineering blogLearn moreCompany blogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mohan-kolli","text":"Mohan Kolli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMohan KolliIT Director at LabCorpBack to speakersIT professional with 23 years of experience as Application Developer, Data Engineer, Data Architect, Data Warehouse lead and leadership roles. Currently working as Director of Enterprise Analytics Platform with portfolio of Data Platform, Data Modeling, Data Integration, Data Engineering and Data Governance. I am the visionary in data engineering and data platform space to develop data driven organization(s) to empower users make decision(s) timely with high confidence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/predictive-analytics","text":"What is Predictive Analytics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPredictive AnalyticsAll>Predictive AnalyticsWhat is Predictive Analytics?Predictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.How Does Predictive Analytics Work?Predictive analytics uses many techniques such as statistical analysis techniques, analytical queries, data mining, predictive modeling, and automated machine learning algorithms to data sets to create predictive models that place a numerical value on the likelihood of a particular event happening and includes what-if scenarios and risk assessment. With predictive analytics, organizations can find and exploit patterns contained within data in order to detect risks and opportunities. Predictive analytics is usually associated with big data, Engineering data, for example, is retrieved from sensors, instruments, and other connected systems. On the other hand, business system data of an organization could incorporate transaction data, sales results, customer complaints, and marketing information. In order to extract value from big data, companies apply algorithms to large data sets using tools like Hadoop and Spark. These can capture, store and process the large volumes of data structured or unstructured, from different sources like connected devices and sensors that measure your business.Different Stages of Predictive Analytics Life CyclePredictive analytics has its own life cycle; its first lifecycle starts with the problem statement that is its birth and goe up to its replacement by another model. Here are the stages of predictive analytics:  Predictive analytics can help you make confident real-time recommendations that reduce costs, improve safety, and inform investments.Additional ResourcesCutting Edge Predictive AnalyticsHealthcare Predictive Analytics within the ORHow Sellpoints Launched a New Predictive Analytics Product with DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/08\/03\/modern-industrial-iot-analytics-on-azure-part-1.html","text":"How to Use Databricks to Scale Modern Industrial IoT Analytics - Part 1 - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorModern Industrial IoT Analytics on Azure - Part 1Customers Leverage Azure Databricks for Industrial IoT Analyticsby Samir Gupta, Lana Koprivica and Hubert DuanAugust 3, 2020 in Company BlogShare this post\nThis post and the three-part series about Industrial IoT analytics were jointly authored by Databricks and members of the Microsoft Cloud Solution Architecture team. We would like to thank Databricks Solutions Architect Samir Gupta and Microsoft Cloud Solution Architects Lana Koprivica and Hubert Dua for their contributions to this and the two forthcoming posts.\nThe Industrial Internet of Things\u00a0 (IIoT) has grown over the last few years as a grassroots technology stack being piloted predominantly in the oil & gas industry to wide scale adoption and production use across manufacturing, chemical, utilities, transportation and energy sectors. Traditional IoT systems like Scada, Historians and even Hadoop do not provide the big data analytics capabilities needed by most organizations to predictively optimize their industrial assets due to the following factors.ChallengeRequired CapabilityData volumes are significantly larger & more frequentThe ability to capture and store sub-second granular readings reliably and cost effectively from IoT devices streaming terabytes of data per dayData processing needs are more complexACID-compliant data processing - time-based windows, aggregations, pivots, backfilling, shifting with the ability to easily reprocess old dataMore user personas want access to the dataData is an open format and easily shareable with operational engineers, data analysts, data engineers, and data scientists without creating silosScalable ML is needed for decision makingThe ability to quickly and collaboratively train predictive models on granular, historic data to make intelligent asset optimization decisionsCost reduction demands are higher than everLow-cost on-demand managed platform that scales with the data and workloads independently without requiring significant upfront capital\nRead Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.Organizations\u00a0 are turning to cloud computing platforms like Microsoft Azure to take advantage of the scalable, IIoT-enabling technologies they have to offer that make ingesting, processing, analyzing and serving time-series data sources like Historians and SCADA systems easy.In part 1, we discuss the end-to-end technology stack and the role Azure Databricks plays in the architecture and design for the industrial application of modern IoT analytics.In part 2, we will take a deeper dive into deploying modern IIoT analytics, ingest real-time IIoT machine-to-machine data from field devices into Azure Data Lake Storage and perform complex time-series processing on Data Lake directly.In part 3, we will look at machine learning and analytics with industrial IoT data.The Use Case - Wind Turbine OptimizationMost IIoT Analytics projects are designed to maximize the short-term utilization of an industrial asset while minimizing its long-term maintenance costs. In this article, we focus on a hypothetical energy provider trying to optimize its wind turbines. The ultimate goal is to identify the set of optimal turbine operating parameters that maximizes each turbine\u2019s power output while minimizing its time to failure.The final artifacts of this project are:An automated data ingestion and processing pipeline that streams data to all end usersA predictive model that estimates the power output of each turbine given current weather and operating conditionsA predictive model that estimates the remaining life of each turbine given current weather and operating conditionsAn optimization model that determines the optimal operating conditions to maximize power output and minimize maintenance costs thereby maximizing total profitA real-time analytics dashboard for executives to visualize the current and future state of their wind farms, as shown below:The Architecture - Ingest, Store, Prep, Train, Serve, VisualizeThe architecture below illustrates a modern, best-of-breed platform used by many organizations that leverages all that Azure has to offer for IIoT analytics.A key component of this architecture is the Azure Data Lake Store (ADLS), which enables the write-once, access-often analytics pattern in Azure. However, Data Lakes alone do not solve the real-world challenges that come with time-series streaming data. The Delta storage format provides a layer of resiliency and performance on all data sources stored in ADLS. Specifically for time-series data, Delta provides the following advantages over other storage formats on ADLS:Required CapabilityOther formats on ADLS Gen 2Delta Format on ADLS Gen 2Unified batch & streamingData Lakes are often used in conjunction with a streaming store like CosmosDB, resulting in a complex architectureACID-compliant transactions enable data engineers to perform streaming ingest and historically batch loads into the same locations on ADLSSchema enforcement and evolutionData Lakes do not enforce schema, requiring all data to be pushed into a relational database for reliabilitySchema is enforced by default. As new IoT devices are added to the data stream, schemas can be evolved safely so downstream applications don\u2019t failEfficient UpsertsData Lakes do not support in-line updates and merges, requiring deletion and insertions of entire partitions to perform updatesMERGE commands are effective for situations handling delayed IoT readings, modified dimension tables used for real-time enrichment, or if data needs to be reprocessed.File CompactionStreaming time-series data into Data Lakes generates hundreds or even thousands of tiny files.Auto-compaction in Delta optimizes the file sizes to increase throughput and parallelism.Multi-dimensional clusteringData Lakes provide push-down filtering on partitions onlyZORDERing time-series on fields like timestamp or sensor ID allows Databricks to filter and join on those columns up to 100x faster than simple partitioning techniques.SummaryIn this post we reviewed a number of different challenges facing traditional IIoT systems.\u00a0 We walked through the use case and the goals for modern IIoT analytics, shared a repeatable architecture that organizations are already deploying at scale and explored the benefits of Delta format for each of the required capabilities.In the next post we will ingest real-time IIoT data from field devices into Azure and perform complex time-series processing on Data Lake directly.They key technology that ties everything together is Delta Lake. Delta on ADLS provides reliable streaming data pipelines and highly performant data science and analytics queries on massive volumes of time-series data. Lastly, it enables organizations to truly adopt a Lakehouse pattern by bringing best of breed Azure tools to a write-once, access-often data store.What\u2019s Next?Learn more about Azure Databricks with this 3-part training series and see how to create modern data architectures by attending this webinar.Try Databricks for freeGet StartedRelated postsModern Industrial IoT Analytics on Azure - Part 1August 3, 2020 by Samir Gupta, Lana Koprivica and Hubert Duan in Company Blog\nThis post and the three-part series about Industrial IoT analytics were jointly authored by Databricks and members of the Microsoft Cloud Solution Architecture...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-meier\/#","text":"Scott Meier - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott MeierDirector, Data Analytics Service, Financial Services Center at U.S. Department of Veterans AffairsBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jason-shiverick","text":"Jason Shiverick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJason ShiverickData Platform Manager at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/greg-nelson","text":"Greg Nelson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGreg NelsonVP of Data Operations at Highmark HealthBack to speakersGreg Nelson, MMCi, CPHIMS, FACHE serves as the Vice President, of Data Operations and is a key member of the executive leadership team for the Enterprise Data and Analytics organization at Highmark Health. \nBefore joining Highmark, Greg held leadership roles at Intermountain Healthcare and ECU Health (formerly Vidant Health.) Greg was also the founder and CEO of ThotWave, a healthcare analytics advisory firm specializing in helping organizations mature their analytics maturity. \nGreg serves as an expert for the International Institute for Analytics (IIA) and as adjunct faculty at Duke University, where he teaches advanced analytics to master\u2019s level students in both the School of Nursing and the Fuqua School of Business.\nAn author with over 200 papers and publications, Mr. Nelson is a regular speaker and keynote presenter at national and international events as well as is also an educator and futurist for industry and association events. As an analytics evangelist and futurist, Greg has brought his 20+ years of analytics advisory work to bear through a recently published book addressing the people and process sides of analytics entitled The Analytics Lifecycle Toolkit (Wiley, 2018). Through this pragmatic treatment of the analytics lifecycle, Greg speaks to both the practical and human-centeredness of analytics in a way that is accessible and useful for all.\nMr. Nelson earned his bachelor\u2019s degree in Psychology from the University of California, Santa Cruz, a Master of Management in Clinical Informatics from Duke University, and conducted Ph.D. level work (ABD) in Social and Cognitive Psychology and Quantitative Methods from the University of Georgia. \nYou can connect with Greg on Twitter @gregorysnelson or LinkedIn at www.linkedin.com\/in\/gregorysnelson\/Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/driving-breakthrough-innovations-with-lakehouse-for-hls","text":"Combine your data and analytics workloads on one platform | DatabricksOn-DemandDriving healthcare innovations with lakehouseHow CRISP saved lives with dataAvailable on-demandWatch to discover the power of Lakehouse for Healthcare and Life Sciences and how it\u2019s revolutionizing the industry by bringing together all your data and analytics workloads to enable transformative innovations in patient care and drug R&D.During the pandemic, the Maryland Department of Health asked Chesapeake Regional Information System for our Patients (CRISP) to provide demographic data to track COVID-19. This would have been impossible to do manually. That\u2019s why CRISP implemented a data platform powered by Databricks and Delta Lake. The organization then processed billions of records from hundreds of sources to help fight the pandemic.Watch to find out how CRISP:Tracked the path of the pandemicDelivered better patient outcomes with the power of data and AIProvided near real-time reporting of key COVID-19 measuresHelped improve access to testing for vulnerable communitiesSpeakersMichael SankyRVP of Industry SolutionsDatabricksAndy HanksAnalytics Platform OwnerCRISPSteve DowlingData EngineerSlalom ConsultingWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/harrison-chase\/#","text":"Harrison Chase - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarrison ChaseCEO at LangChainBack to speakersHarrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python\/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup), and studied stats and CS at Harvard.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/unified-data-analytics-platform","text":"What is the Databricks Unified Data Analytics Platform?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnified Data Analytics PlatformAll>Unified Data Analytics PlatformDatabricks' Unified Data Analytics Platform\u00a0helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at massive scale with no limitations. The platform also enables you to continuously train and deploy ML models for all of your artificial intelligence applications. The top 3 advantages with a Unified Data Analytics Platform are:Innovate faster with big dataMake big data simpleUnifying data science and data engineeringAdditional ResourcesUnified Cloud Data Analytics PlatformUnified Data Analytics - Simplifying Streaming Analytics with Delta Lake and Spark WebinarModern Cloud Data Platform for Dummies eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/register-your-interest-for-databricks-partner-connect?itm_data=TechnologyPartnersProgram-FooterCTA-Apply","text":"Partner Connect | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner ConnectEasily discover and integrate data, analytics and AI solutions with your lakehouseWatch demosPartner Connect makes it easy for you to discover data, analytics and AI tools directly within the Databricks platform \u2014 and quickly integrate the tools you already use today. With Partner Connect, you can simplify tool integration to just a few clicks and rapidly expand the capabilities of your lakehouse.Connect your data and AI tools to the lakehouseEasily connect your preferred data and AI tools to the lakehouse and power any analytics use caseDiscover validated data and AI solutions for new use casesA one-stop portal for validated partner solutions so you can build your next data application fasterSet up in a few clicks with pre-built integrationsPartner Connect simplifies your integrations by automatically configuring resources \u2014 including clusters, tokens and connection files \u2014 to connect with partner solutionsGet started as a partnerDatabricks partners are uniquely positioned to deliver faster analytics insights for customers. Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partner\u201cBuilding on our longtime partnership, Partner Connect enables us to design an integrated experience between our companies and customers. With Partner Connect, we\u2019re delivering a streamlined experience that makes it easier than ever for the thousands of Databricks customers, whether they use Fivetran today or discover us through Partner Connect, to unlock insights in their data, discover more analytics use cases, and get value from their lakehouse faster by easily connecting hundreds of data sources to their lakehouse.\u201d\u2014 George Fraser, CEO at FivetranDemosFivetranConnect data from 180+ popular apps, including SaaS apps (Salesforce, Google Analytics, etc.) into the lakehousedbtGet started with dbt Cloud and Databricks to build data transformationsPower BIBring the advantages of Databricks Lakehouse performance and technology to all your usersTableauEmpower all users with a data lakehouse for modern analytics by connecting Tableau Desktop to Databricks SQLRiverySimplify the data journey from ingestion to transformation and delivery into Delta LakeLabelboxEasily prepare unstructured data for AI and Analytics in the LakehouseProphecyBuild and deploy Spark and Delta pipelines using a visual drag-and-drop interfaceArcionConnect data sources to the lakehouse with a distributed CDC-based replication platformTry for freeResourcesBlogFeb 2023 \u2013 Announcing New Partner Integrations in Partner ConnectSept 2022 \u2013 Introducing New Partner Integrations in Partner ConnectJune 2022 \u2013 Announcing New Partner Integrations in Partner ConnectBuild Your Business on Databricks With Partner ConnectDocumentationDatabricks Partner Connect guideReady to learn more?Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partnerContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/william-zanine\/#","text":"William Zanine - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWilliam ZanineHead of Data Management, Channel and Specialty North America at IQVIABack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/benefits","text":"Benefits | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIf you\u2019re happy, we\u2019re happyBenefits, perks and hybrid work\nYour health and mental well-being are top priorities for us. Check out the many ways we care for our employees.\nSee open jobs OverviewCultureBenefitsDiversityStudents & new gradsFlexible ways of workingTeam Days at the officeBricksters get the best of both worlds: working from home most of the time and coming to the office weekly. Every department has a scheduled Team Day once a week to connect with team members in person \u2014 whether that means having one-on-ones, collaborating or simply eating lunch together.\u00a0It\u2019s about you and your teamFor now, flexibility is the rule of thumb. You could choose to come in every day if you prefer, depending on workspace availability.Some roles are fully remote, which means you wouldn\u2019t be expected to come into the office for Team Days.Benefits and perks*Designed to meet your needs at every stage of lifeMedical, dental, visionFinancial benefitsPaid parental leaveGym reimbursementPersonal development fundMental health and wellnessBusiness travel insuranceDiscounts on goods and servicesAnd more* Varies by locationExtra perks that will make you love coming to the officeFree lunch\u00a0Unlimited beverages and snacksWeekly happy hoursSome perks are special treats that come up every now and then, depending on the office:MassagesYoga classesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/accelerate-business-value-with-delta-sharing","text":"Accelerate Business Value With Delta Sharing | DatabricksOn-DemandAccelerate Business Value With Delta SharingDiscover how to monetize your data and drive greater insightsAvailable on-demandData sharing is crucial to drive business value in today\u2019s digital economy. Organizations are looking to securely share data with their partners\/vendors, internal line of business, and generate revenue streams with data monetization. Databricks Delta Sharing empowers organizations to seamlessly and securely share and consume live data without the limitations enforced by vendor-specific sharing networks or constraints of legacy delivery systems like sFTP.Watch this webinar to learn how SafeGraph and Jefferies Group are leveraging Delta Sharing, the industry\u2019s first open protocol for secure data sharing, to enhance their data delivery and unlock business value of data with enriched location data to provide unique insights.In this webinar you will learn:How Delta Sharing is helping data providers like SafeGraph streamline solutions to share dataHow Delta Sharing is helping SafeGraph reduce the \u201ccost of curiosity\u201d for data consumers like JefferiesHow Jefferies Group leverages SafeGraph\u2019s location data to power unique insights in financial servicesSpeakersRayne GaisfordGlobal Head of Data StrategyEquity Research Jefferies LLCJames LaVersaEnterprise Customer Success ManagerSafeGraphJay BhankhariaSenior Director, Data Provider PartnershipsDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/avanade-legacy-system-migration","text":"Legacy System Migration by Avanade | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionLegacy System Migration by AvanadeMigration solution developed by Avanade and powered by the Databricks Lakehouse PlatformGet startedMove your data to unlock its full valueAzure Databricks is a key enabler for helping organizations scale AI and unlock the value of disparate and complex data. To achieve your AI aspirations and uncover insights that inform better decisions, you can migrate your data to a modern, state-of-the-art data platform and turn it into action and value. If you are looking to accelerate data transformation, Avanade can help you quickly move your data from proprietary and expensive legacy systems to drive operational efficiencies and speed up innovation on the lakehouse. No matter where you are in your data and AI maturity, there is still time and opportunity to transform the value driven from your data by migrating to the Azure Platform and leveraging Azure Databricks.2x faster access to data on the cloud through rapid migration strategy, tools and accelerators30% lower TCO through a streamlined data migration journeyGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/blaise-sandwidi\/#","text":"Blaise Sandwidi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBlaise SandwidiLead Data Scientist, As. ESG Officer, PhD at International Finance Corporation (IFC)\u2013World Bank GroupBack to speakersBlaise Sandwidi is a Lead Data Scientist with IFC\u2019s ESG Global Advisory team. Blaise oversees the development of data science to support ESG risk modeling and data science for development. His past work experience includes positions with private sector institutions focused on building machine learning platforms to enable better investment decisions. Blaise holds a Ph.D. and a master\u2019s degree in finance from the University of Paris-Est, France.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/learn","text":"Formazione | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWFormazioneImmergiti in Databricks e scopri un mondo di risorse a portata di mano: formazione e certificazione, eventi, documentazione e molto altro.Primi passi con DatabricksImpara i fondamentiDatabricks Lakehouse Platform agevola la costruzione e l'esecuzione di pipeline di dati, la collaborazione su progetti di data science e analisi, la costruzione e implementazione di modelli di machine learning. Legge le nostre guide per cominciare a utilizzare la soluzione.Sei un nuovo arrivato in Databricks? Comincia il tuo percorso in azienda sotto la guida in un Customer Success Engineer esperto.Onboarding in Databricks\nLakehouse Fundamentals Training\nWatch 4 short videos, take the quiz and get your badge\nto share on LinkedIn or your r\u00e9sum\u00e9\nGet startedData science e ingegneria dei datiAmministratori di DatabricksAnalisi SQLMachine LearningFormazioneSegui i corsi della Databricks Academy. Scopri come padroneggiare l'analisi dei dati dal team che ha avviato il progetto di ricerca Apache Spark\u2122\ufe0f all'Universit\u00e0 di Berkeley.Databricks AcademyCertificazioneGli esami di certificazione valutano il livello di conoscenza della Databricks Lakehouse Platform e delle metodologie per realizzare con successo progetti di qualit\u00e0. La certificazione favorisce il riconoscimento da parte degli operatori di settore, aiuta a distinguersi dalla concorrenza, ad aumentare la produttivit\u00e0 e a migliorare i risultati, oltre a essere una prova tangibile dell'investimento in formazione.Certificazione DatabricksTrova le risposte alle tue domandeScegli uno dei canali disponibili per chiarimenti su dubbi e domande che potrebbero insorgere nella fase iniziale:Parla con un tecnico di Databricks in direttaCommunity onlineEsplora gli argomenti pi\u00f9 discussi nella community di Databricks.Unisciti alla communityArgomenti pi\u00f9 ricorrenti nei forumdatabricksDelta LakesparksqlpysparkazureawsGCPServe aiuto immediato?Se hai un contratto di assistenza o sei interessato a sottoscriverne uno, verifica le opzioni disponibili. Per richiedere una consulenza strategica (con un Customer Success Engineer o un contratto Professional Services), rivolgiti all'amministratore del tuo spazio di lavoro per entrare in contatto con il tuo Databricks Account Executive.Scoprite le nostre opzioni di supportoGalleria NotebookQuesta galleria mostra alcune possibilit\u00e0 offerte dai Notebook, focalizzate su tecnologie e casi applicativi, che possono essere facilmente importate nell'ambiente di Databricks o nell'edizione gratuita per community.Galleria dei notebook di DatabricksDocumentazioneIl sito con la documentazione tecnica di Databricks fornisce guide pratiche e informazioni di riferimento per gli ambienti Databricks Data Science & Engineering, Databricks Machine Learning e Databricks SQL.Documentazione AWSDocumentazione AzureDocumentazione GoogleEventi e community di DatabricksConvegno Dati + AIPartecipa per assistere agli interventi, agli annunci di prodotto e a oltre 200 sessioni tecniche, con una schiera di esperti del mondo del lavoro, della ricerca e dell'universit\u00e0.Maggiori informazioniEventi globaliPrenota un posto per una delle nostre conferenze internazionali o regionali, demo di prodotti, webinar, eventi o meetup sponsorizzati dai partner.Maggiori informazioniMeetup online su dati e IAScopri che cosa succede nei Meetup di Databricks in tutto il mondo e unisciti a un gruppo vicino o lontano... tutto virtualmente!Maggiori informazioniBeaconsIncontra i Databricks Beacon, membri selezionati della community che \"vanno oltre\" per migliorare la community di gestione dei dati e AI.Maggiori informazioniUniversity AllianceUnisciti alla Databricks University Alliance per accedere a risorse complementari per formatori che vogliono insegnare a utilizzare Databricks.Maggiori informazioniVideocast Data BrewEsplorare Dati + AI con gli espertiBrooke Wenig e Denny LeeSerie videoDibattiti tecnici e meetup onlineBrooke Wenig e Denny LeeColloqui tecniciGestire l'intero ciclo di vita del Machine Learning con MLflowJules DamjiColloqui tecniciPrimi passi con Delta LakeDenny LeeColloqui tecniciApprofondimento su Delta Lake (avanzato)Denny LeeDatabricks Demo Hub (dimostrazioni di prodotto)Studio su Dati + IAMatei ZahariaCofondatore e direttore tecnologicodatabricksReynold XinCofondatore e Chief ArchitectdatabricksSue Ann HongIngegnere softwaredatabricksLeggi i documenti pi\u00f9 recenti scritti da fondatori, personale e ricercatori di Databricks su sistemi distribuiti, IA e analisi dei dati, in collaborazione con prestigiose universit\u00e0 come Berkeley e Stanford.Accesso alla ricercaProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anna-russo\/#","text":"Anna Russo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnna RussoGlobal Director of Data Science at GucciBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dael-williamson","text":"Dael Williamson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDael WilliamsonField CTO at DatabricksBack to speakersAs the EMEA CTO for Databricks, Dael provides thought leadership and guidance for the C-level executives at major customers. Prior to joining Databricks, Dael was the Global Data Technology Lead at Avanade\/Accenture. An entrepreneurial CTO and Business Platform Economist focussed on digital, data & AI led business transformations across different industries. A published data scientist in the field of protein molecular modelling, with extensive experience working in start-ups and enterprises.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-hollander","text":"Jonathan Hollander - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan HollanderVP, Enterprise Data Technology Platforms at TD BankBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/industry-lakehouse-blueprints\/blueprints-solution-sheet?itm_data=resources-pathfactory","text":"\n\n\n\n\n\n\n\nIndustry Lakehouse Blueprints Solution Sheet\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/transaction-enrichment","text":"Improving the Customer Experience With Transaction Enrichment | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorTransaction Enrichment With Merchant ClassificationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAutomate transaction enrichment to better understand your customersThese Solution Accelerators have two purposes. First, it shows how the\u00a0Lakehouse for Financial Services\u00a0enables banks, open banking aggregators and payment processors to address the challenge of merchant classification. Second, it shows how to use ML to enrich transaction data with contextual information \u2014 including store brand and category for downstream use cases, such as customer segmentation or fraud prevention.Gain new customer insights from contextual informationGet the notebookBuild hyper-personalized experiences with transaction dataGet the notebookResourcesCase studyLearn moreBlogLearn moreeBookLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de","text":"Data Lakehouse-Architektur- und KI-Unternehmen \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWEin Lakehouse als Data Warehouse ist die beste WahlOb Daten, Analytics oder KI:\nalles auf einer einzigen PlattformJetzt kostenfrei testenMehr InformationenMit der Lakehouse-Plattform Kosten einsparen und Innovation beschleunigenMehr InformationenEinheitlichEine zentrale Plattform f\u00fcr Ihre Daten \u2013 mit konsequenter Governance und verf\u00fcgbar f\u00fcr alle Analyse- und KI-AnwendungenOffenBasiert auf offenen Standards und bietet Unterst\u00fctzung f\u00fcr jede Cloud \u2013 f\u00fcr eine nahtlose Einbindung in Ihren modernen Daten-StackSkalierbarEffizientes Skalieren mit jeder Workload \u2013 von einfachen Datenpipelines bis hin zu massiven LLMsDatengesteuerte Unternehmen, die sich f\u00fcr ein Lakehouse entschieden haben\nAlle Kunden anzeigen\nLakehouse f\u00fchrt Ihre Datenteams zusammenDatenmanagement und Data EngineeringDatenerfassung und -management optimierenMit automatisiertem und zuverl\u00e4ssigem ETL, offenem und sicherem Datenaustausch und atemberaubender Leistungsf\u00e4higkeit verwandelt Delta Lake Ihren Data Lake in ein Ziel f\u00fcr Ihre gesamten strukturierten, teilstrukturierten und unstrukturierten Daten.Weitere Informationen Demo ansehenData-WarehousingAus vollst\u00e4ndigen Daten neue Erkenntnisse gewinnenDurch den direkten Zugriff auf topaktuelle und vollst\u00e4ndige Daten und mit der Leistungsf\u00e4higkeit von Databricks SQL \u2013 mit einem im Vergleich zu traditionellen Cloud-Data-Warehouses bis zu 12-mal besseren Preis-Leistungs-Verh\u00e4ltnis \u2013 k\u00f6nnen Datenanalysten und Data Scientists jetzt im Handumdrehen neue Erkenntnisse gewinnen.Weitere Informationen Demo ansehenData Science und Machine LearningDen gesamten ML-Lifecycle beschleunigenDas Lakehouse bildet die Grundlage von Databricks Machine Learning, einer datennativen und kollaborativen L\u00f6sung f\u00fcr den gesamten Machine-Learning-Lebenszyklus von der Featurisierung bis zur Produktion. Kombiniert mit hochwertigen und leistungsstarken Datenpipelines beschleunigt Lakehouse Machine Learning und Produktivit\u00e4t des Teams.Weitere Informationen Demo ansehenDaten-Governance und -TeilenVereinheitlichung von Governance und Teilen f\u00fcr Daten, Analytics und KIMit Databricks erhalten Sie ein gemeinsames Sicherheits- und Governance-Modell f\u00fcr alle Ihre Daten-, Analytics- und KI-Assets im Lakehouse in jeder Cloud. Sie k\u00f6nnen Daten auf Datenplattformen, Clouds oder Regionen ohne Replikation oder Sperrung finden und teilen sowie Datenprodukte \u00fcber einen offenen Marketplace verteilen.Weitere Informationen Demo ansehenDas Data Warehouse ist Geschichte. Finden Sie jetzt heraus, warum das Lakehouse in Sachen Architektur f\u00fcr Daten und KI die f\u00fchrende Rolle \u00fcbernommen hat.Discover LakehouseDer Sessionkatalog ist jetzt onlineSeien Sie in San Francisco dabei, um das Lakehouse-\u00d6kosystem kennenzulernen und sich mit aktuellen Fortschritten bei Open-Source-Technologien vertraut zu machenSessions erkundenErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hat.Bericht abrufen600 CIOs. 14 Branchen. 18 L\u00e4nder.Diese neue Studie zeigt, dass eine Datenstrategie entscheidend f\u00fcr den KI-Erfolg ist. Erfahren Sie mehr \u00fcber CIO-Perspektiven.Bericht abrufenPflichtlekt\u00fcre f\u00fcr ML-Engineers und Data Scientists, die nach einer besseren Methode zur Durchf\u00fchrung von MLOps suchenE-Book herunterladenM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-hecht\/#","text":"Chris Hecht - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris Hecht DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de#yourprivacychoices","text":"Data Lakehouse-Architektur- und KI-Unternehmen \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWEin Lakehouse als Data Warehouse ist die beste WahlOb Daten, Analytics oder KI:\nalles auf einer einzigen PlattformJetzt kostenfrei testenMehr InformationenMit der Lakehouse-Plattform Kosten einsparen und Innovation beschleunigenMehr InformationenEinheitlichEine zentrale Plattform f\u00fcr Ihre Daten \u2013 mit konsequenter Governance und verf\u00fcgbar f\u00fcr alle Analyse- und KI-AnwendungenOffenBasiert auf offenen Standards und bietet Unterst\u00fctzung f\u00fcr jede Cloud \u2013 f\u00fcr eine nahtlose Einbindung in Ihren modernen Daten-StackSkalierbarEffizientes Skalieren mit jeder Workload \u2013 von einfachen Datenpipelines bis hin zu massiven LLMsDatengesteuerte Unternehmen, die sich f\u00fcr ein Lakehouse entschieden haben\nAlle Kunden anzeigen\nLakehouse f\u00fchrt Ihre Datenteams zusammenDatenmanagement und Data EngineeringDatenerfassung und -management optimierenMit automatisiertem und zuverl\u00e4ssigem ETL, offenem und sicherem Datenaustausch und atemberaubender Leistungsf\u00e4higkeit verwandelt Delta Lake Ihren Data Lake in ein Ziel f\u00fcr Ihre gesamten strukturierten, teilstrukturierten und unstrukturierten Daten.Weitere Informationen Demo ansehenData-WarehousingAus vollst\u00e4ndigen Daten neue Erkenntnisse gewinnenDurch den direkten Zugriff auf topaktuelle und vollst\u00e4ndige Daten und mit der Leistungsf\u00e4higkeit von Databricks SQL \u2013 mit einem im Vergleich zu traditionellen Cloud-Data-Warehouses bis zu 12-mal besseren Preis-Leistungs-Verh\u00e4ltnis \u2013 k\u00f6nnen Datenanalysten und Data Scientists jetzt im Handumdrehen neue Erkenntnisse gewinnen.Weitere Informationen Demo ansehenData Science und Machine LearningDen gesamten ML-Lifecycle beschleunigenDas Lakehouse bildet die Grundlage von Databricks Machine Learning, einer datennativen und kollaborativen L\u00f6sung f\u00fcr den gesamten Machine-Learning-Lebenszyklus von der Featurisierung bis zur Produktion. Kombiniert mit hochwertigen und leistungsstarken Datenpipelines beschleunigt Lakehouse Machine Learning und Produktivit\u00e4t des Teams.Weitere Informationen Demo ansehenDaten-Governance und -TeilenVereinheitlichung von Governance und Teilen f\u00fcr Daten, Analytics und KIMit Databricks erhalten Sie ein gemeinsames Sicherheits- und Governance-Modell f\u00fcr alle Ihre Daten-, Analytics- und KI-Assets im Lakehouse in jeder Cloud. Sie k\u00f6nnen Daten auf Datenplattformen, Clouds oder Regionen ohne Replikation oder Sperrung finden und teilen sowie Datenprodukte \u00fcber einen offenen Marketplace verteilen.Weitere Informationen Demo ansehenDas Data Warehouse ist Geschichte. Finden Sie jetzt heraus, warum das Lakehouse in Sachen Architektur f\u00fcr Daten und KI die f\u00fchrende Rolle \u00fcbernommen hat.Discover LakehouseDer Sessionkatalog ist jetzt onlineSeien Sie in San Francisco dabei, um das Lakehouse-\u00d6kosystem kennenzulernen und sich mit aktuellen Fortschritten bei Open-Source-Technologien vertraut zu machenSessions erkundenErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hat.Bericht abrufen600 CIOs. 14 Branchen. 18 L\u00e4nder.Diese neue Studie zeigt, dass eine Datenstrategie entscheidend f\u00fcr den KI-Erfolg ist. Erfahren Sie mehr \u00fcber CIO-Perspektiven.Bericht abrufenPflichtlekt\u00fcre f\u00fcr ML-Engineers und Data Scientists, die nach einer besseren Methode zur Durchf\u00fchrung von MLOps suchenE-Book herunterladenM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/healthcare-industry-solutions","text":"Healthcare Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for the Healthcare IndustryDeliver patient-centric care with the power of data and AIData and AI are revolutionizing how healthcare organizations treat patients and deliver value for the broader population.Databricks empowers healthcare organizations to solve some of their hardest problems by unifying data analytics and machine learning to unlock precision care, improve patient engagement and streamline administration processes.Learn more about the Lakehouse for Healthcare and Life SciencesBest practices for bringing AI into the clinic. Read the ebook.Leading healthcare organizations use Databricks to drive innovation in patient careLatest blog posts, webinars, and case studiesWhy Databricks for healthcareUnlock health data and break data silosConnect structured and unstructured data from EHRs, wearables, imaging platforms, genome sequencers and more to deliver a complete view into patient health.Patient insights at population scaleBetter predict health risks with analytics and AI that scale for millions of patient records in the cloud.Deliver reproducibility and complianceCollaborative analytics workspaces that bring data teams together while streamlining the machine learning lifecycle and providing regulatory-grade MLOps.Use casesAcross the healthcare landscape, data and AI is providing insights and predictive capabilities to personalize care, automate claims and payment processing, and improve patient engagement.Administrative process automationAutomate the analysis of claims and EHR data to streamline administrative workflows.\nClaims and revenue cycle automation\nFraud and waste detection\nOptimize staffing and operations\nPopulation healthPredict broader health risks by analyzing social, behavioral and environmental factors at scale.\nIdentify the impact of social determinants of health\nIdentify and manage undiagnosed chronic disease\nBuild predictive risk models\nPatient engagementOptimize patient care cycles by creating tailored experiences.\nReduce churn through Member 360\nReduce healthcare costs with benefits recommendations\nProactively monitor patient health with digital apps\nLearn more about our healthcare solutionsResourcesCase StudiesCVS HealthAustin HealthSanford HealthHealthdirect AustraliaWebinarsDetecting Financial Fraud at Scale with Decision Trees and MLflow on DatabricksImproving Patient Insights With a Modern Clinical Data LakeeBooksUncover New Patient Insights With Natural Language Processing at ScaleAI and Healthcare: Bringing AI Into a Clinical SettingHow HLI Detects Dementia With Deep Learning on Medical ImagesDatabricks for Healthcare Solution SheetReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.\u00a0Try Databricks for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ifigeneia-derekli","text":"Ifigeneia Derekli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIfigeneia DerekliField Engineering Manager & Unity Catalog Specialist at DatabricksBack to speakersField Engineering Manager at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/deloitte-precisionview","text":"PrecisionView\u2122 for HLS by Deloitte and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionPrecisionViewTM by Deloitte\nIndustry-specific solution developed by Deloitte and powered by the Databricks Lakehouse Platform \nGet startedExpand capabilities, increase capacity and enrich internal collaboration for the finance organizationPrecisionView\u2122, Deloitte's proprietary advanced forecasting solution for healthcare and life sciences, leverages data aggregation technologies with predictive analytics as well as cognitive and machine-learning capabilities to let businesses generate improved forecasting accuracy and predictive modeling. The solution also helps generate high-impact insights that relate to the total enterprise, business units, geographies and products. It's no secret that traditional forecasting and predictive modeling methods can be excessively manual and prone to unintentional human bias or sandbagging. PrecisionView, plus the right user experience, can help change that by:Improving business and investment decision-making powered by scenario analysisIdentifying influential business drivers and modeling key business leversDecreasing time-to-insight and enhancing the delivery of financial insights and visualsGet startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/company\/partners\/technology","text":"\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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NOW\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u3068\u306e\u9023\u643a\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3001BI\u3001\u30ac\u30d0\u30ca\u30f3\u30b9\u306e\u305f\u3081\u306e\u30b1\u30a4\u30d1\u30d3\u30ea\u30c6\u30a3\u3092\u5f37\u5316\u3057\u307e\u3059\u3002\u300cDatabricks \u3068 Fivetran \u306e\u6280\u8853\u9023\u643a\u306b\u3088\u308a\u3001\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u30a4\u30f3\u30b5\u30a4\u30c8\u306e\u5927\u5e45\u306a\u5411\u4e0a\u304c\u671f\u5f85\u3067\u304d\u307e\u3059\u3002\u6280\u8853\u306e\u9762\u3067\u3082\u3001\u3053\u306e 2 \u3064\u306e\u30c4\u30fc\u30eb\u306f\u8abf\u548c\u3057\u3066\u4f5c\u7528\u3057\u3001\u307e\u308b\u3067\u30cd\u30a4\u30c6\u30a3\u30d6\u306a\u7d71\u5408\u3067\u3059\u3002\u300dPaul Hewitt \u793e BI & ERP 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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u0000\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/de\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/media-and-entertainment","text":"L\u00f6sungen f\u00fcr Medien und Unterhaltung \u2013 Databricks Lakehouse \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks f\u00fcr Medien und UnterhaltungDie Zukunft der Medien ist daten-, analyse- und KI-gest\u00fctzt \u2013 und Sie k\u00f6nnen dabei seinErste SchrittePlanen Sie eine DemoVier Herausforderungen in der Medien- und UnterhaltungsbrancheErstellen eines einheitlichen Zielgruppenprofils\nDaten, die in unterschiedlichen Systemen erfasst, gespeichert und verwaltet werden, verhindern, dass Medienunternehmen einen vollst\u00e4ndigen \u00dcberblick \u00fcber Zuschauer- und Werbedaten haben.Optimiertes Benutzererlebnis vermitteln\nGanz gleich, welches Ger\u00e4t sie nutzen: Verbraucher erwarten jederzeit reibungslose, personalisierte 1:1-Erlebnisse. F\u00fcr Sie besteht die Herausforderung darin, solche Erlebnisse in Echtzeit und umfassend bereitzustellen.Maximieren aller Mediendaten\nVeraltete Data Warehouses k\u00f6nnen unstrukturierte Daten wie Video-, Bild- und Audiodateien nicht verarbeiten. So werden Unternehmen daran gehindert, das Potenzial ihrer wertvollsten Ressourcen zu erschlie\u00dfen.\u00dcber die Aggregation hinaus zu fortgeschrittener Analytics\nKomplexe KI-Anwendungsf\u00e4lle f\u00fcr den Werbe- und Verbraucherlebenszyklus erfordern derzeit die teure Erfassung und Harmonisierung riesiger Datens\u00e4tze.Data Lakehouse \u2013 das Beste aus beiden Welten auf einer einzigen PlattformEin Data Lakehouse f\u00fchrt das Beste aus Data Warehouse und Data Lake auf einer einzigen einfachen Plattform zusammen, mit der Sie alle Ihre Anwendungsf\u00e4lle aus den Bereichen Daten, Analytics und KI bew\u00e4ltigen. Es setzt dabei auf eine offene und zuverl\u00e4ssige Datenbasis auf, die alle Datentypen effizient verarbeitet und einen gemeinsamen Sicherheits- und Governance-Ansatz auf alle Ihre Daten- und Cloud-Plattformen anwendet.Mehr InformationenDas Lakehouse in AktionSo st\u00e4rkt das Databricks Lakehouse auch Ihre Branche ma\u00dfgeschneidertWerbe- und MarketingtechnologienVerwalten Sie Margen, setzen Sie auf Grundlage Ihrer Daten maximale Pr\u00e4zision im Betrieb durch, steigern Sie die Medienleistung und optimieren Sie Werbemittel \u2013 all dies, um die Arbeit f\u00fcr Ihre Teams zu verbessern.Mehr InformationenRundfunk und StreamingErstellen Sie breit gef\u00e4cherte, personalisierte 1:1-Erlebnisse, verbessern Sie die Werbeleistung und -optimierung und steigern Sie den Mehrwert Ihres gesamten Content-Portfolios.Mehr InformationenGamingNutzen Sie Daten und KI, um die Spieleentwicklung zu verbessern, mehr Spieler zu finden und zu binden und Monetarisierung und Bindung von Spielern zu st\u00e4rken.Mehr InformationenWarum Databricks f\u00fcr Medien und Unterhaltung?Ob Daten, Analytics oder KI: alles auf einer einzigen Plattform\nErschlie\u00dfen Sie das gesamte Potenzial Ihrer Daten, um bei Zielgruppeninteraktion, Monetarisierung und Werbeoptimierung bahnbrechende Ergebnisse zu erzielen.Optimiert f\u00fcr die Echtzeitverarbeitung\nEntdecken Sie umsetzbare Erkenntnisse, f\u00f6rdern Sie die 1:1-Personalisierung und verbessern Sie das Nutzungserlebnis Ihrer Zielgruppe auf Grundlage von maschinellem Lernen.Ihre Gesch\u00e4ftsergebnisse beschleunigen\nNutzen Sie Solution Accelerators, mit denen das Erfassen von Verbraucherdaten (z.\u00a0B. Clickstream-Interaktionen) und das Bereitstellen von Anwendungsf\u00e4llen wie Empfehlungs-Engines und Multi-Touch-Attribution zum Kinderspiel wird.Maximale Zuverl\u00e4ssigkeit und Leistung\nMit dem Databricks Lakehouse setzen Sie beispiellose Optimierungen bei Skalierung, Geschwindigkeit und Kosten um. Deswegen ist es auch nicht verwunderlich, dass das beste Data Warehouse ein Lakehouse ist.Transformation f\u00fcr die Medien- und Unterhaltungsbranche \u2013 mit dem Lakehouse\n\u201eMit der Lakehouse-Plattform von Databricks auf AWS hat Warner Bros. Discovery die Zukunft von Content Discovery und Zuschauererlebnissen neu erfunden. Durch die Nutzung von Daten zur besseren Vorhersage des Verbraucherverhaltens und zur Bereitstellung personalisierter Inhaltsempfehlungen in Echtzeit sind wir in der Lage, das Zuschauererlebnis individuell zu gestalten und die Einbindung unserer Kunden insgesamt zu verbessern.\u201c\u2013 Martin Ma, GVP, Engineering bei Warner Bros. DiscoveryErkenntnisse von F\u00fchrungskr\u00e4ften zu Daten, Analytics und KIErfahren Sie mehr dar\u00fcber, was andere F\u00fchrungskr\u00e4fte aus der Medien- und Unterhaltungsbranche tun, um ihre Datenstrategie umzusetzenMehr InformationenWas kann man mit dem Lakehouse machen?\nSchnellere Ergebnisse f\u00fcr Zielgruppen und Werbetreibende \u2013 dank einer offenen, kollaborativen Plattform f\u00fcr Daten, Analytics und KI360\u00b0-Blick auf Ihr Publikum\nF\u00fchren Sie all Ihre strukturierten und unstrukturierten Daten, z. B. Clickstream, demografische und soziale Daten, in einer einzigen Plattform f\u00fcr Analytics und KI zusammen. Mit einer ganzheitlichen Sicht auf die Customer Journey k\u00f6nnen Unternehmen die Vorlieben f\u00fcr Inhalte verstehen, die zu personalisierteren Erlebnissen und der Entwicklung zielgerichteter Werbung und Interaktion beitragen.Reduzieren der Abwanderung und Erh\u00f6hen des durchschnittlichen Ertrags pro Nutzer\nMit einer flexiblen, cloudbasierten Plattform k\u00f6nnen Unternehmen schnell und zuverl\u00e4ssig riesige Datenmengen verarbeiten und an nachgelagerte Systeme weiterleiten, um auf jedem Kanal und zu jeder Zeit ein 1:1-Erlebnis zu bieten. Da die Erwartungen der Verbraucher in Bezug auf Echtzeit-Empfehlungen immer weiter steigen und Medienunternehmen um die Aufmerksamkeit der Verbraucher k\u00e4mpfen, wird es f\u00fcr viele Unternehmen zur Pflicht, eine Personalisierung in Echtzeit zu gew\u00e4hrleisten.Steigern des Umsatzes durch eine Inhaltsbibliothek\nMedienunternehmen setzen auf unstrukturierte Daten wie Video-, Bild- und Audiodateien. Daher ist die F\u00e4higkeit, solche Daten zu analysieren, f\u00fcr ein effektives Media Asset Management unerl\u00e4sslich. Mit Lakehouse for M&E k\u00f6nnen Marketer archivierte Inhalte f\u00fcr Kampagnen nutzen, Produktionsteams vorhandene Inhalte f\u00fcr neue Produktionen finden und Vertriebsteams selbst erstelltes Material an andere Medienunternehmen verkaufen.Einsatzfertige Modelle f\u00fcr ML\/KI nutzen und ML in den Mittelpunkt Ihres Unternehmens stellen\nNutzen Sie die M\u00f6glichkeiten des Machine Learnings, um die Bed\u00fcrfnisse von Verbrauchern, Mitarbeitern und Werbetreibenden besser zu verstehen. Wenn alle Ihre Daten zentralisiert und nahtlos durch eine umfassende Suite von kollaborativen Analytics- und Machine Learning-Tools verbunden sind, k\u00f6nnen Datenteams zusammenarbeiten, um leistungsstarke Prognosemodelle zu entwickeln, die neue Innovationen in den Bereichen Personalisierung, Monetarisierung von Inhalten und Werbeergebnisse vorantreiben.E-Book herunterladenPartner und L\u00f6sungen\nJede Menge gebrauchsfertige Daten- und Analytics-L\u00f6sungen und -Vorlagen speziell f\u00fcr Medien und Unterhaltung\nUnser Partnerportal erkundenMulti-Touch-ZuordnungMessen der Werbewirksamkeit und Optimieren Ihrer Marketingausgaben mit einer besseren KanalzuordnungErste SchritteToxizit\u00e4t von Spielern\/NutzernF\u00f6rdern problemfreierer Nutzergemeinschaften durch Echtzeit-Erkennung von toxischer Sprache und toxischem VerhaltenErste Schritte\u00dcberlebensanalyse\/LTVVorhersagen, welche Verbraucher abwanderungsgef\u00e4hrdet sind und welche Faktoren den Lebenszyklus der Verbraucher verl\u00e4ngernErste SchritteNeigung zur AbwanderungEffektives Verwalten der Kundenbindung, Verstehen des Lebenszyklus und Reduzieren der AbwanderungsrateErste SchritteVerhaltensorientierte SegmentierungErstellen erweiterter Segmente, um bessere Einkaufsprognosen basierend auf Verhaltensweisen zu erzielenErste SchritteAbsatzprognosen und -zuordnungSteigern der Werbeergebnisse durch Optimierung und Konzentration auf die leistungsst\u00e4rksten Kan\u00e4leErste SchritteEmpfehlungenSteigern von Konversionen und Einbindung mit personalisierten Omnichannel-EmpfehlungenErste SchritteComputer Vision\/LabelboxKommentieren von Bildern und Videos, um die kontextbezogene Anzeigenausrichtung im Lakehouse zu unterst\u00fctzen\n\u00a0\nIn K\u00fcrze verf\u00fcgbarVideo Quality of ExperienceAnalysieren von Batch- und Streaming-Daten, um ein leistungsf\u00e4higes Streaming-Inhaltserlebnis zu gew\u00e4hrleistenErste SchritteReal-Time BiddingErfahren, wie Sie die Sichtbarkeit von Anzeigen in Echtzeit vorhersagen k\u00f6nnen, um Ihre RTB-Strategie zu verbessernErste SchritteAlle L\u00f6sungen anzeigenLakehouse f\u00fcr Medien und Unterhaltung in der PraxisRessourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu Daten und KI f\u00fcr die Medien- und Unterhaltungsbranche.\nRessourcen erkundenE-BookJETZT HERUNTERLADENWebinareMehr InformationenBlogsMehr InformationenM\u00f6chten Sie loslegen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENPlanen Sie eine DemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ali-ghodsi\/#","text":"Ali Ghodsi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAli GhodsiCo-founder and CEO at DatabricksBack to speakersAli Ghodsi, the CEO and co-founder of Databricks, is responsible for the growth and international expansion of the company. He previously served as the VP of Engineering and Product Management before taking the role of CEO in January 2016. In addition to his work at Databricks, Ali serves as an adjunct professor at UC Berkeley and is on the board at UC Berkeley\u2019s RISELab. Ali was one of the original creators of the open source project, Apache Spark, and ideas from his academic research in the areas of resource management and scheduling and data caching have been applied to Apache Mesos and Apache Hadoop. Ali received his MBA from Mid-Sweden University in 2003 and a Ph.D. from KTH\/Royal Institute of Technology in Sweden in 2006 in the area of Distributed Computing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-armbrust\/#","text":"Michael Armbrust - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael ArmbrustDistinguished Engineer at DatabricksBack to speakersMichael Armbrust is committer and PMC member of Apache Spark\u2122 and the original creator of Spark SQL. He currently leads the Delta Live Tables team at Databricks and is the original creator of Spark SQL, Structured Streaming and Delta. He received his PhD from UC Berkeley in 2013, and was advised by Michael Franklin, David Patterson, and Armando Fox. His thesis focused on building systems that allow developers to rapidly build scalable interactive applications, and specifically defined the notion of scale independence. His interests broadly include distributed systems, large-scale structured storage and query optimization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/migration\/data-warehouse","text":"Migrate your data warehouse to Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMigrate your data warehouse to DatabricksBecause the best data warehouse is a lakehouse\nTry Databricks freeContact DatabricksLegacy data warehouses are costly to maintain, unscalable and cannot deliver on data science, ML and real-time analytics use cases. Migrating from your enterprise data warehouse to Databricks lets you scale as your business needs grow and accelerate innovation by running all your data, analytics and AI workloads on a single unified data platform.The case for modernizing your enterprise data warehouseEnterprise data warehouses have traditionally supported only historical reporting \u2014 with no support for forward-looking prescriptive and predictive analytics. They also cannot handle semi-structured, unstructured or real-time data and are not set up for advanced analytics use cases that data science teams need to drive ML and AI\u2013powered innovations. If that wasn\u2019t enough, EDWs store data in closed proprietary formats, impose rigid vendor lock-ins and are prohibitively expensive to scale.Read this TDWI report on how you can overcome these challenges by transitioning from a data warehouse to a data lakehouse.\nThe Wisdom of Transitioning to a Data Lakehouse Strategy\nHow a data lakehouse approach can help you overcome the common limitations of data warehouses and data lakes\nDownload nowWhy migrate your data warehouse to the Databricks Lakehouse?Simplify your data platform\nGet a single modern platform for all your data, analytics and AI use cases. Unify governance and the user experience across clouds and data teams.\nScale cost-effectively\nStop managing servers, and scale on demand with serverless. Run data warehousing at scale with up to 12x better price\/performance.\nAccelerate innovation\nBuild AI, ML and real-time analytics capabilities faster with collaborative, self-service tools and open source technologies such as MLflow and Apache Spark\u2122.\nMigrate with confidence\nAutomated tools, technical guidance, partner solutions and professional services help you eliminate risk and accelerate your migration journey.\nTechnical guidance for data migration, ETL and code migration, and BI reportingData MigrationPull data into Databricks from various database sourcesPush data out from EDWs to cloud storage and use Databricks AutoLoaderUse our ingestion partners such as Fivetran, Qlik Replicate and Arcion from Databricks Partner ConnectETL and Code MigrationBI ReportingReady to take your first step?Contact DatabricksMigration resourcesWebinarModernize Your Data Warehouse\nWatch noweBookMigrating From a Data Warehouse to a Data Lakehouse for Dummies\nDownload nowMigration GuideStrategies to Evolve Your Data Warehouse to the Databricks Lakehouse\nDownload nowBrickbuilder SolutionsLeverage Brickbuilder Solutions from leading consulting partners \u2014 built for migrating your data warehouse to the Databricks LakehouseLegacy System Migration by AvanadeMove your data to unlock its full value\nGet startedMigrate to Cloud and Databricks by CapgeminiStreamline data migration to the Databricks Lakehouse Platform\nGet startedMigrate to Databricks by Celebal TechnologiesQuicker migration from on-premises at lower cost\nGet startedLeapLogic Migration Solution by ImpetusAuto-transform ETL, data warehouse, analytics and Hadoop workloads to Databricks\nGet startedData Wizard for Hadoop\/EDW Migrations by InfosysConfidently move your data to Databricks\nGet startedSnowflake-to-Databricks Migration by LovelyticsEnsure a rapid and sound migration process\nGet startedSAS Migration Accelerator by Tensile AIMigration solution developed by Tensile AI and powered by the Databricks Lakehouse Platform\nGet startedData Intelligence Suite by WiproMigrate with confidence to Databricks\nGet startedCustomers who have successfully migrated their data warehouse to DatabricksMigrating from Hadoop?Learn moreResourceseBooksWhy the Data Lakehouse Is Your Next Data WarehouseMigrating From a Data Warehouse to a Data Lakehouse for DummiesStrategies to Evolve Your Data Warehouse to the Databricks LakehouseEventsModernize Your Data WarehouseHow to Automate the Modernization and Migration of Your Data Warehousing Workloads to Databricks LakehouseData Transformation in the Lakehouse Made Simple With Fivetran and DatabricksTableau Unleashed With a Data LakehouseLeapLogic \u2014 A Cloud Accelerator for Transformation of Legacy Analytics, ETL, DW and HadoopBlogsData Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse PlatformPrescriptive Guidance for Implementing a Data Vault Model on the Databricks Lakehouse PlatformFive Simple Steps for Implementing a Star Schema in Databricks With Delta LakeDimensional Modeling Best Practices and Implementation on a Modern LakehouseGet startedMigration doesn\u2019t have to be a headache. Contact us today to talk about what it could look like for you.Try Databricks freeContact DatabricksProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\u6708 29 \u65e5\uff08\u6728\uff09\u57fa\u8abf\u8b1b\u6f14\n\u30d6\u30ec\u30a4\u30af\u30a2\u30a6\u30c8\u30bb\u30c3\u30b7\u30e7\u30f3\n\u5c55\u793a\n\u696d\u754c\u30d5\u30a9\u30fc\u30e9\u30e0\n\u8a8d\u5b9a\u8a66\u9a13\n\u30af\u30ed\u30fc\u30b8\u30f3\u30b0\u30d1\u30fc\u30c6\u30a3\n\u3054\u767b\u9332\u3092\u304a\u5f85\u3061\u3057\u3066\u3044\u307e\u3059\uff01\u3054\u767b\u9332HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Databricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb | DatabricksDatabricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebDatabricks \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u5168\u6a5f\u80fd\u3092 14 \u65e5\u9593\u7121\u6599\u3067\u304a\u8a66\u3057\u3044\u305f\u3060\u3051\u307e\u3059\u3002AWS\u3001Microsoft Azure\u3001Google Cloud \u306e\u3044\u305a\u308c\u304b\u3092\u304a\u9078\u3073\u304f\u3060\u3055\u3044\u3002\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3001ETL \u3092\u81ea\u52d5\u5316\u6570\u767e\u306b\u304a\u3088\u3076\u30bd\u30fc\u30b9\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3068\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308b\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u4efb\u610f\u306e\u8a00\u8a9e\u3067\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032Python\u3001R\u3001Scala\u3001SQL \u306b\u3088\u308b\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u304c\u53ef\u80fd\u3067\u3059\u3002\u5171\u540c\u7de8\u96c6\u3001\u81ea\u52d5\u30d0\u30fc\u30b8\u30e7\u30f3\u7ba1\u7406\u3001Git \u7d71\u5408\u3001RBAC \u3082\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e 12 \u500d\u306e\u4fa1\u683c\u6027\u80fdDatabricks \u306f\u3001\u4e16\u754c 7000 \u793e\u4ee5\u4e0a\u306e\u304a\u5ba2\u69d8\u306b\u63a1\u7528\u3055\u308c\u3001BI \u3084 AI \u306e\u3042\u3089\u3086\u308b\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002Databricks \u30a2\u30ab\u30a6\u30f3\u30c8\u3092\u4f5c\u6210\u3059\u308b1\/2\u304a\u540d\u524d\uff08\u59d3)\u304a\u540d\u524d\uff08\u540d)\u696d\u52d9\u7528\u30e1\u30fc\u30eb\u30a2\u30c9\u30ec\u30b9\u4f01\u696d\uff0f\u56e3\u4f53\u540d\u5f79\u8077\u540d\u96fb\u8a71\u756a\u53f7\uff08\u4efb\u610f)\u9078\u629e\u3057\u3066\u304f\u3060\u3055\u3044\u56fd\u540d\u9001\u4fe1\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5 (\u66f4\u65b0)\u5229\u7528\u898f\u7d04\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/megan-fogal\/#","text":"Megan Fogal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMegan FogalSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pritesh-patel\/#","text":"Pritesh Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPritesh PatelPublic Sector Leader, UK&I at DatabricksBack to speakersSales leader with years of experience in Public Sector and with passion to deliver citizen and social value through data and AI.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/streaming-analytics","text":"What is Streaming Analytics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWStreaming AnalyticsAll>Streaming AnalyticsHow Does Stream Analytics Work?Streaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a specific event that happens as a direct result of an action or set of actions, like a financial transaction, equipment failure, a social post or a website click or some other measurable activity. The data can originate from the Internet of Things (IoT), transactions, cloud applications, web interactions, mobile devices, and machine sensors. By using streaming analytics platforms organizations can extract business value from data in motion just like traditional analytics tools would allow them to do with data at rest. Real-time streaming analytics help a range of industries by spotting opportunities and risks.The Advantages of Streaming AnalyticsData visualization. Keeping an eye on the most important company information can help organizations manage their key performance indicators (KPIs) on a daily basis. Streaming data can be monitored in real time allowing companies to know what is occurring at every single momentBusiness insights. In case an out of the ordinary business event occurs, it will first show up in the relevant dashboard. It can be used in cybersecurity, to automate detection and response to the threat itself. This is an area where abnormal behavior should be flagged for investigation right away.Increased competitiveness. Businesses looking to gain a competitive advantage can use streaming data to discern trends and set benchmarks faster. This way they can outpace their competitors who are still using the sluggish process of batch analysis.Cutting preventable losses. With the help of streaming analytics, we can prevent or at least reduce the damage of incidents like security breaches, manufacturing issues, customer churn, stock exchange meltdowns, and social media crisis.Analyzing routine business operations. Streaming analytics offers organizations an opportunity to ingest and obtain an instant insight from the real-time data that is pouring in.Your company will be able to answer questions like:How many customers do you have in your store at this very moment, and what are they most likely to purchase?Which vehicles in our fleet are using the most fuel and why?Is there a machinery in your factory that could fail in the next five business days, and what spare parts will be required to keep it running?Your company can now monitor in real time: manufacturing closed-loop control systems; the health of a network or a system; field assets such as trucks, oil rigs, vending machines; and financial transactions such as authentications and validations.Finding missed opportunities. The streaming and analyzing of Big Data can help companies to uncover hidden patterns, correlations and other insights. Companies can get answers from it almost immediately being able to upsell, and cross-sell clients based on what the information presents.Create new opportunities. The existence of streaming data technology brings the type of predictability that cuts costs, solves problems and grows sales. It has led to the invention of new business models, product innovations, and revenue streams.Streaming Analytics with Azure DatabricksTo play this video, click here and accept cookiesAdditional ResourcesSimplifying Streaming Analytics with Delta Lake and Spark WebinarStreaming Analytics with Spark, Kafka, Cassandra, and AkkaGet High-Performance Streaming Analytics with Azure DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/samrat-ray","text":"Samrat Ray - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSamrat RaySenior Staff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-are-continuous-applications","text":"What are Continuous Applications?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContinuous ApplicationsAll>Continuous ApplicationsTry Databricks for freeGet StartedContinuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate systems, such as query serving or interaction with batch jobs. Below is an example of continuous applications can handle the following use cases.Updating data that will be served in real time. The developer would write a single Spark application that handles both updates and serving (e.g. through Spark\u2019s JDBC server), or would use an API that automatically performs transactional updates on a serving system like MySQL, Redis or Apache Cassandra.Extract, transform and load (ETL). The developer would simply list the transformations required as in a batch job, and the streaming system would handle coordination with both storage systems to ensure exactly-once processing.Creating a real-time version of an existing batch job. The streaming system would guarantee results are always consistent with a batch job on the same data.Online machine learning. The machine learning library would be designed to combine real-time training, periodic batch training, and prediction serving behind the same API.Additional ResourcesWriting Continuous Applications with Structured Streaming PySpark APIHeadaches and Breakthroughs in Building Continuous ApplicationsContinuous Applications at Scale of 100 Teams with Databricks Delta and Structured StreamingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/karthik-ramasamy","text":"Karthik Ramasamy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKarthik RamasamyHead of Streaming at DatabricksBack to speakersKarthik Ramasamy is the Head of Streaming at Databricks. Before joining Databricks, he was a Senior Director of Engineering, managing the Pulsar team at Splunk. Before Splunk, he was the co-founder and CEO of Streamlio that focused on building next-generation event processing infrastructure using Apache Pulsar and led the acquisition of Streamlio by Splunk. Before Streamlio, he was the engineering manager and technical lead for real-time infrastructure at Twitter where he co-created Twitter Heron, which was open sourced and used by several companies. He has two decades of experience working with companies such as Teradata, Greenplum and Juniper in their rapid growth stages building parallel databases, big data infrastructure and networking. He co-founded Locomatix, a company that specializes in real-time streaming processing on Hadoop and Cassandra using SQL, which was acquired by Twitter. Karthik has a Ph.D. in computer science from the University of Wisconsin, Madison, with a focus on big data and databases. During his college tenure, several of the research projects he participated in were later spun off as a company acquired by Teradata. Karthik is the author of several publications, patents and a popular book, Network Routing: Algorithms, Protocols and Architectures.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-machine-learning-library","text":"What is a Machine Learning Library (MLlib)?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMachine Learning Library (MLlib)All>Machine Learning Library (MLlib)Try Databricks for freeGet StartedApache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and models instead of solving the complexities surrounding distributed data (such as infrastructure, configurations, and so on). Built on top of Spark, MLlib is a scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives. Spark MLLib seamlessly integrates with other Spark components such as Spark SQL, Spark Streaming, and DataFrames and is installed in the Databricks runtime. The library is usable in Java, Scala, and Python as part of Spark applications, so that you can include it in complete workflows. MLlib allows for preprocessing, munging, training of models, and making predictions at scale on data. You can even use models trained in MLlib to make predictions in Structured Streaming. Spark provides a sophisticated machine learning API for performing a variety of machine learning tasks, from classification to regression, clustering to deep learning.Additional ResourcesManaged MLflow ProductGartner names Databricks a Magic Quadrant Leader in Data Science and Machine Learning PlatformsMoving a Fraud-Fighting Random Forest from scikit-learn to Spark with MLlib, MLflow, and JupyterPractical ML | Virtual EventFree Training: Building and Deploying Machine Learning ModelsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lakhan-prajapati","text":"Lakhan Prajapati - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLakhan PrajapatiDirector of Architecture and Engineering at ZS associatesBack to speakersTechnology Enthusiast, Loves solving complex tech problems for the enterprise. Expertise in the field of cloud, data warehousing, and enterprise architectureLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rahul-pandey","text":"Rahul Pandey - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRahul PandeySolution Architect at adidasBack to speakersRahul is working on Data Engineering and Data Science projects as a Solution Architect at Adidas. His goal is to build cost-effective and efficient architecture designs. He is motivated to raise awareness about sustainability in AI within Data Science teams.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/migration","text":"Databricks \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3078\u306e\u79fb\u884c | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u3078\u306e\u304a\u554f\u3044\u5408\u308f\u305b\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anindya-saha","text":"Anindya Saha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnindya SahaML Platform Software Engineer at nullBack to speakersAnindya Saha is a Machine Learning Platform Engineer, focusing on enabling distributed computing solutions for machine learning and data engineering. He has led implementation of Spark on Kubernetes support on ml platform for feature engineering at scale. He also worked on enabling multi gpus multi nodes distributed model training on machine learning platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/artem-meshcheryakov\/#","text":"Artem Meshcheryakov - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArtem MeshcheryakovConsultant at ORAYLIS GmbHBack to speakersArtem Meshcheryakov has been working in BI & BigData for more than 5 years. \nStarting with Microsoft SQL Server and Oracle for traditional Data Warehousing Projects,\nwithin several years he switched to modern data platforms in the Azure Cloud with the main focus on Azure Databricks. \nFor several years now, he has been working in this area, \nhe has been involved in building solutions using Azure Databricks at \nlarge Scale and developing BigData Use Cases with Databricks.\nAt Oraylis, Artem works as a consultant and is responsible for implementing \nlarge-scale modern data platform in various Azure cloud scenarios.\nArtem is also a certified Databricks champion. \nHe is particularly interested in developing large-scale Big Data use cases \nusing Databricks and the Unity catalog in large enterprise environments.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/university-recruiting","text":"Databricks University Recruiting | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWShape tomorrowStart your career at Databricks and help data teams solve the world\u2019s toughest problemsExplore opportunities OverviewCultureBenefitsDiversityStudents & new gradsStudent internships and college grad opportunitiesWe\u2019re committed to learning and development at every level, so it\u2019s important to our teams that we recruit and develop our next generation of Databricks leaders. Our University Program ensures that interns and new college grads play an integral role in developing our Platform, while participating in fun events to get to know each other and the larger Databricks team.Develop with an innovative global teamFounded in 2013 by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks has grown from a tiny corner office in Berkeley, California, to a company with employees all over the world.\nDatabricks has since become the industry leader for data-driven decision-making with its cloud-based infrastructure, collaborative workspace, team-based version control, integrated libraries for data manipulation and visualization, Spark-compatible optimized runtime environment, and robust security.WayUp Top 100 Internship Programs List for 2020Databricks is proud to be recognized on WayUp's Top 100 Internship Program.Read moreLife at DatabricksResources for studentsHear from the internsRead what it\u2019s likeMastering engineering interviewsLearn the best tips & tricksUse Databricks in your classroomGet hands-on experienceCommunity edition of DatabricksTry out DatabricksFeeling good about our internship opportunities?See internship positionsSee all jobsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2018\/11\/27\/databricks-shows-off-aws-competencies-at-aws-reinvent.html#govcloud","text":"Databricks Shows off AWS Competencies at AWS re:Invent - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDatabricks Shows off AWS Competencies at AWS re:Inventby Michael OrtegaNovember 27, 2018 in Company BlogShare this postPowering innovation on AWS in life sciences, public sector, machine learning, and big data analytics.Databricks, founded by the original creators of Apache SparkTM, is proud to be a Platinum sponsor at AWS re:Invent. Stop by booth #416 to grab some cool schwag and see demos of MLflow, TensorFlow, Apache Spark, and other\u00a0 technologies that are accelerating innovation at a growing number of companies, including HP, Shell, and NBCUniversal.\nThe AWS Competency Program is designed to highlight Amazon Partners that have demonstrated technical proficiency and customer success in specialized solution areas.\nHere\u2019s a quick overview of Databricks\u2019 AWS Competencies:Databricks was recently recognized as an AWS Life Sciences Competency Partner, highlighting our success building innovative data analytics and machine learning solutions for Life Sciences organizations. Our Life Sciences solutions expand on the core capabilities of our Unified Analytics Platform with industry-specific toolsets to serve use cases across the drug development and precision medicine lifecycles.\nOur first offering, the Databricks Unified Analytics Platform for Genomics, is designed to provide the scale and speed bioinformatics teams need to accelerate drug discovery and deliver precision care. Fully-managed in the AWS cloud, the platform provides collaborative workspaces for cross-disciplinary biomedical and pharmaceutical teams \u2013 from bioinformaticians to computational biologists to physician-scientists \u2013 to easily access, analyze, and extract novel insights from large volumes of genomic, imaging, and clinical datasets. The solution provides prebuilt best practice genomic pipelines and popular tertiary analytics tools in a secure, HIPAA compliant environment.\nCustomers including Regeneron, Sanford Health and the Human Longevity Institute have adopted Databricks to drastically scale and improve performance of their genomics workflows on AWS. Learn more about their use cases at our booth #416 at re:Invent.\nThe Databricks Unified Analytics Platform makes it easy for data science and engineering teams to collaborate with business teams around big data analytics and AI. We're focused on removing the challenges associated with AI adoption so that more businesses can fully harness its benefits.\nOur AWS Machine Learning Competency\u00a0highlights our expertise in artificial intelligence (AI) and machine learning. With the Databricks Unified Analytics Platform, data scientists and machine learning practitioners are empowered to analyze data at scale, train and deploy models with ease, and build powerful predictive applications.\nA growing number of customers including Riot Games and Viacom have already delivered on innovative AI use cases with Databricks and AWS. Stop by booth #416 at\u00a0re:Invent for a demo.\nData and analytics has become a strong competitive differentiator for most organizations. As an AWS Data & Analytics Competency Partner, Databricks has demonstrated success helping AWS customers improve the productivity of their data teams and draw insights from their data.\nTransforming data into usable information can involve multiple tools and technologies. The Databricks Unified Analytics platform removes these obstacles, making it easy for organizations to turn data into value, from ingest through production, without the hassle of managing complex infrastructure, systems and tools. Visit our our booth #416 at\u00a0re:Invent to learn more.\nFrom providing better social services to preventing national threats, government agencies rely on secure, efficient and large-scale data processing and analysis to carry out their duties.\nThe Databricks Unified Analytics platform, recognized for it\u2019s robust security model, has been available on the AWS GovCloud, an isolated AWS region designed to host sensitive and regulated data in the cloud, since 2016 and has the Authority to Operate in the AWS Commercial Cloud Service (C2S) for highly sensitive workflows. Databricks on AWS empowers government agencies to securely build and deploy advanced analytics solutions to meet a broad range of public sector use cases.\nVisit our booth #416\u00a0at re:Invent to learn how we help government agencies simplify, scale and accelerate data analytics and AI for mission critical applications.\nMake sure to check out\u00a0reinvent\u00a0to catch up on our latest announcements, demos and sessions taking place at re:Invent. If you're not able to visit us at re:Invent, stop by\u00a0databricks.com\/product\/aws\u00a0for our latest case studies, ebooks and customer webinars.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"Solutions partenaires - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWSolutions partenairesDes solutions sp\u00e9cialis\u00e9es pour le lakehouse et des outils de migration d\u00e9velopp\u00e9s par nos partenairesNous sommes partenaires d'entreprises de premier plan sp\u00e9cialis\u00e9es dans le conseil, afin de concevoir des solutions et des outils de migration innovants pour des cas d'usage sp\u00e9cifiques \u00e0 votre secteur d'activit\u00e9. Les Solutions Brickbuilder de Databricks sont con\u00e7ues par nos partenaires pour vous aider \u00e0 r\u00e9duire les co\u00fbts et augmenter la valeur de vos donn\u00e9es. Gr\u00e2ce \u00e0 leurs ann\u00e9es d'exp\u00e9rience dans le secteur et \u00e0 leur forte implication dans la plateforme Databricks\u00a0Lakehouse, vous avez la garantie de b\u00e9n\u00e9ficier de solutions adapt\u00e9es \u00e0 votre entreprise.Rechercher des partenaires disponiblessearchSecteur publicCloud Data Migration by Accenture - DatabricksEn savoir plusVente au d\u00e9tail et biens de consommationUnified View of Demand by AccentureEn savoir plusTechnologie marketing et publicit\u00e9CPG Control Tower by AvanadeEn savoir plusTechnologie marketing et publicit\u00e9Intelligent Healthcare on Azure Databricks by AvanadeEn savoir plusTechnologie marketing et publicit\u00e9Intelligent ManufacturingEn savoir plusTechnologie marketing et publicit\u00e9Legacy System Migration by AvanadeEn savoir plusTechnologie marketing et publicit\u00e9Risk Management by AvanadeEn savoir plusTechnologie et solutionsMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksEn savoir plusTechnologie et solutionsMigrate to Cloud and Databricks by Capgemini and DatabricksEn savoir plusTechnologie et solutionsCapgemini Revenue Growth ManagementEn savoir plusTechnologie et solutionsMigrate to Databricks by Celebal Technologies and DatabricksEn savoir plusTechnologie et solutionsCognizant Video Quality of ExperienceEn savoir plusTechnologie marketing et publicit\u00e9Persona 360 by DataSentics and DatabricksEn savoir plusTechnologie marketing et publicit\u00e9SAP Migration Accelerator by DataSentics - DatabricksEn savoir plusTechnologie marketing et publicit\u00e9PrecisionView\u2122 by DeloitteEn savoir plusTechnologie marketing et publicit\u00e9Trellis by DeloitteEn savoir plusTechnologie marketing et publicit\u00e9Smart Migration to Databricks by EPAMEn savoir plusTechnologie marketing et publicit\u00e9LeapLogic Migration Solution by ImpetusEn savoir plusLIRE PLUSPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/resources\/whitepaper\/realizing-the-value-of-real-world-evidence?itm_data=menu-promo-WP-RWEFierce","text":"Realizing the Value of Real-World Evidence - DatabricksWhitepaperRemove the barriers to real-world evidence successEveryone knows real-world evidence (RWE) has value. But due to technology challenges, biopharma companies are struggling to achieve the full benefit of their RWE programs. Databricks recently surveyed 109 executives to get a better idea of what\u2019s working, what\u2019s not and the path forward.Get the full results in this whitepaper. You\u2019ll find out:What benefits are driving investments in RWE programsWhich new types of real-world data will emerge in the next two yearsThe top factors inhibiting and contributing to RWE program successHow to build the ideal data architecture to unlock business outcomes with RWERead the whitepaperProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vinod-marur","text":"Vinod Marur - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVinod MarurSVP of Engineering at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/contact","text":"Kontakt \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWKontaktBrauchen Sie Hilfe bei Fortbildung oder Support? Dann rufen Sie diese zus\u00e4tzlichen Ressourcen auf.DokumentationLesen Sie unsere technische Dokumentation zu Databricks auf AWS, Azure oder Google Cloud.Databricks-CommunityHier k\u00f6nnen Sie mit Databricks-Benutzern und Experten diskutieren, sich austauschen und sich vernetzen.WeiterbildungMeistern Sie die Databricks Lakehouse-Plattform mit Schulungen unter Anleitung und im Selbststudium oder werden Sie zertifizierter Entwickler.SupportSie sind schon Kunde? Dann klicken Sie hier, falls Sie ein technisches oder ein Zahlungsproblem haben.Unsere NiederlassungenZeigen Sie alle Niederlassungen weltweit an und nehmen Sie Kontakt auf.Knowledge BaseHier finden Sie schnelle Antworten auf die meistgestellten Fragen zu Databricks-Produkten und -Services.ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"Partnerl\u00f6sungen \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWL\u00f6sungen von PartnernVon Partnern entwickelte Branchen- und Migrationsl\u00f6sungen f\u00fcr das LakehouseWir haben uns mit f\u00fchrenden Consulting-Partnern zusammengetan, um innovative L\u00f6sungen f\u00fcr branchen- und migrationsspezifische Anwendungsf\u00e4lle zu entwickeln. Von unseren Partnern fachgerecht konzipiert, sollen Databricks Brickbuilder-L\u00f6sungen Sie dabei unterst\u00fctzen, Kosten zu senken und den Mehrwert Ihrer Daten zu steigern. Dank der langj\u00e4hrigen Branchenerfahrung unserer Partner und der auf die Lakehouse-Plattform von Databricks zugeschnittenen Entwicklung k\u00f6nnen Sie auf L\u00f6sungen vertrauen, die f\u00fcr Ihr Unternehmen ma\u00dfgeschneidert sind.Nach vorhandenen Partnern suchensearch\u00d6ffentlicher SektorCloud Data Migration by Accenture - DatabricksMehr InformationenEinzelhandel und Konsumg\u00fcterUnified View of Demand by AccentureMehr InformationenWerbe- und MarketingtechnologieCPG Control Tower by AvanadeMehr InformationenWerbe- und MarketingtechnologieIntelligent Healthcare on Azure Databricks by AvanadeMehr InformationenWerbe- und MarketingtechnologieIntelligent ManufacturingMehr InformationenWerbe- und MarketingtechnologieLegacy System Migration by AvanadeMehr InformationenWerbe- und MarketingtechnologieRisk Management by AvanadeMehr InformationenTechnologie und SoftwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksMehr InformationenTechnologie und SoftwareMigrate to Cloud and Databricks by Capgemini and DatabricksMehr InformationenTechnologie und SoftwareCapgemini Revenue Growth ManagementMehr InformationenTechnologie und SoftwareMigrate to Databricks by Celebal Technologies and DatabricksMehr InformationenTechnologie und SoftwareCognizant Video Quality of ExperienceMehr InformationenWerbe- und MarketingtechnologiePersona 360 by DataSentics and DatabricksMehr InformationenWerbe- und MarketingtechnologieSAP Migration Accelerator by DataSentics - DatabricksMehr InformationenWerbe- und MarketingtechnologiePrecisionView\u2122 by DeloitteMehr InformationenWerbe- und MarketingtechnologieTrellis by DeloitteMehr InformationenWerbe- und MarketingtechnologieSmart Migration to Databricks by EPAMMehr InformationenWerbe- und MarketingtechnologieLeapLogic Migration Solution by ImpetusMehr InformationenMEHR LADENM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/it\/legal\/privacynotice#dbadditionalinformation","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. 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For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yaniv-kunda\/#","text":"Yaniv Kunda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYaniv KundaSenior Software Architect at AkamaiBack to speakersYaniv Kunda is a Senior Software Architect at Akamai. With more than 25 years of experience in software engineering and with a particular interest in the infrastructural aspects of the systems he worked on, Yaniv has been focusing on Big Data for the past 4 years. He holds a BA in Computer Sciences from the Interdisciplinary Center Herzliya.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeff-breeding-allison\/#","text":"Jeff Breeding-Allison - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeff Breeding-AllisonSenior Data Scientist at Mars PetcareBack to speakersJeff Breeding-Allison is a Senior Data Scientist at Mars Petcare with years of experience working in demand forecasting at CPG and marketing companies. He was previously a Visiting Assistant Professor of Mathematics at Boston College and at Fordham University in NYC, where he published research on modular forms, automorphic representations, and the representation theory of finite general symplectic groups.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yeshwanth-vijayakumar\/#","text":"Yeshwanth Vijayakumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYeshwanth VijayakumarSr Engineering Manager\/Architect at AdobeBack to speakersYeshwanth Vijayakumar is a Sr Engineering Manager\/Architect on the Unified Profile Team in the Adobe Experience Platform; it\u2019s a PB scale store with a strong focus on millisecond latencies and analytical abilities and easily one of Adobe\u2019s most challenging SaaS projects in terms of scale. He is actively designing\/implementing the Interactive segmentation capabilities which helps us segment over two million records per second using Apache Spark. He looks for opportunities to build new features using interesting data Structures and Machine Learning approaches. In a previous life, he was a ML Engineer on the Yelp Ads team building models for Snippet Optimizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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{"source":"https:\/\/www.databricks.com\/blog\/2022\/03\/03\/hyper-personalization-accelerator-for-banks-and-fintechs-using-credit-card-transactions.html","text":"Hyper-Personalization Accelerator for Banks and Fintechs Using Credit Card Transactions - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHyper-Personalization Accelerator for Banks and Fintechs Using Credit Card TransactionsLakehouse for Financial Services as the strategic platform to accelerate digital transformation in retail bankingby Antoine AmendMarch 3, 2022 in Engineering BlogShare this postJust as Netflix and Tesla disrupted the media and automotive industry, many fintech companies are transforming the Financial Services industry by winning the hearts and minds of a digitally active population through personalized services, numberless credit cards that promise more security, and frictionless omnichannel experiences. NuBank's success story as an eight-year old startup becoming Latin America's most valuable bank is not an isolated case; over 280 other fintechs unicorns are also willing to disrupt the entire payment industry. As noted in the Financial Conduct Authority (FCA) study, \"There are signs that some of the historic advantages of large banks may be starting to weaken through innovation, digitization and changing consumer behavior.\" Faced with the choice of either disrupting or being disrupted, many traditional financial services institutions (FSIs) like JP Morgan Chase have recently announced significant strategic investments to compete with fintech companies on their own grounds \u2013 on the cloud, using data and artificial intelligence (AI).Given the volume of data required to drive advanced personalization, the complexity of operating AI from experiments (proof of concepts\/POCs) to enterprise scale data pipelines, combined with strict data and privacy regulations on the use of customer data on cloud infrastructure, Lakehouse for Financial Services has quickly emerged as the strategic platform for many disruptors and incumbents alike to accelerate digital transformation and provide millions of customers with personalized insights and enhanced banking experiences (see how HSBC is reinventing mobile banking with AI).In our previous solution accelerator, we showed how to identify brands and merchants from credit card transactions. In our new solution accelerator (inspired from the 2019 study of Bruss et. al. and from our experience working with global retail banking institutions), we capitalized on that work to build a modern hyper-personalization data asset strategy that captures a full picture of the consumer and goes beyond traditional demographics, income, product and services (who you are) and extends to transactional behavior and shopping preferences (how you bank). As a data asset, the same can be applied to many downstream use cases, such as loyalty programs for online banking applications, fraud prevention for core banking platforms or credit risk for \"buy now pay later\" (BNPL) initiatives.Transactional contextWhile the common approach to any segmentation use case is a simple clustering model, there are only a few off-the-shelf techniques. Alternatively, when converting data from its original archetype, one can access a wider range of techniques that often yield unexpected results. In this solution accelerator, we convert our original card transaction data into graph paradigm and leverage techniques originally designed for Natural Language Processing (NLP).Similar to NLP techniques where the meaning of a word is defined by its surrounding context, a merchant's category can be learned from its customer base and the other brands that their consumers support. In order to build this context, we generate \"shopping trips\" by simulating customers walking from one shop to another, up and down our graph structure. The aim is to learn \"embeddings,\" a mathematical representation of the contextual information carried by the customers in our network. In this example, two merchants contextually close to one another would be embedded into large vectors that are mathematically close to one another. By extension, two customers exhibiting the same shopping behavior will be mathematically close to one another, paving the way for a more advanced customer segmentation strategy.Merchant embeddingsWord2Vec was developed by Tomas Mikolov, et. al. at Google to make the neural network training of the embedding more efficient, and has since become the de facto standard for developing pre-trained word embedding algorithms. In our solution, we will use the default wordVec model from the Apache Spark\u2122 ML API that we train against our shopping trips defined earlier.\nfrom pyspark.ml.feature import Word2Vec\n \nwith mlflow.start_run(run_name='shopping_trips') as run:\n \n word2Vec_model = Word2Vec() \\\n   .setVectorSize(255) \\\n   .setWindowSize(3) \\\n   .setMinCount(5) \\\n   .setInputCol('walks') \\\n   .setOutputCol(vectors) \\\n   .fit(shopping_trips)\n \n  mlflow.spark.log_model(word2Vec_model, \"model\")\nThe most obvious way to quickly validate our approach is to eyeball its results and apply domain expertise. In this example of brands like \"Paul Smith\", our model can find Paul Smiths' closest competitors to be \"Hugo Boss\", \"Ralph Lauren\" or \"Tommy Hilfiger.\"We did not simply detect brands within the same category (i.e. fashion industry) but detected brands with a similar price tag. Not only could we classify different lines of businesses using customer behavioral data, but our customer segmentation could also be driven by the quality of goods they purchase. This observation corroborates the findings by Bruss et. al.Merchant clusteringAlthough the preliminary results were troubling, there might be groups of merchants more or less similar than others that we may want to identify further. The easiest way to find those significant groups of merchants\/brands is to visualize our embedded vector space into a 3D plot. For that purpose, we apply machine learning techniques like Principal Component Analysis (PCA) to reduce our embedded vectors into 3 dimensions.Using a simple plot, we could identify distinct groups of merchants. Although these merchants may have different lines of business, and may seem dissimilar at first glance, they all have one thing in common: they attract a similar customer base. We can better confirm this hypothesis through a clustering model (KMeans).Transactional fingerprintsOne of the odd features of the word2vec model is that sufficiently large vectors could still be aggregated while maintaining high predictive value. To put it another way, the significance of a document could be learned by averaging the vector of each of its word constituents (see whitepaper from Mikolov et. al.). Similarly, customer spending preferences can be learned by aggregating vectors of each of their preferred brands. Two customers having similar tastes for luxury brands, high-end cars and fine liquor would theoretically be close to one another, hence belonging to the same segment.\ncustomer_merchants = transactions \\\n   .groupBy('customer_id') \\\n   .agg(F.collect_list('merchant_name').alias('walks'))\n\ncustomer_embeddings = word2Vec_model.transform(customer_merchants)\nIt is worth mentioning that such an aggregated view would generate a transactional fingerprint that is unique to each of our end consumers. Although two fingerprints may share similar traits (same shopping preferences), these unique signatures can be used to track unique individual customer behaviors over time.When a signature drastically differs from previous observations, this could be a sign of fraudulent activities (e.g. sudden interest for gambling companies). When signature drifts over time, this could be indicative of life events (having a newborn child). This approach is key to driving hyper-personalization in retail banking: the ability to track customer preferences against real-time data will help banks provide personalized marketing and offers, such as push notifications, across various life events, positive or negative.Customer segmentationAlthough we were able to generate some signal that offers great predictive value to customer behavioral analytics, we still haven't addressed our actual segmentation problem. Borrowing from retail counterparts that are often more advanced when it comes to customer 360 use cases including segmentation, churn prevention or customer lifetime value, we can use a different solution accelerator from our Lakehouse for Retail that walks us through different segmentation techniques used by best-in-class retail organizations.Following retail industry best practices, we were able to segment our entire customer base against 5 different groups exhibiting different shopping characteristics.While cluster #0 seems to be biased towards gambling activities (merchant category 4 in the above graph), another group is more centered around online businesses and subscription-based services (merchant category 6), probably indicative of a younger generation of customers. We invite our readers to complement this view with additional data points they already know about their customers (original segments, products and services, average income, demographics, etc.) to better understand each of those behavioral driven segments and its impact for credit decisioning, next-best action, personalized services, customer satisfaction, debt collection or marketing analytics.Closing thoughtsIn this solution accelerator, we have successfully applied concepts from the world of NLP to card transactions for customer segmentation in retail banking. We also demonstrated the relevance of the Lakehouse for Financial Services to address this challenge where graph analytics, matrix calculation, NLP, and clustering techniques must all be combined into one platform, secured and scalable. Compared to traditional segmentation methods easily addressed through the world of SQL, the disruptive future of segmentation builds a fuller picture of the consumer and can only be solved with data + AI, at scale and in real time.Although we've only scratched the surface of what was possible using off-the-shelf models and data at our disposal, we proved that customer spending patterns can more effectively drive hyper-personalization than demographics, opening up an exciting range of new opportunities from cross-sell\/upsell and pricing\/targeting activities to customer loyalty and fraud detection strategies.Most importantly, this technique allowed us to learn from new-to-bank individuals or underrepresented consumers without a known credit history by leveraging information from others. With 1.7 billion adults worldwide who do not have access to a bank account according to the World Economic Forum, and 55 million underbanked in the US alone in 2018 according to the Federal Reserve, such an approach could pave the way towards a more customer-centric and inclusive future for retail banking.Try the accelerator notebooks on Databricks to test your customer 360 data asset strategy today and contact us to learn more about how we have helped customers with similar use cases.Try Databricks for freeGet StartedRelated postsImproving Customer Experience With Transaction EnrichmentMay 10, 2021 by Milos Colic in Engineering Blog\nThe retail banking landscape has dramatically changed over the past five years with the accessibility of open banking applications, mainstream adoption of Neobanks...\n4 Ways AI Can Future-proof Financial Services\u2019 Risk and ComplianceSeptember 16, 2021 by Fahmid Kabir and Antoine Amend in Industries\nLearn more about Smarter risk and compliance on our new hub. The core function of a bank is to protect assets, identify risks...\nA Data-driven Approach to Environmental, Social and GovernanceJuly 10, 2020 by Antoine Amend in Engineering Blog\nThe future of finance goes hand in hand with social responsibility, environmental stewardship and corporate ethics. In order to stay competitive, Financial Services...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steven-yu\/#","text":"Steven Yu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteven YuPrincipal Solutions Architect at DatabricksBack to speakersTBDLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/data-science","text":"Data Science | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWData ScienceData science collaborativa su larga scalaProva gratuitaProgramma una demoApprofondisci la scienza dei dati su DatabricksDatabricks NotebooksIDE IntegrationReposMachine LearningL'intero flusso di lavoro di data science \u2014 dalla preparazione dei dati, passando per la modellazione, fino alla condivisione delle informazioni \u2014 pu\u00f2 essere snellito con un ambiente di data science unificato e collaborativo, basato su una piattaforma lakehouse aperta. In questo modo si potr\u00e0 accedere velocemente a dati puliti e affidabili, risorse di calcolo preconfigurate, integrazione IDE, assistenza multilingua e strumenti integrati di visualizzazione avanzata per offrire la massima flessibilit\u00e0 ai team di analisi dei dati.Collaborazione lungo l'intero flusso di lavoro di data scienceScrivi codice in Python, R, Scala e SQL, esplora i dati con visualizzazioni interattive e scopri nuove informazioni con i notebook di Databricks. \u00c8 possibile condividere codice in modo affidabile e sicuro con co-creazione, commenti, gestione automatica delle versioni, integrazioni Git e controllo degli accessi per ruoli.Focalizzazione sulla data science, non sull'infrastrutturaNon ci sono limiti imposti dalla quantit\u00e0 di dati conservabili nel proprio laptop o dalla capacit\u00e0 di calcolo disponibile. Migra rapidamente sul cloud il tuo ambiente locale e collega i notebook ai tuoi cluster personali di calcolo e autogestiti.Utilizzare l'ambiente di sviluppo IDE preferito con capacit\u00e0 di calcolo scalabileLa scelta dell'ambiente di sviluppo IDE (Integrated Development Environment) \u00e8 molto soggettiva e incide fortemente sulla produttivit\u00e0.Collegando il proprio IDE preferito a Databricks si potr\u00e0 comunque beneficiare di capacit\u00e0 illimitate di stoccaggio dati e calcolo. In alternativa, si possono utilizzare RStudio o JupyterLab direttamente dall'interno di Databricks per ottenere un'esperienza fluida.Preparare i dati per la data scienceTutti i dati (in batch o in streaming, strutturati o non strutturati) possono essere puliti e catalogati in un unico punto con Delta Lake ed essere accessibili all'intera organizzazione attraverso un data store centralizzato. Man mano che i dati affluiscono, i controlli di qualit\u00e0 automatici garantiscono che i dati siano conformi alle aspettative e pronti per l'analisi. Quando i dati si evolvono con l'acquisizione di nuovi dati e ulteriori elaborazioni, la gestione delle versioni assicura il rispetto delle esigenze di conformit\u00e0.Strumenti visivi low-code per l'esplorazione dei datiUsa gli strumenti visivi in modo nativo dai notebook Databricks per preparare, trasformare e analizzare i tuoi dati, permettendo ai team con vari livelli di esperienza di lavorare con i dati. Una volta concluse le trasformazioni e le visualizzazioni dei dati, potrai generare il codice in esecuzione in background, risparmiando tempo nella scrittura del codice boilerplate per poter dedicare pi\u00f9 tempo ai compiti di alto valore.Scoprire e condividere nuove informazioniI risultati possono ora essere facilmente condivisi ed esportati trasformando velocemente l'analisi in un dashboard dinamico. I dashboard sono sempre aggiornati e possono anche effettuare interrogazioni interattive. Celle, visualizzazioni o notebook possono essere condivisi con il controllo degli accessi per ruoli ed esportati in diversi formati, fra cui HTML e IPython Notebook.Migrazione a DatabricksStanco dei silos di dati, della lentezza e dei costi esorbitanti di sistemi obsoleti come Hadoop e i data warehouse aziendali? Migra a Databricks Lakehouse, la piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI.Migrazione a DatabricksRisorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video su data science e machine learning.\nEsplora risorseReport ed eBookThe Big Book of Data ScienceThe Art of Collaborative Data Science at ScaleModerna piattaforma dati in cloudMLflow \u2013 Una piattaforma di machine learning open-sourceScopri la nuova soluzione Delta SharingDatabricks nominata leader nel Gartner\u00ae Magic Quadrant\u2122 2021 nelle categorie DBMS e DSMLGuida alla migrazione: da Hadoop a DatabricksBlog5 mosse fondamentali per una migrazione efficace da Hadoop all'architettura lakehouseEventi virtualiGuida passo-passo alla migrazione da HadoopPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/julie-ferris\/#","text":"Julie Ferris - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJulie FerrisVice President, Commercial Optimization at Definitive HealthcareBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rakesh-kumar","text":"Rakesh Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRakesh KumarStaff Software Engineer at Lyft IncBack to speakersRakesh Kumar is a staff software engineer on the Realtime Optimization Platform team at Lyft. He started his career as an embedded software engineer for mobile devices; later he moved to server-side engineer to tackle bigger challenges in distributed systems. His interests include machine learning and streaming systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suneel-konidala","text":"Suneel Konidala - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuneel KonidalaSr. Manager at AccentureBack to speakersSuneel is an accomplished leader in Data space for more than two decades. He is a lead partner champion at Accenture's Databricks practice. Suneel is well versed in multiple data and cloud technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/balaji-ramanujam","text":"Balaji Ramanujam - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBalaji RamanujamAVP - Senior Principal Technology Architect at InfosysBack to speakersBalaji is Head of Industry Architecture - Data and AI North America (USA & Canada), with 23 years of experience in Information Technology and experience in Healthcare \/ Life sciences , Banking & Retail industry. He is a Data Technologist with flair and passion for solving complex data problems, helping business build connections and eco-systems (Next generation data trend). He is architecture Leader for North America on Cloud and Data Management , Data engineering and ML engineering technologies with focus on creating Business Platforms and creating industry solutions.\nHe has strong skills in Cloud Data Architecture, Enterprise ML, Data Modeling, design, development and implementation of ETL & BI Analytics solutions. Worked on large programs involving complex business requirements and different business teams. He has played key roles in initiating and enabling new projects. Technical Architect \/Consultant \/ advisor to multiple BI Projects - providing inputs from solution architecture to data model to reporting layer - to enhance the efficiency of a solution.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erin-boelkens","text":"Erin Boelkens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErin BoelkensVP of Product at LiveRampBack to speakersErin Boelkens is Vice President of Product at LiveRamp (NYSE: RAMP). In this role, she oversees LiveRamp solutions that enable clients to manage data assets in a safe and secure way across identity, business development, addressability, healthcare, and data management. Previously, Erin was LiveRamp\u2019s VP of Engineering and Head of Global Identity Engineering, where she led a team of creative and innovative engineers providing industry-leading identity products across offline and online channels. Erin joined the company in 2018 after spending 13 years in engineering, product and data science at Acxiom (Nasdaq: ACXM). Erin holds a bachelor\u2019s degree in computer information systems and a master\u2019s of science in management information systems from Arkansas State University. She is also certified as a Scrum Product Owner and a Scrum Master from the Scrum Alliance, as well as Marketing certification from Pragmatic Marketing. She resides in Little Rock, Arkansas.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ivan-peng\/#","text":"Ivan Peng - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIvan PengSoftware Engineer at DoorDashBack to speakersIvan is a software engineer on the data infrastructure team at DoorDash. His team is responsible for providing the foundation of data and ensuring that it is accurate and delivered in a timely manner. Prior to DoorDash, Ivan was at Nextdoor on the Data Platform team, focusing on experimentation and building a data platform for privacy and compliance. In his spare time, Ivan enjoys playing ultimate frisbee, geeking out about sports analytics, and biking to distant places in lieu of driving.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/11\/16\/evolution-of-the-sql-language-at-databricks-ansi-standard-by-default-and-easier-migrations-from-data-warehouses.html","text":"Evolution of the SQL language at Databricks: ANSI standard by default and easier migrations from data warehouses - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorEvolution of the Sql Language at Databricks: Ansi Standard by Default and Easier Migrations from Data Warehousesby Serge Rielau, Shant Hovsepian and Reynold XinNovember 16, 2021 in Platform BlogShare this postDatabricks SQL\u00a0is now generally available on AWS and Azure.\u00a0Today, we are excited to announce that Databricks SQL will use the ANSI standard SQL dialect by default. This follows the announcement earlier this month about Databricks SQL\u2019s record-setting performance and marks a major milestone in our quest to support open standards. This blog post discusses how this update makes it easier to migrate your data warehousing workloads to Databricks lakehouse platform. Moreover, we are happy to announce improvements in our SQL support that make it easier to query JSON and perform common tasks more easily.Migrate easily to Databricks SQLWe believe Databricks SQL is the best place for data warehousing workloads, and it should be easy to migrate to it. Practically, this means changing as little of your SQL code as possible. We do this by switching out the default SQL dialect from Spark SQL to Standard SQL, augmenting it to add compatibility with existing data warehouses, and adding quality control for your SQL queries.Standard SQL we can all agree onWith the SQL standard, there are no surprises in behavior or unfamiliar syntax to look up and learn.String concatenation is such a common operation that the SQL standard designers gave it its own operator. The double-pipe operator is simpler than having to perform a concat() function call:\nSELECT\n  o_orderstatus || ' ' || o_shippriority as order_info\nFROM\n  orders;\nThe FILTER clause, which has been in the SQL standard since 2003, limits rows that are evaluated during an aggregation. Most data warehouses require a complex CASE expression nested within the aggregation instead:\nSELECT\n  COUNT(DISTINCT o_orderkey) as order_volume,\n  COUNT(DISTINCT o_orkerkey) FILTER (WHERE o_totalprice > 100.0) as big_orders <span style=\"color: #a56319;\">-- using rows that pass the predicate<\/span>\nFROM orders;\nSQL user-defined functions (UDFs) make it easy to extend and modularize business logic without having to learn a new programming language:\nCREATE FUNCTION inch_to_cm(inches DOUBLE)\nRETURNS DOUBLE RETURN 2.54 * inches;\n\nSELECT inch_to_cm(5); <span style=\"color: #a56319;\">-- returns 12.70<\/span>\nCompatibility with other data warehousesDuring migrations, it is common to port hundreds or even thousands of queries to Databricks SQL. Most of the SQL you have in your existing data warehouse can be dropped in and will just work on Databricks SQL. To make this process simpler for customers, we continue to add SQL features that remove the need to rewrite queries.For example, a new QUALIFY clause to simplify filtering window functions makes it easier to migrate from Teradata. The following query finds the five highest-spending customers in each day:\nSELECT\n  o_orderdate,\n  o_custkey,\n  RANK(SUM(o_totalprice)) OVER (PARTITION BY o_orderdate ORDER BY SUM(o_totalprice) DESC) AS rank\nFROM orders\nGROUP BY o_orderdate, o_custkey\nQUALIFY rank -- applies after the window function\nWe will continue to increase compatibility features in the coming months. If you want us to add a particular SQL feature, don\u2019t hesitate to reach out.Quality control for SQLWith the adoption of the ANSI SQL dialect, Databricks SQL now proactively alerts analysts to problematic queries. These queries are uncommon but they are best caught early so you can keep your lakehouse fresh and full of high-quality data. Below is a selection of such changes (see our documentation for a full list).Invalid input values when casting a STRING to an INTEGERArithmetic operations that cause an overflowDivision by zeroEasily and efficiently query and transform JSONIf you are an analyst or data engineer, chances are you have worked with unstructured data in the form of JSON. Databricks SQL natively supports ingesting, storing and efficiently querying JSON. With this release, we are happy to announce improvements that make it easier than ever for analysts to query JSON.Let\u2019s take a look at an example of how easy it is to query JSON in a modern manner. In the query below, the raw column contains a blob of JSON. As demonstrated, we can query and easily extract nested fields and items from an array while performing a type conversion:\nSELECT\n  raw:customer.full_name,     <span style=\"color: #a56319;\">-- nested field<\/span>\n  raw:customer.addresses[0],  <span style=\"color: #a56319;\">-- array<\/span>\n  raw:customer.age::integer,  <span style=\"color: #a56319;\">-- type cast<\/span>\nFROM customer_data;\nWith Databricks SQL you can easily run these queries without sacrificing performance or by having to extract the columns out of JSON into separate tables. This is just one way in which we are excited to make life easier for analysts.Simple, elegant SQL for common tasksWe have also spent time doing spring cleaning on our SQL support to make other common tasks easier. There are too many new features to cover in a blog post, but here are some favorites.Case-insensitive string comparisons are now easier:\nSELECT\n  *\nFROM\n  orders\nWHERE\n  o_orderpriority ILIKE '%urgent'; <span style=\"color: #a56319;\">-- case insensitive string comparison<\/span>\nShared WINDOW frames save you from having to repeat a WINDOW clause. Consider the following example where we reuse the win WINDOW frame to calculate statistics over a table:\nSELECT\n  round(avg(o_totalprice) OVER win, 1) AS price,\n  round(avg(o_totalprice) OVER win, 1) AS avg_price,\n  min(o_totalprice) OVER win           AS min_price,\n  max(o_totalprice) OVER win           AS max_price,\n  count(1) OVER win              AS order_count\nFROM orders\n<span style=\"color: #a56319;\">-- this is a shared WINDOW frame<\/span>\nWINDOW win AS (ORDER BY o_orderdate ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING);\nMulti-value INSERTs make it easy to insert multiple values into a table without having to use the UNION keyword, which is common most other data warehouses:\nCREATE TABLE employees\n(name STRING, dept STRING, salary INT, age INT);\n\n<span style=\"color: #a56319;\">-- this is a multi-valued INSERT<\/span>\nINSERT INTO employees\nVALUES ('Lisa', 'Sales', 10000, 35),\n       ('Evan', 'Sales', 32000, 38),\n       ('Fred', 'Engineering', 21000, 28);\nLambda functions are parameterized expressions that can be passed to certain SQL functions to control their behavior. The example below passes a lambda to the transform function, concatenating together the index and values of an array (themselves an example of structured types in Databricks SQL).\n<span style=\"color: #a56319;\">-- this query returns [\"0: a\",\"1: b\",\"2: c\"]<\/span>\nSELECT\n  transform(\n    array('a','b','c'),\n    (x, i) -> i::string || ': ' || x <span style=\"color: #a56319;\">-- this is a lambda function<\/span>\n  );\nUpdate data easily with standard SQLData is rarely static, and it is common to to update a table based on changes in another table. We are making it easy for users to deduplicate data in tables, create slowly-changing data and more with a modern, standard SQL syntax.Let\u2019s take a look at how easy it is to update a customers table, merging in new data as it arrives:\nMERGE INTO customers    <span style=\"color: #a56319;\">-- target table<\/span>\nUSING customer_updates  <span style=\"color: #a56319;\">-- source table with updates<\/span>\nON customers.customer_id = customer_updates.customer_id\nWHEN MATCHED THEN\n  UPDATE SET customers.address = customer_updates.address\nNeedless to say, you do not sacrifice performance with this capability as table updates are blazing fast. You can find out more about the ability to update, merge and delete data in tables here.Taking it for a spinWe understand language dialect changes can be disruptive. To facilitate the rollout, we are happy to announce a new feature, channels, to help customers safely preview upcoming changes.When you create or edit a SQL endpoint, you can now choose a channel. The \u201ccurrent\u201d channel contains generally available features while the preview channel contains upcoming features like the ANSI SQL dialect.To test out the ANSI SQL dialect, click SQL Endpoints in the left navigation menu, click on an endpoint and change its channel. Changing the channel will restart the endpoint, and you can always revert this change later. You can now test your queries and dashboards on this endpoint.You can also test the ANSI SQL dialect by using the SET command, which enables it just for the current session:\nSET ansi_mode = true; <span style=\"color: #a56319;\">-- only use this setting for testing<\/span>\n\nSELECT CAST('a' AS INTEGER);\nPlease note that we do NOT recommend setting ANSI_MODE to false in production. This parameter will be removed in the future, hence you should only set it to FALSE temporarily for testing purposes.The future of SQL at Databricks is open, inclusive and fastDatabricks SQL already set the world record in performance, and with these changes, it is standards compliant. We are excited about this milestone, as it is key in dramatically improving usability and simplifying workload migration from data warehouses over to the lakehouse platform.Please learn more about changes included in the ANSI SQL dialect. Note that the ANSI dialect is not enabled as default yet for existing or new clusters in the Databricks data science and engineering workspace. We are working on that next.Try Databricks for freeGet StartedRelated postsIntroducing SQL User-Defined FunctionsOctober 20, 2021 by Serge Rielau and Allison Wang in Platform Blog\nA user-defined function (UDF) is a means for a user to extend the native capabilities of Apache Spark\u2122 SQL. SQL on Databricks has s...\nDatabricks SQL: Delivering a Production SQL Development Experience on the Data LakeSeptember 30, 2021 by Miranda Luna and Cyrielle Simeone in Platform Blog\nDatabricks SQL is now generally available on AWS and Azure. Databricks SQL (DB SQL) is a simple and powerful SQL analytics platform for...\nNew Performance Improvements in Databricks SQLSeptember 8, 2021 by Reynold Xin, Can Efeoglu and Cyrielle Simeone in Platform Blog\nDatabricks SQL is now generally available on AWS and Azure. Originally announced at Data + AI Summit 2020 Europe, Databricks SQL lets you...\nEvolution of the Sql Language at Databricks: Ansi Standard by Default and Easier Migrations from Data WarehousesNovember 16, 2021 by Serge Rielau, Shant Hovsepian and Reynold Xin in Platform Blog\nDatabricks SQL is now generally available on AWS and Azure. Today, we are excited to announce that Databricks SQL will use the ANSI...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sanket-amin","text":"Sanket Amin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSanket AminSenior Manager of CAS Data Science and Analytics at Collins AerospaceBack to speakersSanket Amin\u2019s data analysis journey starts with research and development of vibration based predictive algorithms for jet engines. This naturally led him to investigate opportunities to analyze large volumes and other aircraft data signals. He has worked on projects with many important aerospace companies and organizations including NASA, GE, Pratt and Whitney, NAVAIR, and AFRL. He currently leads a team a data science team at Collins Aerospace\u2019s Connected Aviation Solutions business unit.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/demand-forecasting","text":"What is Demand Forecasting?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDemand ForecastingAll>Demand ForecastingTry Databricks for freeGet StartedWhat is demand forecasting?Demand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.Retailers are facing a trillion-dollar problem due to unavailable products at the time consumers demand them. Poor demand forecasting is causing companies to put the wrong product on the shelf, or an even bigger issue, to have in-store stock outagesHow can Lakehouse for Retail enable demand forecasting?Lakehouse for Retail enables real-time access to data. Moving from batch-oriented access, analysis, and compute will allow data to be \u201calways-on,\u201d therefore driving real-time decisions and business intelligence. The Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader, and Photon to enable organizations to make data available for real-time decisions.Lakehouse for Retail supports the largest data jobs at nearly real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for true real-time stream ingestion of data, and even analytics on streaming data. Data warehouses require the extraction, transformation, loading, and then additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest data sets to power real-time decisions in BI tools.What data sources are needed for successful demand forecasting?Demand forecasting is an integral part of delivering products to consumers. To successfully deliver products to consumers, retailers must work with manufacturers in these operational processes and use cases: Sales and Operations Planning (S&OP), supply chain optimization, inventory control and optimization, and production scheduling. Data originates from several sources that feeds the demand forecasting models, including:\nPoint of sale: sales transaction is in the form of structured real-time dataHistorical demand: Historical demand can be housed in enterprise resource planning systems (SAP) and usually structured in batch formatExternal data: Social feeds, news, and competitor information is usually in a real-time unstructured formatClick-stream: semi-structured in real-timeExternal data: even weather can be a factor in determining demand (think of tornado or hurricane)Additional ResourcesCollaborating Across the Retail Value Chain with Data and AIImproving On-Shelf Availability for Items With AI Out of Stock ModelingHow Starbucks forecasts demand at scaleBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\uad00\ub9ac\ud558\uace0, \uc218\uba85 \uc8fc\uae30\ub97c \uc774\ud574\ud558\uba70, \uc774\ud0c8\ub960 \uac10\uc18c\uc2dc\uc791\ud558\uae30\ud589\ub3d9 \uc138\ubd84\ud654\uace0\uae09 \uace0\uac1d \uc138\ubd84\ud654\ub85c \ud589\ub3d9\uc5d0 \uae30\ubc18\ud55c \uad6c\ub9e4 \uc608\uce21\uc758 \uc815\ud655\ub3c4 \ud5a5\uc0c1\uc2dc\uc791\ud558\uae30\ub9e4\ucd9c \uc608\uce21 \ubc0f \uae30\uc5ec\ucd5c\uace0\uc758 \uc131\uacfc\ub97c \ub0b4\ub294 \ucc44\ub110\uc744 \ucd5c\uc801\ud654\ud558\uace0 \uc774\uc5d0 \uc9d1\uc911\ud558\uc5ec \uad11\uace0 \uc131\uacfc \ud5a5\uc0c1\uc2dc\uc791\ud558\uae30\ucd94\ucc9c\uac1c\uc778 \ub9de\ucda4\ud615 \uc634\ub2c8\ucc44\ub110 \ucd94\ucc9c\uc73c\ub85c \uc804\ud658 \ubc0f \ucc38\uc5ec \ud5a5\uc0c1\uc2dc\uc791\ud558\uae30\ucef4\ud4e8\ud130 \ube44\uc804\/Labelbox\uc774\ubbf8\uc9c0\uc640 \uc601\uc0c1\uc5d0 \uc8fc\uc11d\uc744 \ub2ec\uc544 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ucee8\ud14d\uc2a4\ud2b8 \uad11\uace0 \ud0c0\uac8c\ud305 \uc9c0\uc6d0\n\u00a0\n\ucd9c\uc2dc \uc608\uc815\ub3d9\uc601\uc0c1 \ud658\uacbd \ud488\uc9c8\ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uc5ec \uc6b0\uc218\ud55c \uc2a4\ud2b8\ub9ac\ubc0d \ucf58\ud150\uce20 \ud658\uacbd \uc81c\uacf5\uc2dc\uc791\ud558\uae30\uc2e4\uc2dc\uac04 \uc785\ucc30\uc2e4\uc2dc\uac04\uc73c\ub85c \uad11\uace0 \uc870\ud68c \uac00\ub2a5\uc131\uc744 \uc608\uce21\ud558\uc5ec RTB \uc804\ub7b5\uc744 \ud5a5\uc0c1\ud558\ub294 \ubc29\ubc95 \uc54c\uc544\ubcf4\uae30\uc2dc\uc791\ud558\uae30\ubaa8\ub4e0 \uc194\ub8e8\uc158 \ubcf4\uae30\ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ub370\ubaa8\ub9ac\uc18c\uc2a4\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\u0000\u0000\uc11c \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8 \uc0b0\uc5c5\uc744 \uc704\ud55c \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI eBook\uacfc \ub3d9\uc601\uc0c1\uc744 \ucc3e\uc544\ubcf4\uc138\uc694\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\uc9c0\uae08 \ub2e4\uc6b4\ub85c\ub4dc\uc6e8\ube44\ub098\uc790\uc138\ud788\ube14\ub85c\uadf8\uc790\uc138\ud788\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uadc0\uc0ac\uc758 \ube44\uc988\ub2c8\uc2a4 \ubaa9\ud45c\ub97c \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uace0 \uc11c\ube44\uc2a4 \ud300\uc5d0\uc11c \uadc0\uc0ac\uc758 \uc131\uacf5\uc744 \ub3c4\uc6b8 \ubc29\ubc95\uc744 \ud568\uaed8 \uc54c\uc544\ubcf4\uace0\uc790 \ud569\ub2c8\ub2e4.Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\ub370\ubaa8 \uc608\uc57d\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aikaterini-kalou","text":"Aikaterini Kalou - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAikaterini KalouPrincipal Data Scientist at CitrixBack to speakersAikaterini Kalou is a Principal Data Scientist with nine years of solid experience in successfully leading complex data-driven initiatives from inception to modelling and design to successful release. She has numerous achievements in leading product differentiation through machine learning and advanced analytics in various domains (networking, security and employee productivity). Aikaterini has demonstrated technical leadership of cross-functional teams and actively practicing employee growth, coaching and mentoring, along with effective communication experience up to executive level. Building up on own curiosity and solid research practice foundations obtained during PhD studies, she is a proven innovator driving intellectual property creation (numerous patents filed\/granted) and contributing to organization vision. Participating actively in Dev Conf, Tech Fair and Tech Talk events. Aikaterini is excited about leveraging the power of Analytics & Data Science at the heart of decision making in customer and enterprise world. Passionate about leading diverse teams, fostering team culture, and consistently delivering measurable results.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/de\/product\/machine-learning","text":"Databricks Machine Learning | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWMachine LearningIhre KI-Projekte mit einem datenzentrierten Ansatz f\u00fcr Machine Learning beschleunigenKostenlos testenPlanen Sie eine Demo\nErstellen Sie Ihr eigenes gro\u00dfes Sprachmodell wie Dolly\n26 April, 2023 | 9:00AM BST I 10AM CEST\nJetzt registrierenTiefer in Data Engineering mit Databricks eintauchenManaged MLflowModellregisterML RuntimeKollaborative NotebooksFeature-StoreAutoMLErkl\u00e4rbare KIRepositorysModell\u00fcberwachungModellbereitstellungDatabricks Machine Learning basiert auf einer offenen Lakehouse-Architektur. Die L\u00f6sung unterst\u00fctzt ML-Teams bei der Aufbereitung und Verarbeitung von Daten, optimiert die team\u00fcbergreifende Zusammenarbeit und standardisiert den gesamten Lebenszyklus von der Experimentierphase bis zur Produktion.$6M+ an EinsparungenCONA Services verwendet Databricks f\u00fcr den gesamten ML-Lebenszyklus, um die Lieferkette f\u00fcr Hunderttausende von Gesch\u00e4ften zu optimieren.Mehr Informationen3,9\u00a0Millionen Real an EinsparungenVia nutzt maschinelles Lernen, um die Nachfrage genau zu prognostizieren und die Rechenkosten um 25\u00a0% zu senken.Mehr Informationen\u00dcber 50 Mio. $ KostensenkungAmgen verbessert die datenwissenschaftliche Zusammenarbeit, um die Arzneimittelforschung zu beschleunigen und Betriebskosten zu sparen.Mehr InformationenAlle Datenaspekte f\u00fcr ML vereinfachenDa Databricks ML auf einer offenen Lakehouse-Grundlage mit Delta Lake aufsetzt, erm\u00f6glichen Sie es Ihren Machine-Learning-Teams damit, auf Daten jeglichen Typs und Umfangs zuzugreifen, sie zu untersuchen und aufzubereiten. Verwandeln Sie Funktionen in Produktionspipelines mit Self-Service-Unterst\u00fctzung, ohne auf den Support Ihrer Data Engineers angewiesen zu sein.Tracking und Governance f\u00fcr Experimente automatisierenManaged MLflow verfolgt Ihre Experimente automatisch und protokolliert Parameter, Kennzahlen, die Versionierungen von Daten und Code sowie Modellartefakte bei jedem Trainingsdurchlauf. Sie k\u00f6nnen fr\u00fchere Durchl\u00e4ufe unkompliziert einsehen, Ergebnisse vergleichen und fr\u00fchere Resultate nach Bedarf reproduzieren. Sobald Sie die f\u00fcr die Produktion am besten geeignete Modellversion ermittelt haben, registrieren Sie sie in der Modellregistrierung, um die \u00dcbergabe w\u00e4hrend des Bereitstellungslebenszyklus einfacher zu gestalten.Den gesamten Modelllebenszyklus von den Daten bis zur Produktion und zur\u00fcck verwaltenNach der Registrierung der trainierten Modelle k\u00f6nnen Sie sie mit der Modellregistrierung w\u00e4hrend des gesamten Lebenszyklus kollaborativ verwalten. Modelle k\u00f6nnen versioniert werden und verschiedene Stadien durchlaufen, z.\u00a0B. Experimentieren, Staging, Produktion und Archivierung. Das Lebenszyklusmanagement l\u00e4sst sich in Genehmigungs- und Governance-Workflows mit rollenbasierter Zugriffskontrolle integrieren. Kommentare und E-Mail-Benachrichtigungen erm\u00f6glichen eine intensive Zusammenarbeit der Datenteams.ML-Modelle in gro\u00dfem Umfang mit niedriger Latenz bereitstellenStellen Sie Modelle mit einem einzigen Klick bereit, ohne sich um Serververwaltung oder Skalierungseinschr\u00e4nkungen k\u00fcmmern zu m\u00fcssen. Mit Databricks k\u00f6nnen Sie Ihre Modelle \u00fcberall als REST-API-Endpunkte mit Verf\u00fcgbarkeit auf Unternehmensniveau bereitstellen.ProduktkomponentenKollaborative NotebooksDatabricks Notebooks unterst\u00fctzen Python, R, SQL und Scala nativ, d.\u00a0h., Anwender k\u00f6nnen unter Verwendung der Sprachen und Bibliotheken ihrer Wahl zusammenarbeiten, um aussagekr\u00e4ftige Erkenntnisse zu gewinnen, zu visualisieren und zu teilen.Mehr InformationenMachine Learning Runtime1-Klick-Zugriff auf vorkonfigurierte und ML-optimierte Cluster, die auf einer skalierbaren und zuverl\u00e4ssigen Verteilung der g\u00e4ngigsten ML-Frameworks (wie PyTorch, TensorFlow und scikit-learn) basieren \u2013 mit integrierten Optimierungen f\u00fcr un\u00fcbertroffene Leistung auch bei enormen Datenmengen.Mehr InformationenFeature-StoreVereinfachen Sie die Wiederverwendung von Funktionen mit einer auf der Datenherkunft basierenden Funktionenssuche, die automatisch protokollierte Datenquellen heranzieht. Stellen Sie Funktionen f\u00fcr Training und Bereitstellung mit einer vereinfachten Modellbereitstellung zur Verf\u00fcgung, f\u00fcr die keine \u00c4nderungen an der Client-Anwendung erforderlich sind.Mehr InformationenAutoMLErm\u00f6glichen Sie allen Akteuren vom ML-Experten bis hin zum Citizen Data Scientist die Mitwirkung. Hierzu wurde ein \u201eGlass-Box-Ansatz\u201c f\u00fcr AutoML implementiert, der nicht nur das leistungsst\u00e4rkste Modell bereitstellt, sondern auch Code zur weiteren Optimierung durch Experten erzeugt.Mehr InformationenManaged MLflowManaged MLflow baut auf MLflow, der weltweit f\u00fchrenden Open-Source-Plattform f\u00fcr den ML-Lebenszyklus, auf und hilft beim schnellen \u00dcberf\u00fchren von ML-Modellen aus der Experimentierphase in die Produktion \u2013 mit Sicherheit, Zuverl\u00e4ssigkeit und Skalierbarkeit auf Unternehmensniveau.Mehr InformationenBereitstellen von produktionsbereiten ModellenStellen Sie Modelle in jeder Gr\u00f6\u00dfenordnung mit einem Klick zur Verf\u00fcgung, mit der Option, serverloses Computing zu nutzen.Mehr InformationenModell\u00fcberwachung\u00dcberwachen Sie die Modellleistung und wie sie sich in Echtzeit auf Gesch\u00e4fts-Metrics auswirkt. Databricks bietet durchg\u00e4ngige Transparenz und Herkunft von Modellen in der Produktion bis hin zu Quelldatensystemen und hilft dabei, die Modell- und Datenqualit\u00e4t \u00fcber den gesamten ML-Lebenszyklus hinweg zu analysieren und Probleme zu lokalisieren, bevor sie sch\u00e4dliche Auswirkungen haben.Mehr InformationenRepositorysMithilfe von Repositorys k\u00f6nnen Engineers Git-Workflows in Databricks nachstellen und Datenteams so die Nutzung automatisierter CI\/CD-Workflows und das Portieren von Code erm\u00f6glichen.Mehr InformationenZu Databricks migrierenSind die Datensilos, die langsame Leistung und die hohen Kosten f\u00fcr Altsysteme wie Hadoop und Enterprise Data Warehouses m\u00fcde? Holen Sie sich eine einzige moderne Plattform f\u00fcr alle Ihre Daten-, Analytics- und KI-Anwendungsf\u00e4lle.Zu Databricks migrierenRessourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nErkunden Sie die Ressourcenbibliothek, um E-Books und Videos zu Themen Datenwissenschaft und Machine Learning zu finden.\nRessourcen erkundenE-BooksDas gro\u00dfe Buch der MLOpsDie neue Delta-Sharing-L\u00f6sung erkundenTakeda migrierte von On-Premises-Hadoop zu DatabricksDemos und BlogsTiefer in L\u00f6sungen f\u00fcr Machine Learning von Databricks eintauchen5 wichtige Schritte f\u00fcr eine erfolgreiche Migration von Hadoop zur Lakehouse-ArchitekturVirtuelle VeranstaltungenAutoML: Schnelles, vereinfachtes Machine Learning f\u00fcr jedermannVirtuelles MLOps-Event \u201eStandardizing MLOps at Scale\u201cAutomatisieren des ML-Lebenszyklus mit Databricks Machine LearningVirtuelles MLOps-Event \u201eOperationalizing Machine Learning at Scale\u201cBuilding Machine Learning PlatformsDelta Lake \u2013 die Grundlage f\u00fcr unser LakehouseSchritt-f\u00fcr-Schritt-Anleitung zur Hadoop-MigrationM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/de\/product\/open-source","text":"Open-Source | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWOpen-SourceEinige der weltweit beliebtesten Open-Source-Datentechnologien wurden urspr\u00fcnglich von Databricks-Ingenieuren erfundenAn einem Treffen teilnehmenUnsere beliebtesten Open-Source-ProjekteApache Spark\u2122Apache Spark ist eine vereinheitlichte Engine zum Ausf\u00fchren von Data-Engineering-, Data-Science- und ML-Workloads.\nWas ist Apache Spark?\nSpark und Databricks im Vergleich\nspark.apache.org besuchen\nDelta LakeMit Delta Lake k\u00f6nnen Sie eine Lakehouse-Architektur auf Speichersysteme wie AWS S3, ADLS, GCS und HDFS aufsetzen.\nWeitere Informationen zu Delta Lake\ndelta.io besuchen\nTech-Talks: Erste Schritte mit Delta Lake\nMLflowMLflow verwaltet den ML-Lebenszyklus, einschlie\u00dflich Experimente, Reproduzierbarkeit, Implementierung und einer zentralen Modellregistrierung.\nManaged MLflow auf Databricks\nMLFLOW.ORG BESUCHEN\nTech Talks: Den ML-Lifecycle verwalten\nRedashMit Redash kann wirklich jeder Anwender SQL nutzen, um Daten aus gro\u00dfen und kleinen Datenquellen zu untersuchen, abzufragen, zu visualisieren und zu teilen.\nRedash in GitHub besuchen\nDelta-FreigabeDelta Sharing ist das branchenweit erste offene Protokoll f\u00fcr die sichere Datenfreigabe. Mit Delta Sharing wird der Datenaustausch mit anderen Organisationen zum Kinderspiel.\nDelta Sharing besuchen\nDatabricks unterst\u00fctzt au\u00dferdem die folgenden beliebten Open-Source-TechnologienTensorFlowDatabricks unterst\u00fctzt TensorFlow, eine Bibliothek f\u00fcr Deep Learning und allgemeine Berechnungen auf Clustern\nTensorFlow auf Databricks\nPyTorch\u2122PyTorch-Sch\u00f6pfer Facebook und Databricks entwickeln gemeinsam Integrationen\nPyTorch auf Databricks\nKeras\u2122In Python geschriebene Deep-Learning-API, die auf TensorFlow aufbaut. Verf\u00fcgbar in Databricks Runtime f\u00fcr ML\nKeras auf Databricks\nRStudioEine Sammlung von Open-Source-Tools f\u00fcr kollaborative Data Science mit R\nR-Programmierung f\u00fcr Big Data\nScikit-learnWeit verbreitetes Python-Paket f\u00fcr maschinelles Lernen, das auf NumPy, SciPy und Matplotlib aufbaut\nScikit-learn in Databricks\nXGBoostEine verteilte Gradient-Boosting-Bibliothek mit Bindungen in Sprachen wie Python, R und C++XGBoost auf DatabricksTerraformHashiCorp Terraform ist ein beliebtes Open-Source-Tool zum Erstellen einer sicheren und vorhersehbaren Cloud-Infrastruktur f\u00fcr mehrere Cloud-Anbieter. Der Terraform-Anbieter von Databricks erm\u00f6glicht es Kunden, ihre gesamten Databricks-Workspaces zusammen mit dem Rest ihrer Infrastruktur mit einem flexiblen, leistungsstarken Tool zu verwalten. Die Verwendung von Terraform erleichtert Kunden auch den Einsatz von Best Practices mit Infrastructure as Code (IaC).Terraform auf DatabricksM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/12\/12\/announcing-general-availability-data-lineage-unity-catalog.html","text":"Announcing General Availability of Data lineage in Unity Catalog - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing General Availability of Data lineage in Unity Catalogby Tao Feng, Paul Roome, Sachin Thakur, Hongyi Zhang, Menglei Sun and Shuai LuDecember 12, 2022 in Platform BlogShare this postToday, we are excited to announce the general availability of data lineage in Unity Catalog, available on AWS and Azure. With data lineage general availability, you can expect the highest level of stability, support, and enterprise readiness from Databricks for mission-critical workloads on the Databricks Lakehouse Platform. Refer the data lineage guides (AWS | Azure) to get started.In this blog, we explore how organizations leverage data lineage as a key lever of a pragmatic data governance strategy, some of the key features available in the GA release, and how to get started with data lineage in Unity Catalog.Driving better data observability and compliance with data lineageUnity Catalog provides a unified governance solution for data, analytics and AI, empowering data teams to catalog all their data and AI assets, define fine-grained access permissions using a familiar interface based on ANSI SQL, audit data access and share data across clouds, regions and data platforms.With automated data lineage in Unity Catalog, data teams can now automatically track sensitive data for compliance requirements and audit reporting, ensure data quality across all workloads, perform impact analysis or change management of any data changes across the lakehouse and conduct root cause analysis of any errors in their data pipelines. Learn more about common use cases for data lineage in our previous blog.\"Data Lineage has enabled us to get insights into how our datasets are used and by whom. This serves as both basic documentation as well as identifies who would be affected by dataset changes or deprecations to cut down on incidents\" \u2014 Sam Shuster, Staff Engineer, Edmunds\"Lineage is the last crucial piece for access control. It allows analysts to leverage data to do their jobs while adhering to all usage standards and access controls, even when recreating tables and data sets in another environment\" \u2014 Chris Locklin, Data Platform Manager, Grammarly\u201cLineage helps Milliman professionals see where data is coming from, what transformations did it go through and how it is being used for the life of the project. This well-documented end-to-end process complements the standard actuarial process\u201d \u2014 Dan McCurley, Cloud Solutions Architect, MillimanKey features of data lineage available in the GA releaseAutomated real-time lineage: Unity Catalog automatically captures and displays data flow diagrams in real-time for queries executed in any language (Python, SQL, R, and Scala) and execution mode (batch and streaming). Real-time lineage reduces the operational overhead of manually creating data flow trails. Data lineage is automatically aggregated across all workspaces connected to a Unity Catalog metastore, this means that lineage captured in one workspace can be seen in any other workspace that shares the same metastore.Unified column and table lineage graph: With Unity Catalog, users can now see both column and table lineage in a single lineage graph, giving users a better understanding of what a particular table or column is made up of and where the data is coming from. Users can navigate the lineage graph upstream or downstream with a few clicks to see the full data flow diagram.Table and column lineage in Unity CatalogGoing beyond just tables and columns: Unity Catalog also tracks lineage for notebooks, workflows, and dashboards. This improves end-to-end visibility into how data is used in your organization and allows you to understand the impact of any data changes on downstream consumers.Lineage for notebooks, workflows and dashboardsBuilt-in security: Lineage graphs are secure by default and use the Unity Catalog's common permission model. Users must have the appropriate permissions to view the lineage data flow diagram, adding an extra layer of security and reducing the risk of unintentional data breaches. For example, if users do not have the SELECT privilege on a table, they will be unable to explore the table's lineage. Similarly, users can only see lineage information for notebooks, workflows, and dashboards that they have permission to view.Built-in security for lineage graphsPartner integrations: Unity Catalog also offers rich integration with various data governance partners via Unity Catalog REST APIs, enabling easy export of lineage information.Getting started with data lineage in Unity CatalogWatch the demo below to see data lineage in action.To play this video, click here and accept cookiesData lineage is included at no extra cost with Databricks Premium and Enterprise tiers. All workloads referencing the Unity Catalog metastore now have data lineage enabled by default, and all workloads reading or writing to Unity Catalog will automatically capture lineage. To take advantage of automatically captured Data Lineage, please restart any clusters or SQL Warehouses that were started prior to December 7th, 2022. If you already have a Databricks account, you can get started by following the data lineage guides (AWS | Azure). If you are not an existing Databricks customer, sign up for a free trial with a Premium or Enterprise workspace.Try Databricks for freeGet StartedRelated postsAnnouncing the Availability of Data Lineage With Unity CatalogJune 8, 2022 by Paul Roome, Tao Feng and Sachin Thakur in Platform Blog\nUpdate: Data Lineage is now generally available on AWS and Azure. We are excited to announce that data lineage for Unity Catalog, the...\nSimplify Access Policy Management With Privilege Inheritance in Unity CatalogOctober 21, 2022 by Jim Thorstad, Paul Roome and Sachin Thakur in Platform Blog\nUnity Catalog, now generally available on AWS and Azure, provides a unified governance solution for data, analytics and AI on the lakehouse. Thousands...\nAnnouncing General Availability of Delta SharingAugust 26, 2022 by Matei Zaharia, Celia Kung, Xiaotong Sun, Steve Mahoney, Itai Weiss, Sachin Thakur and Jay Bhankharia in Announcements\nToday we are excited to announce that Delta Sharing is generally available (GA) on AWS and Azure. With the GA release, you can...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-strengthens-commitment-korea-appointing-jungwook-jang","text":"Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country Manager - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerJanuary 17, 2023Share this postFormer Kyndryl and IBM executive joins Databricks\u2019 Asia Pacific leadership team to drive further adoption of the lakehouse platform in the region\nSeoul, Korea, 17 January 2023 - Databricks, the lakehouse company, today announced the appointment of Jungwook Jang as the Country Manager for Korea, following the expansion of its business into the Korean market in April 2022.\u00a0\nAn experienced leader in the Korean tech and cloud industry, Jungwook brings more than 20 years of enterprise technology and leadership experience to the role and will be responsible for leading the local teams and driving data platform modernization with lakehouse adoption for Korean businesses across industries.\nPrior to joining Databricks, Jungwook served as the Managing Director of Kyndryl Korea and was previously the General Manager of IBM GTS Korea and the Country Manager of AWS Korea.\u00a0\n\u201cWe are so thrilled to welcome Jungwook to the leadership team and I look forward to seeing him lead the Korean business to new heights with his experience in scaling high-growth organizations,\u201d said Ed Lenta, Senior Vice President and General Manager of Asia Pacific and Japan at Databricks. \u201cKorea is fast emerging as a leader in AI technology and innovation with its robust digital infrastructure in place, and we\u2019re in an exciting time to be accelerating adoption of the data architecture of the future with Databricks\u2019 Lakehouse Platform.\u201d\u00a0\n\u201cData is the key to unlocking the potential of AI and fueling digital transformation for businesses across every industry. With the Korean government\u2019s support and customers\u2019 drive for digital innovation and advancement of AI adoption, I\u2019m excited for Korean businesses of all sizes to experience the power of the Databricks Lakehouse Platform to unify their data and AI needs and achieve innovation on the modernized data platform,\u201d said Jungwook Jang, Vice President and Country Manager for Databricks Korea.\u00a0\u00a0\nDatabricks helps Korean businesses including Amorepacific, Bagelcode, Devsisters, Musinsa and Weverse Company generate data-driven and AI-powered insights to improve operations and customer experiences.\u00a0\n-End-\u00a0\nAbout Databricks\u00a0\nDatabricks is the lakehouse company. More than 7,000 organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, and over 50% of the Fortune 500 \u2014 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\nPress Contact:\u00a0\n[email\u00a0protected]\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ian-sotnek","text":"Ian Sotnek - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIan SotnekDirector of Product at AI Squared, IncBack to speakersIan Sotnek is co-founder and Director of Product of AI Squared, Incorporated. Ian's multidisciplinary background encompasses degrees and academic work in applied neuroscience as well as in machine learning governance and policy. This experience has prepared him to contribute to the human-computer interaction focus of AI Squared, where he leads the design and development of their open data science platform for machine learning development, governance, and integration.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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(Macintosh)<\/stEvt:softwareAgent>\n                  <stEvt:changed>\/<\/stEvt:changed>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n            <\/rdf:Seq>\n         <\/xmpMM:History>\n         <illustrator:StartupProfile>Print<\/illustrator:StartupProfile>\n         <illustrator:CreatorSubTool>AIRobin<\/illustrator:CreatorSubTool>\n         <pdf:Producer>Adobe PDF library 15.00<\/pdf:Producer>\n         <xmpTPg:NPages>1<\/xmpTPg:NPages>\n         <xmpTPg:HasVisibleTransparency>False<\/xmpTPg:HasVisibleTransparency>\n         <xmpTPg:HasVisibleOverprint>False<\/xmpTPg:HasVisibleOverprint>\n         <xmpTPg:MaxPageSize rdf:parseType=\"Resource\">\n            <stDim:w>10.074014<\/stDim:w>\n            <stDim:h>1.566839<\/stDim:h>\n            <stDim:unit>Inches<\/stDim:unit>\n         <\/xmpTPg:MaxPageSize>\n         <xmpTPg:PlateNames>\n            <rdf:Seq>\n               <rdf:li>Cyan<\/rdf:li>\n               <rdf:li>Magenta<\/rdf:li>\n               <rdf:li>Yellow<\/rdf:li>\n               <rdf:li>Black<\/rdf:li>\n            <\/rdf:Seq>\n         <\/xmpTPg:PlateNames>\n         <xmpTPg:SwatchGroups>\n            <rdf:Seq>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <xmpG:groupName>Default Swatch Group<\/xmpG:groupName>\n                  <xmpG:groupType>0<\/xmpG:groupType>\n                  <xmpG:Colorants>\n                     <rdf:Seq>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>White<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>Black<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>67.187500<\/xmpG:magenta>\n                           <xmpG:yellow>63.671875<\/xmpG:yellow>\n                           <xmpG:black>73.828125<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Red<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>96.875000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Yellow<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>3.906250<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>93.750000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Green<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>82.812500<\/xmpG:cyan>\n                           <xmpG:magenta>7.031250<\/xmpG:magenta>\n                           <xmpG:yellow>95.312500<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Cyan<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>14.453125<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Blue<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>96.093750<\/xmpG:magenta>\n                           <xmpG:yellow>3.906250<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Magenta<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>1.171875<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>1.171875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=15 M=100 Y=90 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>17.968750<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>7.812500<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=90 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>89.843750<\/xmpG:magenta>\n                           <xmpG:yellow>84.765625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=80 Y=95 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>79.687500<\/xmpG:magenta>\n                           <xmpG:yellow>94.140625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=50 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>50.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.828125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=35 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>35.156250<\/xmpG:magenta>\n                           <xmpG:yellow>83.984375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=5 M=0 Y=90 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>5.468750<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=20 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>19.921875<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.437500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=50 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>50.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>99.218750<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=10 Y=100 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>85.937500<\/xmpG:cyan>\n                           <xmpG:magenta>16.796875<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>3.515625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=90 M=30 Y=95 K=30<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>89.843750<\/xmpG:cyan>\n                           <xmpG:magenta>33.203125<\/xmpG:magenta>\n                           <xmpG:yellow>97.265625<\/xmpG:yellow>\n                           <xmpG:black>25.781250<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=75 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>74.609375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=80 M=10 Y=45 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>78.906250<\/xmpG:cyan>\n                           <xmpG:magenta>10.937500<\/xmpG:magenta>\n                           <xmpG:yellow>45.312500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=70 M=15 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>70.312500<\/xmpG:cyan>\n                           <xmpG:magenta>16.015625<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=50 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>84.765625<\/xmpG:cyan>\n                           <xmpG:magenta>49.609375<\/xmpG:magenta>\n                           <xmpG:yellow>0.390625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=100 M=95 Y=5 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>92.968750<\/xmpG:magenta>\n                           <xmpG:yellow>6.640625<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=100 M=100 Y=25 K=25<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>100.000000<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>30.468750<\/xmpG:yellow>\n                           <xmpG:black>21.875000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=100 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.000000<\/xmpG:cyan>\n                           <xmpG:magenta>98.046875<\/xmpG:magenta>\n                           <xmpG:yellow>1.562500<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=50 M=100 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>51.171875<\/xmpG:cyan>\n                           <xmpG:magenta>99.218750<\/xmpG:magenta>\n                           <xmpG:yellow>1.953125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=35 M=100 Y=35 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>35.937500<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>35.156250<\/xmpG:yellow>\n                           <xmpG:black>8.984375<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=10 M=100 Y=50 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>9.765625<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>48.046875<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=95 Y=20 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>94.531250<\/xmpG:magenta>\n                           <xmpG:yellow>19.921875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=25 M=25 Y=40 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>25.390625<\/xmpG:cyan>\n                           <xmpG:magenta>25.000000<\/xmpG:magenta>\n                           <xmpG:yellow>40.234375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li 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<\/xmpTPg:SwatchGroups>\n         <dc:format>application\/pdf<\/dc:format>\n         <dc:title>\n            <rdf:Alt>\n               <rdf:li xml:lang=\"x-default\">Multi-Tier_Architecture_Diagram_working_v2<\/rdf:li>\n            <\/rdf:Alt>\n         <\/dc:title>\n         <illustrator:Type>Document<\/illustrator:Type>\n         <illustrator:CreatorSubTool>AIRobin<\/illustrator:CreatorSubTool>\n         <xmpMM:DocumentID>xmp.did:cb545c20-7786-4275-b10d-0339f813912a<\/xmpMM:DocumentID>\n         <xmpMM:InstanceID>uuid:697d70ea-2e82-6744-be3c-97636fe5aa8f<\/xmpMM:InstanceID>\n         <xmpMM:OriginalDocumentID>xmp.did:332dcfc4-9608-49af-a62b-f841b4e7958c<\/xmpMM:OriginalDocumentID>\n         <xmpMM:RenditionClass>proof:pdf<\/xmpMM:RenditionClass>\n         <xmpMM:DerivedFrom rdf:parseType=\"Resource\">\n            <stRef:instanceID>uuid:f5bcd0d3-3708-5e46-8243-588151e8aa32<\/stRef:instanceID>\n            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<\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>Black<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>67.187500<\/xmpG:magenta>\n                           <xmpG:yellow>63.671875<\/xmpG:yellow>\n                           <xmpG:black>73.828125<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Red<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           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<xmpTPg:HasVisibleTransparency>False<\/xmpTPg:HasVisibleTransparency>\n         <xmpTPg:HasVisibleOverprint>False<\/xmpTPg:HasVisibleOverprint>\n         <xmpTPg:MaxPageSize rdf:parseType=\"Resource\">\n            <stDim:w>10.074014<\/stDim:w>\n            <stDim:h>1.566839<\/stDim:h>\n            <stDim:unit>Inches<\/stDim:unit>\n         <\/xmpTPg:MaxPageSize>\n         <xmpTPg:PlateNames>\n            <rdf:Seq>\n               <rdf:li>Cyan<\/rdf:li>\n               <rdf:li>Magenta<\/rdf:li>\n               <rdf:li>Yellow<\/rdf:li>\n               <rdf:li>Black<\/rdf:li>\n            <\/rdf:Seq>\n         <\/xmpTPg:PlateNames>\n         <xmpTPg:SwatchGroups>\n            <rdf:Seq>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <xmpG:groupName>Default Swatch Group<\/xmpG:groupName>\n                  <xmpG:groupType>0<\/xmpG:groupType>\n                  <xmpG:Colorants>\n                     <rdf:Seq>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>White<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>Black<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>67.187500<\/xmpG:magenta>\n                           <xmpG:yellow>63.671875<\/xmpG:yellow>\n                           <xmpG:black>73.828125<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Red<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>96.875000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Yellow<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>3.906250<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>93.750000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Green<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>82.812500<\/xmpG:cyan>\n                           <xmpG:magenta>7.031250<\/xmpG:magenta>\n                           <xmpG:yellow>95.312500<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Cyan<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>14.453125<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Blue<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>96.093750<\/xmpG:magenta>\n                           <xmpG:yellow>3.906250<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Magenta<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>1.171875<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>1.171875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=15 M=100 Y=90 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>17.968750<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>7.812500<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=90 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>89.843750<\/xmpG:magenta>\n                           <xmpG:yellow>84.765625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=80 Y=95 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>79.687500<\/xmpG:magenta>\n                           <xmpG:yellow>94.140625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=50 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>50.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.828125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=35 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>35.156250<\/xmpG:magenta>\n                           <xmpG:yellow>83.984375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=5 M=0 Y=90 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>5.468750<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=20 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>19.921875<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.437500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=50 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>50.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>99.218750<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=10 Y=100 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>85.937500<\/xmpG:cyan>\n                           <xmpG:magenta>16.796875<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>3.515625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=90 M=30 Y=95 K=30<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>89.843750<\/xmpG:cyan>\n                           <xmpG:magenta>33.203125<\/xmpG:magenta>\n                           <xmpG:yellow>97.265625<\/xmpG:yellow>\n                           <xmpG:black>25.781250<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=75 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>74.609375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=80 M=10 Y=45 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>78.906250<\/xmpG:cyan>\n                           <xmpG:magenta>10.937500<\/xmpG:magenta>\n                           <xmpG:yellow>45.312500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=70 M=15 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>70.312500<\/xmpG:cyan>\n                           <xmpG:magenta>16.015625<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=50 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>84.765625<\/xmpG:cyan>\n                           <xmpG:magenta>49.609375<\/xmpG:magenta>\n                           <xmpG:yellow>0.390625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=100 M=95 Y=5 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>92.968750<\/xmpG:magenta>\n                           <xmpG:yellow>6.640625<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=100 M=100 Y=25 K=25<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>100.000000<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>30.468750<\/xmpG:yellow>\n                           <xmpG:black>21.875000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=100 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.000000<\/xmpG:cyan>\n                           <xmpG:magenta>98.046875<\/xmpG:magenta>\n                           <xmpG:yellow>1.562500<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=50 M=100 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>51.171875<\/xmpG:cyan>\n                           <xmpG:magenta>99.218750<\/xmpG:magenta>\n                           <xmpG:yellow>1.953125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=35 M=100 Y=35 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>35.937500<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>35.156250<\/xmpG:yellow>\n                           <xmpG:black>8.984375<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=10 M=100 Y=50 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>9.765625<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>48.046875<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=95 Y=20 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>94.531250<\/xmpG:magenta>\n                           <xmpG:yellow>19.921875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=25 M=25 Y=40 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           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<stEvt:instanceID>xmp.iid:ea7e1438-6535-4d79-abb5-30fb2e815009<\/stEvt:instanceID>\n                  <stEvt:when>2020-02-07T08:22-08:00<\/stEvt:when>\n                  <stEvt:softwareAgent>Adobe Illustrator 24.0 (Macintosh)<\/stEvt:softwareAgent>\n                  <stEvt:changed>\/<\/stEvt:changed>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>saved<\/stEvt:action>\n                  <stEvt:instanceID>xmp.iid:29762535-10f7-43c9-8920-9a83b344df78<\/stEvt:instanceID>\n                  <stEvt:when>2020-03-10T13:01:46-04:00<\/stEvt:when>\n                  <stEvt:softwareAgent>Adobe Illustrator 24.0 (Macintosh)<\/stEvt:softwareAgent>\n                  <stEvt:changed>\/<\/stEvt:changed>\n               <\/rdf:li>\n               <rdf:li rdf:parseType=\"Resource\">\n                  <stEvt:action>converted<\/stEvt:action>\n                  <stEvt:parameters>from application\/postscript to application\/vnd.adobe.illustrator<\/stEvt:parameters>\n               <\/rdf:li>\n            <\/rdf:Seq>\n         <\/xmpMM:History>\n         <illustrator:StartupProfile>Print<\/illustrator:StartupProfile>\n         <illustrator:CreatorSubTool>AIRobin<\/illustrator:CreatorSubTool>\n         <pdf:Producer>Adobe PDF library 15.00<\/pdf:Producer>\n         <xmpTPg:NPages>1<\/xmpTPg:NPages>\n         <xmpTPg:HasVisibleTransparency>False<\/xmpTPg:HasVisibleTransparency>\n         <xmpTPg:HasVisibleOverprint>False<\/xmpTPg:HasVisibleOverprint>\n         <xmpTPg:MaxPageSize rdf:parseType=\"Resource\">\n            <stDim:w>10.074014<\/stDim:w>\n            <stDim:h>1.566839<\/stDim:h>\n            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<xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>Black<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>69.531250<\/xmpG:cyan>\n                           <xmpG:magenta>67.187500<\/xmpG:magenta>\n                           <xmpG:yellow>63.671875<\/xmpG:yellow>\n                           <xmpG:black>73.828125<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Red<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>96.875000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Yellow<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>3.906250<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>93.750000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Green<\/xmpG:swatchName>\n                          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<xmpG:yellow>84.765625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=80 Y=95 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>79.687500<\/xmpG:magenta>\n                           <xmpG:yellow>94.140625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=50 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>50.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.828125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=35 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>35.156250<\/xmpG:magenta>\n                           <xmpG:yellow>83.984375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=5 M=0 Y=90 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>5.468750<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=20 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>19.921875<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.437500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n  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<xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=10 Y=100 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>85.937500<\/xmpG:cyan>\n                           <xmpG:magenta>16.796875<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>3.515625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=90 M=30 Y=95 K=30<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>89.843750<\/xmpG:cyan>\n                           <xmpG:magenta>33.203125<\/xmpG:magenta>\n                           <xmpG:yellow>97.265625<\/xmpG:yellow>\n                           <xmpG:black>25.781250<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=75 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>74.609375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=80 M=10 Y=45 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>78.906250<\/xmpG:cyan>\n                           <xmpG:magenta>10.937500<\/xmpG:magenta>\n                           <xmpG:yellow>45.312500<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=70 M=15 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>70.312500<\/xmpG:cyan>\n                           <xmpG:magenta>16.015625<\/xmpG:magenta>\n                           <xmpG:yellow>0.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=50 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>84.765625<\/xmpG:cyan>\n                           <xmpG:magenta>49.609375<\/xmpG:magenta>\n                           <xmpG:yellow>0.390625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=100 M=95 Y=5 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>92.968750<\/xmpG:magenta>\n                           <xmpG:yellow>6.640625<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n           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<xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>96.875000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Yellow<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>3.906250<\/xmpG:cyan>\n                           <xmpG:magenta>0.000000<\/xmpG:magenta>\n                           <xmpG:yellow>93.750000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n         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          <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Blue<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>99.218750<\/xmpG:cyan>\n                           <xmpG:magenta>96.093750<\/xmpG:magenta>\n                           <xmpG:yellow>3.906250<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>CMYK Magenta<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>1.171875<\/xmpG:cyan>\n                           <xmpG:magenta>98.828125<\/xmpG:magenta>\n                           <xmpG:yellow>1.171875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=15 M=100 Y=90 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>17.968750<\/xmpG:cyan>\n                           <xmpG:magenta>100.000000<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>7.812500<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=90 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>89.843750<\/xmpG:magenta>\n                           <xmpG:yellow>84.765625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=80 Y=95 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.000000<\/xmpG:cyan>\n                           <xmpG:magenta>79.687500<\/xmpG:magenta>\n                           <xmpG:yellow>94.140625<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=50 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>50.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.828125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=35 Y=85 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.390625<\/xmpG:cyan>\n                           <xmpG:magenta>35.156250<\/xmpG:magenta>\n                           <xmpG:yellow>83.984375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=5 M=0 Y=90 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>5.468750<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>90.625000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=20 M=0 Y=100 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>19.921875<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>98.437500<\/xmpG:yellow>\n                           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<xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=85 M=10 Y=100 K=10<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>85.937500<\/xmpG:cyan>\n                           <xmpG:magenta>16.796875<\/xmpG:magenta>\n                           <xmpG:yellow>100.000000<\/xmpG:yellow>\n                           <xmpG:black>3.515625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=90 M=30 Y=95 K=30<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>89.843750<\/xmpG:cyan>\n                           <xmpG:magenta>33.203125<\/xmpG:magenta>\n                           <xmpG:yellow>97.265625<\/xmpG:yellow>\n                           <xmpG:black>25.781250<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=75 M=0 Y=75 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>75.390625<\/xmpG:cyan>\n                           <xmpG:magenta>0.390625<\/xmpG:magenta>\n                           <xmpG:yellow>74.609375<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=80 M=10 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<xmpG:cyan>75.000000<\/xmpG:cyan>\n                           <xmpG:magenta>98.046875<\/xmpG:magenta>\n                           <xmpG:yellow>1.562500<\/xmpG:yellow>\n                           <xmpG:black>0.390625<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=50 M=100 Y=0 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>51.171875<\/xmpG:cyan>\n                           <xmpG:magenta>99.218750<\/xmpG:magenta>\n                           <xmpG:yellow>1.953125<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=35 M=100 Y=35 K=10<\/xmpG:swatchName>\n                           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rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=0 M=95 Y=20 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>0.781250<\/xmpG:cyan>\n                           <xmpG:magenta>94.531250<\/xmpG:magenta>\n                           <xmpG:yellow>19.921875<\/xmpG:yellow>\n                           <xmpG:black>0.000000<\/xmpG:black>\n                        <\/rdf:li>\n                        <rdf:li rdf:parseType=\"Resource\">\n                           <xmpG:swatchName>C=25 M=25 Y=40 K=0<\/xmpG:swatchName>\n                           <xmpG:mode>CMYK<\/xmpG:mode>\n                           <xmpG:type>PROCESS<\/xmpG:type>\n                           <xmpG:cyan>25.390625<\/xmpG:cyan>\n                           <xmpG:magenta>25.000000<\/xmpG:magenta>\n                           <xmpG:yellow>40.234375<\/xmpG:yellow>\n                      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{"source":"https:\/\/www.databricks.com\/fr\/product\/open-source","text":"Open Source | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWOpen SourceLes ing\u00e9nieurs de Databricks sont les cr\u00e9ateurs de plusieurs technologies de donn\u00e9es open source parmi les plus populaires au mondeParticipez \u00e0 un MeetupNos projets Open Source les plus populairesApache Spark\u2122Apache Spark est un moteur unifi\u00e9 pour ex\u00e9cuter des charges de travail de data engineering, de Data Science et de ML.\nQu'est-ce qu'Apache Spark\u00a0?\nComparaison de Spark et Databricks\nRendez-vous sur spark.apache.org\nDelta LakeDelta Lake vous permet de construire une architecture de lakehouse sur des syst\u00e8mes de stockage tels qu'AWS S3, ADLS, GCS et HDFS.\nEn savoir plus sur Delta Lake\nRendez-vous sur Delta.io\nConf\u00e9rences sur la tech\u00a0: d\u00e9marrer avec Delta Lake\nMLflowMLflow g\u00e8re le cycle de vie du ML, y compris l'exp\u00e9rimentation, la reproductibilit\u00e9, le d\u00e9ploiement et un registre central des mod\u00e8les.\nMLflow manag\u00e9 sur Databricks\nSE RENDRE SUR MLFLOW.ORG\nConf\u00e9rences\u00a0: g\u00e9rer le cycle de vie du machine learning\nRedashRedash permet \u00e0 quiconque d'exploiter SQL pour explorer, interroger, visualiser et partager des donn\u00e9es \u00e0 partir de petites ou de grandes sources de donn\u00e9es (small et big data).\nD\u00e9couvrez Redash sur GitHub\nDelta SharingDelta Sharing est le premier protocole ouvert pour le partage s\u00e9curis\u00e9 des donn\u00e9es. Il permet d'\u00e9changer facilement des donn\u00e9es avec d'autres organisations.\nD\u00e9couvrez Delta Sharing\nDatabricks prend en charge ces technologies open source courantes suppl\u00e9mentairesTensorFlowDatabricks prend en charge TensorFlow, une biblioth\u00e8que de r\u00e9f\u00e9rence pour le deep learning et les clusters de calcul\nTensorFlow sur Databricks\nPyTorch\u2122Facebook, le cr\u00e9ateur de PyTorch, et Databricks ont collabor\u00e9 sur des int\u00e9grations communes.\nPyTorch sur Databricks\nKeras\u2122API de deep learning \u00e9crite en Python, Keras s'ex\u00e9cute sur TensorFlow. Elle est disponible dans Databricks Runtime pour ML.\nKeras sur Databricks\nRStudioUne suite d'outils open source pour la Data Science collaborative \u00e0 l'aide de R \u200b\nProgrammation R pour le Big Data\nScikit-learnPackage Python largement utilis\u00e9 dans le Machine Learning bas\u00e9 sur NumPy, SciPy et Matplotlib\u200b\u200b\nScikit-learn sur Databricks\nxgboostUne biblioth\u00e8que distribu\u00e9e de boosting de gradient reli\u00e9e aux langages tels que Python, R et C++.XGBoost sur DatabricksTerraformHashiCorp Terraform est un outil open source populaire qui permet de cr\u00e9er une infrastructure cloud s\u00fbre et pr\u00e9visible englobant plusieurs fournisseurs de services cloud. Le fournisseur Terraform de Databricks permet aux clients de disposer d'un outil flexible et puissant pour g\u00e9rer l'ensemble de leurs espaces de travail Databricks et le reste de leur infrastructure. L'utilisation de Terraform encourage \u00e9galement les clients \u00e0 adopter les bonnes pratiques avec l'infrastructure en tant que code (IaC).Terraform sur DatabricksPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/br\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/binwei-yang","text":"Binwei Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBinwei Yangsoftware engineer at intelBack to speakersBinwei Yang is a big data analytics architect at Intel, focusing on performance optimization of big data software, accelerator design and utilization in big data framework, as well as the big data and HPC framework integration. Prior to the big data role, Binwei worked in intel micro architecture team and focusing on performance simulation and analysis.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hyukjin-kwon","text":"Hyukjin Kwon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHyukjin KwonStaff Software Engineer at DatabricksBack to speakersHyukjin is a Databricks software engineer as the tech-lead in OSS PySpark team, Apache Spark PMC member and committer, working on many different areas in Apache Spark such as PySpark, Spark SQL, SparkR, infrastructure, etc. He is the top contributor in Apache Spark, and leads efforts such as Project Zen, Pandas API on Spark, and Python Spark Connect.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/meena-ram","text":"Meena Ram - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMeena RamSr Director, Enterprise Data and Records Management Office at CIBCBack to speakersMeena Ram knows the Value of Data and has successfully bridged the gaps between business and technology stakeholders over the past 15 years. \nMeena Ram is the Head of Enterprise Data Management at Canadian Imperial Bank of Commerce (CIBC).\nOverseeing CIBC\u2019s Data practice across Canada and US Region. Before leading CIBC\u2019s Enterprise Data Management Office, Meena played a key role in setting the vision and strategy of Enterprise Data hubs to support analytics, working on complex data structures and delivering multi-million dollar migrations in Capital Markets. Prior to CIBC, Meena was a Data and Analytics Consultant for Deloitte where she working on various high profile institutions both in the US and Canada providing advisory and development solutions. Meena was a Business Intelligence and ETL developer for CGI\u2019s Wealth Management servicing 4 major clients. In the UK, Meena was managing multiple Data Warehouses for Citibank\u2019s credit card platforms. Meena holds a Bachelor in Software Engineering and a Masters in Artificial Intelligence from Manchester University. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/delta-live-tables","text":"Delta Live Tables | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta Live TablesReliable data engineering made easySign upWatch a demoDelta Live Tables (DLT) makes it easy to build and manage reliable batch and streaming data pipelines that deliver high-quality data on the\u00a0Databricks Lakehouse Platform. DLT helps data engineering teams simplify\u00a0ETL\u00a0development and management with declarative pipeline development, automatic data testing, and deep visibility for monitoring and recovery.Easily build and maintain data pipelinesWith Delta Live Tables, easily define end-to-end data pipelines in SQL or Python. Simply specify the data source, the transformation logic, and the destination state of the data \u2014 instead of manually stitching together siloed data processing jobs. Automatically maintain all data dependencies across the pipeline and reuse ETL pipelines with environment-independent data management. Run in batch or\u00a0streaming\u00a0mode and specify incremental or complete computation for each table.Automatic data quality testingDelta Live Tables helps to ensure accurate and useful BI, data science and machine learning with high-quality data for downstream users. Prevent bad data from flowing into tables through validation and integrity checks and avoid data quality errors with predefined error policies (fail, drop, alert or quarantine data). In addition, you can monitor data quality trends over time to get insight into how your data is evolving and where changes may be necessary.Cost-effective streaming through efficient compute autoscalingDelta Live Tables Enhanced Autoscaling is designed to handle streaming workloads which are spiky and unpredictable. It optimizes cluster utilization by only scaling up to the necessary number of nodes while maintaining end-to-end SLAs, and gracefully shuts down nodes when utilization is low to avoid unnecessary spend.Deep visibility for pipeline monitoring and observabilityGain deep visibility into pipeline operations with tools to visually track operational stats and data lineage. Reduce downtime with automatic error handling and easy replay. Speed up maintenance with single-click deployment and upgrades.Shell trusts Delta Live Tables\u201cAt Shell, we are aggregating all our sensor data into an integrated data store. Delta Live Tables has helped our teams save time and effort in managing data at the multi-trillion-record scale and continuously improving our AI engineering capability. With this capability augmenting the existing lakehouse architecture, Databricks is disrupting the ETL and data warehouse markets, which is important for companies like ours. We are excited to continue to work with Databricks as an innovation partner.\u201d\u2013 Dan Jeavons, General Manager \u2013 Data Science, ShellUse casesUnify batch and streaming ETLBuild and run both batch and\u00a0streaming\u00a0pipelines in one place with controllable and automated refresh settings, saving time and reducing operational complexity. For data streaming on the lakehouse, streaming ETL with Delta Live Tables is the best place to start.Simplify data pipeline deployment and testingWith different copies of data isolated and updated through a single code base, data lineage information can be captured and used to keep data fresh anywhere. So the same set of query definitions can be run in development, staging and production.Meet regulatory requirementsCapture all information about your table for analysis and auditing automatically with the event log. Understand how data flows through your organization and meet compliance requirements.Resources\nAll the resources you need. All in one place.\nExplore resources on the benefits of data engineering with Delta Live Tables on Databricks.\nExplore resourcesWhitepapersGet the whitepaperWebinarsWatch nowDemosExplore nowReady to get started?Try Databricks freeGetting started with Delta Live TablesDelta Live Tables documentationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/martin-grund\/#","text":"Martin Grund - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMartin GrundSenior Staff Software Engineer at DatabricksBack to speakersMartin Grund is a Senior Staff Software Engineer and Tech Lead at Databricks working at the intersection between query processing, data governance and security. Martin has previously led the engineering for Amazon Redshift Spectrum and worked on Cloudera Impala. He holds a PhD in computer science from the Hasso-Plattner-Institute in Germany.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/franco-patano","text":"Franco Patano - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFranco PatanoProduct Specialist at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/feature-engineering","text":"Feature Engineering | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWFeature EngineeringAll>Feature EngineeringFeature engineering for machine learningFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of feature engineering and the role it plays in ML lifecycle management.Features, in the context of machine learning, are the input data that is used to train a model. They are the attributes of some entity that the model will learn about. Raw data typically must be processed before it can be used as input to an ML model. Good feature engineering makes the process of model development more efficient and leads to models that are simpler, more flexible and more accurate.What is feature engineering?Feature engineering is the process of transforming and enriching data to improve the performance of machine learning algorithms used to train models using that data.Feature engineering includes steps such as scaling or normalizing data, encoding non-numeric data (such as text or images), aggregating data by time or entity, joining data from different sources, or even transferring knowledge from other models. The goal of these transformations is to increase the ability of machine learning algorithms to learn from the data set and thus make more accurate predictions.Why is feature engineering important?Feature engineering is important for several reasons. Firstly, as mentioned earlier, machine learning models sometimes can't operate on raw data, and so the data must be transformed into a numeric form that the model can understand. This could involve converting text or image data into numeric form, or creating aggregate features such as average transaction values for a customer.Sometimes relevant features for a machine learning problem may exist across multiple data sources, and so effective feature engineering involves joining these data sources together to create a single, usable data set. This allows you to use all of the available data to train your model, which can improve its accuracy and performance.Another common scenario is that other models' output and learning can sometimes be reused in the form of features for a new problem, using a process known as transfer learning. This allows you to leverage the knowledge gained from previous models to improve the performance of a new model. Transfer learning can be particularly useful when dealing with large, complex data sets where it is impractical to train a model from scratch.Effective feature engineering also enables reliable features at inference time, when the model is being used to make predictions on new data. This is important because the features used at inference time must be the same as the features used at training time, in order to avoid \"online\/offline skew,\" where the features used at the time of prediction are calculated differently than those used for training.How is feature engineering different from other data transformations?The goal of feature engineering is to create a data set that can be trained to build a machine learning model. Many of the tools and techniques used for data transformations are also used for feature engineering.Because the emphasis of feature engineering is to develop a model, there are several requirements that are not present with all feature transformations. For example, you may want to reuse features across multiple models or across teams in your organization. This requires a robust method for discovering features.Also, as soon as features are reused, you will need a way to track where and how features are computed. This is called feature lineage. Reproducible feature computations are of particular importance for machine learning, since the feature not only must be computed for training the model but also must be recomputed in exactly the same way when the model is used for inference.What are the benefits of effective feature engineering?Having an effective feature engineering pipeline means more robust modeling pipelines, and ultimately more reliable and performant models. Improving the features used both for training and inference can have an incredible impact on model quality, so better features means better models.From a different perspective, effective feature engineering also encourages reuse, not only saving practitioners time but also improving the quality of their models. This feature reuse is important for two reasons: it saves time, and having robustly defined features helps prevent your models from using different feature data between training and inference, which typically leads to \"online\/offline\" skew.What tools are needed for feature engineering?Generally the same tools that are used for data engineering can be used for feature engineering, as most of the transforms are common between the two. This usually entails some data storage and management system, access to standard open transformation languages (SQL, Python, Spark, etc.), and access to some type of compute to run the transformations.There are, however, some additional tools that can be implemented for feature engineering in the form of specific Python libraries that can help with the machine learning\u2013specific data transformations \u2014 such as embedding text or images, or one-hot encoding categorical variables. There are also some open source projects that aid in tracking features that a model uses.Data versioning is an important tool for feature engineering, since models can often be trained on a data set that has since been modified. Having proper data versioning allows you to reproduce a given model while your data naturally evolves over the course of time.What is a feature store?A feature store is a tool designed to address the challenges of feature engineering. A feature store is a centralized repository for features across an organization. Data scientists can use a feature store to discover and share features and track feature lineage. A feature store also ensures that the same feature values are used at training and inference times. This reproducible feature computation is of particular importance for machine learning, since the feature not only must be computed for training the model but also must be recomputed in exactly the same way when the model is used for inference.Why use Databricks Feature Store?Databricks Feature Store is fully integrated with other components of Databricks. You can use Databricks notebooks to develop code to create features and build models based on those features. When you serve models with Databricks, the model automatically looks up feature values from the feature store for inference. The Databricks Feature Store also provides the benefits of feature stores described in this article:Discoverability. The Feature Store UI, accessible from the Databricks workspace, lets you browse and search for existing features.Lineage. When you create a feature table with Databricks Feature Store, the data sources used to create the feature table are saved and accessible. For each feature in a feature table, you can also access the models, notebooks, jobs and endpoints that use the feature.In addition, Databricks Feature Store provides:Integration with model scoring and serving. When you use features from Databricks Feature Store to train a model, the model is packaged with feature metadata. When you use the model for batch scoring or online inference, it automatically retrieves features from Databricks Feature Store. The caller does not need to know about them or include logic to look up or join features to score new data. This makes model deployment and updates much easier.Point-in-time lookups. Databricks Feature Store supports time series and event-based use cases that require point-in-time correctness.Additional ResourcesComprehensive guide to feature storesFeature store workflow overviewDatabricks feature storeBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/malav-shah\/#","text":"Malav Shah - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMalav ShahSenior Data Scientist at DIRECTVBack to speakersMalav Shah is a Senior Data Scientist at DIRECTV. He joins DIRECTV from AT&T, where he worked on multiple consumer businesses \u2013 including broadband, wireless, and video \u2013 and deployed ML models across a wide array of use cases spanning the full customer lifecycle. Malav holds a Master\u2019s Degree in Computer Science with a specialization in ML from Georgia Tech, a degree he puts to good use every day by applying modern ML techniques to help the company deliver innovative entertainment experiences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/darshana-sivakumar\/#","text":"Darshana Sivakumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDarshana SivakumarStaff Product Manager at DatabricksBack to speakersDarshana is a Product Manager on the Marketplace team at Databricks. She is passionate about helping organizations propel innovation through data and AI. Prior to Databricks, she spent some years at HashiCorp, building Vault. Before that, she was at AWS for a few years, where she helped launch brand new analytics services such as AWS Glue and Amazon Athena.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/pandas-dataframe","text":"The complete guide to pandas DataFramePlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWpandas DataFrameAll>pandas DataFrameTry Databricks for freeGet StartedWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as efficient as possible while you're manipulating and analyzing data.One of the most useful data structures you can use for this purpose is pandas DataFrame.pandas is an open-source library written for the Python programming language which provides fast and adaptable data structures and data analysis tools. Wes McKinney originally wrote this easy-to-use data manipulation tool. It's built on the NumPy package, and its key data structure is called the DataFrame.If you're thinking, \"Hang on. Slow down. What is pandas DataFrame?\"', then don't worry, we'll go into depth about it shortly. For now, all you need to know is that pandas DataFrame is a user-friendly tool that's well-suited for use in fields that rely heavily on data. That includes scientific computing, machine learning and, as mentioned, data science.We'll break down the specifics of pandas just below. Some of the topics we'll be covering include how to make a pandas DataFrame and how to start working with pandas DataFrame, as well as the advantages of using pandas DataFrame.pandas provides two types of data structures:pandas DataFrame (2-dimensional)pandas Series (1-dimensional)pandas uses data such as CSV or TSV files or a SQL (Structured Query Language) database and turns them into a Python object with rows and columns known as a DataFrame. These objects are quite similar to tables available in statistical software (e.g., Excel or SPSS). Similar to the way Excel works, pandas DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables, as well as to extract valuable information from the given data set.You can execute pandas API on Apache Spark 3.2. This lets you evenly distribute pandas workloads, ensuring everything gets done the way it should.Now that we've covered the two types of data structure that pandas offers, it's time to take a step back and look at what a pandas DataFrame actually is. We'll give you a quick definition, followed by a handy list of the types of inputs that the DataFrame can accept.What is a pandas DataFrame?pandas DataFrame is a way to represent and work with tabular data. It can be seen as a table that organizes data into rows and columns, making it a two-dimensional data structure. A DataFrame can be created from scratch, or you can use other data structures, like NumPy arrays.When you use pandas DataFrame, you can import data in various formats and from various sources. You can, for example, import NumPy arrays, alongside being able to import pandas content.Here are the main types of inputs accepted by a DataFrame:Dict of 1D ndarrays, lists, dicts or Series2-D numpy.ndarrayStructured or record ndarrayA SeriesAnother DataFrameCommon questions on how to work with pandas DataFramesKnowing which structures pandas provides and what exactly a pandas DataFrame is doesn't necessarily equate to knowing everything about pandas DataFrames. That's why we're dedicating this section to answering some of the most common questions regarding how to go about working with pandas DataFrames.If your questions aren't among the six we'll be answering below, please keep reading. We'll be covering several other topics, as well as answering a few more key questions before this article's over.1. How to delete indices, rows or columns from a pandas DataFrameNot all DataFrame columns (or rows or indices) are always equally necessary. In fact, sometimes, you'll find you need to delete a DataFrame object, which is why we'll show you how to do so.We'll go through how to delete each one in turn, starting with indices. For these and all following examples in the article, we'll abbreviate \"DataFrame\" as \"df\" in our code, as it is a common practice.While DataFrames always have some kind of index, making it difficult to delete indices completely, you can modify your index label or remove its name altogether. Removing the name works by executing the del df.index.name command.You can also choose to reset your DataFrame index. This helps when you've got duplicate index values. All you need to do is reset your index, drop any duplicates and then reinstate the new, duplicate-free column index.Deleting columns is a little easier. By using the drop ( ) method, you can take out columns. This requires you to enter the column labels you want to get rid of, so make sure you've got the right column names down before you issue the drop ( ) command. Also, if you set inplace to True, you'll be able to remove columns without reassigning the DataFrame.Lastly, we'll show you how to delete DataFrame rows.Executing df.drop_duplicates( ) will remove duplicate rows depending on the criteria you provide for row labels. You can also opt for the same .drop() method that also works for columns, except you'd be providing a row index to drop instead. Be sure to reset the index after you do this.To specifically remove rows with missing values, you can use DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False). This will automatically take out any rows with null values. You can also adjust the parameters of the function to determine whether missing values get removed in a particular selection of data.If you're looking to replace the null values with specific values, you can use the .fillna() command instead of deleting them with .dropna().2. How to rename the index or columns of a pandas DataFrameRenaming indices and columns is a lot easier and more straightforward than deleting them. To rename these objects, all you have to do is use the .rename( ) method and fill in the index (or columns) you want to give a new value.If you change the inplace argument to False in the renaming task, the DataFrame won't be reassigned when changing the names of the columns.3. How to format the data in your pandas DataFrameMost of the time, DataFrame users need to edit, change and format the values in their DataFrames. We're going to look at some of the most important strategies to know about if that's what you're looking to do.When you want to replace every instance of a string, you can use the .replace() command, filling in the gaps in the format of (value you're changing, value you're changing it to).The program then automatically substitutes every instance of the string or value you're looking to change for the item you're changing it to.Another type of formatting you might need is the ability to take away parts of strings that you don't need. The map ( ) command will apply your chosen lambda function to each element in that column if you use it on the \"result\" column.You can also split column text into multiple rows, though this is a little more complicated, so please bear with us as we walk you through a brief tutorial.First, you've got to identify the rows that are too long so that you know which ones you're looking to split. Once you've got them down, you'll want to take the column that they're in and strings on a space. The next step is to take the values that will be split across rows and put them into a Series object.If you've got NaN values in your Series, don't worry, you're heading in the right direction. Simply stack the Series, and you'll guarantee the final copy of the Series won't have any unwanted NaN values.To get the stacked Series into the desired format, you'll have to drop the level so it lines up with the DataFrame. After that, it's just a matter of transforming your Series to a DataFrame, putting it back into the DataFrame it came from and then deleting the faulty column from your original DataFrame. The last step (deleting the column) prevents you from generating duplicates.The last kind of formatting you can apply to the data in your DataFrame takes the form of applying a function to the DataFrame's rows or columns.Start by selecting the row you'd like to work on using .loc[ ] or .iloc[ ].But since we're in DataFrame, you'd more specifically be using df.loc and df.iloc. Then, once you've got the right rows picked out, you can use apply ( ) to, as it happens, apply functionalities like doubler to either a row or a column.4. How to create an empty DataFrameCreating an empty DataFrame boils down to using the pandas DataFrame() function.If you're hoping to initialize the DataFrame with NaNs, you can simply opt for using numpy.nan, which has a type float. This means the data values in your new DataFrame will also be of type float by default. By entering the dtype attribute and then filling in the type you're looking for, you can get around this default setting.The DataFrame ( ) function relies on you passing the data you're looking to put into your DataFrame, as in, your indices and columns. This data can have as many different types as you need. Plus, as we've established, you can always force its data type to be what you want it to be using the dtype attribute.You can choose to specify the axis labels or index that your empty DataFrame will use. If you don't do this, the pandas DataFrame will automatically construct them for you using common sense rules.5. Does pandas recognize dates when importing data?In principle, yes, it does. In practice, it's a little more complicated.pandas can pick up on the fact that dates are being entered, but it works best when you give it a small nudge in the right direction. To be more specific, you'll want to add in the parse_dates argument whenever you're importing data from a CSV file or something similar. For a CSV file, that would look something like this:pd.read_csv('yourFile', parse_dates=True)This approach works best for dates that use numeric formatting. However, not all dates take this type of format.For unusual date formats, or for ones that DataFrame has some trouble recognizing, you'll want to create your own parsers. These might take the form of a lambda function that uses a format string to control the date and time input recognition.Whichever way you choose to go about giving pandas that nudge, it will recognize dates and times after you're done. That means that with minimal input on your end, you can instruct your DataFrame to pick up on any date-based information you feed it.6. When, why and how you should reshape your pandas DataFrameData analysis is one of the most important uses of pandas DataFrame. That's why it's important to be able to shape and reshape your DataFrame, so the structure you shape it into is ideally suited for your data analysis needs.So, the answer to the question \"When should I reshape my DataFrame?\" is: when its current format isn't useful to the data analysis you plan to conduct and when you're not looking to create new columns or rows for that purpose. And the reason why you should reshape it is that you're looking for the shape that's the best fit for your data analysis.That leaves just one question: \"How?\"You can choose to pivot or stack. You can also use the \"unstacking and melting\" method. We'll break down in detail how each one of those three approaches works and how you can go about using them for reshaping your DataFrame.Reshaping your DataFrame with the Pivot methodLet's start by looking at the pivot option. This creates a new table from your original one, allowing you to shape the new copy to look just the way you want it. Using this function relies on passing three arguments.First, there are the values. This argument is the point at which you choose the values of the original DataFrame that are going to be incorporated into the new one, so you can choose what to include and what you'd rather leave out.Next, you'll pass columns. Any that you do pass are going to become columns in your final table.Lastly, you've got to choose which indices you want to use in your new table.It's important to be specific about what data you want to incorporate in your resulting table. You can't, for example, include rows that contain duplicate values in your specified columns because an error message will appear. Another example is that you'll pivot by multiple columns if you don't pick out exactly which values you want to include in the final table.We'll move on to considering stacking next.Reshaping your DataFrame with the Stacking methodStacking DataFrames makes them taller. You might recognize that fact. We touched on stacking in the third question during the walkthrough of how to format the data in your DataFrame.The technical explanation is that you're moving the innermost column index, changing it into the innermost row index instead. This gets you a DataFrame that's got a new index with a new level of row labels, which will be located at the innermost level.Now it's time to consider how to unstack. As you might imagine, it's the inverse process of stacking; where stacking moves the innermost column index, unstacking moves the innermost row index. So, when you unstack, you're moving the innermost row index so it can be used as the innermost column index instead. Unstacking is used in conjunction with melting, so we'll look at that next.Reshaping your DataFrame with the Melting methodMelting is ideal for times when your DataFrame uses one or more columns as identifier variables, with the rest of the columns being measured variables. In those instances, melting basically lets you make your DataFrame longer, not wider.You'll essentially un-pivot your measured variables to the row axis so that the melt can make sure the measured variables are placed in the height of the DataFrame rather than its width. The final product will contain two columns: one for variables and one for values.How to use pandas DataFramesYou can use DataFrames in much the same way you'd use Excel spreadsheets, and pandas DataFrame is no exception.Essentially, you can use pandas DataFrame as a data structure. It can also be used to process and analyze data, just like a spreadsheet can be.When you've got data you need to read or manipulate, pandas is a useful tool to help you accomplish that goal. We've already described how to input data into pandas DataFrame, and since pandas is compatible with a lot of different types of data, you can import lots of types of data into it. This ensures you can work with your information no matter what format it takes.You can then use the formatting processes we've outlined above to transform your data into the format you need it to be in. You can transform the data you've already got, shaping it into a more usable format that's better suited for your needs.Since pandas was designed specifically to be used with Python, you can use the two in conjunction pretty much all of the time. That means you can easily perform tasks like scaling SHAP calculations with PySpark and pandas.We're going to get more specific on how to perform particular tasks and functions within pandas DataFrames. We'll cover things like creating pandas DataFrames, indexing and iterating before getting into the details regarding the advantages of using pandas in the first place.How to create a pandas DataFrameSince pandas DataFrames are versatile tools that can be used in lots of different ways, they can also be created using a few different strategies.We've already covered how to set up an empty pandas DataFrame in the response to question 4. This is one of the methods you can use to create a new pandas DataFrame. This method is best for when you don't already have another data structure to essentially \"relocate\" into pandas, or in other words, when you want to start with a completely blank slate.We'll be looking at how to create a pandas DataFrame from a NumPy ndarray just now.The short of it is that you can make DataFrames quite easily from NumPy arrays. All you need to do is pass your chosen array to the DataFrame ( ) function in your pandas data argument, which will then use your NumPy data to shape your new DataFrame. The argument will look something like this:print(pd.dataframe [ ] )And the data you're entering goes inside the angle brackets.The values, index, and column names should already be included in your NumPy array so that pandas can use your specific information to create the right DataFrame for you.One benefit of using pandas DataFrames is that the DataFrame ( ) function can take on a lot of different structures as input. When you're creating structures using non-NumPy structures, the process works pretty much the same way. That is to say, you'd still be passing your arrays into the DataFrame ( ) function, then instructing pandas to use that information to create your new DataFrame.You can even use a DataFrame as your input to create the new DataFrame. To do this, you'd use my_df = pd.DataFrame ( ), inserting your input data into the formula.The keys of your original dictionary will be contained within the index of your Series and, with it your DataFrame. Once the import is complete, your keys will be sorted automatically.You can use the shape property, together with the .index property, to learn about the dimensions of your newly-created DataFrame. This will show you both its width and height. If you're looking to find out exclusively about its height, you'll want to use the LEN ( ) function (again, together with the .index property), which will show you your DataFrame's height.Both of these approaches show you the dimensions of your DataFrame inclusive of all NaN values. On the other hand, using df[0].count ( ) will show you the DataFrame's height without any NaN values.Indexing in pandas DataFramesYou can think of indexing data in the same way you'd think of indexing physical items in a collection. In other words, indexing in pandas involves sorting data and organizing it by picking out the specific values, rows and columns you're looking to work with.The indexing that pandas DataFrame lets you do is similar to the kind that you can perform in Excel. The biggest difference is that pandas indexing is more detailed and versatile, giving you access to a wider range of options for handling your data in the way you want to.In pandas, you can start indexing by choosing the specific rows and\/or columns of data in your DataFrame that you're looking to work with. The exact selection can take a lot of forms. Sometimes, you'll want to use only a few rows but all columns; other times, it's the other way around. You might also need a handful of specific rows and columns.Since you're choosing specific subsets of data, indexing is also sometimes referred to as subset selection.Let's talk about how indexing works in pandas DataFrame.You can actually use four separate ways to index in pandas, so we'll give a quick overview of each of these. First, there's df[ ], which is an indexing operator function. You can also use df.loc[ ] when you're dealing with labels. df.iloc[ ] is mainly used for data that's focused on positions and\/or integer-based data. Lastly, there's df.ix[ ], a function for both label- and integer-based data.The four indexing styles we just mentioned are called indexers, and they're some of the most common methods of indexing data.Iterating through a pandas DataFrameIt's a good idea to be prepared for the times when you need to repeatedly execute the same group of statements in pandas DataFrame, or, in other words, when you want to iterate over rows.This is another function that's quite easy to perform in pandas. You'll want to use both a for loop and an iterrows ( ) command together to set up the iteration. This lets you put your DataFrame rows into a loop in the form of (index, Series) pairs.That way, you can get (index, row) tuples in your results.When you're iterating in pandas, you're instructing the DataFrame to iterate as a dictionary would. That is to say, you're iterating over the keys of the object, taking the items one after another in rows and columns.Advantages of using pandas DataFramesCan easily load data from different databases and data formats:\nCan be used with lots of different data typesHave intuitive merging and joining data sets that use a common key in order to get a complete viewSegment records within a DataFrameAllow smart label-based slicing, creative indexing and subsetting of large data setsAggregate and summarize quickly in order to get eloquent stats from your data by accessing in-built functions within pandas DataFramesDefine your own Python functions featuring certain computational tasks and apply them on your DataFrame recordsHave syntax that helps you get more work done with less writing\nAllows you, in two lines or less, to accomplish the same things that may take up to 15 lines in C++ or JavaStreamline workflows, get more done each day and increase the amount of data you're actually able to process and analyzeAccess to a wide variety of features, all of which are fully compatible with Python, since pandas was designed to be used with Python\nAre more accessible due to the Python-pandas combination, given that many industry professionals are well-versed in PythonHandle large volumes of data with ease and efficiency, and, thanks to the syntax we've already mentioned, speedCustomize your data approach thanks to flexible data handling that lets you edit data easily, as well as apply any necessary functions to itAre more accessible due to the fact they are open-source, ensuring anyone who needs them can use themAre compatible with lots of different types of programming languages, even beyond the one they were designed for. It works with Java and HTML, for exampleCan easily be converted into other formats, such as _jsonTop 5 pandas DataFrame visualization toolsWhile pandas DataFrame offers users the chance to use a lot of different features and functions and to flexibly manipulate any data they enter into the pandas library, it's not designed to be a highly visual tool. Basically, it gives you more of a backstage view.That's incredibly useful for a lot of reasons. For example, sometimes, you do need a visual representation of the data you're entering.Consider, for example, how pandas compares to a similar tool like Excel. In Excel, you can click a few buttons and automatically turn your purely numerical data into a visually appealing graph, chart or other representation. pandas doesn't come with a feature like this.For that reason, you'll want to look outside of pandas DataFrame itself for data visualization tools.We've compiled the five best DataFrame visualization tools below. The top two are JavaScript tools, while the other three are data analysis applications that aren't associated with Java. We'll break down the details of each tool, showing you why it's useful and what earned it the ranking we've given it.With all of that said, let's start with a look at the top two tools and why JavaScript tools take those spots.JavaScript toolsOriginally referred to as LiveScript, JavaScript is one of the most popular programming languages today, thanks to its flexible, dynamic nature. The syntax that it uses is similar to that of C, another widely-used programming language.When you use JavaScript, you can create interactive web pages. You can also adjust existing web pages. Like pandas DataFrame, JavaScript is capable of manipulating data, so you can use it to perform calculations or validate data-based conclusions. It's also useful for anyone looking to insert dynamic text into HTML or CSS documents.In this instance, we're looking at JavaScript tools that can be used for pandas DataFrame visualizations.The reason why JavaScript tools are able to take the top two spots on our list of best visualization tools is that JavaScript, as a language, is always evolving. It's widely used not just because it's broadly useful, but also because it's constantly growing and developing the more people use it. So tools created using this language can be more flexible and up-to-date with the needs of their users.Now, let's look at Qgrid, the top JavaScript tool for pandas DataFrame visualization, followed by PivotTable.js, which is the second-best tool for this purpose.1. QgridDeveloped by Quantopian, Qgrid gives your DataFrame extra interactivity by using the SlickGrid component, letting you sort and filter the data in your pandas DataFrame in a displayed version. Qgrid is a Jupyter notebook widget.Using Qgrid, you get to filter your data by its type. This means you get access to an easy-to-use filtering system with Qgrid.A particularly useful Qgrid feature when it comes to data visualization is its ability to let you configure rendering features. After you've finalized your configurations, you can then read your chosen data in a DataFrame. This makes Qgrid particularly well-suited for data manipulation or for anyone who needs to closely inspect their data.Let's look at a quick overview of how Qgrid works.To use it, you assign a specific amount of space to QGridLayout using its parent layout or with a parentWidget ( ). The tool then splits this space into rows and columns, placing each widget that's been assigned to it into the appropriate cell.2. PivotTable.jsTaking second place on our list of top tools to use with pandas, PivotTable.js is a JavaScript module that uses a pivot table library. It lets you summarize and pivot data, helping you interact with your data more easily and accessibly.A major benefit of PivotTable.js is that it's really easy to use. All you need to do is click and drag, and you'll be able to make full use of its features.Those features include simple visualization, alongside statistical analysis of the data in your pandas DataFrame. It's a great tool for pivoting and summarizing data so that you can get an overview of the data in your pandas DataFrame that's easier to understand at a glance. Also, after you've built a table, you can filter the data that's contained within it, giving you extra utility with the same widget.PivotTable.js is also useful for dragging and dropping pivot charts and tables into pandas DataFrame. You can use this method to transfer tables from Jupyter and IPython Notebook, giving you more flexibility regarding the data that you input into your pandas library.Data analysis applicationspandas DataFrams are, as we've established, highly useful for anyone looking to analyze their data.Working with data can be complicated. When data gets generated, it won't be automatically organized unless you plug it into the right tool or apply the correct formulas to it. That's part of what makes data analysis applications so valuable; analyzing data, even well-organized data, is just a lot quicker when you can program a function to do it for you.In this section, we're going to consider the three data analysis applications that are best suited to helping you visualize information stored in your pandas DataFrame.3. pandasGUIpandasGUI is a Python-based library that was created to help with data manipulation and summary statistics. They're applied to the data in your DataFrame library using a GUI (graphical user interface), which involves performing any intended operations in the interface. pandasGUI is designed to let you input commands in the UI (user interface), and the program then executes them in pandas itself.A quick note for anyone looking to install pandasGUI is that it's best to set up a new, separate virtual environment for this specific purpose. You can then install your pandasGUI library in this environment. That way, you'll have a cleaner installation and be able to use the tool more quickly.Once the installation and setup are complete, you can get started right away. Pass your DataFrame to the function, and pandasGUI will automatically be populated with rows and columns that it draws from your data set. You can even load more than one data set at a time using this method, letting you get an easy overview of lots of information at once.Your data will be accessible to you from the GUI once it's been passed to the function successfully. From there, you can interact with, edit, analyze and manipulate that data in lots of different ways. It more or less works like an Excel spreadsheet in terms of available functions and layout appearance.Data in the GUI format can be copied and pasted into other formats as well. This makes it particularly easy to transfer the data to your visualization tool of choice if the type of visualization you're looking for is something like a chart or a graph.Essentially, pandasGUI is particularly simple to use. It's also very user-friendly, even to less experienced coders. That's why it's earned this spot as the third-most useful data visualization tool for pandas DataFrame.4. TablooTabloo describes itself as a \"minimalistic dashboard app for visualizing tabular data.\" You can run it from Python, meaning it's fully compatible with pandas as well.This data visualization tool uses a Flask backend, though it's also compatible with other types of backend languages. The backend gets used to give you a simple interface that lets you make visual sense of the data you're putting into your pandas DataBase.Tabloo also lets you plot your data. That means you don't have to turn to external software to start seeing those graphs and charts you need, which is convenient if you're looking for a quick visualization and don't want to have to go searching for more tools to give that to you.In terms of the way it's used, Tabloo has a lot in common with pandasGUI. It also organizes data into cells, which can then be manipulated using much the same functions that pandasGUI is also capable of running. However, it's a little more difficult to apply more than one filter at a time in Tabloo, which is something pandasGUI is very capable of handling.The syntax Tabloo operates on is query syntax, like pandasGUI.An important difference between pandasGUI and Tabloo is that the former is more feature-rich. You simply get more options for handling your data when you use pandasGUI, which is why Tabloo ranks lower on this list despite providing users with undeniably useful features.5. D-TaleFeaturing an architecture that's comparable to Tabloo's, D-Tale takes up the last spot on this list. D-Tale uses a Flask backend, much like Tabloo, alongside a React front end that helps you make the most of the extensive array of options D-Tale lets you use.The user interface you see when you use D-Tale is, as the application's name suggests, quite detailed. You can access this by importing your pandas data into D-Tale. It'll then automatically be organized into rows and columns for you, which come with a great number of sorting features you can use to get the data set to look exactly as you want it. You can use Lock, Hide, Delete and Rename features, among others, for any row or column you choose, for example.D-Tale also lets you draw up visual representations of your data that range from charts to histograms and beyond.A useful D-Tale feature is that you can export code from the application at any time. That code can then easily be pasted into another application to check its validity or to process the data in other ways.D-Tale also lets you handle the formatting of your data. For example, let's say you've got dates included in your data set. If you'd like your dates to separate months and days from each other using a backslash instead of a period, you can adjust this in D-Tale.pandas DataFrames in a nutshellWhen you're looking to process, manipulate and analyze data, pandas DataFrame is your friend.It's a library that's designed to be used in combination with Python, making it accessible to just about anyone with even a passing familiarity with Python. It's capable of processing data in lots of different kinds of formats, too, ensuring you can input your data easily no matter what form that data takes.We've covered the biggest advantages that come with using pandas in this article, but we'll give you a quick summary of them anyway. pandas DataFrame lets you aggregate data quickly and easily. It's also compatible with multiple visualization tools, providing maximum flexibility. Unlike other scripting languages, it's able to do a lot of things with just a few lines of code commands, making it quicker to use on a regular basis.In a word, pandas DataFrame is useful, and that's true for anyone looking to process their data.Additional ResourcesOptimize Conversion Between Apache Spark and Pandas DataFrame DocumentationFrom Pandas to Apache Spark\u2019s DataFrameBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/milos-colic\/#","text":"Milos Colic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMilos ColicTech Lead EMEA Public Sector - Sr. Solutions Architect at DatabricksBack to speakersMilos Colic is Tech Lead for Public Sector UK&I at Databricks. He is passionate about big data processing and has been working with Apache Spark for more than 5 years. Milos has co-authored Mosaic framework built on top of Spark to process geospatial data efficiently at large scales. He has been very active on the Databricks blog writing about Data Products, FAIR Standards, Geospatial, Data Linking, Personalization in Retail Banking, GDPR, data sharing and more.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Databricks kostenlos testen | DatabricksDatabricks kostenlos testenTesten Sie die komplette Databricks-Plattform 14 Tage lang kostenlos in AWS, Microsoft Azure oder Google Cloud. Die Wahl des Cloud-Anbieters liegt bei Ihnen.Datenaufnahme vereinfachen und ETL automatisierenNehmen Sie Daten aus Hunderten von Quellen auf. Verwenden Sie einen einfachen deklarativen Ansatz zur Erstellung von Datenpipelines.In Ihrer bevorzugten Sprache zusammenarbeitenCode in Python, R, Scala und SQL mit Co-Authoring, automatischer Versionierung, Git-Integrationen und RBAC.12x besseres Preis\/Leistungsverh\u00e4ltnis als Cloud Data WarehousesErfahren Sie, warum mehr als 7.000 Kunden weltweit auf Databricks f\u00fcr all ihre Workloads von BI bis KI vertrauen.Erstellen Sie Ihr Databricks-Konto1\/2VornameNachnameBerufliche E-Mail-AdresseUnternehmenStellenbezeichnungRufnummer (Optional)Bitte ausw\u00e4hlenLandWeiterDatenschutzhinweis (aktualisiert)Terms of UseIhre DatenschutzwahlenIhre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ajali-sen\/#","text":"Ajali Sen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAjali SenSenior Manager at AccentureBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=EMEA","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/scalable-route-generation","text":"Scalable Route Generation | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorScalable Route GenerationPre-built code sample data and step-by-step instructions ready to go in a Databricks notebookGet startedIncrease margins by optimizing delivery routesDelivery has become an integral part of the modern retail experience. Customers increasingly expect goods to be delivered to their front doors more quickly than ever. Organizations that can meet this demand are attracting and retaining customers, forcing more and more retailers into the delivery game. But with narrowing margins and narrowing delivery time windows, retailers face challenges with profitability, often only breaking even on delivery. To be able to continue offering delivery as a viable option, organizations need to leverage data and AI to gain a competitive edge.Get started with our Solution Accelerator for Scalable Route Generation to optimize delivery routes and increase profitability by:Evaluating new algorithms against large volumes of data without capacity constraints or fear of interfering with other workloadsIterating more rapidly on algorithms with faster evaluation cycles, fine-tuning work to drive innovationBetter optimizing the way in which you get drivers from stores to customers\u2019 homes in the most cost-effective manner\u00a0Download notebookResourcesBlogLearn moreSolution AcceleratorLearn moreCustomer StoryLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/\/legal\/acceptable-use-policy","text":"Acceptable Use Policy \u2013 Paid (Including Trial) | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAcceptable Use Policy \u2013 Paid (Including Trial)For the paid (including trial) version of DatabricksThis Databricks acceptable use policy (\u201cAUP\u201d) sets forth certain restrictions relating to the access to, and use of, the Databricks Services by you or someone on your behalf under your agreement with Databricks applicable to the Databricks Services (\u201cAgreement\u201d). The restrictions set forth in this AUP are not exhaustive. Any capitalized terms used but not defined herein shall have the meaning set forth in the Agreement. This AUP may be updated by Databricks from time to time upon reasonable notice, which may be provided through the Databricks Services or by posting an updated version of this AUP. Updates of the AUP become binding, including on existing users, on the later of the date specified in the updated AUP or thirty (30) days after posting. Any modification to the AUP within an update will relate solely to restrictions on use of, and access to, the Databricks Services. Any violation of this AUP may result in the suspension or termination of your access to and use of the Databricks Services.You shall not (and shall not permit your Authorized Users to):attempt to access, search, or create accounts for any of our services by any means other than our publicly supported interfaces or as otherwise authorized by us;create multiple accounts for the purpose of extending your free trial;interfere with or disrupt (or attempt to interfere with or disrupt) the Databricks Services, or gain (or attempt to gain) access to any Systems that connect thereto (except as required to appropriately access and use the Databricks Services);use the Databricks Services to violate the security or integrity of, or otherwise abuse, any System of any party (including without limitation the Platform Services or Support Services), including but not limited to gaining unauthorized access to any System (including attempting to probe, scan, monitor, or test the vulnerability of a System), forging any headers or other parts of any message describing its origin or routing, interfering with the proper functioning of any System (including any deliberate attempt by any means to overload a System), implementing denial-of-service attacks, operating non-permissioned network services (including open proxies, mail relays or recursive domain name servers), using any means to bypass System usage limitations, or storing, transmitting or installing malicious code;use the Databricks Services to distribute or facilitate the sending of unsolicited or unlawful (i) email or other messages, or (ii) promotions of any kind;use the Databricks Services to engage in or promote any other fraudulent, deceptive or illegal activities;use the Databricks Services to process, store or transmit material, including any Customer Data, in violation of any Law or any third party rights, including without limitation privacy rights;provide a custom deployment name for your Workspace that might reasonably be considered inappropriate or that includes the trade name of any third party unless such party has provided you with express writing permission;disclose any benchmarking of the Databricks Services except as set forth in the\u00a0Service Specific Terms; oruse the Databricks Services in any circumstances where failure could lead to death, personal injury or environmental damage, and you further acknowledge that the Databricks Services are not designed or intended for such use.Databricks may modify custom deployment names if they are found to be in violation of this AUP.Inactive Monthly PAYG accounts:If an account for which Databricks is providing Monthly PAYG Services is found to be inactive, the account may be suspended or terminated by Databricks, and any Customer Content relating to such account that is stored within the Subscription Services or other Databricks Systems may be deleted. Databricks will provide at least 30 days\u2019 notice (in accordance with the Agreement) prior to permanently deleting your account, unless we deem it reasonably necessary to suspend or terminate your account without notice. For the avoidance of doubt, if we determine that the email associated with your account is invalid (e.g., because it bounces upon our notification of inactivity), we may terminate your account without further notice.An account may be considered inactive if:No Customer Authorized User has logged into the account for at least six months;No Customer Instructional Input was ever created within or input into the account and at least three months has passed since the account was established; orIf your account is set up to be paid by credit card, you (i) did not provide a valid credit card number or (ii) you failed to update an expired or invalid credit card number and at least three months has passed without a valid credit card number being on file, provided that for the avoidance of doubt this provision does not limit Databricks\u2019 right to terminate your account for non-payment relating to actual usage.\u00a0Last modified: October 1, 2021ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/special-events\/#","text":"Special Events - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpecial EventsYour pass will give you free access to a host of special events across four days in San Francisco. Attend parties and get-togethers, networking opportunities, meetups and specialist panels, such as the Women in Data discussion.MeetupsWomen in Data + AIPartiesMeetupsJoin like-minded professionals at our Data + AI Summit meetups to discuss the latest news, innovations and trends across the data, analytics and AI ecosystem.\nCome to a meetup!Eat, socialize and network with fellow data prosLearn new tips and tricks for your favorite technologiesSee what new features are in the pipelineWomen in Data and AIAttend our popular Women in Data and AI panel discussion and explore the array of activities and opportunities for women in data to connect. Join us for a special luncheon, a meetup at our after-party and much, much more throughout Summit.\nAs an attendee, you can: Hear from women who are making an impact and revolutionizing the world of data, analytics and AI \u2014 during a lunch and learn sessionJoin us at a dedicated meetup and offsite party for Data + AI Summit womenNetwork throughout the event with inspirational women who work in data, analytics and AIPartiesEnjoy exclusive parties \u2014 celebrate the world of data, analytics and AI with your fellow data professionals throughout four days in San Francisco.\nJoin us for a variety of social gatherings including an offsite party featuring live entertainment and more fun activities! Details coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/impetus-leaplogic","text":"LeapLogic Migration Solution by Impetus and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionLeapLogic Migration Solution by ImpetusMigration solution developed by Impetus and powered by the Databricks Lakehouse Platform\nGet startedAuto-transform ETL, data warehouse, analytics and Hadoop workloads to DatabricksModernizing legacy workloads to a unified ecosystem like the Databricks Lakehouse Platform helps enterprises overcome capacity and elasticity concerns, reduce infrastructure and maintenance costs, and create a single source of truth. LeapLogic \u2014 an Impetus product \u2014 auto-transforms legacy ETL, data warehouse, analytics and Hadoop workloads to modern data infrastructure on Databricks. This allows 70-90% of legacy code, scripts and business logic to be automatically transformed into production-ready output.With LeapLogic, customers have successfully accelerated time-to-market and reduced risks associated with manual migration. Impetus also offers engineering services to accelerate, optimize, re-architect, and scale on Databricks. Now, your transformation to Databricks will happen faster and more accurately, thanks to the superior analysis, automation, and validation of LeapLogic. Benefits include:Comprehensive: includes a pre-migration impact assessment plus complete audit of people, process, and technologyProven: optimizes and transforms diverse workloads to create repeatable, extensible frameworks\u200b that are proven across industries and use casesFast: automates conversion of complex workloads to deliver data migration with velocity, reliability, and consistencyGet startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/slava-frid\/#","text":"Slava Frid - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSlava FridCTO at WorldQuant PredictiveBack to speakersSlava is a 20+ year technology industry veteran who has led award-winning teams in finance, media, & non-profit sectors & enjoys pushing the envelope of what is considered possible. He is currently embracing the challenge of helping to build a new way to enable Quantitative Researchers to answer toughest questions businesses & organizations have. He received his degree in Econ from Wharton and a Computer Science degree from UPenn\u2019s School of Engineering. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vincent-chen\/#","text":"Vincent Chen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVincent ChenDirect of Product \/ Founding Engineer at Snorkel AIBack to speakersVincent Chen leads product for machine learning experiences in Snorkel Flow. Before that, he led Snorkel's ML Engineering team and performed research at the Stanford AI Lab, where he worked on the foundations of data-centric machine learning systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ankit-mathur","text":"Ankit Mathur - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnkit MathurTech Lead, Model Serving GPUs at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shawn-gilleran\/#","text":"Shawn Gilleran - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShawn GilleranPrincipal Cloud Solutions Lead at LiveRampBack to speakersShawn Gilleran leads cloud solutions at LiveRamp, helping clients leverage identity for safe and effective data use in the cloud. With over 30 years in IT, he's an expert in managed infrastructure, specializing in identity resolution for marketing, compliance, and modeling. Prior to LiveRamp, he spent 25 years at Acxiom and founded Vortex, a company focused on data monetization. Shawn holds a BS in computer science and is a patent holder for marketing technologies. He resides in Little Rock, AR.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/careers","text":"Lavorare in Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Lavorare in DatabricksAbbiamo una missione: aiutare i team di gestione dei dati a risolvere i problemi pi\u00f9 difficili del mondo. Vuoi unirti a noi?Vedi le posizioni aperte OverviewCultureBenefitsDiversityStudents & new gradsSali di livello nel tuo percorso di carriera. Migliora il tuo futuro.Databricks guida la rivoluzione dei dati e dell'AI. Abbiamo creato una nuova categoria chiamata lakehouse. Oggi, migliaia di aziende stanno utilizzando questa tecnologia per risolvere problemi come il cambiamento climatico, le frodi, la perdita di clienti e molti altri. Se cerchi un'opportunit\u00e0 che possa veramente dare una svolta alla tua carriera, questa \u00e8 la tua occasione.Perch\u00e9 il lakehouse \u00e8 il futuroPerch\u00e9 Databricks?Cresciamo velocemente e attraiamo i migliori talenti al mondo. I \"Brickster\" (cos\u00ec ci piace chiamarci) sono un gruppo speciale di pensatori brillanti, curiosi e svelti. Se chiedi a un Brickster perch\u00e9 ama lavorare da noi, probabilmente ti parler\u00e0 della nostra cultura.Scopri i nostri principi culturaliTrova il tuo teamAmministrazioneSviluppo dell'attivit\u00e0Successo dei clientiIngegneriaIngegneria applicataFinanzaITLegaleMarketingAttivit\u00e0 operativePersonale e HRProdottoServizi professionaliSelezione del personaleVenditeSicurezzaTirocini e prime esperienzeBenefit, vantaggi e lavoro ibridoPer lavorare al meglio, salute e benessere sono fondamentali. Per questo motivo offriamo grandi benefit e vantaggi, incluse modalit\u00e0 di lavoro flessibili. Tutto dipende da quale soluzione \u00e8 pi\u00f9 adatta a te e al tuo team.Scopri i nostri vantaggiDiversit\u00e0, equit\u00e0 e inclusioneCrediamo che percorsi formativi, prospettive e competenze differenti alimentino il nostro successo. Per questo motivo lavoriamo con grande impegno per coltivare un ambiente inclusivo e solidale. Scopri come stiamo arrivando alla parit\u00e0 di retribuzione, eliminando i pregiudizi inconsci nella selezione del personale e altro ancora.Iniziative di inclusioneSediOltre al quartier generale di San Francisco, in California, oggi abbiamo oltre 20 uffici in 12 Paesi. Con oltre 4.500 Brickster in tutto il mondo e una strategia di crescita ambiziosa, siamo fra le societ\u00e0 di software cloud che crescono pi\u00f9 velocemente.Scopri le nostre sedi nel mondoAmeriche\n\u00a0San FranciscoSeattleWashington, D.C.New YorkApprofondisciEuropa\n\u00a0LondraAmsterdamBerlinoMonaco di BavieraApprofondisciAsia-Pacifico\n\u00a0TokyoSingaporeSeulHangzhouApprofondisciOpportunit\u00e0 per studenti e neolaureatiSiamo impegnati a formare la prossima generazione di leader di Databricks. Per questo siamo determinati a garantire ai nostri stagisti e neolaureati un ruolo centrale nello sviluppo della nostra piattaforma.Il nostro University Program \u00e8 pensato per aiutarti a sfruttare al meglio la tua esperienza, dagli hackathon di ingegneria alle olimpiadi per stagisti, dalle serate di giochi di societ\u00e0 agli happy hour.Esplora le opportunit\u00e0 di lavoro e tirocinio Trasparenza dell'assicurazione sanitaria nella copertura (solo per Stati Uniti)ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/roger-dunn\/#","text":"Roger Dunn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRoger DunnCo-founder, CTO at ExponamBack to speakersRoger is founder and CTO of Exponam, the most recent in a series of technology product companies he has launched. Roger is a pioneer in design of complex systems at the intersection of security, data, and massively scalable distributed computing. He has 30+ years corporate and government experience in architecture and development. He has held senior positions at Apple, Microsoft, and KPMG.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#1565677c6374766c557174617477677c767e663b767a78","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c33927a00079c\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/databricks-sql","text":"Databricks SQL Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWExtended Time SQL Price Promotion - Save 40%+ Take advantage of our 15-month promotion on Serverless SQL and the brand new SQL ProLearn moreOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorDatabricks SQLRun all SQL and BI applications at scale with up to 12x better price-performance, a unified governance model, open formats and APIs, and your tools of choice \u2014 no lock-in.Select planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudSelect regionSelectLoading...Compare featuresFeature DetailSQL ClassicSQL ProSQL\u00a0ServerlessExtended Time Price PromotionPromo Nov. 1, 2022 to Jan. 31, 2024Promo Nov. 1, 2022 to Jan. 31, 2024Data Exploration and\nConnectivityIntelligent auto complete, ANSI SQL & Rest APIIntelligent auto complete, ANSI SQL & Rest APIIntelligent auto complete, ANSI SQL & Rest APIPerformanceMassively parallel processingMassively parallel processing & Predictive I\/OMassively parallel processing & Predictive I\/OSQL ETL\/ELTQuery federation, materialized views and workflow integrationQuery federation, materialized views and workflow integrationData Science and MLPython UDF, notebooks integration & geospatialPython UDF, notebooks integration & geospatialHigh Concurrency BIFully managed compute, workload management & query result cachingGovernance and ManageabilityQuery profiling, unity catalog integration & platform manageabilityQuery profiling, unity catalog integration & platform manageabilityQuery profiling, unity catalog integration & platform manageabilityEnterprise SecuritySee Platform Capabilities and Add-Ons for details* indicates Public Preview feature\n**No data transfer charges to cloud storage region while feature in Preview. See FAQ for more details\n\u00a0\nPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements\nCalculate priceStart free trialContact usWhat is the difference between SQL Serverless and SQL Classic \/ Pro?For SQL Classic and Pro, Databricks deploys cluster resources into your Cloud provider environment, and you are responsible for paying for the corresponding Compute infrastructure charges. For Serverless compute, Databricks deploys the cluster resources in Databricks\u2019 Cloud provider account and you are not required to separately pay for Compute infrastructure charges. Please see here for more details.What cross-region data transfer charges may be incurred in Serverless offerings?The cross-regions storage access feature is currently in Preview. If your source data is in a different cloud region, Databricks is currently waiving charges for transferring data from the Databricks Serverless environment's region to your cloud storage\u2019s region. We will start charging for this at market-competitive rates in the future when the feature is Generally Available (GA). Please note, the Cloud provider may still charge you directly for transferring data to the region the Databricks serverless environment is running in.Do the promotional discounts for SQL Pro and SQL Serverless stack on top of my negotiated discounts?Yes, the promotional discounts stack on top of any contracted discounts that you may have negotiated.How are the promotional discounts for SQL Pro and SQL Serverless implemented?On AWS, the promotional discounts are implemented through a reduction in the DBU rate that is emitted for SQL Pro and Serverless SQL warehouses during the promotional period.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/\/legal\/acceptable-use-policy-ce","text":"Acceptable Use Policy - CE | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAcceptable Use Policy - CEFor Databricks Community EditionUse of the Community Edition Services is subject to this Acceptable Use Policy - CE. \u00a0Databricks may update this policy at any time by providing revised terms at this link. \u00a0It is your responsibility to check this site periodically for updates. You will be deemed to have accepted the updated terms if you use the Community Edition Services after the date a revision is posted.Capitalized terms have the meaning stated in the Community Edition Terms of Service.You agree not to, and not to allow third parties to:use the Community Edition Services to process Prohibited Data or provide the Community Edition Services with access to Prohibited Data;attempt to access, search, or create accounts for any of our services by any means other than our publicly supported interfaces or as otherwise authorized by us, and that you will not sign up for more than two accounts for your own use regardless of the email address or name you use to register;copy, modify, disassemble, decompile, reverse engineer or attempt to view or discover the source code of the Community Edition Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Community Edition Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Community Edition Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible subscription to any Databricks product or service;interfere with or disrupt (or attempt to interfere with or disrupt) the Community Edition Services, or gain (or attempt to gain) access to any Systems (as defined below) or networks that connect thereto (except as required to appropriately access and use the Community Edition Services);use the Community Edition Services to violate the security or integrity of, or otherwise abuse, any application, computing device, system or network (each a \u201cSystem\u201d) of any party, including but not limited to gaining unauthorized access to any System (including attempting to probe, scan, monitor, or test the vulnerability of a System), forging any headers or other parts of any message describing its origin or routing, interfering with the proper functioning of any System (including any deliberate attempt by any means to overload a System), implementing denial-of-service attacks (inundating a target with communications requests so it cannot respond effectively or at all to legitimate traffic), operating non-permissioned network services (including open proxies, mail relays or recursive domain name servers), using any means to bypass System usage limitations, or storing, transmitting or installing malicious code;use the Community Edition Services to distribute or facilitate the sending of unsolicited or unlawful (i) email or other messages, or (ii) promotions of any kind;use the Community Edition Services to engage in or promote any other fraudulent, deceptive or illegal activities;use the Community Edition Services to process, store or transmit material, including any of Your Data, in violation of any law or any third party rights, including without limitation privacy rights;disclose any benchmarking of the Databricks Services except as set forth in the Service Specific Terms; oruse the Community Edition Services in hazardous or mission-critical circumstances or for uses requiring fail-safe performance, or where failure could lead to death, personal injury or environmental damage, and you further acknowledge that the Community Edition Services are not designed or intended for such use and Databricks bears no responsibility for any harmful impact resulting from such use.Inactive accountsIn general, users are expected to be active members within the Databricks community. If an account is found to be inactive, the account may be suspended or terminated by Databricks and any data (including your Notebooks) may be deleted. Databricks will attempt to provide at least 30 days notice (in accordance with the Community Edition Terms of Service) prior to permanently deleting your account, unless we deem it necessary to suspend or terminate your account without notice.An account may be considered inactive if:You have not logged into your account for at least six months;You never created a Notebook;Last modified: November 3, 2021ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/hl7v2","text":"HL7v2 Interoperability With Smolder | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHL7v2 Interoperability With SmolderPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAnalyze HL7v2 messages in real timeEnabling the seamless flow of healthcare data is critical to empowering healthcare professionals with the information they need to deliver optimal patient care. With the Databricks Lakehouse for Healthcare and Life Sciences, healthcare data teams can:Automate the real-time ingestion of HL7v2 messagesAddress incremental data updates seamlesslyPrepare dynamic patient data for analytics and AI at scaleDownload Smolder notebookResourcesBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arujit-pradhan","text":"Arujit Pradhan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArujit PradhanSoftware Engineer at CoinbaseBack to speakersArujit is a Software Engineer working on the Data Platform & Services team at Coinbase, where he builds frameworks for Centralized Streaming Ingestion and Change Data Capture Infrastructure. Before joining Coinbase he worked at Gojek in the Data & ML Platform team building Streaming Processing and Feature Store Infrastructure and was one of the core developers in the Open DataOps Foundation. When not working, he watches anime, reads Manga and bikes.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/learn\/training\/home","text":"Advance your data + AI skills with Databricks Academy - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCommunity loginAcademy loginBecome an expert and drive outcomesBuild a strong lakehouse foundation with Databricks training and certification to demonstrate your competence and accelerate your career.\nData + AI Summit - Join Generation AI\nLearn LLMs, machine learning and data engineering in hands-on trainings and elevate your career with complimentary onsite certifications\nRegister todayPartner technical enablementAs a Databricks partner, you receive complimentary access to Databricks\u2019 Training Program.Learn moreBecome a lakehouse expertAcquire a foundational knowledge of data, analytics and AI to increase your productivity and drive more impactful resultsDemonstrate your competenceBuild your credibility and reputation by earning certifications across areas from data analysis to data engineering and machine learningElevate your careerAccelerate your career opportunities by being at the leading edge of technology innovationLakehouse FundamentalsThe Lakehouse architecture is quickly becoming the new industry standard for data, analytics, and AI. Get up to speed on Lakehouse by taking this free on-demand training \u2014 then earn a badge you can share on your LinkedIn profile or r\u00e9sum\u00e9.Take Lakehouse Fundamentals for freeRole-based learning pathsWe provide custom-fit learning paths for multiple roles and career paths. These paths include\u00a0self-paced courses,\u00a0instructor-led training\u00a0and certifications or accreditations, where appropriate.Pre-purchased service credits (success credits and\/or learning subscriptions) can be used toward instructor-led training by submitting a request through our\u00a0Public Training Request Form.Learn more about role-based learning pathsCertificationCertification exams assess your knowledge of the Databricks Lakehouse Platform usage and the underlying methods required to successfully implement quality projects. Certification helps you gain industry recognition, competitive differentiation, greater productivity and results, and a tangible measure of your educational investment.View certificationsBy the numbers95% indicated that Databricks certifications helped them solve greater challenges in their role93% indicated that Databricks certifications helped them drive greater efficiency in their current role88% indicated that Databricks certifications helped them drive greater cost savings in their current roleTraining eventsRole-based instructor-led trainingExpand all | Collapse all\u00a0column1column2Apache Spark\u2122 Programming With DatabricksUpcoming public classesThis course uses a case study driven approach to explore the fundamentals of Spark Programming with Databricks, including Spark architecture, the DataFrame API, query optimization, Structured Streaming, and Delta.Data Analysis With Databricks SQLUpcoming public classesData Engineering With DatabricksUpcoming public classesDeep Learning With DatabricksUpcoming public classesIntroduction to Python for Data Science & Data EngineeringUpcoming public classesMachine Learning in ProductionUpcoming public classesOptimizing Apache Spark\u2122 on DatabricksUpcoming public classesScalable Machine Learning With Apache Spark\u2122Upcoming public classesFoundational and onboarding eventsExpand all | Collapse all\u00a0column1column2Get Started With Data Engineering on DatabricksUpcoming onboarding trainingsEligibility: Prospective and existing customers, and partnersLearning objectives:\n- Introduction to Databricks Lakehouse\n- Basic workspace functionality\n- Databricks Repos\nGet Started With Data Analysis on DatabricksUpcoming onboarding trainingsGet Started With Platform Administration on Databricks\nUpcoming onboarding trainings\nGet Started With Machine Learning on Databricks\nUpcoming onboarding trainings\nIf you have any questions, please refer to the\u00a0training FAQ.If you need assistance with our training offerings, please file a\u00a0training support ticket.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/legal\/mcsa","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/tensorflow","text":"TensorFlow on Databricks \u2013 The Unified Analytics Platform Optimized for TensorFlow | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTensorFlow\u2122 on DatabricksGet startedHomeVariablesPlaceholdersUsing a GPUClustering and k-meansDistributed Computing with TensorFlowDocumentationReady-to-use TensorFlowGet clusters up and running in seconds on both AWS and Azure CPU and GPU instances for maximum flexibility.Get started quickly with out-of-the-box integration of TensorFlow, Keras, and their dependencies with the\u00a0Databricks Runtime for Machine Learning.Benefit from a range of low-level and high-level APIs to train cutting-edge neural networks using TensorFlow, Keras, and Apache Spark.Scale-out computationEasily scale-out computation in a distributed fashion with the new Databricks\u00a0HorovodRunner.Benefit from accelerated hardware support (CUDA and cuDNN) for greater performances on the most demanding jobs.Automatically scale resources based on your needs, and keep costs under control by separating storage from compute resources.End-to-end collaborative experienceEasily access, explore, and prepare high-quality data sets, in batch or real-time, and at massive scale with\u00a0Machine learning.Share notebooks and keep track of changes with version history and Github integration, using Python, R, Scala or Java.Share, run, and keep track of experiments locally or in the cloud, and deploy models on any platform with\u00a0MLflow.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/product\/aws?itm_data=menu-item-awsProduct","text":"Databricks on AWS Data Platform - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks on AWSA plataforma de dados simples e unificada, perfeitamente integrada com a AWS\n\u00a0Introdu\u00e7\u00e3oAgendar uma demonstra\u00e7\u00e3oO Databricks on AWS permite que voc\u00ea armazene e gerencie todos os seus dados em uma plataforma simples e aberta de lakehouse que combina o melhor dos data warehouses e data lakes para unificar todas as suas an\u00e1lises e cargas de trabalho de IA.Data engineering confi\u00e1velSQL Analytics em todos os seus dadosData science colaborativaMachine learning de produ\u00e7\u00e3oPor que Databricks on AWS?Simples\nA Databricks permite uma \u00fanica arquitetura de dados unificada no S3 para an\u00e1lise SQL, data science e machine learningRela\u00e7\u00e3o custo\/desempenho 12 vezes melhor\nObtenha desempenho de data warehouse a pre\u00e7os de data lake com clusters de compute baseados em SQLComprovado\nMilhares de clientes implementaram o Databricks on AWS para fornecer uma plataforma de an\u00e1lise inovadora para todos os casos de uso de an\u00e1lise e IADollar Shave Club: Personaliza\u00e7\u00e3o de experi\u00eancias do cliente com o Databricks\nBaixar o e-bookHotels.com: Otimiza\u00e7\u00e3o da experi\u00eancia do h\u00f3spede com machine learning\nBaixar o estudo de casoHP: Da prepara\u00e7\u00e3o de dados ao deep learning \u2014 como a HP est\u00e1 unificando suas an\u00e1lises com a Databricks\nAssista ao webinar sob demandaIntegra\u00e7\u00f5es em destaqueAWS GravitonAWS GravitonOs clusters da Databricks s\u00e3o compat\u00edveis com inst\u00e2ncias do\u00a0AWS Graviton. Essas inst\u00e2ncias usam processadores Graviton projetados pela AWS com base na arquitetura de conjunto de instru\u00e7\u00f5es Arm64. De acordo com a AWS, esses tipos de inst\u00e2ncia t\u00eam uma rela\u00e7\u00e3o custo\/desempenho mais alta do que todos os outros tipos no Amazon EC2.\u00a0Leia maisAWS SecurityAmazon RedshiftAWS GlueImplanta\u00e7\u00e3o empresarialCasos de usoEngines de recomenda\u00e7\u00e3o personalizados\nProcesse todos os seus dados em tempo real para fornecer as recomenda\u00e7\u00f5es de produtos e servi\u00e7os mais relevantes.Sequenciamento gen\u00f4mico\nModernize sua pilha de tecnologia para melhorar a experi\u00eancia do paciente e do m\u00e9dico com o pipeline DNASeq mais r\u00e1pido em escala.Detec\u00e7\u00e3o e preven\u00e7\u00e3o\nde fraudes\nAproveite dados hist\u00f3ricos completos juntamente com streams de dados em tempo real para identificar rapidamente transa\u00e7\u00f5es financeiras irregulares e suspeitas.RecursosArtigos t\u00e9cnicosComo aproveitar seu data lake para insights anal\u00edticosComo reunir big data e IA no setor de servi\u00e7os financeirosO valor oculto da migra\u00e7\u00e3o do HadoopWebinarsModernize sua plataforma de dados e an\u00e1lises com confian\u00e7a com Databricks e AWSPor que as startups centradas em dados dependem do lakehouseUse os benef\u00edcios da an\u00e1lise em tempo real para uma tomada de decis\u00e3o r\u00e1pida no QubyLoyaltyOne simplifica e dimensiona pipelines de an\u00e1lise de dados com Delta LakeLiberte o potencial do seu data lakeCria\u00e7\u00e3o de um data lakehouse no DoorDash e GrammarlySetoresAproveitando AI e ML para extrair insights acion\u00e1veis de dados cl\u00ednicos em escala populacional dentro do PrognosComo o machine learning est\u00e1 mudando a an\u00e1lise de dados no governoTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/willy-lulciuc\/#","text":"Willy Lulciuc - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWilly LulciucSr. Software Engineer at AstronomerBack to speakersWilly Lulciuc is a Software Engineer at Astronomer working on observability and lineage. He makes datasets discoverable and meaningful with metadata. He co-created Marquez and is now involved in the OpenLineage initiative. Previously, he was the Founder Engineering of Datakin, a data lineage startup. When he's not reviewing code and creating indirections, he can be found experimenting with analog synthesizers.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/naveen-zutshi","text":"Naveen Zutshi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNaveen ZutshiChief Information Officer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/product-quality-inspection","text":"Product Quality Inspection | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorProduct Quality InspectionPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedOptimize product quality inspection with computer visionThe promise of computer vision to improve product quality inspections has become a reality with the advances in deep learning. With the Databricks Lakehouse for Manufacturing, organizations can:Implement an end-to-end computer vision pipeline for product quality inspectionBuild and train deep learning models to classify images and detect product defectsUse Databricks Model Serving to deploy models cost-effectively and with optimal performanceDownload notebookResourceseBookRead nowSolution AcceleratorRead nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/real-world-evidence","text":"Real-World Evidence | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorReal-World EvidencePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedUnlock the value of real-world evidenceReal-world data (RWD) is changing the way biotech and pharmaceutical organizations develop, deliver and measure the effectiveness of medical treatments in the real world. Yet, most organizations struggle to transform their large volumes of unstructured RWD into novel insights. Generating real-world evidence (RWE) at scale requires a new approach to data and AI that can only be achieved with a modern data lakehouse.OMOP AcceleratorBuild a Common Data Model for observational research (example based on OMOP version 5.31 CDM)Read the full write-upDownload notebookPSM Solution AcceleratorImplement propensity score matching (PSM), a statistical matching technique for observational research and real world evidence generationRead the full write-upDownload notebookSurvival Analysis Solution AcceleratorMeasure factors contributing to outcomes and mortality (example shown for lung cancer)Download notebookResourcesWhitepaperRead nowOn-demand webinarWatch nowSolution guideRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/machine-learning-with-mlflow","text":"MLflow Demo: Streamline Machine Learning | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Science and Machine Learning on Databricks DemoGet started for freeDownload NotebookIn this demo, we walk through a real-world data science and machine learning use case on Databricks, showing how different members of the data team can interact and collaborate on the Databricks platform.We also show how\u00a0MLflow on Databricks\u00a0simplifies and streamlines the end-to-end machine learning workflow, using the MLflow tracking server to track and catalog each model training run, along with the MLflow Model Registry to shepherd ML models through testing and staging environments into production, directly from Databricks.See full list of demosTake a deeper dive into machine learning with MLflowLearn moreVideo transcriptWelcome to Databricks. The lakehouse is a simple and open data platform for storing and managing all of your data, that supports all of your analytics and AI use cases. It\u2019s where data scientists and data engineers and ML engineers and analysts collaborate to prepare and analyze data, build models and deploy them to production.\nToday, we will focus on the data scientists who, as you will see here, are trying to explain life expectancy from health indicator data. And along the way, we\u2019ll see how our platform supports the whole lifecycle from data ingest to production.Collapse full transcriptExpand full transcriptCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/social-determinants-of-health","text":"Social Determinants of Health | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorSocial Determinants of HealthPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedUsing Delta Sharing to Democratize Insights Into Social Determinants of HealthDriving seamless access to data on social determinants of health is critical to empowering healthcare professionals with the information they need to reduce health inequities across social groups. With the Databricks Lakehouse for Healthcare and Life Sciences, healthcare data teams can:Explore the impact of social determinants of health on outcomesCleanse and normalize all social attributes seamlesslyPrepare social determinants of health data for analytics and AI at scaleDownload notebookResourcesOn-Demand DemoWatch nowOn-Demand WorkshopWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dipankar-mazumdar","text":"Dipankar Mazumdar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDipankar MazumdarDeveloper Advocate at DremioBack to speakersDipankar is currently a Developer Advocate at Dremio where his focus is helping data\/platform engineering teams on lakehouse platform & various open-sourced projects such as Apache Iceberg & Arrow that allows data teams to apply & scale analytics. In his past roles, he worked at the intersection of Machine Learning & Data visualization. Dipankar is a co-author of the upcoming O\u2019Reilly book on Apache Iceberg. He also holds a MS in Computer Science with research focused on ExplainableAI.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/keith-anderson","text":"Keith Anderson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKeith AndersonSolution Principal at Hitachi SolutionsBack to speakersI am a Solution Principal with Hitachi Solutions (Azure & Databricks partner) working with customers on solving data & AI problems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/platform-administration","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/celia-kung","text":"Celia Kung - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCelia KungEngineering Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chen-guo\/#","text":"Chen Guo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChen GuoStaff Software Engineer at CoinbaseBack to speakersChen Guo is a staff software engineer from the Data Platform & Service team at Coinbase. His current work focuses on designing and developing SOON (Spark cOntinuOus iNgestion), a unified streaming ingestion framework, and SONAS (SOON as a Service). Before Coinbase, he worked at LinkedIn's Big Data Infrastructure team to build cloud-based ingestion and offline processing infrastructure using Azure Data Factory and contributed to Apache Gobblin. When not working, he loves reading and sports.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/data-analysis-platform","text":"What is a Data Analysis Platform?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Analysis PlatformAll>Data Analysis PlatformTry Databricks for freeGet StartedWhat is a Data Analysis Platform?A data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visualize data from the various sources a company might have. A comprehensive data analysis platform incorporates several tools with various capabilities, from predictive analytics and data visualization to location intelligence, natural language, and content analytics. Its main scope is to turn every kind of data into actionable insights for real business outcomes.  These platforms address the demands of users, especially those working with big data, on the inadequacy of relational database management systems (RDBMS) and enable organizations to make more-informed business decision.A comprehensive big data analysis platform should be able to:integrate different Big Data sources and provide a transparent view to the users;manage and protect the organization\u2019s data assets in order to guarantee generally understandable, correct, complete and secure corporate data;monitor the data, resources, and applications to review and evaluate the health and performance of the whole systemA well-executed big data analysis, irrespective of whether the data is qualitative or quantitative, provides the possibility to:describe and summarise the dataidentify relationships between variablescompare variablesidentify the difference between variablesuncover hidden markets,discover unfulfilled customer demandsdiscover unfulfilled customer demands and cost reduction opportunitiesforecast outcomesdrive game-changing, significant improvementsIf we are talking about big data Hadoop is the preferred choice for such a requirement mainly because proved to be reliable, flexible, economical, and a scalable solution. Even though Hadoop is capable of storing this large scale data on HDFS (Hadoop Distributed File System), it does not mean that it is the only solution available. There are multiple other tools available in the market for analyzing this huge data such as MapReduce, Pig and Hive.Additional ResourcesUnified Cloud Data Analytics PlatformSolve Your Biggest Data + ML Challenges with Databricks eBookOASIS\u2014Collaborative Data Analysis Platform Using Apache SparkModern Cloud Data Platform for Dummies eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ivan-peng","text":"Ivan Peng - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIvan PengSoftware Engineer at DoorDashBack to speakersIvan is a software engineer on the data infrastructure team at DoorDash. His team is responsible for providing the foundation of data and ensuring that it is accurate and delivered in a timely manner. Prior to DoorDash, Ivan was at Nextdoor on the Data Platform team, focusing on experimentation and building a data platform for privacy and compliance. In his spare time, Ivan enjoys playing ultimate frisbee, geeking out about sports analytics, and biking to distant places in lieu of driving.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/emad-mostaque\/#","text":"Emad Mostaque - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEmad MostaqueCEO at stability.aiBack to speakersEmad Mostaque received his master's degree in mathematics and computer science from Oxford University in 2005. He then went on to spend 13 years working at various hedge funds in the United Kingdom. \nIn 2019 he founded Symmitree, a startup that aimed to reduce the cost of technology for individuals living in poverty, which he worked on for one year. In late 2020 he founded Stability AI. Much of the company's funding comes directly from Mostaque, who is a former hedge fund manager, as well as other investment companies such as Eros Investments. The company spent $600,000 of its $10 million initial funding to train Stable Diffusion (https:\/\/en.wikipedia.org\/wiki\/Stable_Diffusion) and announced a $100 million seed round of a valuation of $1 billion. \nIn March 2023, he signed an open letter calling for \"all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4\".Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=business%20development","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/order-picking-optimization","text":"Order Picking Optimization | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorOrder Picking OptimizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedOptimize order picking to increase profitabilityDemand for buy-online pick up in-store (BOPIS), curbside and same-day home delivery is forcing retailers to use local stores as rapid fulfillment centers. Caught off guard in the early days of the pandemic, many retailers scrambled to introduce and expand the availability of these services, using existing store inventories and infrastructure to deliver goods in a timely manner. As shoppers return to stores, requests for these services are unabated, and recent surveys show expectations for still more and faster options will only increase in the years to come. This is leaving retailers asking not only how best to deliver these capabilities in the longer term but also how to do so while remaining profitable.Get started with our Solution Accelerator for Order Picking to apply optimization logic to each order to:Avoid unexpected delivery outcomes and assess the impact of small variations on order pickingMinimize total store travel time to increase profitabilityDownload notebookResourcesSolution AcceleratorLearn moreBlogLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal\/privacynotice#dbhowweshareyourinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected]ks.com.Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/hadoop-cluster","text":"What Is a Hadoop Cluster?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHadoop ClusterAll>Hadoop ClusterWhat Is a Hadoop Cluster?Apache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by using an algorithm (like the MapReduce algorithm), and distributing them across a Hadoop cluster. A Hadoop cluster is a collection of computers, known as nodes, that are networked together to perform these kinds of parallel computations on big data sets. Unlike other computer clusters, Hadoop clusters are designed specifically to store and analyze mass amounts of structured and unstructured data in a distributed computing environment. Further distinguishing Hadoop ecosystems from other computer clusters are their unique structure and architecture. Hadoop clusters consist of a network of connected master and slave nodes that utilize high availability, low-cost commodity hardware. The ability to linearly scale and quickly add or subtract nodes as volume demands makes them well-suited to big data analytics jobs with data sets highly variable in size.Hadoop Cluster ArchitectureHadoop clusters are composed of a network of master and worker nodes that orchestrate and execute the various jobs across the Hadoop distributed file system. The master nodes typically utilize higher quality hardware and include a NameNode, Secondary NameNode, and JobTracker, with each running on a separate machine. The workers consist of virtual machines, running both DataNode and TaskTracker services on commodity hardware, and do the actual work of storing and processing the jobs as directed by the master nodes. The final part of the system are the Client Nodes, which are responsible for loading the data and fetching the results. Master nodes are responsible for storing data in HDFS and overseeing key operations, such as running parallel computations on the data using MapReduce.The worker nodes comprise most of the virtual machines in a Hadoop cluster, and perform the job of storing the data and running computations. Each worker node runs the DataNode and TaskTracker services, which are used to receive the instructions from the master nodes.Client nodes are in charge of loading the data into the cluster. Client nodes first submit MapReduce jobs describing how data needs to be processed and then fetch the results once the processing is finished.What is cluster size in Hadoop?A Hadoop cluster size is a set of metrics that defines storage and compute capabilities to run Hadoop workloads, namely :Number of nodes : number of Master nodes, number of Edge Nodes, number of\u00a0 Worker Nodes.Configuration of each type node: number of cores per node, RAM and Disk Volume.What are the advantages of a Hadoop Cluster?Hadoop clusters can boost the processing speed of many big data analytics jobs, given their ability to break down large computational tasks into smaller tasks that can be run in a parallel, distributed fashion.Hadoop clusters are easily scalable and can quickly add nodes to increase throughput, and maintain processing speed, when faced with increasing data blocks.The use of low cost, high availability commodity hardware makes Hadoop clusters relatively easy and inexpensive to set up and maintain.Hadoop clusters replicate a data set across the distributed file system, making them resilient to data loss and cluster failure.Hadoop clusters make it possible to integrate and leverage data from multiple different source systems and data formats.It is possible to deploy Hadoop using a single-node installation, for evaluation purposes.What are the challenges of a Hadoop Cluster?Issue with small files - Hadoop struggles with large volumes of small files - smaller than the Hadoop block size of 128MB or 256MB by default. It wasn't designed to support big data in a scalable way. Instead, Hadoop works well when there are a small number of large files.\u00a0 Ultimately when you increase the volume of small files, it overloads the Namenode as it stores namespace for the system.High processing overhead - reading and writing operations in Hadoop can get very expensive quickly especially when processing large amounts of data. This all comes down to Hadoop's inability to do in-memory processing and instead data is read and written from and to the disk.Only batch processing is supported - Hadoop is built for small volumes of large files in batches. This goes back to the way data is collected and stored which all has to be done before processing starts. What this ultimately means is that streaming data is not supported and it cannot do real-time processing with low latency.Iterative Processing - Hadoop has a data flow structure is set-up in sequential stages which makes it impossible to do iterative processing or use for ML.Additional ResourcesStep-by-Step Migration: Hadoop to DatabricksCloud Modernization With Databricks and AWSDatabricks migration hubHidden value of Hadoop migration whitepaperIt\u2019s time to reconsider your relationship with HadoopDelta Lake and ETLMaking Apache Spark\u2122 Better with Delta LakeBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/epam-smart-migration","text":"Smart Migration to Databricks by EPAM | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionSmart Migration to Databricks by EPAMMigration solution developed by EPAM and powered by the Databricks Lakehouse Platform\nLearn moreDrive efficiency and value by migrating to DatabricksMigrations are often perceived as complex, risky and costly undertakings. To help organizations overcome these fears and create simpler, smoother migrations, EPAM has developed a Smart Migration solution for Databricks with its Data Cloud Migration and Cloud Data Factory frameworks. With EPAM's AI-powered Smart Migration solution, organizations can determine an optimal migration and modernization strategy, establish metadata-driven governance processes, and accelerate their migrations while ensuring data quality. EPAM offers an integrated toolset that analyzes an existing data ecosystem to identify dependencies and risks, optimize and refine the scope, and provide goal-driven recommendations based on the company's experience and best practices. The tool also establishes a proven operational model to ensure successful execution and adoption of the new solution.Furthermore, every change is an opportunity. To capitalize on that, EPAM's Smart Migration solution with industrialized accelerators guides next-gen capability development to unlock the full potential of the Databricks Lakehouse Platform, offer new services and products, and fuel innovation. With Smart Migration, you can:Reduce migration costs and effort by >50%Improve governance and risk managementAdd long-term value through modernizationLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\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\nPD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0iVVRGLTgiPz4KPCFET0NUWVBFIHBsaXN0IFBVQkxJQyAiLS8vQXBwbGUvL0RURCBQTElTVCAxLjAvL0VOIiAiaHR0cDovL3d3dy5hcHBsZS5jb20vRFREcy9Qcm9wZXJ0eUxpc3QtMS4wLmR0ZCI+CjxwbGlzdCB2ZXJzaW9uPSIxLjAiPgo8ZGljdD4KCTxrZXk+Q1RGb250Q29weXJpZ2h0TmFtZTwva2V5PgoJPHN0cmluZz5Db3B5cmlnaHQgMjAxMCwgMjAxMiwgMjAxNCBBZG9iZSBTeXN0ZW1zIEluY29ycG9yYXRlZCAoaHR0cDovL3d3dy5hZG9iZS5jb20vKSwgd2l0aCBSZXNlcnZlZCBGb250IE5hbWUg4oCYU291cmNl4oCZLjwvc3RyaW5nPgoJPGtleT5DVEZvbnREZXNpZ25lck5hbWU8L2tleT4KCTxzdHJpbmc+UGF1bCBELiBIdW50PC9zdHJpbmc+Cgk8a2V5PkNURm9udEZhbWlseU5hbWU8L2tleT4KCTxzdHJpbmc+U291cmNlIFNhbnMgUHJvPC9zdHJpbmc+Cgk8a2V5PkNURm9udEZ1bGxOYW1lPC9rZXk+Cgk8c3RyaW5nPlNvdXJjZSBTYW5zIFBybyBTZW1pYm9sZDwvc3RyaW5nPgoJPGtleT5DVEZvbnRHZXRHbHlwaENvdW50PC9rZXk+Cgk8aW50ZWdlcj4xOTQyPC9pbnRlZ2VyPgoJPGtleT5DVEZvbnRMaWNlbnNlTmFtZU5hbWU8L2tleT4KCTxzdHJpbmc+VGhpcyBGb250IFNvZnR3YXJlIGlzIGxpY2Vuc2VkIHVuZGVyIHRoZSBTSUwgT3BlbiBGb250IExpY2Vuc2UsIFZlcnNpb24gMS4xLiBUaGlzIGxpY2Vuc2UgaXMgYXZhaWxhYmxlIHdpdGggYSBGQVEgYXQ6IGh0dHA6Ly9zY3JpcHRzLnNpbC5vcmcvT0ZMLiBUaGlzIEZvbnQgU29mdHdhcmUgaXMgZGlzdHJpYnV0ZWQgb24gYW4g4oCYQVMgSVPigJkgQkFTSVMsIFdJVEhPVVQgV0FSUkFOVElFUyBPUiBDT05ESVRJT05TIE9GIEFOWSBLSU5ELCBlaXRoZXIgZXhwcmVzcyBvciBpbXBsaWVkLiBTZWUgdGhlIFNJTCBPcGVuIEZvbnQgTGljZW5zZSBmb3IgdGhlI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{"source":"https:\/\/www.databricks.com\/it\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/healthcare-and-life-sciences","text":"Lakehouse f\u00fcr Gesundheitswesen und Life Sciences \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse f\u00fcr Gesundheitswesen und Life SciencesBessere Resultate f\u00fcr Patienten dank Daten und KIErste SchrittePlanen Sie eine DemoVier zentrale Datenprogramme in Gesundheitswesen und Life SciencesFragmentierte Patientendaten\nDatensilos und eingeschr\u00e4nkte Unterst\u00fctzung f\u00fcr unstrukturierte Daten hindern Unternehmen daran, den Weg des Patienten zu verstehen.Rasant wachsendes Volumen bei den Gesundheitsdaten\nHerk\u00f6mmliche On-Premises-Datenarchitekturen sind in der Verwaltung komplex und zudem kostspielig zu skalieren. Dies gilt insbesondere angesichts der heutigen enormen riesigen Datenmengen, die im Gesundheitswesen zu bew\u00e4ltigen sind \u2013 auch und gerade wegen der Zunahme bei Bildgebung und Genomik.Pflege und Betrieb in Echtzeit\nData Warehouses und unzusammenh\u00e4ngende Tools behindern die Gewinnung von Echtzeiterkenntnissen, wie sie f\u0000\u00fcr Entscheidungen in der Intensivpflege und die sichere Produktion und Bereitstellung wichtiger Therapeutika erforderlich sind.Komplexit\u00e4t moderner Gesundheitsanalyse\nSchwachbr\u00fcstige ML-Funktionen machen es den Unternehmen unm\u00f6glich, alle Anwendungsf\u00e4lle \u2013 von Next-Generation-Modellen f\u00fcr die Patientenversorgung bis hin zu Predictive Analytics in der Arzneimittelforschung \u2013 in Angriff zu nehmen.Lakehouse f\u00fcr Gesundheitswesen und Life SciencesEinheitliche Daten- und KI-Plattform\nZentrale Plattform, die alle Ihre Daten und Analysen zusammenf\u00fchrt, um transformative Innovationen in der Pflege und der Arzneimittelforschung zu erm\u00f6glichen\nL\u00f6sungen von Partnern\nWeltweit f\u00fchrende Anbieter von L\u00f6sungen f\u0000\u00fcr Gesundheitswesen und Life Sciences \u2013 wie Deloitte, Accenture und ZS Associates \u2013 entwickeln jetzt f\u00fcr das Lakehouse. Profitieren Sie von sofort einsatzbereiten Angeboten, die den datengesteuerten Wandel in der Arzneimittelforschung und -entwicklung und der Pflege beschleunigen.\nTools zur Beschleunigung\nGemeinsam haben Databricks und seine Partner eine Reihe von Solution Accelerators entwickelt, die die Erfassung von Daten aus dem Gesundheitswesen (z.\u00a0B. HL7-Nachrichten) erleichtern und die Implementierung von L\u00f6sungen f\u00fcr Anwendungsf\u00e4lle wie die Analyse medizinischer Texte oder die \u00dcberwachung der Arzneimittelsicherheit erlauben.\nBranchenzusammenarbeit\nErm\u00f6glichen Sie einen sicheren und offenen Datenaustausch und die Zusammenarbeit mit Organisationen aus dem gesamten Gesundheitswesen, um lebensrettende Forschung zu beschleunigen und die Versorgung zu verbessern.\nMit Lakehouse die Zukunft der Pflege gestalten\n\u00a0\n\u201eDatabricks Lakehouse f\u00fcr Gesundheitswesen und Life Sciences stellt GE Healthcare eine moderne, offene und kollaborative Plattform zur Erstellung von Patientensichten f\u00fcr alle Behandlungsbereiche zur Verf\u00fcgung. Mit diesen F\u00e4higkeiten konnten wir kostspielige, veraltete Datensilos abbauen und unseren Teams aktuelle und korrekte Erkenntnisse zur Verf\u00fcgung stellen.\u201c\u2013 Joji George, Chief Technology Officer, LCS Digital, GE HealthcareWas der Einsatz von Lakehouse f\u00fcr Gesundheitswesen und Life Sciences bringt\nBeschleunigte Forschung und bessere Patientenergebnisse dank einer offenen, kollaborativen Plattform f\u00fcr Daten und KI360\u00b0-Ansicht des Patienten\nF\u00fchren Sie alle strukturierten und unstrukturierten Daten \u2013 Patienten-, F&E- und Betriebsdaten \u2013 auf einer zentralen Plattform f\u00fcr Analysen und KI zusammen. Mit einer ganzheitlichen Sicht auf die Patient Journey k\u00f6nnen Unternehmen auf den jeweiligen Patienten zugeschnittene Behandlungen anbieten.Keine Beschr\u00e4nkungen mehr bei Studien auf Populationsebene\nAnalysieren Sie die Daten von Millionen von Patienten schnell und zuverl\u00e4ssig \u2013 mit einer skalierbaren Plattform in der Cloud. Mit Erkenntnissen auf Populationsebene erhalten Unternehmen einen umfassenderen \u00dcberblick \u00fcber Gesundheitstrends und k\u00f6nnen so bessere Therapien entwickeln.Echtzeitanalysen, Echtzeitbetrieb\nErfassen und verarbeiten Sie Streaming-Daten schnell und ortsunabh\u00e4ngig, um Analysen in Echtzeit durchzuf\u00fchren. Die Anwendungsm\u00f6glichkeiten reichen von der Verwaltung der Bettenkapazit\u00e4t in Krankenh\u00e4usern bis hin zur Optimierung von Arzneimittelherstellung und -vertrieb.ML-gest\u00fctzte Arzneimittelforschung und Patientenversorgung\nNutzen Sie die M\u00f6glichkeiten des maschinellen Lernens, um Krankheiten besser verstehen und Gesundheitsbed\u00fcrfnisse vorhersagen zu k\u00f6nnen. Alle Ihre Daten sind nahtlos mit einem Komplettpaket kollaborativer Tools f\u00fcr fortschrittliche Analysen vernetzt.E-Book herunterladenPartner und L\u00f6sungenSteigen Sie ein \u2013 mit einer Vielzahl von Daten- und Analysel\u00f6sungen und Vorlagen speziell f\u00fcr Gesundheitswesen und Life SciencesIntelligente GesundheitsversorgungVerbessern Sie Patientenerlebnisse und Gesundheitsergebnisse mit personalisierten Patientenabl\u00e4ufen und Zugang zur Versorgung.Erste SchrittePrecisionView\u2122Erweitern Sie F\u00e4higkeiten, erh\u00f6hen Sie die Kapazit\u00e4t und bereichern Sie die interne Zusammenarbeit f\u00fcr Gesundheits- und Biowissenschaften.Erste SchritteHealth Data InteroperabilityAutomatisieren Sie die Erfassung von FHIR-Streaming-Bundles im Lakehouse f\u00fcr nachgelagerte Patientenanalysen im gro\u00dfen Ma\u00dfstab.Erste SchritteErste SchritteIntelligentes Datenmanagement f\u00fcr die biomedizinische ForschungErstellen Sie eine konsistente Wertsch\u00f6pfungskette und machen Sie so aus wissenschaftlichen Daten ein Asset Ihres Unternehmens.Erste SchritteAlle Partnerl\u00f6sungen anzeigenDatenmodelle und Kohortenbildung: OMOP und Propensity Score MatchingEinfache Erfassung und Standardisierung realer Daten in Ihrem Lakehouse f\u00fcr Beobachtungsanalysen im gro\u00dfen Ma\u00dfstabErste SchritteInteroperabilit\u00e4t: Erfassen von HL7V2-NachrichtenAutomatisieren der Erfassung von HL7V2-Streaming-Nachrichten in Ihrem Lakehouse f\u00fcr EchtzeitanalysenErste SchritteInteroperabilit\u00e4t: Erfassen von FHIR-BundlesAutomatisieren der Erfassung von FHIR-Streaming-Bundles in Ihrem Lakehouse f\u00fcr nachgelagerte PatientenanalysenErste SchritteBildgebung: Digitale PathologieklassifizierungVerbesserung diagnostischer Workflows mit Deep Learning durch die Erkennung von Metastasen in digitalen GewebeprobenErste SchritteF&E: Identifizierung von WirkstoffzielenUmfassende Analyse genetischer Assoziationen zur Unterst\u00fctzung von F&E-Teams bei der Ermittlung neuer WirkstoffzieleErste SchritteBev\u00f6lkerungsgesundheit: Vorhersage von KrankheitsrisikenErstellen von Prognosemodellen zu Krankheitsrisiken f\u00fcr eine Verbesserung von PflegemanagementprogrammenErste SchritteNLP: Erkennen unerw\u00fcnschter WirkungenVerbessern der \u00dcberwachung der Arzneimittelsicherheit durch Erkennung unerw\u00fcnschter Arzneimittelwirkungen mit unserer gemeinsam mit John Snow Labs entwickelten NLP-L\u00f6sungErste SchritteNLP: Extrahieren von Onkologie-RealdatenVerwandeln Sie unstrukturierte onkologische Notizen in neue Erkenntnisse f\u00fcr Patienten \u2013 mit unserer gemeinsam mit John Snow Labs entwickelten NLP-L\u00f6sungErste SchritteNLP: Automatisches Entfernen von PatientendatenAutomatisieren der Entfernung sensibler Patienteninformationen aus Textdaten mit unserer gemeinsam mit John Snow Labs entwickelten NLP-L\u00f6sungErste SchritteAlle L\u00f6sungen anzeigenLakehouse f\u00fcr Gesundheitswesen und Life Sciences in AktionM\u00f6chten Sie mehr erfahren?Gesundheitswesen\nPatientenzentrierte Pflege mit der Leistungsf\u00e4higkeit von Daten und KIBiowissenschaften\nNeue Behandlungen f\u00fcr Patienten in Not mit Data Analytics und KIVerbesserung der Gesundheitsergebnisse mit Daten und KIE-Book herunterladen \u2192Ressourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu Daten und KI f\u00fcr das Gesundheitswesen und die Biowissenschaften.\nRessourcen erkundenE-BooksBessere Ergebnisse mit dem Lakehouse f\u00fcr Gesundheitswesen und Life SciencesNeue Patienteneinblicke mit nat\u00fcrlicher Sprachverarbeitung in gro\u00dfem Umfang gewinnenMit dem Lakehouse das Versprechen realer Daten einl\u00f6senL\u00f6sungsblatt: Einf\u00fchrung in das Lakehouse f\u00fcr das Gesundheitswesen und BiowissenschaftenWebinareWorkshop: FHIR Up-Patienten-Analytics in Echtzeit mit dem LakehouseWebinar: Innovationen im Gesundheitswesen mit dem Chesapeake Regional Information System f\u00fcr unsere Patienten f\u00f6rdernWorkshop: Standardisierung von Daten mit OMOP und Vorhersage des Krankheitsrisikos mit MLWorkshop: Extrahieren von Realdaten mit NLPWorkshop: Beschleunigte Forschung und Entwicklung mit Realdaten und KIBlogsAmgen beschleunigt Arzneimittelentwicklung und -bereitstellung mit dem Lakehouse f\u00fcr das Gesundheitswesen und BiowissenschaftenWir stellen vor: Das Lakehouse f\u00fcr das Gesundheitswesen und BiowissenschaftenH\u00f6here Arzneimittelsicherheit durch Erkennung unerw\u00fcnschter Nebenwirkungen mithilfe von NLPDas Open Source Genomics Toolkit von Databricks \u00fcbertrifft f\u00fchrende ToolsExtrahieren von Onkologie-Erkenntnissen aus klinischen Real-World-Daten mit NLPM\u00f6chten Sie loslegen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENPlanen Sie eine DemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/customers\/healthdirect-australia","text":"Customer Story: Healthdirect Australia | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYPutting patients\u2019 health first with data and AI6xImprovement in data processing20Million records ingested in 20 minutesWatch video INDUSTRY: Healthcare SOLUTION: Clinical health data lake PLATFORM USE CASE: Delta Lake,data science,machine learning,ETL CLOUD: AWS\u201cDatabricks delivered the time to market as well as the analytics and operational uplift that we needed in order to be able to meet the new demands of the healthcare sector.\u201d\n\u2014 Peter James, Chief Architect, Health Direct AustraliaAs the shepherds of the National Health Services Directory (NHSD), Healthdirect is focused on leveraging terabytes of data covering time-driven activity-based healthcare transactions to improve health care services, offerings, and support. With governance requirements, team siloes, and a legacy system that was difficult to scale, they moved to Databricks, boosting data processing for downstream machine learning while improving data security to meet HIPAA requirements.Data quality and governance, silos, and the inability to scaleDue to regulatory pressures, Healthdirect Australia set forth to improve overall data quality and ensure a level of governance on top of that. But they ran into challenges when it came to data storage and access. Multiple data silos also served as a blocker to efficiently prepare data for downstream analytics. These disjointed data sources impacted the consistency of data reads as data was oftentimes out-of-sync between the various systems in their stack. The low-quality data also led to higher error rates and processing inefficiencies. This fragmented architecture created significant operational overhead and limited their ability to have a comprehensive view of the patient.Further, they needed to ingest over 1 billion data points due to a changing landscape of customer demand such as bookings, appointments, pricing, eHealth transaction activity, etc. \u2014 estimated at over 1TB of data.\u201cWe had a lot of data challenges. We just couldn\u2019t process efficiently enough. We were starting to get batch overruns. We were starting to see that a 24-hour window isn\u2019t the most optimum time in which we want to be able to deliver healthcare data and services,\u201d explained Peter James, Chief Architect, Health Direct Australia.Ultimately, Healthdirect realized they needed to modernize their end-to-end process and tech stack to properly support the business.Modernizing analytics with Databricks and Delta LakeDatabricks provides Healthdirect Australia with a unified data analytics platform that simplifies data engineering and accelerates data science innovation. The notebook environment enables them to make content changes in a controlled fashion rather than having to run bespoke jobs each time.\u201cDatabricks has provided a big uplift for our teams and our data operations,\u201d said James. \u201cThe analysts were working directly with the data operations teams. They are able to achieve the same pieces of work together within the same timeframes that used to take twice as long. They\u2019re working together and we\u2019re seeing just a massive acceleration in the speed at which we can deliver service.\u201dWith Delta Lake, they\u2019ve created logical data zones: Landing, Raw, Staging, and Gold. Within these zones, they store their data \u201cas-is\u201d, in their structured or unstructured state, in Delta Lake Tables. From there they use a metadata-driven schema and hold the data within a nested structure within that table. What this allows them to do is handle data consistently from every source and simplifies the mapping of data to the various applications pulling the data.Meanwhile, through Structure Streaming, they were able to convert all of their ETL batch jobs into streaming ETL jobs that could serve multiple applications consistently. Overall, the advent of Spark Structured Streaming, Delta Lake, and Databricks\u2019 unified data analytics platform provide significant architecture improvements that have boosted performance, reduced operational overheads, and increased process efficiencies.Faster data pipelines results in better patient-driven healthcareAs a result of the performance gains delivered by Databricks and the improved data reliability through Delta Lake, Healthdirect Australia realized improved accuracy of their fuzzy name match algorithm from less than 80% with manual verification to 95% and no manual intervention.The processing improvements with Delta Lake and Structured Streaming allowed them to process more than 30,000 automated updates per month. Prior to Databricks, they had to use unreliable batch jobs that were highly manual to process the same number of updates over a span of 6 months \u2014 a 6X improvement in data processing.They were also able to increase their data load rate to 1 million records per minute, loading their entire 20 million record data set in 20 minutes. Before the adoption of Databricks this used to take more than 24 hours to process the same 1 million transactions, blocking analysts from making swift decisions to drive results.Last, data security which was critical due to compliance requirements, was greatly improved. Databricks provides standard security accreditations like HIPAA. Healthdirect was able to use Databricks to meet Australia\u2019s security requirements. This yielded significant cost reductions and gave them continuous data assurance by monitoring changes to access privileges like changes in roles, meta-data level security changes, data leakage, etc.\u201cDatabricks delivered the time to market as well as the analytics and operational uplift that we needed in order to be able to meet the new demands of the healthcare sector,\u201d said James.Looking ahead, the future looks bright for Healthdirect Australia. With the help of Databricks, they have proven the value of data and analytics and how it can impact their business vision. With transparent access to data that boasts well-documented lineage and quality, participation across various business and analyst groups has increased \u2014 empowering teams to more easily and quickly extract value from their data with the goal of improving healthcare for everyone.Related ContentSessionTechnical Talk at Spark + AI Summit NA 2020: Building a Federated Data Directory Platform for Public HealthReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/audience\/digital-native","text":"\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u306a\u30d3\u30b8\u30cd\u30b9\u3068\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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|\u5348\u524d8\u6642(\u592a\u5e73\u6d0b\u6a19\u6e96\u6642)\n\u00a0\n\u88fd\u9020\u696d\u306e\u305f\u3081\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u767a\u898b\u3059\u308b\n\u30b3\u30fc\u30cb\u30f3\u30b0\u304c\u3001\u624b\u4f5c\u696d\u306b\u3088\u308b\u691c\u67fb\u3092\u6700\u5c0f\u9650\u306b\u6291\u3048\u3001\u8f38\u9001\u30b3\u30b9\u30c8\u3092\u524a\u6e1b\u3057\u3001\u9867\u5ba2\u6e80\u8db3\u5ea6\u3092\u9ad8\u3081\u308b\u91cd\u8981\u306a\u610f\u601d\u6c7a\u5b9a\u3092\u3069\u306e\u3088\u3046\u306b\u884c\u3063\u3066\u3044\u308b\u304b\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u4eca\u3059\u3050\u767b\u9332\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeacons2023\u5e746\u670826\u65e5\uff5e29\u65e5\n\n\u76f4\u63a5\u53c2\u52a0\u3059\u308b\u304b\u3001\u57fa\u8abf\u8b1b\u6f14\u306e\u30e9\u30a4\u30d6\u30b9\u30c8\u30ea\u30fc\u30e0\u306b\u53c2\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3054\u767b\u9332\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29REGISTER NOW\u30af\u30e9\u30a6\u30c9\u3092\u6d3b\u7528\u3059\u308b\u4f01\u696d\u306e\u305f\u3081\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u3092\u30b9\u30b1\u30fc\u30e9\u30d6\u30eb\u306b\u30b5\u30dd\u30fc\u30c8\u3059\u308b\u5358\u4e00\u306e\u9ad8\u6027\u80fd\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\n\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u6210\u9577\u30b9\u30d4\u30fc\u30c9\u304c\u901f\u3051\u308c\u3070\u901f\u3044\u307b\u3069\u3001\u30c7\u30fc\u30bf\u306f\u8907\u96d1\u306b\u306a\u3063\u3066\u3044\u304d\u307e\u3059\u3002Databricks Lakehouse Platform - \u30c7\u30fc\u30bf\u3001\u30a2\u30ca\u30ea\u30c6\u30a3\u30af\u30b9\u3001AI\u3078\u306e\u30b7\u30f3\u30d7\u30eb\u3067\u30b3\u30b9\u30c8\u52b9\u7387\u306e\u9ad8\u3044\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308a\u3001\u4f55\u5343\u3082\u306e\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u4f01\u696d\u3084\u30b9\u30bf\u30fc\u30c8\u30a2\u30c3\u30d7\u4f01\u696d\u306e\u751f\u7523\u6027\u3092\u9ad8\u3081\u3066\u3044\u307e\u3059\u3002\n\u00a0\u3002\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u67d4\u8edf\u6027\u3092\u6d3b\u7528\u3057\u305f\u9769\u65b0\n\u5834\u6240\u3092\u554f\u308f\u305a\u3001\u3044\u3064\u3067\u3082\u30c7\u30fc\u30bf\u3092\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u30d9\u30f3\u30c0\u30fc\u30ed\u30c3\u30af\u30a4\u30f3\u306f\u3042\u308a\u307e\u305b\u3093\u3002Apache Spark\u2122 \u306e\u958b\u767a\u8005\u304c\u30aa\u30fc\u30d7\u30f3\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3068 API \u3067\u69cb\u7bc9\u3057\u305f\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3067\u3059\u3002\n\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u898b\u308b\u30b9\u30b1\u30fc\u0000\u0000\u30e9\u30d6\u30eb\u306a\u30c7\u30fc\u30bf\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306e\u69cb\u7bc9\nDatabricks \u304c\u30a4\u30f3\u30d5\u30e9\u3092\u81ea\u52d5\u7ba1\u7406\u3057\u3001\u3055\u3089\u306b\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u3068\u30d0\u30c3\u30c1\u30c7\u30fc\u30bf\u306e ETL \u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3067\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u9ad8\u901f\u306a\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\n\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u3092\u898b\u308b\u8fc5\u901f\u306a\u77e5\u898b\u306e\u62bd\u51fa\n\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3001\u5909\u63db\u3001\u30af\u30a8\u30ea\u3092 \uff11\u3064\u306e\u5834\u6240\u3067\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u30b5\u30fc\u30d0\u30fc\u306e\u7ba1\u7406\u3092\u4e0d\u8981\u306b\u3057\u3001\u30b5\u30fc\u30d0\u30fc\u30ec\u30b9\u3067\u30aa\u30f3\u30c7\u30de\u30f3\u30c9\u306b\u62e1\u5f35\u3057\u3001\u6700\u5927 12 \u500d\u306e\u4fa1\u683c\u6027\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\nDatabricks SQL \u3092\u898b\u308bML \u3092\u6d3b\u7528\u3057\u305f\u6b21\u4e16\u4ee3\u30a2\u0000\u30d7\u30ea\u306e\u958b\u767a\n\u5b9f\u9a13\u304b\u3089\u5b9f\u904b\u7528\u307e\u3067\u306e\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u3092\u9ad8\u901f\u5316\u3057\u307e\u3059\u3002\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u53ef\u80fd\u306a Notebook\u3001MLflow\u3001MLOps \u306a\u3069\u306e\u30c4\u30fc\u30eb\u3092\u6d3b\u7528\u3057\u3066\u751f\u7523\u6027\u3092\u5411\u4e0a\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\nML \u6a5f\u80fd\u3092\u898b\u308bDatabricks \u3092\u4f7f\u3063\u3066\u307f\u308bDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\nDatabricks on AWS \u306e 14 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40\uff05 \u524a\u6e1b\u3057\u3001\u751f\u7523\u6027\u3092\u5411\u4e0a\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u5f93\u91cf\u5236\u8ab2\u91d1\u5236\u3084\u5272\u5f15\u4fa1\u683c\u30aa\u30d7\u30b7\u30e7\u30f3\u3092\u3054\u7528\u610f\u3057\u3066\u3044\u307e\u3059\u3002\n\u6599\u91d1\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u898b\u308b\u6280\u8853\u30b5\u30dd\u30fc\u30c8\nDatabricks \u306e\u30a8\u30ad\u30b9\u30d1\u30fc\u30c8\u304b\u3089\u3001\u3088\u308a\u65e9\u304f\u7b54\u3048\u3092\u898b\u3064\u3051\u308b\u305f\u3081\u306e\u30b5\u30dd\u30fc\u30c8\u3092\u53d7\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u30bb\u30eb\u30d5\u30b5\u30fc\u30d3\u30b9\u306e Notebook \u3092\u5229\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u8fc5\u901f\u306b\u958b\u767a\u3067\u304d\u307e\u3059\u3002\nNotebook \u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u898b\u308b\u30d3\u30eb\u30c8\u30aa\u30f3\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30c9\u30ea\u30d6\u30f3\u306a\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3092\u6e56\u7554\u306b\u69cb\u7bc9\u3057\u3001Databricks\u3067\u30d3\u30b8\u30cd\u30b9\u306e\u6210\u9577\u3092\u52a0\u901f\u3055\u305b\u3088\u3046\u30b9\u30bf\u30fc\u30c8\u30a2\u30c3\u30d7\u306e\u305f\u3081\u306e Databricks\u30b9\u30bf\u30fc\u30c8\u30a2\u30c3\u30d7\u30fb\u30d7\u30ed\u30b0\u30e9\u30e0\u3067\u3059\u3050\u306b\u59cb\u3081\u3089\u308c\u308b\u3002Databricks \u3067\u5229\u7528\u3067\u304d\u308b\u7121\u6599\u306e\u30af\u30ec\u30b8\u30c3\u30c8\u3001\u5c02\u9580\u5bb6\u306e\u30a2\u30c9\u30d0\u30a4\u30b9\u3001Go To Market 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Security\u3001Iterable\u3001Zipline\u3068\u3044\u3063\u305f\u30ea\u30fc\u30c7\u30a3\u30f3\u30b0\u30ab\u30f3\u30d1\u30cb\u30fc\u306b\u3088\u308b\u5b9f\u969b\u306e\u4f7f\u7528\u4f8b\u3082\u7d39\u4ecb\u3055\u308c\u3066\u3044\u307e\u3059\u3002eBook \u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u95a2\u9023\u30ea\u30bd\u30fc\u30b9eBook\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u3068\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3068\u306f\uff1f\u305d\u308c\u305e\u308c\u306e\u5f37\u307f\u30fb\u5f31\u307f\u3068\u6b21\u4e16\u4ee3\u306e\u30c7\u30fc\u30bf\u7ba1\u7406\u30b7\u30b9\u30c6\u30e0\u300c\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u300d\u3092\u89e3\u8aac\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30af\u6a5f\u68b0\u5b66\u7fd2\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30afeBook\uff1aDelta Lake \u30b7\u30ea\u30fc\u30ba\u30aa\u30f3\u30c7\u30de\u30f3\u30c9\u52d5\u753b\uff1aDelta Lake \u2015 \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u57fa\u76e4MLOps \u306e\u30d3\u30c3\u30b0\u30d6\u30c3\u30af\u30c7\u30fc\u30bf\u30c1\u30fc\u30e0\u306b\u3088\u308bDatabricks Lakehouse\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3078\u306e\u30ac\u30a4\u30c9\u30af\u30a4\u30c3\u30af\u30b9\u30bf\u30fc\u30c8\u30ac\u30a4\u30c9ETL\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306e\u5b9f\u884cDelta Live Tables \u306b\u3088\u308b\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3SQL\u30ac\u30a4\u30c9\uff1a\u30af\u30a8\u30ea\u3068\u30c0\u30c3\u30b7\u30e5\u30dc\u30fc\u30c9\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/wipro-data-intelligence-suite","text":"Data Intelligence Suite by Wipro | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionData Intelligence Suite by WiproMigration solution developed by Wipro and powered by the Databricks Lakehouse Platform\nGet startedMigrate with confidence to DatabricksModernizing data is a top priority, but there are challenges to doing it efficiently and cost-effectively. Data Intelligence Suite by Wipro enables end-to-end automation of the cloud migration and transformation journey (including Hadoop, EDW, ETL and SAS workload migrations) across Azure, AWS and GCP with a suite of low-code\/no code and AI\/ML infused accelerators. The Data Intelligence Suite helps with assessment of the existing landscape, migration planning, automated data movement and validation. With the Wipro Data Intelligence Suite, you can achieve:Up to 20%-30% reduction in total cost of ownershipAverage of 50% productivity gains in migration effortsHigh efforts savings for large migrations of ~20%-35%Get startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/data-science-machine-learning\/dsml-demo?itm_data=MLproduct-pf-dsml","text":"\n\n\n\n\n\n\n\nData Science and Machine Learning | Databricks Demo\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ori-zohar\/#","text":"Ori Zohar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOri ZoharPrincipal Product Marketing Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/itai-yaffe","text":"Itai Yaffe - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingItai YaffeSenior Big Data Architect at AkamaiBack to speakersItai Yaffe is a Senior Big Data Architect at Akamai.\nPrior to Akamai, Itai was a Senior Solutions Architect at Databricks, a Principal Solutions Architect at Imply, and a big data tech lead at Nielsen Identity, where he dealt with big data challenges using tools like Spark, Druid, Kafka, and others.\nHe is also a part of the Israeli chapter's core team of Women in Big Data. Itai is keen on sharing his knowledge and has presented his real-life experience in various forums in the past.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/philippe-leonhart\/#","text":"Philippe Leonhart - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPhilippe LeonhartDigital Transformer, Corporate Business Services at MichelinBack to speakersFormer Sales Rep, moving to business analysis and later project management. My passionate about solving issues using digital tools! I believe that a true digital transformation relies on a better symbiosis between Information System actors and Business actors. For this, 2 core levers : making the expression of requirements a core competency and shift the roles in the delivery with citizen development. I\u2019m looking forward to share this perspective with you!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeff-breeding-allison","text":"Jeff Breeding-Allison - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeff Breeding-AllisonSenior Data Scientist at Mars PetcareBack to speakersJeff Breeding-Allison is a Senior Data Scientist at Mars Petcare with years of experience working in demand forecasting at CPG and marketing companies. He was previously a Visiting Assistant Professor of Mathematics at Boston College and at Fordham University in NYC, where he published research on modular forms, automorphic representations, and the representation theory of finite general symplectic groups.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Databricks kostenlos testen | DatabricksDatabricks kostenlos testenTesten Sie die komplette Databricks-Plattform 14 Tage lang kostenlos in AWS, Microsoft Azure oder Google Cloud. Die Wahl des Cloud-Anbieters liegt bei Ihnen.Datenaufnahme vereinfachen und ETL automatisierenNehmen Sie Daten aus Hunderten von Quellen auf. Verwenden Sie einen einfachen deklarativen Ansatz zur Erstellung von Datenpipelines.In Ihrer bevorzugten Sprache zusammenarbeitenCode in Python, R, Scala und SQL mit Co-Authoring, automatischer Versionierung, Git-Integrationen und RBAC.12x besseres Preis\/Leistungsverh\u00e4ltnis als Cloud Data WarehousesErfahren Sie, warum mehr als 7.000 Kunden weltweit auf Databricks f\u00fcr all ihre Workloads von BI bis KI vertrauen.Erstellen Sie Ihr Databricks-Konto1\/2VornameNachnameBerufliche E-Mail-AdresseUnternehmenStellenbezeichnungRufnummer (Optional)Bitte ausw\u00e4hlenLandWeiterDatenschutzhinweis (aktualisiert)Terms of UseIhre DatenschutzwahlenIhre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/azure-databricks-cloud-integration?itm_data=azureproduct-resources-videos","text":"Azure Databricks Demo: Seamless Cloud Integration | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure Databricks Cloud Integration DemoDownload NotebooksTry DatabricksThe Azure Databricks Lakehouse Platform gives you the best of data lakes and data warehouses, on a simple, open and collaborative platform that securely integrates with your existing Azure services. In this demo, we cover several of the most common Azure Databricks integrations, including Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI and more.See full list of demosDive deeper into Azure DatabricksTo play this video, click here and accept cookiesVideo transcriptIntro to Lakehouse on Azure Databricks\nAzure Databricks is the jointly developed Data + AI service from Databricks and Microsoft for data engineering, data science, analytics and machine learning. The Azure Databricks Lakehouse Platform gives you the best of data lakes and data warehouses, on a simple, open and collaborative platform that securely integrates with your existing Azure services.\nBatch ETL pipelines with Azure Data Factory and Azure Databricks\nOrchestrating data pipelines for extract, transform and load (ETL) operations is easier than ever thanks to the integration between Azure Databricks and Azure Data Factory. In this demo, we\u2019ll be working with power output and maintenance system records from a fleet management system used to maintain wind turbines across the United States. We\u2019ve created an Azure Data Factory pipeline that uses COPY commands to incrementally ingest data from the fleet management system in SQL server to our landing zone in Azure Data Lake Storage Gen2. Data Factory then executes a Databricks notebook to process the data using Databricks Auto Loader, and saves it into Delta Lake tables.Collapse full transcriptExpand full transcriptCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacolon-walker\/#","text":"Jacolon Walker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacolon WalkerCo-founder & CTO at MonadBack to speakersJacolon is the Co-founder & CTO of Monad. A 15-year veteran of the security industry, Jacolon has built and overseen SOC, appsec, incident response, threat intelligence and security engineering programs at companies like Palantir, Opendoor, and Collective Health. Jacolon holds a B.S. in Computer Science from the University of Texas at Dallas. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shiv-trisal\/#","text":"Shiv Trisal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShiv TrisalGTM Director, Manufacturing & Energy at DatabricksBack to speakersShiv has successfully led diverse product and strategy teams and delivered game-changing data and AI-led innovation across Diversified Manufacturing, Transportation and Logistics and Aerospace industries, with roles at Ernst & Young, Booz & Co.\/Strategy & and Raytheon Technologies. As an industry leader, Shiv regularly connects with executives to cover key trends and help enable data and AI strategies to unlock strategic competitive advantage in Manufacturing and Logistics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/recommendation-engines","text":"Recommendation Engines for Personalization | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorRecommendation Engines for PersonalizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookIncrease conversion with personalized recommendationsCustomers have different needs at each stage of the buyer journey. Choose the right recommender model for your scenario. Have a cold start problem? Try content-based recommenders. Nudging an existing customer to add to their cart? Wide-and-deep recommenders can help.NOTEBOOK 1Image-based recommendationsBuild a similarity-based image recommendation system for e-commerce that takes into account the visual similarity of items as an input for making product recommendations.Get the notebooksNOTEBOOK 2Market-based recommendationsBuild a recommender that leverages product affinities to suggest additional items.Get the notebooksNOTEBOOK 3Wide-and-deep recommendationsBuild a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.Get the notebooksNOTEBOOK 4Matrix factorization (ALS) recommendationsBuild a matrix factorization recommender to infer user ratings for various products. The alternating least squares (ALS) implementation for this recommender demonstrates patterns for matrix factorization that scale to accommodate the large numbers of user and product combinations found in real-world scenarios.Get the notebooksResourcesBlogLearn moreBlogLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hari-rajaram","text":"Hari Rajaram - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHari RajaramSr Director \/ Principal Data Architect at ProcoreBack to speakersHari is an accomplished technologist leader with more than two decades of experience in the data field. In addition, he is a tech enabler who has designed several technical architecture solutions for start-ups to enterprise.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/contact?itm_data=PricingPage-Demo","text":"Contact Us - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContact usNeed assistance with training or support? See these additional resources.DocumentationRead technical documentation for Databricks on AWS, Azure or Google CloudDatabricks CommunityDiscuss, share and network with Databricks users and expertsTrainingMaster the Databricks Lakehouse Platform with instructor-led and self-paced training or become a certified developerSupportAlready a customer? Click here if you are encountering a technical or payment issueOur office locationsSee all our office locations globally and get in touchKnowledge baseFind quick answers to the most frequently asked questions about Databricks products and servicesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vadivel-selvaraj\/#","text":"Vadivel Selvaraj - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVadivel SelvarajStaff Software Engineer at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks auf Google CloudOffene Lakehouse-Plattform trifft auf offene Cloud, um Data Engineering, Data Science und Analytics zusammenzuf\u00fchrenErste SchritteDatabricks auf Google Cloud ist ein gemeinsam entwickelter Service, mit dem Sie alle Ihre Daten auf einer einfachen, offenen Lakehouse-Plattform speichern k\u00f6nnen, die die Vorz\u00fcge von Data Warehouses und Data Lakes vereint. F\u00fchren Sie alle Analyse- und KI-Workloads auf einer einzigen Plattform zusammen. Dank der engen Verzahnung mit Google Cloud Storage, BigQuery und der Google Cloud AI Platform kann Databricks nahtlos mit Daten und KI-Diensten in der Google Cloud arbeiten.\nZuverl\u00e4ssiges Data EngineeringSQL Analytics\nf\u00fcr alle Ihre DatenKollaborative Data ScienceMachine Learning in der Produktion\nWarum Databricks auf Google Cloud?OffenBasierend auf offenen Standards, offenen APIs und einer offenen Infrastruktur \u2013 damit Sie Daten so abrufen, verarbeiten und analysieren k\u00f6nnen, wie Sie es wollenOptimiertStellen Sie Databricks auf der Google Kubernetes Engine \u2013 der ersten Kubernetes-basierten Databricks-Runtime in einer Cloud \u2013 bereit, um schneller Erkenntnisse zu gewinnen.IntegriertErhalten Sie auf der Google Cloud Console mit nur einem Klick Zugriff auf Databricks \u2013 mit integrierter Sicherheit, Abrechnung und Verwaltung.Erfahren Sie mehr von diesen Kunden\n\u201eDatabricks auf Google Cloud vereinfacht den Prozess der Umsetzung beliebig vieler Anwendungsf\u00e4lle auf einer skalierbaren Computing-Plattform und reduziert die Planungszyklen, die f\u00fcr die Bereitstellung einer L\u00f6sung f\u00fcr jede von uns gestellte gesch\u00e4ftliche Frage oder Problemstellung erforderlich sind.\u201c\u2013 Harish Kumar, Global Data Science Director bei ReckittOptimierte Integration mit Google CloudGoogle Cloud-SpeicherGoogle Cloud-SpeicherErm\u00f6glichen Sie nahtlosen Schreib-\/Lesezugriff f\u00fcr Daten in Google Cloud Storage (GCS) und nutzen Sie das offene Delta Lake-Format, um Databricks mit leistungsstarken Funktionen f\u00fcr Zuverl\u00e4ssigkeit und Performance zu erg\u00e4nzen.Google Kubernetes-EngineBigQuery (BigQuery)Big-Cloud-Identit\u00e4tGoogle Cloud AI-PlattformGoogle Cloud-AbrechnungLookerPartner\u00f6kosystemRessourcenVirtuelle VeranstaltungenVirtueller Workshop: Der Open Data LakeNeuigkeitenDatabricks kooperiert mit Google Cloud, um seine Plattform f\u00fcr globale Unternehmen bereitzustellenBlogs und BerichteAnk\u00fcndigung der Einf\u00fchrung von Databricks auf Google CloudEinf\u00fchrung von Databricks auf Google Cloud \u2013 jetzt in der \u00f6ffentlichen VorschauDatabricks auf Google Cloud \u2013 DatenblattDatabricks auf Google Cloud jetzt allgemein verf\u00fcgbarData Engineering, Data Science und Analytics mit Databricks auf Google CloudM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/unlock-the-potential-inside-your-data-lake-aws","text":"Unlock the Potential Inside Your Data Lake | DatabricksWatch On-demandUnlock the Potential Inside Your Data LakeLearn how Apple and Disney+ unified analytics and AI for successOrganizations are looking for ways to get more out of their data lakes. This is your chance to learn how Apple and Disney+ have implemented Delta Lake, making their data lake performant and reliant for analytics and AI.Learn how leaders like Apple and Disney+ are improving the reliability and performance of their data lakes using Delta LakeWe will cover:Introduction to the lakehouse and why organizations are moving to this new data and AI paradigm, which combines the the cost and scale of a data lake with the performance and reliability of a data warehouseHear from Dominique Brezinski on how Apple is using Delta Lake to make their data available for their entire data team, including data scientists, data engineers and data analystsHear from Rekha Bachwani and Martin Zapletal how Disney+ has rapidly scaled to provide a personalized and seamless experience to tens of millions of customers.See two demos of how data engineers and data scientists can get the most from their lakehouse using Databricks on AWSFeatured SpeakersDominique BrezinskiDistinguished EngineerApple Information SecurityRekha BachwaniPrincipal EngineerDisney+Martin ZapletalDirector of EngineeringDisney+Franco PatanoSenior Solutions ArchitectDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ben-wilson\/#","text":"Ben Wilson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBen WilsonPrincipal Specialist Solutions Architect at DatabricksBack to speakersBen works on the team supporting MLflow and other notable Open Source ML products at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/Company\/careers\/university-recruiting","text":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks University Recruiting \u2013 Databricks\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\nMenu\n\n\n\n\n\n\n\n\n\n\n\n\n\nMenu\n\n\n\n\n\nPlatform\n\n\n\n\n\n\n\n\nThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingOpen Source TechSecurity and Trust Center\n\nSolutions\n\n\n\n\n\n\n\n\nSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform Migration\n\nLearn\n\n\n\n\n\n\n\n\nDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeacons\n\nCustomers\n\n\n\nPartners\n\n\n\n\n\n\n\n\nCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks\n\nCompany\n\n\n\n\n\n\n\n\nAbout UsCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact Us\n\n\n\n\n\nTry Databricks\nWatch Demos\nContact Us\nLogin\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSearch\n\n\n\n\n\n\n\nMenu \n\n\n\n\n\n\n\n\nMenu \n\nPlatform-Platform column-The Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingOpen Source TechSecurity and Trust CenterPromotion Column\n\n\nDiscover how to build and manage all your data, analytics and AI use cases with the Databricks Lakehouse Platform \n\nRead now\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSolutions-Solutions column-Solutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all Industries-Solutions column2-Solutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationPromotion Column\n\n\nNew survey of biopharma executives reveals real-world success with real-world evidence.\n\nSee survey results\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nLearn-Learn column-DocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity Alliance-Learn column2EventsData + AI SummitBlogLabsBeaconsPromotion Column\n\n\nJune 26\u201329, 2023\nRegistration for Data + AI Summit virtual experience is now open!\n\nRegister now\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nCustomersPartners-partners column-Cloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks\n\n\nConnect with validated partner solutions in just a few clicks.\n\nLearn more\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nCompany-Company column-About UsCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsPromotion Column\n\n\nSee why Gartner named Databricks a Leader for the second consecutive year\n\nGet the report\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks\nWatch Demos\nContact Us\nLogin\n\n\n\n\nSearch\n\n\n\n\n June 26-29 \nREGISTER NOW \n\n\n\n\n\n\nDatabricks University Recruiting\n\n\n\nStart your career at Databricks and help data teams solve the world\u2019s toughest problems\n Explore opportunities\n\n\n\n\n\n\n\n\n\nStudent internships and college grad opportunities\nWe\u2019re committed to learning and development at every level, so it\u2019s important to our teams that we recruit and develop our next generation of Databricks leaders. Our University Program ensures that interns and new college grads play an integral role in developing our Platform, while participating in fun events to get to know each other and the larger Databricks team.\n\n\n\n\n\nMake an impact in San Francisco Bay Area, Amsterdam, Berlin, and Greater Seattle Area\nWe offer internships and full time opportunities in San Francisco Bay Area, Amsterdam, Berlin, and Greater Seattle Area. Our interns are integrated into full-time teams and work on projects that have a huge impact on our customers! Read more about our Interns\u2019 work with MLFlow, automation, and collaborating with cofounders.\n\n\n\n\n\n\n\n\n \nSlide 1 - copy - copyLunch-and-learns and donut meetings with the team were a great way to learn about a wide range of topics like company culture, career growth, life advice, and to get to know the people you're working with.\u2013Hannah, Summer 2020Slide 1At Databricks, I was able to participate in not one, but two hackathons in twelve weeks. Unlike most companies, at Databricks all engineers participate in hackathons and all of our standard work grinds to a halt for two entire days. Not only was it a nice change of scenery from my regular intern project but I actually ended up working with some staff engineers on my second project who had been at Databricks forever. It was pretty surreal to be able to collaborate side by side with them as we worked on implementing our feature, which involved diving deep into how Spark execution works. After all, the unofficial wisdom at Databricks says that \u201call of our popular features come from Hackathons\u201d!\u2013Ned, Summer 2020Slide 1 - copy - copyIf I had to describe my time at Databricks in one word, I'd say ownership; you really are the owner of your project. I had full control over the design and course of the project and could change the direction as it made sense. I was fully trusted to do that!\u2013Andrew, Winter & Fall 2020Slide 1 - copyI\u2019ve been so impressed with how caring and expressive my teammates are! They made me feel comfortable asking *any* question and helped me overcome my imposter syndrome. They really embody the culture of collaboration and ownership here.\u2013Sandra, New Grad \n\n\n\n\nLife at Databricks\n\n\n\n\n \nSlide 1 - copyIt\u2019s a Good Time to be a Brickster!\nDespite what has been an incredibly challenging year for so many, both personally and professionally, we are proud to have a more passionate and engaged team of Bricksters than ever. And we\u2019re fortunate that our momentum hasn\u2019t slowed down - if anything, it's accelerated.\nRead more from our Culture Blog\nSlide 1 - copy - copyWomen\u2019s Equality Day: Cultivating Leadership, Communication and Negotiation Skills\nDatabricks is committed to fostering an environment that promotes equality and inclusion. For Women\u2019s Equality Day on August 26, we invited Coco Brown, founder and CEO of Athena Alliance \u2014 a digital platform dedicated to revolutionizing leadership \u2014 to present a talk about women in leadership and the path to the boardroom.\nRead more from our Culture Blog\n \n\n\n\n\n\n\nResources for students\n\n\nHear from the interns\nRead what it\u2019s like\n\n\nMastering engineering interviews\nLearn the best tips and tricks\n\n\nUse Databricks in your classroom\nGet hands-on experience\n\n\nCommunity edition of Databricks\nTry out Databricks\n\n\n\n\nSee internship positions\nSee all jobs\n\n\n\n\n\n\n\nProduct\n\nPlatform Overview\nPricing\nOpen Source Tech\nTry Databricks\nDemo\n\n\nLearn & Support\n\nDocumentation\nGlossary\nTraining & Certification\nHelp Center\nLegal\nOnline Community\n\n\nSolutions\n\nBy Industries\nProfessional Services\n\n\nCompany\n\nAbout Us\nCareers at Databricks\nDiversity and Inclusion\nNewsroom\nCompany Blog\nContact Us\n\n\n\nSee Careers\nat Databricks\n\n\nEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Italiano (Italy)Portugu\u00eas (Brazil)Worldwide\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks Inc.\n160 Spear Street, 15th Floor\nSan Francisco, CA 94105\n1-866-330-0121\n \n\n\n\u00a9 Databricks 2023. All rights reserved. Apache,\nApache Spark,\nSpark and the Spark logo are trademarks of the Apache Software\nFoundation.\n\n\n\n\n\n\n\n\n\n\n\nPrivacy Notice | Terms of Use | Your Privacy Choices | Your California Privacy Rights \n\n\n\n\n\n\n\n\n\n\n\n\nSearch\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steve-sobel","text":"Steve Sobel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteve SobelGlobal Lead - Communications, Media & Entertainment at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/percy-liang\/#","text":"Percy Liang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPercy LiangProfessor of Computer Science at StanfordBack to speakersPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/audience\/digital-native","text":"Entreprises et applications digital-natives | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLe lakehouse pour les entreprises n\u00e9es dans le cloudCr\u00e9ez des capacit\u00e9s de donn\u00e9es, d'analytique et d'IA et faites-les \u00e9voluer plus vite sur une m\u00eame plateforme de donn\u00e9es hautes performances.\nD\u00e9marrerRegarder les d\u00e9mosPlus votre croissance est rapide, plus vos donn\u00e9es deviennent complexes. Innovez plus rapidement sur Databricks Lakehouse Platform - une approche simple et rentable des donn\u00e9es, de l'analyse et de l'IA qui rend plus productifs des milliers d'entreprises et de startups natives du monde num\u00e9rique.Innovez avec la flexibilit\u00e9 de l'open source\nUtilisez vos donn\u00e9es partout et comme vous le souhaitez, sans d\u00e9pendre d'un fournisseur. Les d\u00e9veloppeurs d'Apache Spark\u2122 ont cr\u00e9\u00e9 un lakehouse reposant sur des formats ouverts et des API.\nD\u00e9couvrir les projets open sourceCr\u00e9ez des charges de donn\u00e9es \u00e9volutives\nB\u00e9n\u00e9ficiez de performances fiables et ultra-rapides sur les charges ETL \u2013 autant en streaming qu'en batch \u2013 et laissez Databricks g\u00e9rer votre infrastructure.\nD\u00e9couvrir le Data EngineeringAcc\u00e9dez rapidement aux insights contenus dans les donn\u00e9es\nIng\u00e9rez, transformez et interrogez toutes vos donn\u00e9es au m\u00eame endroit. Arr\u00eatez de g\u00e9rer des serveurs. \u00c9voluez en fonction de vos besoins avec le serverless. Rapport performance\u00a0\/\u00a0prix 12 fois sup\u00e9rieur\nD\u00e9couvrir Databricks SQLD\u00e9veloppez des applications de nouvelle g\u00e9n\u00e9ration avec le ML\nAcc\u00e9l\u00e9rez le cycle de vie du ML, de l'exp\u00e9rimentation \u00e0 la production. Optimisez votre productivit\u00e9 avec des outils comme les notebooks collaboratifs, MLflow et MLOps.\nD\u00e9couvrir les capacit\u00e9s MLD\u00e9marrer avec DatabricksEssayer Databricks\nCommencez votre essai gratuit de 14 jours avec Databricks sur AWS en quelques \u00e9tapes. Acc\u00e9dez \u00e0 des ressources pour toute votre \u00e9quipe de donn\u00e9es.\nEssayer gratuitementD\u00e9veloppez vos comp\u00e9tences\nB\u00e9n\u00e9ficiez de formations et de certifications adapt\u00e9es \u00e0 vos besoins dans de multiples domaines\u00a0: analytique de donn\u00e9es, data engineering, data science et machine learning.\nObtenir une formationOptimisez les co\u00fbts\nR\u00e9duisez les co\u00fbts d\u2019infrastructure jusqu\u2019\u00e0 40\u00a0% et gagnez en productivit\u00e9 avec un service g\u00e9r\u00e9. Explorez nos plans de facturation \u00e0 la consommation et nos offres de remises.\nD\u00e9couvrir la tarificationAssistance technique\nObtenez plus rapidement des r\u00e9ponses en faisant appel \u00e0 nos experts Databricks. Vous pourrez d\u00e9velopper rapidement votre solution de donn\u00e9es avec nos notebooks en libre-service.\nD\u00e9couvrir les notebooksProgrammes int\u00e9gr\u00e9sConstruisez vos applications bas\u00e9es sur les donn\u00e9es sur le lac et acc\u00e9l\u00e9rez la croissance de votre entreprise avec Databricks.Databricks pour les start-upsD\u00e9marrez rapidement avec le programme de d\u00e9marrage. D\u00e9couvrez comment obtenir des cr\u00e9dits gratuits, des conseils d'experts et un accompagnement pour acc\u00e9der au march\u00e9.En savoir plusPartenaires int\u00e9gr\u00e9s\u00a0Devenez un partenaire int\u00e9gr\u00e9 et acc\u00e9dez \u00e0 des avantages techniques, de mise sur le march\u00e9 et de co-marketing qui vous aideront \u00e0 \u00e9tendre votre port\u00e9e et \u00e0 d\u00e9velopper votre activit\u00e9.En savoir plusDes entreprises de nouvelle g\u00e9n\u00e9ration s'appuie sur DatabricksArchitectures de solutions pour les entreprises digital-nativesPipelines ETL hautes performances et \u00e9volutifsCr\u00e9ez une plateforme ETL et data engineering de bout en bout\u00a0: vous serez alors libre d'extraire de pr\u00e9cieux insights de tous vos clouds. Vous n'aurez plus \u00e0 cr\u00e9er et maintenir des pipelines ou \u00e0 ex\u00e9cuter des charges ETL.Appuyez-vous sur des outils ax\u00e9s sur la production, comme Delta Live Tables, Unity Catalog et Workflows.Profitez d'une int\u00e9gration Git robuste, d'outils d'orchestration et de contr\u00f4les de qualit\u00e9 des donn\u00e9es.Unifiez les op\u00e9rations en batch et en streaming sur une architecture simplifi\u00e9e, et rationalisez le d\u00e9veloppement et le test des pipelines de donn\u00e9es.Assurez la qualit\u00e9 et optimisez le saut des donn\u00e9es avec Delta Lake, un protocole de fichiers open source utilisable par Apache Spark, Trino, Presto, Flink et bien d'autres.D\u00e9marrerAnalytique SQL et entreposage des donn\u00e9esImportez, transformez et interrogez toutes vos donn\u00e9es au m\u00eame endroit pour d\u00e9livrer des insights m\u00e9tier en temps r\u00e9el.Ex\u00e9cutez toutes vos applications SQL et BI \u00e0 grande \u00e9chelle, en b\u00e9n\u00e9ficiant d'un rapport performance\u00a0\/\u00a0prix jusqu'\u00e0 12\u00a0fois sup\u00e9rieur. Assurez la gouvernance et la s\u00e9curit\u00e9 des donn\u00e9es.G\u00e9rez la high concurrency gr\u00e2ce \u00e0 un \u00e9quilibrage des charges enti\u00e8rement manag\u00e9 et \u00e0 l'\u00e9volutivit\u00e9 des ressources de calcul.Utilisez des formats ouverts et des API, ainsi que vos outils habituels d'ingestion, de transformation et de BI gr\u00e2ce \u00e0 des connecteurs personnalis\u00e9s.R\u00e9duisez l'effort de gestion des ressources gr\u00e2ce au calcul serverless.D\u00e9marrerMachine learning innovantAm\u00e9liorez la productivit\u00e9 et la collaboration au sein du lakehouse et acc\u00e9l\u00e9rez vos projets de ML et de data science.Profitez d'outils et d'options de collaboration avec l'approche transparente du machine learning automatis\u00e9.Pr\u00e9parez, traitez et g\u00e9rez les donn\u00e9es, les fonctionnalit\u00e9s et les mod\u00e8les avec la simplicit\u00e9 du libre-service gr\u00e2ce au Magasin de fonctionnalit\u00e9s h\u00e9berg\u00e9.Harmonisez le cycle de vie ML, de l'exp\u00e9rimentation \u00e0 la production, avec MLflow, et suivez l'\u00e9volution des param\u00e8tres, des m\u00e9triques et des it\u00e9rations des mod\u00e8les au fil du temps.D\u00e9ployez des mod\u00e8les en batch ou en serverless, via des points de terminaison REST en temps r\u00e9el.D\u00e9marrerPartenaires technologiques\nD\u00e9couvrez et int\u00e9grez directement vos outils et services de donn\u00e9es et d\u2019IA pr\u00e9f\u00e9r\u00e9s depuis la plateforme Databricks\nD\u00e9couvrir Partner ConnectSolutions pour l'industrieLes leaders de la nouvelle g\u00e9n\u00e9ration d\u00e9veloppent leurs solutions d'analytique des donn\u00e9es et d'IA avec DatabricksD\u00e9couvrir les solutions par secteur d'activit\u00e9Vente au d\u00e9tail et biens de consommation\nPrenez des d\u00e9cisions en temps r\u00e9el et optimisez l\u2019exp\u00e9rience client.\nEn savoir plusServices financiers\nPr\u00e9parez l'avenir de vos services financiers ax\u00e9s sur les donn\u00e9es et l'IA.\nEn savoir plusJeux vid\u00e9os\nMisez sur la puissance des donn\u00e9es et de l\u2019IA pour r\u00e9v\u00e9ler des exp\u00e9riences de jeu hors normes.\nEn savoir plusCommunications, m\u00e9dias et divertissement\u00a0\nCr\u00e9ez des contenus ax\u00e9s sur les donn\u00e9es et l'IA pour inventer un niveau sup\u00e9rieur d'exp\u00e9rience utilisateur.\nEn savoir plusTechnologie et solutions\nD\u00e9veloppez des solutions nouvelle g\u00e9n\u00e9ration avec des fonctionnalit\u00e9s avanc\u00e9es de donn\u00e9es et de ML.\nEn savoir plusTechnologies de la sant\u00e9\nOffrez de meilleurs r\u00e9sultats aux patients gr\u00e2ce aux donn\u00e9es et \u00e0 l'IA.\nEn savoir plusGuide techniqueR\u00e9soudre les probl\u00e8mes courants li\u00e9s aux donn\u00e9esPour les startups et les entreprises natives du num\u00e9riqueD\u00e9couvrez comment prendre en charge les cas d'utilisation des donn\u00e9es au fur et \u00e0 mesure que vous \u00e9voluez, tout en am\u00e9liorant la rentabilit\u00e9 et la productivit\u00e9. Vous b\u00e9n\u00e9ficierez de diagrammes d'architecture, de solutions \u00e9tape par \u00e9tape et de guides de d\u00e9marrage rapide. Vous trouverez \u00e9galement des cas d'utilisation r\u00e9els d'entreprises de premier plan telles que Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable et Zipline.Recevez un exemplaireRessourcesEbooksQu'est-ce qu'un lakehouse\u00a0?Le Grand Livre du Data EngineeringLe Grand livre sur les cas d'usage Machine LearningLe guide complet du Delta LakeDelta Lake\u00a0: la fondation de votre LakehouseLe Grand Livre des MLOpsGuide de l'\u00e9quipe de donn\u00e9es sur la plateforme Databricks LakehouseGuides de d\u00e9marrage rapideEx\u00e9cutez des charges ETLPipelines de donn\u00e9es avec les Delta Live TablesGuide SQL\u00a0: requ\u00eates et tableaux de bordGuide de la data scienceGuide du machine learningBlogsAnnoncesOpen SourceTendances sectoriellesSolutionsPr\u00eat \u00e0 vous lancer\u00a0?Obtenir un essai gratuitProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vika-smilansky","text":"Vika Smilansky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVika SmilanskyDirector of Product Marketing at ThoughtSpotBack to speakersVika is a Director of Product Marketing at ThoughtSpot, leading customer marketing as well as messaging and positioning for ThoughtSpot\u2019s embedded analytics platform, ThoughtSpot Everywhere. Before joining Thoughtspot in 2019, she worked in Product Marketing on data integration solutions at Oracle. Vika holds a Master in Communication Management from the University of Southern California.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paula-martinez","text":"Paula Martinez - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaula MartinezCEO & Cofounder at MarvikBack to speakersPaula Mart\u00ednez cofounded Marvik, a machine learning consulting and development company that specializes in Computer Vision, Predictive Analytics and Natural Language Processing. Paula is an Electrical Engineer and holds a Master in technological business management. She was selected as a Google Developer Expert in machine learning and co-organizes machine learning meetups. She has also completed programs at MIT and Berkeley among others.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hao-zhu\/#","text":"Hao Zhu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHao ZhuSenior Manager at NVIDIABack to speakersHao Zhu is senior manager, accelerated Spark applications at NVIDIA. Hao and his team mainly cover customer engagement and application development for RAPIDS Accelerator for Apache Spark. Hao is experienced in Hadoop, database, massively parallel processing query engines, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabien-cochet\/#","text":"Fabien Cochet - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabien CochetIT Expert on Data and Analytics at MichelinBack to speakersWorking at Michelin for a decade, mainly around data. Inspiring and helping others and transforming our ways of doing all the things that drive Fabien Cochet every day. He likes racking his brains and thinking out of the box, especially about the solutions we design. Fabien is always curious and willing to explore new approaches and technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speakers\/#","text":"Speakers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpeakersBrowse the roster to find new and familiar faces alike. The Data + AI Summit draws experts from all over the globe across a wide array of fields.\nFeatured speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAll speakersAayush PatelData & Platform EngineerSkywatchAbhishek PatelHead of Databricks COELTIMindtreeAdam WilsonCo-Founder, Chief of ProductDivirod, Inc.Adi PolakData & AI TechnologistTechnologistAdriana IspasStaff Product ManagerDatabricksAikaterini KalouPrincipal Data ScientistCitrixAjali SenSenior ManagerAccentureAjmal AzizSolutions ArchitectDatabricksAkira AjisakaSenior Software Development EngineerAmazon Web ServicesAlain BrianconVP Data Science Profiles by KantarKantar GroupAlbert HuSenior Analytics EngineerRec RoomAlessandro GaravagliaLead ML EngineerGucciAlexander BoothAssistant Director of Research & DevelopmentTexas Rangers Baseball Club, LLCAlexander VanadioPrincipal ConsultantOptivAli GhodsiCo-founder and CEODatabricksAlon GubkinCo-Founder & CTOAporiaAman KapoorHead of Data PlatformPetronasAmanda MilbergSenior Partner Sales EngineerDataikuAmine BenhamzaLead Solutions ArchitectDatabricksAmir SkovronikDistinguished Software EngineerAkamaiAmrinder Singh OberaiEMR Migrations LeadDatabricksAnanya GhoshBusiness Application Owner for DatabricksNationwide InsuranceAndrew BlanceInnovation ConsultantWaterstonsAndria FuquenTechnical Program ManagerImmutaAndy HanksSenior Data Architect, Analytics PlatformCRISP Shared ServicesAnfisa KaydakVP, Data Product & EngineeringHealthverityAngela ChuSenior Solution ArchitectDatabricksAnil PuliyerilSenior ArchitectHabuAnindita MahapatraLead Solutions ArchitectDatabricksAnindya SahaML Platform Software EngineerAnkit MathurTech Lead, Model Serving GPUsDatabricksAnna RussoGlobal Director of Data ScienceGucciAnton OkolnychyiSoftware EngineerAppleAntoni BaumSoftware EngineerAnyscaleAntonio CasteloCollibraAnup SeguCo-Head of Data EngineeringYipitDataArtem MeshcheryakovConsultantORAYLIS GmbHArthur LiSenior Software EngineerInstacartArujit PradhanSoftware EngineerCoinbaseArun PamulapatiSr. Staff Security Field EngineerDatabricksAshwin GangadharSenior Solutions ArchitectMongoDBAtiyah CurmallyPrincipal Environmental SpecialistInternational Finance CorporationAustin FordStaff Product ManagerDatabricksAvinash SooriyarachchiSenior Solutions ArchitectDatabricksBalaji RamanujamAVP - Senior Principal Technology ArchitectInfosysBasak EskiliML EngineerAhold DelhaizeBehzad BordbarLead Data ScientistMarks & SpencerBeinan WangSenior Staff Software EngineerAlluxioBen CoppersmithSr. Manager, Data PlatformDisney StreamingBen WilsonPrincipal Specialist Solutions ArchitectDatabricksBeth MattsonSenior Data EngineerOur Family WizardBin MuVice President and Head of Data & AnalyticsAdobeBinwei Yangsoftware engineerintelBlaise SandwidiLead Data Scientist, As. ESG Officer, PhDInternational Finance Corporation (IFC)\u2013World Bank GroupBob ZhangSenior Technical Program ManagerMicrosoftBrad CorwinChief Data ScientistBooz Allen HamiltonBradley AxenMachine Learning EngineerBlockBrendan BarsnessData and Analytics ArchitectDeloitteBrooke WenigDirector, Machine Learning PracticeDatabricksCan ElfeogluStaff Product ManagerDatabricksCelia KungEngineering ManagerDatabricksChang SheCEOLanceDBChao SunSoftware EngineerAppleChen GuoStaff Software EngineerCoinbaseChris StevensSenior Staff Software EngineerDatabricksChris VoLead Member of Tech StaffAT&TChris InkpenSolutions architectHoneywellChris HechtDatabricksChris MantzData ArchitectSlalomChristian Acu\u00f1aSenior Data EngineerGrammarlyChristian HamiltonDirector, Data Science Technology84.51Christina TaylorData EngineerToptalChristina TaylorSenior Staff Data EngineerCatalyst SoftwareChristopher LocklinEngineer Manager, Data PlatformGrammarlyChunxu TangResearch ScientistAlluxioCody FergusonData & AI Management Branch ChiefChief Digital and Artificial Intelligence Office - AdvanaCorey ZumarSoftware EngineerDatabricksCorey ZwartChief Technology OfficerPumpJack DataworksCort LunkeData & Analytics Lead - TruterraLand O'LakesCraig WileySr. Director of Product, Lakehouse AIDatabricksCyrielle SimeonePrincipal Product Marketing ManagerDatabricksDael WilliamsonField CTODatabricksDan HoustonManager, Data Science and Exploration Advanced AnalyticsUSPSDan SmithHead of Technology Data & AnalyticsPerenti GroupDanica FineSenior Developer AdvocateConfluentDaniel TenedorioSr. Staff Software EngineerDatabricksDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL)MITDarshana SivakumarStaff Product ManagerDatabricksDarth VaderSith LordThe Galactic EmpireDatin Ts. Habsah Binti NordinChief Data OfficerPETRONASDavid SkinnerChief Strategy OfficerAcxiomDavid TempelmanResident Solutions ArchitectDatabricksDawn SongProfessor, Department of Electrical Engineering and Computer ScienceUC BerkeleyDeepa ParanjpeDirector of EngineeringDiscoveryDeepak SekarSr. Solution ArchitectDatabricksDenny LeeSr. Staff Developer AdvocateDatabricksDerek SlagerCTOAmperityDerek SugdenAd Measurement Lead \u2013 Measurement & AttributionEffectvDevlina DasSenior Software EngineerInstacartDeylo WooData Engineer ArchitectProvidence Health ServicesDilip BiswalSenior ArchitectAdobeDillon BostwickSolutions ArchitectDatabricksDipankar MazumdarDeveloper AdvocateDremioDon ScottVP, New Product DevelopmentHitachi Solutions AmericaDon Bosco DuraiCofounder and CTOPrivaceraDonghwa KimSr. Director of IT ArchitectureOntada, a McKesson CompanyDouglas MooreLead Specialist Solutions ArchitectDatabricksDurga KalaSr. DirectorVisa Inc.Egor GryaznovCTO and Co-founderBigeyeEllen SulcsDirector, Data Products & EngineeringT-MobileEllie HajarianSnr IT ManagerTD BankElliot ShmuklerCo-Founder & CEOAnomaloEmad MostaqueCEOstability.aiEric PeterSr Staff Product ManagerDatabricksEric SchmidtFormer CEO and Chairman, Google; Co-FounderSchmidt FuturesErika EhrliSenior Director of Product MarketingDatabricksErin BoelkensVP of ProductLiveRampErni DurdevicSpecialist Solutions Architect (Geospatial)DatabricksFabian JakobsSr Staff Software EngineerDatabricksFabien CochetIT Expert on Data and AnalyticsMichelinFabio Luis Correia da SilvaArchitecture SpecialistBradescoFaraz YasrobiSoftware EngineerGrammarlyFrancisco RiusHead of Data Science and Data EngineeringMinecraft at MicrosoftFranco PatanoProduct SpecialistDatabricksFrank MunzPrincipal Technical Marketing EngineerDatabricksGanesh DeivarayanSr ManagerAmerican AirlinesGaurav SarafProduct ManagerDatabricksGavita RegunathPrincipal Data ScientistAdvancing AnalyticsGeoffrey FreemanSolutions ArchitectT-MobileGidon GershinskyLead Systems ArchitectAppleGilad AsulinBig Data Engineer Team LeaderAkamai Technologies, IncGreg NelsonVP of Data OperationsHighmark HealthGreg KroleskiProduct ManagementDatabricksGregory LittleDCDAO for Enterprise Platforms and Business OptimizationDoD CFO Transformation OfficeHannes M\u00fchleisenCo-Founder and CEODuckDB LabsHao ZhuSenior ManagerNVIDIAHari ShankarSenior Director, R&DVizioHari RajaramSr Director \/ Principal Data ArchitectProcoreHarrison ChaseCEOLangChainHarsh MishraLead Enterprise ArchitectAustralian Rail Track CorporationHeiko UdluftChief Technology OfficerDivirod, Inc.Himanshu AroraResident Solutions ArchitectDatabricksHimanshu RajaDatabricksHitesh SahniHead of Cloud Data Platforms and Data Engineering SolutionsDeutsche Post DHLHolly SmithSenior Resident Solutions ArchitectDatabricksHuaxin GaoSoftware EngineerAppleHyukjin KwonStaff Software EngineerDatabricksIan SotnekDirector of ProductAI Squared, IncIan GallowaySenior Director, ApplicationsCollins AerospaceIfigeneia DerekliField Engineering Manager & Unity Catalog SpecialistDatabricksIoannis PapadopoulosCloud TechnologistDatabricksItai YaffeSenior Big Data ArchitectAkamaiIvan PengSoftware EngineerDoorDashJacek LaskowskiIT Freelancerjapila.plJackie BrosamerDirector of Software EngineeringBlockJacob RennChief TechnologistAI Squared, IncJacolon WalkerCo-founder & CTOMonadJaison DominicSenior Manager Information SystemsAmgenJames DemmelDr. Richard Carl Dehmel Distinguished ProfessorUniversity of California, BerkeleyJames NormanPrincipal Software EngineerNikeJamie BakerDirector of ProductMatillionJason ShiverickData Platform ManagerRivianJay BhankhariaSenior Director, Data PartnershipsDatabricksJay YangPrincipal Data EngineerProcoreJeff Breeding-AllisonSenior Data ScientistMars PetcareJeff MrozTechnical SME for Cloud and Big DataWoolpert \/ US Army Corps of EngineersJeffrey HessLead TechnologistBooz Allen HamiltonJeffrey ParkinsonVP, Core Data EngineeringNorthwestern MutualJeffrey ChouCo-Founder, CEOSync ComputingJegadeesan PugazhenthiLead Big Data EngineerAT&TJeremy LewallenProduct ManagerDatabricksJiajun YaoSoftware EngineerAnyscaleJim HibbardSenior Developer AdvocateDatabricksJim ThorstadSolutions ArchitectDatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchUniversity of California at BerkeleyJoanna GurryExecutive, Data DeliveryNational Australia Bank (NAB)Joe WalshDirector of Measurement & AttributionEffectvJohn RousselCIOCalifornia Department of Public Health (CDPH)John ThompsonGlobal Head, Artificial IntelligenceEYJohn KutayDirector of Product ManagementStriimJon OsbornField CTOAscend.ioJonathan KellerSr. Director, Product ManagementDatabricksJonathan HollanderVP, Enterprise Data Technology PlatformsTD BankJonathan NeoData EngineerCanvaJordan PeckPrincipal Technical Account ManagerSnowplowJordan DonmoyerManager, Customer Data SolutionsThe Hershey CompanyJoseph SarsfieldMachine Learning EngineerMarks & SpencerJoseph BradleyLead Product SpecialistDatabricksJules DamjiLead Developer AdvocateAnyscaleJulie FerrisVice President, Commercial OptimizationDefinitive HealthcareJulien Le DemChief ArchitectAstronomerJun Rong LauData Engineer\/AnalystGrabTaxi Holding Pte LtdJunta NakaiRVP, Industry Solutions, Financial Services and SustainabilityDatabricksJustin BreeseSr. Product ManagerDatabricksJustin DeBrabantSVP of ProductActionIQJustin LaiDistinguished Data ArchitectBlackBerryJustin ThompsonDirector, IT Data and AnalyticsJetBlueKarthik RamasamyHead of StreamingDatabricksKasey UhlenhuthStaff Product ManagerDatabricksKeith AndersonSolution PrincipalHitachi SolutionsKeshav SanthanamPhD StudentStanford UniversityKetan GanatraSolution ArchitectDatabricksKieran TaylorSenior Software Engineer IIInstacartKrishti BikalSenior Executive - Director BI & AnalyticsEmeraldKyle HaleProduct SpecialistDatabricksKylie TaylorData ScientistMars PetcareLakhan PrajapatiDirector of Architecture and EngineeringZS associatesLarry FeinsmithHead of Global Tech Strategy, Innovation and PartnershipsJP Morgan Chase & Co.Lee YangSr. Principal SW EngineerNVIDIALeena DalviAssistant Vice President, Enterprise Data & AnalyticsNavy Federal Credit UnionLeo DuncanSr. Solutions ArchitectKyvos Insights Inc.Leon EllerSolutions ArchitectDatabricksLewis MbaeHead of Customer EngineeringRudderStackLin QiaoCo-creator of PyTorch, Co-founder and CEOFireworksLindsay MicoHead of Data ScienceProvidence HealthLindsey WoodlandExecutive Vice President, Client Data Science605Lior GavishCTO and Co-founderMonte Carlo DataLiping HuangSenior Solutions ArchitectDatabricksLorenzo De TomasiData Architect, Data Platforms Lead at BarillaBarilla G. e R. Fratelli S.p.A.Lucas dos Santos CelestinoPlatform Product ManagerAB InbevLuk VerhelstData ArchitectVolvo Group (consultant)Luyang WangLead Distinguished ScientistVerizonMacGregor WinegardAssociate Data EngineerKPMGMaciej SzpakowskiCo-founderProphecyMadalina TanasieChief Technology OfficerCollibraMaggie DavisPrincipal, Data EngineeringSlalomMahesh PrakriyaDirector in Intelligence PlatformMicrosoftMalav ShahSenior Data ScientistDIRECTVManbir PaulVP of Engineering, Data Insights and MarTechSephoraMani KandasamyTech FellowDeloitte Consulting LLPManu SharmaCEOLabelboxMarcel KramerHead of Data EngineeringABN AMRO Bank N.VMaria VechtomovaML EngineerAhold DelhaizeMaria DaibertData Platform Product ManagerAB InbevMarianna CervinoGlobal Data ScientistGucciMarius PangaSolutions ArchitectDatabricksMark LeeSenior Specialist Solutions ArchitectDatabricksMark D'AndreaGlobal Chief Revenue OfficerAccuweatherMartin GrundSenior Staff Software EngineerDatabricksMat KeepSenior Director, MongoDB Products TeamMongoDBMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflowDatabricksMatt McKenzieGM, TechnologyTabcorpMatteo QuattrocchiDirector, Policy-EMEABSAMatthew HayesVice President of SAP BusinessQlikMatthew PowersDeveloper AdvocateDatabricksMatthew HayesSoftware EngineerDatabricksMatthew DoxeySenior EpidemiologistWashington State Department of HealthMatthew KarasickChief Product OfficerHabuMaxime AgostiniCEOSarus Technologies IncMeena RamSr Director, Enterprise Data and Records Management OfficeCIBCMegan FogalSolutions ArchitectDatabricksMenglei SunSenior Software EngineerDatabricksMiao WangSenior Engineering ManagerAdobeMichael ShtelmaLead Specialist Solutions ArchitectDatabricksMichael ArmbrustDistinguished EngineerDatabricksMichael GreenSenior Data ScientistHitachi Solutions AmericaMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious DiseasesCalifornia Department of Public Health (CDPH)Michael SankyRVP, Industry Solutions, Healthcare and Life SciencesDatabricksMike ConoverSoftware EngineerDatabricksMike TangAssociate Director, Responsible AIVerizonMike Del BalsoCo-founder + CEOTectonMilos ColicTech Lead EMEA Public Sector - Sr. Solutions ArchitectDatabricksMiranda LunaProduct ManagementDatabricksMitch ErtlePartner Solutions EngineerSigma ComputingMohan KolliIT DirectorLabCorpMorgan HsuDirector, Data and ML EngineeringFanDuelMostafa MokhtarPrincipal Software EngineerDatabricksMurali MadireddiArchitectAccentureNabil RaadSVP of Data and AnalyticsGM FinancialNadine FarahHead of Dev RelOnehouseNaresh YegireddiStaff Data EngineerIndigo AGNat FriedmanCreator of Copilot; Former CEOGithubNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North AmericaHitachi Solutions America Ltd.Naveen ZutshiChief Information OfficerDatabricksNeil PatelLead Specialist Solutions ArchitectDatabricksNic JansmaSenior Principal Lead EngineerAkamaiNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, TechnologyGlaxoSmithKlineNick KingFounder & CEOData KineticNicolas PelaezTechnical MarketingDatabricksNihar ShethSenior Product ManagerAWS - AmazonNitu NiveditaManaging DirectorAccentureNoam BresslerML Team LeadDeepchecksNoritaka SekiyamaPrincipal Big Data ArchitectAmazon Web ServicesOliver DykstraData EngineerTexas RangersOnik KurktchianHead of S&P Global Marketplace WorkbenchS&P GLOBALOri ZoharPrincipal Product Marketing ManagerDatabricksOz KatzCTO @ Treeverse, co-creator of lakeFSTreeverse LTDPakshal Kumar H DhelariaSenior Software Engineer 1CitrixPamela PettitSolutions ArchitectDatabricksParth ChandraSoftware EngineerApplePascal van BellenSenior ConsultantORAYLIS GmbHPatrick HallPrincipal Scientist | Visiting FacultyBNH.AI | GWUPaul RoomeStaff Product ManagerDatabricksPaul MracekSenior Solutions ArchitectDatabricksPaul WellmanVP, Executive Product Owner, Data-as-a-ServiceTD BankPaul MarshSenior Director Application DevelopmentNew York JetsPaula MartinezCEO & CofounderMarvikPearl UbaruSr. Technical Marketing EngineerDatabricksPedro BoaretoChapter Leader of Analytics EngineeringBradescoPercy LiangProfessor of Computer ScienceStanfordPhilippe LeonhartDigital Transformer, Corporate Business ServicesMichelinPieter NoordhuisSr. Staff Software EngineerDatabricksPouya Barrach-YousefiData Pro and Director Strategic AccountsProphecyPrashanth BabuLead Product SpecialistDatabricksPrateek ChawlaFounding EngineerMonte CarloPraveen VemulapalliDirector- TechnologyAT&TPravin DarbareVice President of Data AnalyticsWorkdayPritesh PatelPublic Sector Leader, UK&IDatabricksPulkit ChadhaSr. Solutions ArchitectDatabricksRafael BarcelosSoftware ArchitectMicrosoft CorporationRafi KurlansikLead Solutions ArchitectDatabricksRaghu JayachandranSenior Manager Enterprise DataRaceTrac Inc.Rahil BhatnagarDevelopment Lead, LOLAAnheuser BuschRahul PandeySolution ArchitectadidasRajesh IyerVice President Financial Services Insights & DataCapgeminiRakesh KumarStaff Software EngineerLyft IncRakesh SinghLead ArchitectABN AMRO Bank N.VRashmi KansakarDirector, Data & Cloud Architect84.51Rekha BachwaniEngineering Director, ML EngineeringThe Walt Disney CompanyReynold XinCo-founder and Chief ArchitectDatabricksRicardo PortillaPrincipal Solution ArchitectDatabricksRisha RavindranathSr Manager, Data GovernanceComcast AdvertisingRob SakerGlobal VP, Retail and ManufacturingDatabricksRobin SutaraField CTODatabricksRobinson CreightonPrincipal Analyst, Enterprise Data OpsComcast AdvertisingRodrigo BeceiroCTO & CofounderMarvikRoger DunnCo-founder, CTOExponamRoie Schwaber-CohenStaff Developer AdvocatePineconeRomit JadhwaniSr. Director, Data Analytics, Engineering and IntegrationsDatabricksRong MaSoftware EngineerintelRuifeng ZhengSenior Software EngineerDatabricksRyan BoydCo-founderMotherDuckRyan HarrisPrincipal Cybersecurity EngineerHSBCRyan JohnsonSenior Staff EngineerDatabricksSaad AnsariSenior Staff Product ManagerDatabricksSachin Balgonda PatilSolutions ArchitectDatabricksSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSamrat RaySenior Staff Product ManagerDatabricksSanjeev KumarVice President, Data Analytics and AIGainwell TechnologiesSanket AminSenior Manager of CAS Data Science and AnalyticsCollins AerospaceSarah PollittGroup Product ManagerMatillionSatish GarlaSr Solutions ArchitectDatabricksSatya NadellaChairman and CEOMicrosoft, Live Virtual GuestScott MeierDirector, Data Analytics Service, Financial Services CenterU.S. Department of Veterans AffairsScott StarbirdGeneral Counsel, Public Affairs and Strategic PartnershipsDatabricksScott BellPrincipal Consultant and Databricks SMERapidDataScott CastleChief Strategy OfficerSisenseSean KnappFounder & CEOAscend.ioSean OwenPrincipal Product SpecialistDatabricksSeth BabcockHead of Connected Aviation Tech Ops Solutions and AnalyticsCollins AerospaceShasidhar ErantiSpecialist Solutions ArchitectDatabricksShawn GilleranPrincipal Cloud Solutions LeadLiveRampShawn BenjaminData and Business Intelligence ChiefU.S. Department of Homeland Security - USCISShir ChorevCTODeepchecksShiv TrisalGTM Director, Manufacturing & EnergyDatabricksSiddharth BhaiSr. Manager, Product ManagementDatabricksSidharth KunnathPrincipal ArchitectAmerican Airlines, IncSimon WhiteleyCTOAdvancing AnalyticsSirui SunDatabricksSlava FridCTOWorldQuant PredictiveSneh KakiletiVice President, Product ManagementZoomInfoSpencer CookSenior Solutions Architect - Financial ServicesDatabricksSreekanth RatakondaPrincipal Solutions ArchitectLabcorpSridhar DevarapalliSenior Director, Product ManagementDatabricksSrinivasa KanamathaSenior ManagerBlackBerryStan LinSenior Software EngineerMicrosoft CorporationStefania LeoneSr. Manager Product ManagementDatabricksStephen SheltonVice President, Business IntelligencePluto TVSteve MahoneySr Manager, Product ManagementDatabricksSteve SobelGlobal Lead - Communications, Media & EntertainmentDatabricksSteven YuPrincipal Solutions ArchitectDatabricksSumesh NairDirector of Engineering, Data and Cloud StrategyOptum, United HealthGroupSuneel KonidalaSr. ManagerAccentureSunil RanganathanDirector, MLOPsTredenceSuresh MatlapudiLead Solutions Architect and Specialist SME, MigrationsDatabricksSurya TuragaSr. Solutions ArchitectDatabricksSuze HowseHead of Enterprise DataMarks and SpencerTanmay KumarSenior ManagerDeloitte Consulting LLPTathagata DasDatabricksTaylor HosbachData ScientistDIRECTVTeja TangedaPrincipal Data EngineerAmerican AirlinesTEST BecknerTESTTESTTest1 TestCFP1102testThet KoPrincipal Data EngineerSEEKThomas La PianaSenior Software EngineerEthycaThomas RoachSr. Solutions ArchitectDatabricksThorsten JacobsSr. Solutions ArchitectDatabricksTianyu LiuLead Data Scientist (Analytics)GrabTimothy AhrensMessaging Design Division ChiefDepartment of StateTodd GreensteinProduct ManagerDatabricksTomer PatelSoftware Engineering ManagerAkamai TechnologiesTony WangPhD studentStanfordUri MayHuntersVadivel SelvarajStaff Software EngineerRivianVarun SharmaPrincipal Data EngineerVisa Inc.Vicky AndonovaManager, Applied Machine LearningAnomaloVika SmilanskyDirector of Product MarketingThoughtSpotVikas Reddy AravabhumiStaff Backline EngineerDatabricksVincent ChenDirect of Product \/ Founding EngineerSnorkel AIVinit DoshiSenior ManagerTredenceVinod MarurSVP of EngineeringDatabricksVolker TjadenManager Solution ArchitectsDatabricksVuong NguyenSenior Solutions ArchitectDatabricksWassym BensaidSr. Vice President, Software DevelopmentRivianWeston HutchinsProduct ManagerDatabricksWill GirtenSr. Specialist Solutions ArchitectDatabricksWilliam ZanineHead of Data Management, Channel and Specialty North AmericaIQVIAWilly LulciucSr. Software EngineerAstronomerXiao LiSenior Engineering ManagerDatabricksXuefu WangSr. Data ScientistThe Trade DeskYali SassoonCPOSnowplowYang YouPresidential Young ProfessorNational University of SingaporeYaniv KundaSenior Software ArchitectAkamaiYaron SingerCEO & Co-FounderRobust IntelligenceYeshwanth VijayakumarSr Engineering Manager\/ArchitectAdobeYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and TechnologyU.S. ArmyYuki SaitoTechnical EvangelistNTT DATA CorporationZachary BannorData Engineering ManagerCond\u00e9 NastZachary HuangPhDColumbia UniversityZaheera ValaniSenior Director of EngineeringDatabricksZeashan PappaSenior Product Specialist - Data GovernanceDatabricksZoe DurandSenior Product ManagerDatabricksSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mark-dandrea\/#","text":"Mark D'Andrea - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMark D'AndreaGlobal Chief Revenue Officer at AccuweatherBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/miranda-luna\/#","text":"Miranda Luna - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMiranda LunaProduct Management at DatabricksBack to speakersMiranda focuses on making all aspects of the Databricks SQL experience delightful. She resides in Seattle where outside of work she can usually be found skiing or golfing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/siddharth-bhai\/#","text":"Siddharth Bhai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSiddharth BhaiSr. Manager, Product Management at DatabricksBack to speakersSiddharth Bhai is a product management leader at Databricks, with 15+ years of experience, including long stints at Google and Microsoft. He has deep experience in identity, security, provisioning, and cloud computing. He has spoken at major industry conferences, including Hybrid Identity Protection, Directory Experts Conference, Microsoft TechEd, and Google Cloud Next. This summer, he\u2019s interested in hearing about how teams in the real world are using Databricks. Come say hi if you see him!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/workflows","text":"Databricks Workflows | Workflow Authoring, Deep Platform IntegrationSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWorkflowsReliable orchestration for data, analytics and AITry for freeWhat is Databricks Workflows?The fully managed lakehouse orchestration service for all your teams to build reliable data, analytics and AI workflows on any cloud.Orchestrate any combination of notebooks, SQL, Spark, ML models and dbt as a\u00a0Jobs\u00a0workflow, including calls to other systems. Build ETL pipelines that are automatically managed, including ingestion and lineage, using\u00a0Delta Live Tables. Databricks Workflows is available on GCP, AWS and Azure, giving you full flexibility and cloud independence.Orchestrate anything anywhereRun diverse workloads for the full data and AI lifecycle on any cloud. Orchestrate\u00a0Delta Live Tables\u00a0and\u00a0Jobs\u00a0for SQL, Spark, notebooks, dbt, ML models and more.Simple workflow authoringAn easy point-and-click authoring experience for all your data teams, not just those with specialized skills.Deep platform integrationDesigned and built into the Databricks Lakehouse Platform giving you deep monitoring capabilities and centralized observability across all your workflows.Proven reliabilityHave full confidence in your workflows leveraging our proven experience running tens of millions of production workloads daily across AWS, Azure and GCP.Fully managedRemove operational overhead with a fully managed orchestration service, so you can focus on your workflows not on managing your infrastructure.\u201cDatabricks Workflows allows our analysts to easily create, run, monitor and repair data pipelines without managing any infrastructure. This enables them to have full autonomy in designing and improving ETL processes that produce must-have insights for our clients. We are excited to move our Airflow pipelines over to Databricks Workflows.\u201d\u2014 Anup Segu, Senior Software Engineer, YipitData\u201cDatabricks Workflows freed up our time dealing with the logistics of running routine workflows. With newly implemented repair\/rerun capabilities, it helped to cut down our workflow cycle time by continuing the job runs after code fixes without having to rerun the other completed steps before the fix. Combined with ML models, data store and SQL analytics dashboard etc., it provided us with a complete suite of tools for us to manage our big data pipeline.\u201d\u2014 Yanyan Wu, VP, Head of Unconventionals Data, Wood Mackenzie \u2013 A Verisk BusinessResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.\nExplore resourcesBlogsIntroducing Databricks WorkflowsIntroducing Repair and RerunDemosWorkflowsDelta Live TablesWebinarTackle Data Transformation With Delta Live TablesReady to get started?Sign up for accessDelta Live Tables documentationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeremy-lewallen","text":"Jeremy Lewallen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeremy LewallenProduct Manager at DatabricksBack to speakersJeremy Lewallen is a Staff Product Manager on DBSQL. He leads the the workload management, performance, control plane, API, and concurrency product direction.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-carbin","text":"Michael Carbin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer Science at Massachusetts Institute of TechnologyBack to speakersMichael Carbin is an associate professor in MIT\u2019s Department of Electrical Engineering and Computer Science and a principal investigator at the Computer Science and Artificial Intelligence Laboratory, where he leads the Programming Systems Group. His group investigates the semantics, design, and implementation of systems that operate in the presence of uncertainty in their environment (perception), implementation (neural networks or approximate transformations), or execution (unreliable hardware). Carbin has received a Sloan Research Fellowship, a Facebook Research Award, a Google Faculty Research Award and an NSF Career Award. He earned a BS in computer science at Stanford University and an MS and PhD in electrical engineering and computer science from MITLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/antoni-baum","text":"Antoni Baum - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAntoni BaumSoftware Engineer at AnyscaleBack to speakersAntoni is a Software Engineer at Anyscale, working on Ray AIR and the rest of Ray ML ecosystem.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"Soluzioni dei partner - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWSoluzioni dei partnerSoluzioni per migrazione e settori industriali specifici sviluppate dai partner per il lakehouseAbbiamo collaborato con i maggiori partner di consulenza per costruire soluzioni innovative per casi d'uso di migrazione e settori industriali specifici. Le Databricks Brickbuilder Solution sono concepite dai nostri partner per aiutare le aziende a ridurre i costi e aumentare il valore ricavato dai dati. Grazie alla pluriennale esperienza nel settore dei nostri partner e a soluzioni realizzate appositamente per Databricks Lakehouse Platform, ogni azienda pu\u00f2 avere la certezza di trovare soluzioni su misura per la sua attivit\u00e0.Cerca partner attivisearchSettore pubblicoCloud Data Migration by Accenture - DatabricksMaggiori informazioniRetail e largo consumoUnified View of Demand by AccentureMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingCPG Control Tower by AvanadeMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingIntelligent Healthcare on Azure Databricks by AvanadeMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingIntelligent ManufacturingMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingLegacy System Migration by AvanadeMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingRisk Management by AvanadeMaggiori informazioniTecnologia e softwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksMaggiori informazioniTecnologia e softwareMigrate to Cloud and Databricks by Capgemini and DatabricksMaggiori informazioniTecnologia e softwareCapgemini Revenue Growth ManagementMaggiori informazioniTecnologia e softwareMigrate to Databricks by Celebal Technologies and DatabricksMaggiori informazioniTecnologia e softwareCognizant Video Quality of ExperienceMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingPersona 360 by DataSentics and DatabricksMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingSAP Migration Accelerator by DataSentics - DatabricksMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingPrecisionView\u2122 by DeloitteMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingTrellis by DeloitteMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingSmart Migration to Databricks by EPAMMaggiori informazioniTecnologie di pubblicit\u00e0 e marketingLeapLogic Migration Solution by ImpetusMaggiori informazioniCARICA ALTRIPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/federal-government#videoinfo-6","text":"Federal Government Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData analytics and AI for federal agenciesUnlock innovation to deliver better public services with data and machine learningFrom the Federal Data Strategy to the AI Executive Order, it\u2019s clear that the U.S. federal government is focused on modernizing its data analytics and warehousing capabilities.The Databricks Lakehouse Platform empowers federal agencies to unlock the full potential of their data to deliver on their mission objectives and better serve citizens.Empowering Federal agencies to leverage data\u00a0and AI to deliver on mission objectivesTrusted by leading public sector agencies+ Any other Apache Spark\u2122\ufe0f compatible clientSee how industry leaders are using Databricks to improve the experience for citizens across all public servicesLatest blog posts, webinars, and case studiesWhy Databricks for the federal governmentModernize your data analytics130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Deliver mission outcomes effectively and efficiently130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Create better experiences for citizens130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Learn moreExtensive compliance for quick and easy approval to operate (ATO)Databricks has achieved ATOs on the regions, networks and compliance controls that support your mission objectivesCloudsC2S\nSC2S\nGovCloud\nPublic Cloud\nNetworksPublic\nNIPR\nSIPR\nJWICS\nCompliance controlsFedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICS-503\nHow Databricks fuels innovation for the federal governmentHealthcareImprove the delivery and quality of healthcare services for citizens with powerful analytics and a 360\u00b0 view of patients.\nPatient 360\u00a0\nSupply chain optimization\u00a0\nInsurance management\u00a0Genomics\u00a0\nDrug discovery and deliveryDefenseApply the power of predictive analytics to geospatial, IoT and surveillance data to improve operations and protect the nation.\u00a0\nLogistics\nPredictive maintenance\u00a0\nSurveillance and reconnaissance\u00a0\nLaw enforcement and readinessHomeland SecurityDetect and prevent criminal activities and national threats with real-time analytics and data-driven decision-making.\u00a0\nCustoms and border protection\u00a0\nImmigration and citizenship\u00a0\nCounter-terrorism\u00a0\nFederal emergency aid managementPublic Authority\/CommerceProactively detect anomalies with machine learning to mitigate risk and prevent fraudulent activity.\u00a0\nTax fraud and collection\u00a0\nProcess and operations management\u00a0\nGrants management\u00a0\nCustomer 360EnergyImprove energy management with data insights that ensure energy resiliency and sustainability.\u00a0\nSecurity of energy infrastructure\u00a0\nSmarter energy management\u00a0\nEnergy exploration\u00a0\nElectrical grid reliabilityIntelligence CommunityLeverage real-time insights to make informed decisions that can impact the safety of our citizens and the world.\u00a0\nThreat detection\u00a0\nNeutralize cyberattacks\u00a0\nIntelligence surveillance and reconnaissance\u00a0\nSocial media analyticsResourcesCustomer StoriesDriving Digital Transformation to Put Patients First at CMSData Governance Best Practices \u2014 Lessons Learned From the Centers for Medicare and Medicaid ServicesLessons Learned From Modernizing the USCIS Data Analytics PlatformModernizing the Air Force With Big Data and AIWebinarsRapid Response to Hospital Operations Using Data and AI During COVID-19Geospatial Analytics and AI in the Public SectorModern Data Analytics Architecture for the GovernmentImproving Threat Detection With Big Data and AINewsAzure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)Government-Grade Security in the AWS CloudBringing Unified Analytics to Government ClientsEmpowering the U.S. Intelligence Community With Mission-Critical Analytics and AISummit talksAutomating the Federal Aviation Administration\u2019s (FAA) System-Wide Information Management (SWIM) Data Ingestion and AnalysisGeospatial Analytics at Scale: Analyzing Human Movement Patterns During a PandemicReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.\u00a0Try for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andria-fuquen","text":"Andria Fuquen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndria FuquenTechnical Program Manager at ImmutaBack to speakersAndria Fuquen is a Technical Program Manager at Immuta, a data security focused company. She has over 7 years of experience across engineering, data systems, governance and security. At Immuta, her role is to help customers achieve success through their onboarding phase and become empowered to further streamline their data security practices. Ms. Fuquen is a strong advocate for diversity and supporting women in tech, proudly representing the Latina community. When not working, Andria enjoys spinning vinyl records and perfecting her salsa moves.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/denny-lee","text":"Denny Lee - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDenny LeeSr. Staff Developer Advocate at DatabricksBack to speakersDenny is a Databricks Developer Advocate. A hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale data platforms, and predictive analytics systems. He also has a Masters of Biomedical Informatics from Oregon Health and Sciences University and has implemented powerful data solutions for enterprise Healthcare customers. His current technical focuses include Distributed Systems, Apache Spark, Deep Learning, Machine Learning, and Genomics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/noritaka-sekiyama\/#","text":"Noritaka Sekiyama - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNoritaka SekiyamaPrincipal Big Data Architect at Amazon Web ServicesBack to speakersNoritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team at Amazon Web Services. He has more than 10 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/real-time-bidding-optimization","text":"Real-Time Bidding Optimization - Databricks World's Lakehouse Platform | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorReal-Time Bidding OptimizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedOptimize your real-time bidding strategyFrom display to video, the value of an impression can only be realized if an ad is viewed by a user. Therefore, when using programmatic advertising to buy inventory, it's important to take viewability into account. In this Solution Accelerator, learn how to predict ad viewability to optimize your real-time bidding strategy.Maximize return on ad spendIncrease conversionsReach your target audienceDownload the notebookResourcesCase StudyLearn moreExplainer videoLearn moreExplainer videoLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the \u201cPlatform Services\u201d), which are subject to the\u00a0Databricks Terms of Service\u00a0(or with respect to the Community Edition, the\u00a0Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (\u201cDatabricks\u201d) and our subscribers (\u201cSubscribers\u201d) (any such agreement, a \u201cServices Agreement\u201d).PLEASE READ CAREFULLY THESE TERMS AND THE\u00a0DATABRICKS PRIVACY POLICY\u00a0(\u201cPRIVACY POLICY\u201d) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. 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If you are using the Sites on behalf of any entity you represent and warrant that you are authorized to accept these Terms on such entity\u2019s behalf and, by accepting these Terms, you are hereby binding such entity to the Terms.Subject to your compliance with these Terms, solely for so long as you are permitted by Databricks to access and use the Sites, and provided that you keep intact all copyright and other proprietary notices, you may view Content and you may download and print the materials that Databricks specifically makes available for downloading from the Sites (such as white papers or user documentation), in each case solely for informational purposes and solely for personal or internal business use.ACCEPTANCE OF TERMS\nDatabricks provides the Sites to you conditioned upon your accepting all of the Terms, without modification. Your use of the Sites constitutes your agreement with such Terms. We reserve the right to change, modify, add to, or remove portions of these Terms in our sole discretion at any time and we will, at our sole discretion, either post the modification on\u00a0https:\/\/www.databricks.com\/terms-of-use\u00a0or provide you with email notice of the modification. You should check these Terms periodically for changes and you can determine when these Terms were last revised by referring to the \u201cLast Updated\u201d reference at the top of these Terms. Any modification shall be effective immediately upon the uploading of modified Terms. You indicate your agreement to comply with, and be bound by, any such modification by continuing to use or access the Sites after modified Terms are posted. 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If you believe that we might have any information from or about a child under 18, please contact us at\u00a0[email\u00a0protected]\u00a0with the subject \u201cChild Data\u201c.Databricks reserves the right to disclose any Submissions, and the circumstances surrounding their transmission, to any third party to operate the Sites, to protect Databricks or its suppliers or representatives, to protect users of the Sites, to comply with legal or regulatory obligations, to enforce these Terms, or for any other reason. Databricks is not responsible or liable for the conduct of, or your interactions with, any other users of the Sites (whether online or offline), or for any associated loss, damage, injury or harm. By using the Site, you may be exposed to Submissions that are offensive, indecent or objectionable and you agree that Databricks bears no liability for such exposure.REQUIRED CONDUCT WHILE USING OUR SITES\nWhile using the Sites you will comply with all applicable laws, rules and regulations. In addition, Databricks expects users of the Sites to respect the rights and dignity of others. Your use of the Sites is conditioned on your compliance with the rules of conduct set forth in this Section; any failure to comply may also result in termination of your access to the Sites pursuant to Section 9 (Suspension or Termination of Access to Our Sites). In using the Sites, you agree that you will not, and will not allow or authorize any third party to:\n\u00a0Use the Sites or any Content for any purpose that is illegal, fraudulent, deceptive or unauthorized by these Terms, or would give rise to civil liability, or to solicit the performance of any illegal activity or other activity which infringes the rights of Databricks or others, or to encourage or promote any such activity.Engage in or promote any conduct that is offensive, harassing, predatory, stalking, violent, threatening, discriminatory, racist, hateful, or otherwise harmful, against any individual or group.Harvest or collect information about any third parties, including their email addresses or other personally identifiable information.Send, by email or other means, any unsolicited or unauthorized advertising, promotional materials, junk mail, spam, chain letter, pyramid scheme, political campaign message, offering of an investment opportunity, or any other form of solicitation, or conceal or forge headers of emails or other messages, or otherwise misrepresent the identity of senders, for the purpose of sending spam or other unsolicited messages.Impersonate or post on behalf of, or express or imply the endorsement of, any individual or entity, including Databricks or any of its representatives, or otherwise misrepresent your affiliation with a person or entity.Use the Sites in any manner, whether deliberate or otherwise, including without limitation a denial of service attack, that could in any way (a) interfere with, damage, disable, overburden or impair the functioning of the Sites, or Databricks\u2019 systems or networks, or any systems or networks connected to the Sites, or (b) violate any requirements, procedures, policies or regulations of such systems or networks.Operate non-permissioned network services, including open proxies, mail relays or recursive domain name servers, or use any means to bypass user limitations relating to the Sites.Use any robot, spider, crawler, scraper, deep-link, page-scrape, site search\/retrieval application or other manual or automated device, program, algorithm or methodology or interface not provided by us to access, acquire, copy, retrieve, index, scrape, data mine, in any way reproduce or circumvent the navigational structure or presentation of the Sites or monitor any portion of the Sites or to extract data, or to sell, resell, frame, mirror or otherwise exploit for any commercial purpose, any portion of, use of, or access to the Sites (including any Content, Software and other materials available through the Sites), or attempt to circumvent any content filtering techniques we may employ.Remove any copyright, trademark or other proprietary rights notice from the Sites or from Content or other materials contained on or originating from the Sites.Create a database of any type by systematically downloading and storing any Content unless expressly permitted by Databricks to do so.Attempt to gain unauthorized access to any portion or feature of the Sites, or any other systems or networks connected to the Sites or to any Databricks server, or to any of the services offered on or through the Sites, by hacking, password mining or any other illegitimate means.Use or attempt to use any account you are not authorized to use.Probe, scan, monitor or test the vulnerability of the Sites or any network connected to the Sites, or breach the security or authentication measures on the Sites or any network connected to the Sites.Modify, adapt, create derivative works of, translate, reverse engineer, decompile or disassemble any portion of the Sites (including any Content or other materials available through the Sites), or do anything that might discover source code or bypass or circumvent measures employed to prevent or limit access to any area, Content or code within the Sites except as, and solely to the extent, expressly authorized under applicable law overriding any of these restrictions.Develop any third-party applications that interact with the Sites or Content without our prior written consent.Use or apply the Sites in any manner directly or indirectly competitive with any business of Databricks.\u00a0LINKS\nWe may from time-to-time at our discretion host or provide links to services, products, web pages, websites or other content of third parties (\u201cThird-Party Content\u201d). 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Subject to the foregoing, these Terms will be binding upon and will inure to the benefit of the parties and their respective representatives, heirs, administrators, successors and permitted assigns. No provision of these Terms is intended for the benefit of any third party, and the parties do not intend that any provision should be enforceable by a third party. Our relationship is an independent contractor relationship, and neither these Terms nor any actions by either party may be interpreted as creating an agency or partnership relationship. Nothing in these Terms shall be construed to obligate Databricks to enter into or engage with you on any commercial transaction.If you are provided access to any Software, you acknowledge that such Software may be subject to regulation by local laws and United States government agencies which prohibit export or diversion of certain products or information about products to certain countries and certain persons. 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The availability or exercise of our right to obtain injunctive relief will not limit our right to seek or obtain any other remedy.You agree that we will not be liable for delays, failures, or inadequate performance of the Sites resulting from conditions outside of our reasonable control, including but not limited to natural disasters or other acts of God, failure of telecommunications networks or any other network or utility, threatened or actual acts of terrorism or war, riots, labor strikes, or governmental acts or orders.Last Updated May 25, 2018ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/volker-tjaden","text":"Volker Tjaden - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVolker TjadenManager Solution Architects at DatabricksBack to speakersVolker leads a team of Solutions Architects at Databricks. His career in Data & AI started out as an economics student at university where he focused on statistical and computational methods working with large datasets. After completing a PhD, he held various consulting and management positions in different industries where he built data driven solutions to business problems such as dynamic pricing in banking, automated supply chains in retail and IoT platforms in manufacturing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gidon-gershinsky","text":"Gidon Gershinsky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGidon GershinskyLead Systems Architect at AppleBack to speakersGidon Gershinsky designs and builds Data Security solutions at Apple. He plays a leading role in the Apache Parquet community work on big data encryption and integrity verification technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/medicare-risk-adjustment","text":"Automate Medicare Risk Adjustments With NLP | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorMedicare Risk AdjustmentPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedIdentify undiagnosed conditions for reimbursementsIn the United States, the Centers for Medicare & Medicaid Services (CMS) reimburses private Medicare insurers based on beneficiary risk. Most insurers rely on claims data to calculate member risk, but that provides a narrow, point-in-time view of health. To address this gap, Databricks and John Snow Labs Solution Accelerator for Medicare Risk Adjustment automates the extraction of undiagnosed member conditions from unstructured clinical notes with NLP models, improving downstream reimbursements.Detect undiagnosed conditions in unstructured text with NLPAppend ICD-10 and HCC codes with pretrained modelsCalculate revised RAF scores to improve reimbursementsDownload notebookResourceseBookRead nowOn-demand webinarWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/don-bosco-durai\/#","text":"Don Bosco Durai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon Bosco DuraiCofounder and CTO at PrivaceraBack to speakersBosco is an enterprise security thought leader. Bosco co-founded XASecure which reinvented security at scale for Big Data which later became Apache Ranger. Bosco is currently co-founder and CTO at Privacera addressing data security & access governance challenges in the Cloud. He is also actively involved in the Open-Source communities as a committer in open source projects like Apache Ranger, Ambari, and HAWQ.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-castle\/#","text":"Scott Castle - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott CastleChief Strategy Officer at SisenseBack to speakersScott Castle is Chief Strategy Officer for Sisense, leading go-to-market, cloud, messaging and business strategy. He brings more than 25 years of experience in software development and product management at leading technology companies including Adobe, Periscope Data, Electric Cloud (acquired by Cloudbees), and FileNet (acquired by IBM).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/photon","text":"Photon | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPhotonThe next generation engine for the LakehouseGet startedLearn morePhoton is the next generation engine on the Databricks Lakehouse Platform that provides extremely fast query performance at low cost \u2013 from data ingestion, ETL, streaming, data science and interactive queries \u2013 directly on your data lake. Photon is compatible with Apache Spark\u2122 APIs, so getting started is as easy as turning it on \u2013 no code changes and no lock-in.Cheaper and fasterBuilt from the ground up for the fastest performance at lower cost, Photon provides up to 80% TCO savings while accelerating data and analytics workloads \u2014 up to 12x speedups.Built for all use casesPhoton is the first engine that enables data teams to standardize on one set of APIs for all workloads \u2014 ETL, analytics and data science \u2014 in batch or streaming.No code changesPhoton is an ANSI-compliant engine designed to be compatible with modern Apache Spark APIs and just works with your existing code \u2014 SQL, Python, R, Scala and Java \u2014 no rewrite required.Why Photon?Query performance on Databricks has steadily increased over the years, powered by Apache Spark and thousands of optimizations packaged as part of the Databricks Runtimes (DBR). Photon \u2014 a new native vectorized engine entirely written in C++ \u2014 provides an additional 2x speedup per the TPC-DS 1TB benchmark, and customers have observed 3x\u20138x speedups on average, based on their workloads, compared to the latest DBR versions.Use casesProduction jobsAccelerate large-scale production jobs on SQL and Spark DataFramesIoT applicationsFaster time-series analysis using Photon compared to Spark and traditional Databricks RuntimeData privacy and complianceQuery petabyte-scale data sets to identify and delete records without duplicating data with Delta Lake, production jobs and PhotonLoading data into Delta Lake and ParquetPhoton\u2019s vectorized I\/O speeds up data loads for Delta Lake and Parquet tables, lowering overall runtime and the cost of data engineering jobsHow does it work?Best price\/performance for analytics in the cloudWritten from the ground up in C++, Photon takes advantage of modern hardware for faster queries, providing up to 12x better price\/performance compared to other cloud data warehouses \u2014 all natively on your data lake.Works with your existing code and avoids vendor lock-inPhoton is designed to be compatible with the Apache Spark DataFrame and SQL APIs to ensure workloads run seamlessly without code changes. All you have to do to benefit from Photon is turn it on. Photon will seamlessly coordinate work and resources and transparently accelerate portions of your SQL and Spark queries. No tuning or user intervention required.Optimizing for all data use cases and workloadsWhile we started Photon primarily focused on SQL to provide customers with world-class data warehousing performance on their data lakes, we\u2019ve significantly increased the scope of ingestion sources, formats, APIs and methods supported by Photon since then. As a result, customers have seen dramatic infrastructure cost savings and speedups on Photon across all their modern Spark workloads (e.g., Spark SQL and DataFrame).Discover moreDelta LakeDatabricks SQLUnity CatalogDelta Live TablesResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.\nExplore resourcesPapersPhoton: A Fast Query Engine for Lakehouse Systems (SIGMOD Paper)EventsHow AT&T Data Science Team Solved an Insurmountable Big Data Challenge on Databricks with Two Different Approaches using Photon and RAPIDS Accelerator for Apache SparkRadical Speed on the Lakehouses: Photon under the hoodRadical Speed for SQL Queries on Databricks: Photon Under the HoodBlogsApache Spark and Photon Receive SIGMOD AwardsDatabricks Sets Official Data Warehousing Performance RecordNew Performance Improvements in Databricks SQLAnnouncing Photon Public Preview: The Next-Generation Query Engine on the Databricks Lakehouse PlatformReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aayush-patel","text":"Aayush Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAayush PatelData & Platform Engineer at SkywatchBack to speakersAayush is a data and platform engineer at Skywatch, where he focuses on developing robust data platforms and scalable data products. He specializes in creating high-fidelity data systems and is currently working on building a collaborative enterprise solution for large organizations to purchase and share earth observation data. Aayush has previously built data frameworks, such as a no-code reporting platform that leverages a centralized metrics catalog to generate uniform data reports.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/elliot-shmukler\/#","text":"Elliot Shmukler - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingElliot ShmuklerCo-Founder & CEO at AnomaloBack to speakersElliot Shmukler is the co-founder and CEO at Anomalo, where he and the team are building software to help data teams detect and root cause issues in their data before anyone else notices. Before starting Anomalo, Elliot has long championed using data to make decisions and build products as a senior Silicon Valley executive at companies like Instacart, Wealthfront, LinkedIn, and eBay. Elliot is a recognized Silicon Valley expert in data-driven product management and consumer growth strategies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/junta-nakai\/#","text":"Junta Nakai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJunta NakaiRVP, Industry Solutions, Financial Services and Sustainability at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/financial-services","text":"Lakehouse per servizi finanziari | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLakehouse per servizi finanziariPotenziare le future istituzioni di servizi finanziari guidate da dati e AICominciaProgramma una demoQuattro problematiche di gestione\ndei dati nei servizi finanziariGovernance e gestione dei dati\nLa mancanza di agilit\u00e0 dei dati e riproducibilit\u00e0 dei modelli ostacola il rispetto dei requisiti normativi specifici dei servizi finanziari.Conoscenza pi\u00f9 approfondita dei clienti\nI silos di dati impediscono di avere una vista completa del comportamento dei clienti, delle opportunit\u00e0 di cross-selling e delle informazioni necessarie per una personalizzazione diffusa su larga scala.Decisioni in tempo reale\nQuando si \u00e8 vincolati a un fornitore e si utilizzano strumenti scollegati, diminuisce la capacit\u00e0 di fare analisi in tempo reale per supportare e democratizzare scelte finanziarie pi\u00f9 intelligenti.Accesso ai dati di terze parti\nLe tecnologie tradizionali non consentono di ricavare informazioni approfondite su finanza e clienti da set di dati non strutturati e alternativi che crescono velocemente e, inoltre, non offrono funzionalit\u00e0 di condivisione di dati aperti per promuovere la collaborazione.Lakehouse per servizi finanziariPiattaforma unificata per dati e AI\nUna piattaforma unificata che riunisce tutti i carichi di lavoro di gestione e analisi dei dati per realizzare innovazioni trasformative nelle moderne istituzioni di servizi finanziari.\n\u00a0\nSoluzioni dei partner\nI principali fornitori mondiali stanno sviluppando soluzioni per la lakehouse per servizi finanziari. I clienti potranno cos\u00ec sfruttare offerte preconfigurate per accelerare la trasformazione guidata dai dati.\nStrumenti per accelerare i risultati del business\nDatabricks e i suoi partner hanno creato una gamma completa di acceleratori che semplificano la realizzazione di casi d'uso comuni nei servizi finanziari, dagli investimenti ESG alla lotta alle frodi.\nCollaborazione con il settore\nCondivisione di dati sicura e aperta con il nostro ecosistema di dati (che comprende S&P Global, Intercontinental Exchange, FactSet e Nasdaq) per realizzare innovazioni che favoriscono la creazione di valore sostenibile.\nTrasformare i servizi finanziari con\nla piattaforma lakehouse\n\u201cLa visione della gestione dei dati e dell'AI del Nasdaq si fonda su Databricks Lakehouse. Utilizziamo la piattaforma per elaborare enormi quantit\u00e0 di dati finanziari e alternativi complessi, per generare nuovi dati e informazioni approfondite per i nostri clienti. Databricks svolge un ruolo importante anche per il nostro obiettivo di ammodernare la fornitura e il consumo di dati. La soluzione ci consente di inviare i dati direttamente agli spazi di lavoro di analisi, in modo che i clienti possano analizzare e integrare dati mission-critical senza dover trasferire continuamente terabyte di dati.\"\u2014 Bill Dague, Head of Nasdaq Data Link, NasdaqPerch\u00e9 la piattaforma lakehouse per servizi finanziari?\nUnificare dati e AI su una piattaforma aperta e collaborativa che consente di ridurre al minimo il rischio, offrire ai clienti esperienze superiori e accelerare l'innovazioneApproccio governato alla gestione del rischio e alla conformit\u00e0\nSemplificare la complessit\u00e0 della reportistica normativa, della gestione del rischio e della conformit\u00e0, snellendo in modo sicuro l'acquisizione, l'elaborazione e la trasmissione di dati per realizzare pratiche migliori di governance dei dati.Prodotti e servizi personalizzati\nUnificare una grande variet\u00e0 di dati (dai dati di mercato ai dati alternativi) per offrire esperienze iper-personalizzate che promuovono le opportunit\u00e0 di cross-selling, la soddisfazione del cliente e la quota di portafoglio.Informazioni approfondite in tempo reale per decisioni pi\u00f9 efficaci\nLa rapida acquisizione di dati da tutte le sorgenti su larga scala consente di migliorare le scelte di investimento, individuare velocemente nuove frodi e applicare funzionalit\u00e0 in tempo reale alle pratiche di gestione del rischio.Condivisione di dati aperti e monetizzazione dei dati\nRaccogliere grandi quantit\u00e0 di dati interni e di terze parti per condividere soluzioni finanziarie innovative, monetizzare nuovi prodotti di dati e fornire funzionalit\u00e0 di analisi avanzate per qualsiasi cloud o strumento senza vincolarsi a tecnologie proprietarie.Scarica l'eBookPartner e soluzioniPuntare su formati aperti e standardizzazione dei dati per analisi e AIGestione del rischioIntegrare velocemente i dati in modelli di valore a rischio per restare al passo con rischi e minacce emergenti.CominciaModernizzazione delle carte esistenti e dei portafogli bancari principaliEffettua una conversione rapida da sorgenti esterne e sviluppa capacit\u00e0 di conversione completamente configurabili e industrializzate.CominciaPersona 360Completa, unifica e cattura profili di clienti in un modello intelligente per la gestione dei dati.CominciaScopri tutte le soluzioni dei partnerSicurezza informatica su larga scalaIndividuare velocemente le minacce, investigare l'impatto e ridurre i rischi con Splunk e DatabricksCominciaPunteggio ESGAdottare una visione quantitativa della sostenibilit\u00e0 e garantire che le aziende rispondano delle loro azioniCominciaGestione del rischio modernaAdottare un approccio pi\u00f9 agile alla gestione del rischio unificando i dati e l'IA nel LakehouseCominciaIndividuazione di frodi con analisi e AI geospazialiAnalizzando i dati geospaziali si possono comprendere meglio i comportamenti di spesa dei clienti, in particolare chi sono e come operano in bancaCominciaArricchimento delle transazioni con classificazione merceologicaAutomatizzando l'arricchimento delle transazioni, si pu\u00f2 comprendere meglio il comportamento dei clienti e portare la personalizzazione all'estremoCominciaModelli AI basati su regole per combattere le frodi finanziarieRinnovare le strategie antifrode per ridurre i costi operativi e aumentare la fiducia dei clientiCominciaTrasmissione puntuale e affidabile di report normativiCombinare modelli di dati del settore dei servizi finanziari con il cloud per implementare standard di governance elevati con una spesa di sviluppo contenutaCominciaModernizzare le piattaforme con dati di investimentiSfruttare tutta la potenza dei dati del mercato finanziario per focalizzarsi sulla fornitura di prodotti ai clientiCominciaAntiriciclaggio (AML)Realizzare casi d'uso basati su AI come abbinamenti casuali (fuzzy match) e analisi di immagini per combattere il riciclaggio di denaro e il terrorismo finanziarioCominciaVedi tutte le soluzioniLakehouse per servizi finanziari in azioneVincere insieme: Dati + AI promuovono la collaborazione nel lakehouseREGISTRATI SUBITO \u2192Risorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video su dati e AI per i servizi finanziari.\nEsplora risorseeBook e infografiche[Infografica] Dati per ancorare una nuova era della gestione del rischioScopri come \u00e8 facile sfruttare il potenziale di dati e AI nei servizi finanziariSfruttare dati alternativi e di terze parti nei servizi finanziari \u2192ESG dalla teoria alla pratica con l'analisi dei dati e l'AI Prevenire le frodi con Dati + AI: Istruzioni per combattere le minacce moderne \u2192 Video e downloadMetodologie per investimenti ESG spiegabili e trasparenti \u2192Sicurezza informatica nei servizi finanziari \u2192Accelerare l'innovazione guidata da dati e AI nei servizi finanziari \u2192Analisi ESG: video esplicativo \u2192Modernizzare la gestione del rischio \u2192Moderne piattaforme di investimento con il Lakehouse for Financial Services \u2192Scheda della soluzione Industry Lakehouse BlueprintsBlogAccelerator per banche e fintech che utilizzano le transazioni con carta di creditoUn approccio guidato dai dati ai fattori ESG (ambientale, sociale, governance) \u2192Costruire una moderna piattaforma per la gestione del rischio nei servizi finanziari \u2192Usare i dati per porre fine alle frodi sulle carte di credito: Capital One e altre best practice \u2192Strategie per ammodernare le piattaforme di gestione dei dati di investimento \u2192Migliorare l'esperienza del cliente con l'arricchimento delle transazioni \u2192 Suggerimenti preziosi per i servizi finanziari dal Data + AI Summit 2022 \u2192Lakehouse per servizi finanziariPronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProgramma una demoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/eric-peter","text":"Eric Peter - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEric PeterSr Staff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/mlops","text":"What is MLOps?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMLOpsAll>MLOpsWhat is MLOps?MLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. MLOps is a collaborative function, often comprising data scientists, devops engineers, and IT.What is the use of MLOps?MLOps is a useful approach for the creation and quality of machine learning and AI solutions. By adopting an MLOps approach, data scientists and machine learning engineers can collaborate and increase the pace of model development and production, by implementing continuous integration and deployment (CI\/CD) practices with proper monitoring, validation, and governance of ML models.Why do we need MLOps?Productionizing machine learning is difficult. The machine learning lifecycle consists of many complex components such as data ingest, data prep, model training, model tuning, model deployment, model monitoring, explainability, and much more. It also requires collaboration and hand-offs across teams, from Data Engineering to Data Science to ML Engineering. Naturally, it requires stringent operational rigor to keep all these processes synchronous and working in tandem. MLOps encompasses the experimentation, iteration, and continuous improvement of the machine learning lifecycle.What are the benefits of MLOps?The primary benefits of MLOps are efficiency, scalability, and risk reduction. Efficiency: MLOps allows data teams to achieve faster model development, deliver higher quality ML models, and faster deployment and production. Scalability: MLOps also enables vast scalability and management where thousands of models can be overseen, controlled, managed, and monitored for continuous integration, continuous delivery, and continuous deployment. Specifically, MLOps provides reproducibility of ML pipelines, enabling more tightly-coupled collaboration across data teams, reducing conflict with devops and IT, and accelerating release velocity. Risk reduction: Machine learning models often need regulatory scrutiny and drift-check, and MLOps enables greater transparency and faster response to such requests and ensures greater compliance with an organization's or industry's policies.What are the components of MLOps?The span of MLOps in machine learning projects can be as focused or expansive as the project demands. In certain cases, MLOps can encompass everything from the data pipeline to model production, while other projects may require MLOps implementation of only the model deployment process. A majority of enterprises deploy MLOps principles across the following:Exploratory data analysis (EDA)Data Prep and Feature EngineeringModel training and tuningModel review and governanceModel inference and servingModel monitoringAutomated model retrainingWhat are the best practices for MLOps?The best practices for MLOps can be delineated by the stage at which MLOps principles are being applied.Exploratory data analysis (EDA) - Iteratively explore, share, and prep data for the machine learning lifecycle by creating reproducible, editable, and shareable datasets, tables, and visualizations.Data Prep and Feature Engineering- Iteratively transform, aggregate, and de-duplicate data to create refined features. Most importantly, make the features visible and shareable across data teams, leveraging a feature store.Model training and tuning - Use popular open source libraries such as scikit-learn and hyperopt to train and improve model performance. As a simpler alternative, use automated machine learning tools such as AutoML to automatically perform trial runs and create reviewable and deployable code.Model review and governance- Track model lineage, model versions, and manage model artifacts and transitions through their lifecycle. Discover, share, and collaborate across ML models with the help of an open source MLOps platform such as MLflow.Model inference and serving - Manage the frequency of model refresh, inference request times and similar production-specifics in testing and QA. Use CI\/CD tools such as repos and orchestrators (borrowing devops principles) to automate the pre-production pipeline.Model deployment and monitoring - Automate permissions and cluster creation to productionize registered models. Enable REST API model endpoints.Automated model retraining - Create alerts and automation to take corrective action In case of model drift due to differences in training and inference data.What is the difference between MLOps and DevOps?MLOps is a set of engineering practices specific to machine learning projects that borrow from the more widely-adopted DevOps principles in software engineering. While DevOps brings a rapid, continuously iterative approach to shipping applications, MLOps borrows the same principles to take machine learning models to production. In both cases, the outcome is higher software quality, faster patching and releases, and higher customer satisfaction.Does training large language models (LLMOps) differ from traditional MLOps?While many of the concepts of MLOps still apply, there are other considerations when training large language models like Dolly. Let\u2019s go through some of the key points where training LLMs might differ from the traditional MLOps approach:Computational Resources: Training and fine-tuning large language models typically involves performing orders of magnitude more calculations on large data sets. To speed this process up, specialized hardware like GPUs are used for much faster data-parallel operations. Having access to these specialized compute resources becomes essential for both training and deploying large language models. The cost of inference can also make model compression and distillation techniques important.Transfer Learning: Unlike many traditional ML models that are created or trained from scratch, many large language models start from a foundation model and are fine-tuned with new data to improve performance in a more specific domain. Fine-tuning allows state-of-the-art performance for specific applications using less data and fewer compute resources.Human Feedback: One of the major improvements in training large language models has come through reinforcement learning from human feedback (RLHF). More generally, since LLM tasks are often very open-ended, human feedback from your application\u2019s end users is often critical for evaluating LLM performance. Integrating this feedback loop within your LLMOps pipelines can often increase the performance of your trained large language model.Hyperparameter Tuning: In classical ML, hyperparameter tuning often centers around improving accuracy or other metrics. For LLMs, tuning also becomes important for reducing the cost and computational power requirements of training and inference. For example, tweaking batch sizes and learning rates can dramatically change the speed and cost of training. Thus, both classical ML and LLMs benefit from tracking and optimizing the tuning process, but with different emphases.Performance Metrics: Traditional ML models have very clearly defined performance metrics, such as accuracy, AUC, F1 score, etc. These metrics are fairly straightforward to calculate. When it comes to evaluating LLMs, however, a whole different set of standard metrics and scoring apply \u2014 such as bilingual evaluation understudy (BLEU) and Recall-Oriented Understudy for Gisting Evaluation (ROGUE) that require some extra considering when implementing.\u00a0What is an MLOps platform?An MLOps platform provides data scientists and software engineers with a collaborative environment that facilitates iterative data exploration, real-time co-working capabilities for experiment tracking, feature engineering, and model management, as well as controlled model transitioning, deployment, and monitoring. An MLOps automates the operational and synchronization aspects of the machine learning lifecycle.Try Databricks - a fully managed environment for MLflow - the world's leading open MLOps Platform. https:\/\/www.databricks.com\/try\/databricks-free-mlAdditional ResourcesTake your ML projects from planning to productionMLOps for DummiesThe Big Book of Machine Learning Use CasesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/james-demmel\/#","text":"James Demmel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJames DemmelDr. Richard Carl Dehmel Distinguished Professor at University of California, BerkeleyBack to speakersProf. James Demmel is a Distinguished Professor of Mathematics and Computer Science at the University of California, Berkeley. He is the former chair of the Computer Science Division and EECS Department of UC Berkeley. Demmel is known for his work on numerical linear algebra libraries, including LAPACK, ScaLAPACK and SuperLU. Demmel\u2019s work on high-performance computing, such as communication-avoiding algorithms, has been recognized by many honors and awards. He is a member of the National Academy of Sciences, National Academy of Engineering, American Academy of Arts and Sciences; Fellow of the AAAS, ACM, AMS, IEEE, and SIAM; ACM Paris Kanellakis Theory and Practice Award, IPDPS Charles Babbage Award, IEEE Sidney Fernbach Award, 13 best paper prizes. Demmel was one of just two scientists honored the Leslie Fox Prize for Numerical Analysis in 1986 and he was the winner of the J.H. Wilkinson Prize in Numerical Analysis and Scientific Computing, the IEEE's Sidney Fernbach Award \"for computational science leadership in creating adaptive, innovative, high-performance linear algebra software\", and the IEEE Computer Society Charles Babbage Award.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/eric-schmidt\/#","text":"Eric Schmidt - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEric SchmidtFormer CEO and Chairman, Google; Co-Founder at Schmidt FuturesBack to speakersEric Schmidt is an accomplished technologist, entrepreneur and philanthropist. He joined Google in 2001 and helped grow the company from a Silicon Valley startup to a global leader in technology alongside founders Sergey Brin and Larry Page. Eric served as Google\u2019s Chief Executive Officer and Chairman from 2001\u20132011, as well as Executive Chairman and Technical Advisor. Under his leadership, Google dramatically scaled its infrastructure and diversified its product offerings while maintaining a strong culture of innovation. In 2017, he co-founded Schmidt Futures, a philanthropic initiative that bets early on exceptional people making the world better. Eric founded the Special Competitive Studies Project in 2021, a nonprofit initiative focused on strengthening America\u2019s long-term AI and technological competitiveness in national security, the economy and society.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/technology-partner-program","text":"Databricks Technology Partner Program - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWProgramma Partner TecnologiciEntra in contatto con migliaia di clienti di Databricks pronti a utilizzare il tuo prodottoIscrivitiDatabricks si integra con i migliori prodotti per dati e AI e li promuove sul mercato. Offriamo ai nostri partner supporto tecnico e commerciale per acquisire nuovi clienti ed espandere l'attivit\u00e0.Vantaggi per i partner tecnologiciIncentivi alle venditeIncentivi alla struttura operativa di Databricks per promuovere la vendita dei tuoi prodottiAccesso ai clientiAcquisisci direttamente nuovi clienti con Databricks Partner ConnectMaggiori informazioniSupporto per il marketingAccedi a risorse di marketing per allargare il tuo raggio d'azioneAccesso al team di prodotti e R&DAccesso al personale di Databricks per prodotti, progettazione e supportoAmbiente di prova gratuitoCostruisci e testa in un ambiente di prova gratuito (sandbox)Programmi di marketing congiuntoPartecipa a programmi di marketing congiunto con DatabricksPronto per lavorare insieme?IscrivitiTrova un partnerProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sumesh-nair","text":"Sumesh Nair - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSumesh NairDirector of Engineering, Data and Cloud Strategy at Optum, United HealthGroupBack to speakersExperienced and Accomplished senior IT leader with a 20-year track record of excellence. An Agile enthusiast with a history of transforming organizations to optimize product engineering & delivery. A servant-leader known for building high-performing teams to discover new solutions, challenge norms, and gain competitive advantages in the market. An experienced leader with P&L Oversight background, multi-channel product leadership, and driving organizational change by exceeding expectations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/infosys-data-wizard-migrations","text":"Data Wizard for Hadoop\/EDW Migrations by Infosys | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionData Wizard for Hadoop\/EDW Migrations by InfosysMigration solution developed by Infosys and powered by the Databricks Lakehouse Platform\nGet startedConfidently move your data to DatabricksInfosys Data Wizard is a comprehensive solution with a set of accelerators for seamless data migration. It makes data warehouse and data lake migrations to the Databricks Lakehouse Platform seamless, secure, manageable, quick and risk-free. It offers an intuitive graphical user interface that is designed to follow execution approaches through different phases of migration \u2014 from project initiation to configuration, inventory collection, analysis, migration, validation, all the way through data certification, tracking and management. With Infosys Data Wizard, you can achieve:A 50%\u201360% acceleration in the data migration lifecycleA 30% reduction in the cost of migrationsA risk-free migration with comprehensive data certificationGet startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#82efebe9e7acefededece7fbc2e6e3f6e3e0f0ebe1e9f1ace1edef","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c348409ee5773\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-doxey","text":"Matthew Doxey - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew DoxeySenior Epidemiologist at Washington State Department of HealthBack to speakersMatt Doxey is a public health data scientist with the Washington State Department of Health's Center for Data Science, where he leads data science and disease modeling initiatives. An epidemiologist by training with experience in global health initiatives and improving health outcomes in under-served communities, Matt is passionate about using innovative, data-driven methods and technologies to protect and enhance community and population health through better data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/11\/18\/build-your-business-on-databricks-with-partner-connect.html","text":"Build Your Business on Databricks With Partner Connect - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorBuild Your Business on Databricks With Partner Connectby Dave Eyler, Pankaj Dugar and Zaheera ValaniNovember 18, 2021 in Platform BlogShare this postAt Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and create a platform others can extend. To see the importance of this, think of the apps on your phone. Were they all made by Apple or Google? How much less valuable would your phone be if that\u2019s all you had?\nThat\u2019s why today we are announcing the launch of Partner Connect that brings together the best data, analytics, and AI tools in one place for our customers to discover and integrate with. We\u2019ve designed Partner Connect to meet the needs of both customers and partners, because that\u2019s the only way we can create a virtuous cycle that will continue to grow and generate value for both groups.\nPartner Connect is not just a list of logos, it\u2019s a deep integration into Databricks that is directly visible and accessible to Databricks customers, and this is what makes it so valuable. By making their products available in Partner Connect, our partners can expect three key benefits that will help them build their businesses.\nNew leadsWith thousands of existing customers using the Databricks Lakehouse Platform and more joining every day, our partners in Partner Connect can expect significantly more inbound connections. Whether that means new customers or increased consumption from your existing customers, it\u2019s a win either way.\nDeep integrationPartner Connect creates a seamless experience for Databricks customers to create a new free trial account of our partners\u2019 products AND automatically connect that account to their Databricks workspace. That means Databricks customers can find your product, create an account in your system, and play with your product with their Databricks Lakehouse already connected. How does it work? Partner Connect was built to invoke our partner\u2019s APIs to establish connections, create accounts and pass details for the connection back to Databricks. The hardest parts of onboarding have been automated.\nVisibility & confidenceWe want our sales teams and our partners to work and co-sell together. By putting your product in Partner Connect, it serves as a clear signal to the market that your product\u2019s connection to Databricks Is built on a deep, quality integration. That means customer champions, our sales teams, and our partners can recommend it with full confidence, and that makes all the difference.\nWe look forward to working with you! If you would like to discuss adding your product to Partner Connect, please visit the Partner Connect registration page.Try Databricks for freeGet StartedSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/learn","text":"Learn | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLearnDive in and explore a world of Databricks resources \u2014 at your fingertips. You\u2019ll find training and certification, upcoming events, helpful documentation and more.Getting started with DatabricksLearn the BasicsThe Databricks Lakehouse Platform makes it easy to build and execute data pipelines, collaborate on data science and analytics projects and build and deploy machine learning models. Check out our Getting Started guides below.New to Databricks? Start your journey with Databricks guided by an experienced Customer Success Engineer.Databricks onboarding\nLakehouse Fundamentals Training\nWatch 4 short videos, take the quiz and get your badge\nto share on LinkedIn or your r\u00e9sum\u00e9\nGet startedData science and engineeringDatabricks AdministratorsSQL analyticsMachine learningTrainingGet trained through Databricks Academy. Learn how to master data analytics from the team that started the Apache Spark\u2122 research project at UC Berkeley.Databricks AcademyCertificationCertification exams assess how well you know the Databricks Lakehouse Platform and the methods required to successfully implement quality projects. They help you gain industry recognition, competitive differentiation, greater productivity and results, and a tangible measure of your educational investment.Databricks CertificationGet Your Questions AnsweredChoose from the following ways to get clarity on questions that might come up as you are getting started:Ask a Databricks technical expert liveOnline CommunityExplore popular topics within the Databricks community.Connect with the communityPopular forum topicsDatabricksDelta LakeSparkSQLPySparkAzureAWSGCPNeed hands on help?If you have a support contract or are interested in one, check out our options below. For strategic business guidance (with a Customer Success Engineer or a Professional Services contract), contact your workspace Administrator to reach out to your Databricks Account Executive.Check out our support optionsNotebook GalleryThis gallery showcases some of the possibilities through Notebooks focused on technologies and use cases which can easily be imported into your own Databricks environment or the free community edition.Databricks Notebook GalleryDocumentationThe Databricks technical documentation site provides how-to guidance and reference information for the Databricks data science and engineering, Databricks machine learning and Databricks SQL persona-based environments.AWS documentationAzure documentationGoogle documentationDatabricks events and communityData + AI SummitJoin us for keynotes, product announcements and 200+ technical sessions \u2014 featuring a lineup of experts in industry, research and academia.Learn moreGlobal eventsSave your spot at one of our global or regional conferences, live product demos, webinars, partner-sponsored events or meetups.Learn moreData + AI online meetupsFind out what\u2019s happening at Databricks Meetup groups around the world and join one near or far \u2014 all virtually.Learn moreBeaconsMeet the Databricks Beacons, a group of community members who go above and beyond to uplift the data and AI community.Learn moreUniversity AllianceJoin the Databricks University Alliance to access complimentary resources for educators who want to teach using Databricks.Learn moreData Brew VidcastExploring Data + AI With ExpertsBrooke Wenig and Denny LeeVideo SeriesOnline Tech Talks and MeetupsBrooke Wenig and Denny LeeTech TalksManaging the Complete Machine Learning Lifecycle Using MLflowJules DamjiTech TalksGetting Started With Delta LakeDenny LeeTech TalksDiving Into Delta Lake (Advanced)Denny LeeDatabricks Demo Hub (Product Demos)Data + AI ResearchMatei ZahariaCo-Founder and Chief TechnologistDatabricksReynold XinCo-Founder and Chief ArchitectDatabricksSue Ann HongSoftware EngineerDatabricksRead recent papers from Databricks founders, staff and researchers on distributed systems, AI and data analytics \u2014 in collaboration with leading universities such as UC Berkeley and Stanford.Access researchProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/menglei-sun","text":"Menglei Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMenglei SunSenior Software Engineer at DatabricksBack to speakersMenglei Sun is a senior software engineer at Databricks working on data lineage and data discovery related projects. Previously, Menglei worked at Houzz, BlackRock on data infrastructure, data engineering and platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/murali-madireddi","text":"Murali Madireddi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMurali MadireddiArchitect at AccentureBack to speakersMurali is an accomplished architect with strong expertise in ETL, DW and Data lakes.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=operations","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/privacy","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/blog\/2022\/03\/22\/amgen-modernizes-analytics-with-a-unified-data-lakehouse-to-speed-drug-development-delivery.html","text":"How Amgen Modernized Its Analytics With a Unified Data Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHow the Lakehouse Democratizes Data to Help Amgen Speed Drug Development & Deliveryby Jaison Dominic and Kerby JohnsonMarch 22, 2022 in CustomersShare this postThis is a guest authored post by Jaison Dominic, Product Owner, and Kerby Johnson, Distinguished Software Engineer, at Amgen.Amgen, the world\u2019s largest independent biotech company, has long been synonymous with innovation. For 40 years, we\u2019ve pioneered new drug-making processes and developed life-saving medicines, positively impacting the lives of millions around the world. In order to continue fulfilling our mission to best serve patients, we recently embarked on another journey of innovation: a complete digital transformation.In the process of reimagining how to leverage our data for better outcomes across the business \u2014 from improving R&D productivity to optimizing supply chains and commercialization \u2014 it quickly became obvious that the types of problems our data teams were looking to solve had drastically changed in the last handful of years. Additionally, these problems were no longer isolated by skillset, department or function. Instead, the most impactful problems were cross-functional in nature and required bringing together people with different, unique expertise to attack problems in a novel way. In our quest to modernize, we chose the Databricks Lakehouse Platform as the foundation for our digital transformation journey. As a result, we were able to unlock the potential of our data across various organizations, streamlining operational efficiency and accelerating drug discovery.Today, we are sharing our success story in the hopes that others can learn from our journey and apply it to their own business strategies.From data warehouse to data lake \u2013 and the problems withinWithin three core verticals of Amgen - clinical trials, manufacturing, and commercialization \u2013 lies a wealth of valuable data. But increasing volumes of data presented challenges when it came to actually using that data efficiently.We were unable to truly weave together the various aspects of our business, which impacted operational efficiency as we scaled both internally and in our number of customers. The key was to not only make it easy to access and process data but to do so in a collaborative manner that ties in different personas that have different viewpoints on the data \u2014 a connected data fabric that enables better cross-functional collaboration. If you\u2019re only looking at it from one or two perspectives, you\u2019re going to miss valuable key points from others.For example, consider the question: How do you granularly forecast demand so you can produce the right amount of therapeutics for patients in need?If you\u2019re looking at the answer from a supply chain and manufacturing perspective, you\u2019re missing commercial sales forecast data. On the other hand, you don\u2019t want to take the commercial sales forecast as the gospel of the amount of production needed because what if they blow their sales numbers out of the water, which is always the hope, and you\u2019ve underestimated what manufacturing needs to produce?In order to solve today\u2019s problems, businesses need to focus on different data relationships and connections so that they can look at the same data from multiple lenses \u2014 but how can they enable this? At Amgen, we\u2019ve broken the foundation of modern data requirements down as follows:Data needs to be organized and easy to use.Sharing data and re-using that of others in a natural way is a must.Analytics should be able to operate off a trusted shared view of data.Different forms of analytics from descriptive (BI) to predictive (ML) helps facilitate new discoveries and predictions on one version of the data.Data needs to be able to evolve as new types are brought in, changes from one system to another occur, new domains are added, etc. but the core of it all should remain consistent.The need for this to be the case is likely known by most organizations, but seeing it come to life has been particularly difficult for enterprises with counter-intuitive processes: each team owning, managing and organizing their data differently, requiring yet another project if they simply want to share it. We too struggled with not only several years of accumulating more data than we knew what to do with, but also with the lack of process and infrastructure to ensure everyone was able to work off the same data.To try and address our early data needs, we transitioned from a legacy technology infrastructure over to a Hadoop-based data lake a few years back. With a Hadoop data lake, we were able to keep structured and unstructured data in one place, but significant data challenges remained, both on the technical side and when it came to processes, cost and organization. The shared clusters caused \u201cNoisy Neighbor\u201d problem and were difficult and costly to scale.For my role, as a product owner of the platform, managing a single shared cluster was a nightmare. It was always on, there was never a good time to upgrade versions, and we had distributed costs which meant, for example, figuring out how to charge one group for high storage and low compute and another group for high compute and low storage.This approach also required stitching together a variety of different tools in order to meet the needs of each individual group, which created significant collaboration challenges. And like so many others, we had a variety of ways that end-users were consuming data: Jupyter Notebooks, R Studio, Spotfire and Tableau, which only added to the complexity and challenge of making data readily available to those that need it.How the lakehouse architecture solves our problemsAdopting the Databricks Lakehouse Platform has enabled a variety of teams and personas to do more with our data. With this unifying and collaborative platform, we\u2019ve been able to utilize a single environment for all types of users and their preferred tools, keeping operations backed by a consistent set of data.We\u2019re leveraging Delta Lake to enable ACID compliance, historical lookback, and lower the barrier to entry for developers to begin coding by providing a common data layer for data analysts and data scientists alike to use data to optimize supply chains and improve operations. We\u2019re also leveraging AWS Glue to connect different Databricks environments together so it\u2019s one data lake \u2013 whether the data is stored in one AWS account or 10 different accounts. It\u2019s all connected.This has enabled us to provide sufficient flexibility for a variety of needs while standardizing on Apache Spark\u2122 for data and analytics. The unified data layer within the lakehouse allows Amgen to reliably process data of any type and size, while providing the application teams with the flexibility to move the business forward.What size clusters do you want? How much do you want to spend? Is it more important to get your reports an hour faster, or to cut costs? Decisions like these can now be made by individual teams. Collectively, this standardization of tools and languages, and a single source of truth for data scientists, analysts, and engineers, is what started enabling connected teams.Our current data architecture uses an Amazon S3 as the single source of truth for all data, Delta Lake as the common data layer, the Glue data catalog as the centralized metastore for Databricks, an ELK stack for monitoring with Kibana, Airflow for orchestration, and consumption, whether it\u2019s analysts or data scientists, all operating off the Databricks Lakehouse Platform.This common data architecture, and integrating these architectural patterns has enabled us to shift our focus from platform maintenance to really digging into what the business actually wants and what our users care about. The key has been our ability to leverage the lakehouse approach to unify our data across our various data teams while aligning with our business goals.With data at the ready, various data teams from engineering to data science to analysts can access and collaborate on data. Databricks\u2019 collaborative notebooks support their programming language of choice to easily explore and start leveraging the data for downstream analytics and ML. As we start to use Databricks SQL, our analysts can find and explore the latest and freshest data without having to move it into a data warehouse. They can run queries without sacrificing performance, and easily visualize results with their tools of choice \u2014 either through built-in visualizations and dashboards or Tableau, which is primarily used by business partners throughout the company.Our data scientists also benefit from using Databricks Machine Learning to simplify all aspects of ML. And since Databricks ML is built on the lakehouse foundation with Delta Lake and MLflow, our data scientists can prepare and process data, streamline cross-team collaboration and standardize the full lifecycle from experimentation to production without depending on data engineering support. This improved approach to managing ML has had a direct impact on decreasing the time it takes to enroll in clinical trials.Improving patient outcomes with connected data and teamsThe implementation of the Databricks Lakehouse Platform has ultimately helped us continue to achieve our goals of serving patients and improving the drug development lifecycle in a modern world. Our data ingestion rates have increased significantly, improving processing times by 75% resulting in 2x faster delivery of insights to the business, all while reducing compute costs by ~25% over static Hadoop clusters.With Databricks, we can take a modern approach to deliver on a myriad of use cases by focusing on the data, the relationships, and the connections rather than just the technology. Since partnering with Databricks in 2017, we\u2019ve seen massive growth adoption across the company. To date, 2,000+ data users from data engineering to analysts have accessed 400TB of data through Databricks to support 40+ data lake projects and 240 data science projects.What this looks like in practice is easy to use, easy to find data that enables a number of use cases across the company:Genomic exploration and research at scale: Harnessing the power of genomic data has allowed us to accelerate the drug discovery process this could significantly increase our chances to find new drugs to cure grievous illnesses.Optimized clinical trial designs: Now we can bring in a variety of data from purchased data to real-world evidence, and leverage insights from this wide variety of clinical data to improve the likelihood of success and potentially save tens of millions of dollars.Supply chain and inventory optimization: Manufacturing efficiency and inventory management is a challenge for every manufacturing industry, and drug manufacturing is no exception. Efficient manufacturing and optimized supply chain management can help save millions of dollars to the business, and help get the right drugs to the right patients at the right time.As Amgen\u2019s success demonstrates, novel solutions to age-old problems require a refresh of a business\u2019s platforms, tools, and methods of innovation. And as adoption continues to rise at Amgen, we\u2019ll explore new ways to take advantage of the lakehouse approach to foster collaboration and transparency with tools like Delta Sharing. Another intriguing tool that could provide value is Delta Live Tables, which could help us simplify ETL development and management even more, as well as benefit our downstream data consumers. Ultimately, Databricks has helped us to move the starting line for advanced analytics, so we can spend more time-solving problems that can benefit the patients who need treatments, and less time rebuilding the foundational infrastructure that enables it.Next StepsLearn more about the Databricks Lakehouse for Healthcare and Life SciencesWatch the Amgen talk from a recent webinarTry Databricks for freeGet StartedRelated postsIntroducing Lakehouse for Healthcare and Life SciencesMarch 9, 2022 by Michael Sanky and Michael Ortega in News\nEach of us will likely generate millions of gigabytes of health data in our lifetimes: medical and pharmacy claims, electronic medical records with...\nUnlocking the Power of Health Data With a Modern Data LakehouseJuly 19, 2021 by Michael Ortega, Michael Sanky and Amir Kermany in Engineering Blog\nA single patient produces approximately 80 megabytes of medical data every year. Multiply that across thousands of patients over their lifetime, and you're...\nImproving Drug Safety With Adverse Event Detection Using NLPJanuary 17, 2022 by Amir Kermany, Michael Ortega, Moritz Steller, David Talby and Michael Sanky in Engineering Blog\nDon't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution...\nSee all Customers postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/kr\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks SQL \uc694\uae08 \ud504\ub85c\ubaa8\uc158 \u2014 40% \uc774\uc0c1 \uc808\uac10SQL Serverless \ubc0f \uc0c8\ub85c\uc6b4 SQL Pro\uc744 \ub300\uc0c1\uc73c\ub85c \ud55c 15\uac1c\uc6d4 \ud504\ub85c\ubaa8\uc158\uc744 \ud65c\uc6a9\ud574 \ubcf4\uc138\uc694.\uc790\uc138\ud788Databricks SQL\ucd5c\uace0\uc758 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks SQL(DB SQL)\uc740 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \uc11c\ubc84\ub9ac\uc2a4 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub85c, \ucd5c\ub300 12\ubc30 \ud5a5\uc0c1\ub41c \uac00\uaca9-\uc131\ub2a5\uc73c\ub85c \ubaa8\ub4e0 SQL \ubc0f BI \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \ub300\uaddc\ubaa8\ub85c \uc2e4\ud589\ud560 \uc218 \uc788\uc73c\uba70, \ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4 \ubaa8\ub378, \uac1c\ubc29\uc801 \ud615\uc2dd \ubc0f API, \uc6d0\ud558\ub294 \ub3c4\uad6c\ub97c \uc9c0\uc6d0\ud558\uc5ec \uacf5\uae09\uc5c5\uccb4\uc5d0 \uc885\uc18d\ub418\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4.\ucd5c\uace0\uc758 \uac00\uaca9-\uc131\ub2a5\ube44\uc6a9\uc774 \uc808\uac10\ub418\uace0, \ucd5c\uace0\uc758 \uac00\uaca9-\uc131\ub2a5\uc744 \uc81c\uacf5\ud560 \ubfd0\ub9cc \uc544\ub2c8\ub77c, \uc11c\ubc84\ub9ac\uc2a4 \ub355\ubd84\uc5d0 \ud074\ub77c\uc6b0\ub4dc \uc778\ud504\ub77c\ub97c \uad00\ub9ac\ud558\uac70\ub098 \uad6c\uc131, \ud655\ub300\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4.\uac70\ubc84\ub10c\uc2a4 \uae30\ubcf8 \uc81c\uacf5\uac1c\ubc29\uc801 \ud45c\uc900\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \ud558\ub098\uc758 \uc0ac\ubcf8\uc744 \uc124\uc815\ud558\uace0, \ud45c\uc900 SQL\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \ub370\uc774\ud130 \ud300\uc5d0\uc11c \ud558\ub098\uc758 \ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4 \uacc4\uce35\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\ud48d\ubd80\ud55c \uc5d0\ucf54\uc2dc\uc2a4\ud15cSQL \ubc0f Fivetran, dbt, Power BI, Tableau \ub4f1\uc758 \ub3c4\uad6c\uc640 Databricks\ub97c \ud568\uaed8 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \uc800\uc7a5\ub41c \ub370\uc774\ud130\ub97c \uc218\uc9d1, \ubcc0\ud658 \ubc0f \ucffc\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc0ac\uc77c\ub85c \ud574\uc81c\ubaa8\ub4e0 \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 \ub354\uc6b1 \ube60\ub974\uac8c \ub370\uc774\ud130\uc5d0 \uc561\uc138\uc2a4\ud558\uc5ec \ub370\uc774\ud130\uc2a4\ud2b8\ub9bc \uc2e4\uc2dc\uac04 \ubd84\uc11d\uc744 \uc2e4\ud589\ud558\uace0, BI\uc5d0\uc11c ML\uae4c\uc9c0 \uc6d0\ud65c\ud55c \uc9c4\ud589\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uc5b4\ub5bb\uac8c \uc791\ub3d9\ud558\ub098\uc694?\uc5d0\ucf54\uc2dc\uc2a4\ud15c\uacfc\uc758 \ub9e4\ub044\ub7ec\uc6b4 \ud1b5\ud569\u00a0\uc0ac\uc6a9 \ud3b8\uc774\uc131\u00a0\uc2e4\uc2dc\uac04 \uc131\ub2a5\u00a0\uc911\uc559 \uc9d1\uc911\ud615 \uac70\ubc84\ub10c\uc2a4\u00a0\uac1c\ubc29\uc801\uc774\uace0 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c \uae30\ubc18\uc5b4\ub514\uc11c\ub098 \uc190\uc27d\uac8c \ub370\uc774\ud130\ub97c \uc218\uc9d1, \ubcc0\ud658 \ubc0f \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc704\uce58\uc640 \uad00\uacc4\uc5c6\uc774 \uc5b4\ub514\uc11c\ub098 \ub370\uc774\ud130\ub85c \uc791\uc5c5\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4. \uc560\ub110\ub9ac\uc2a4\ud2b8\uc640 \ubd84\uc11d \uc5d4\uc9c0\ub2c8\uc5b4\ub294 \ud134\ud0a4 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uc5ec Fivetran\uc73c\ub85c \ud074\ub77c\uc6b0\ub4dc \uc2a4\ud1a0\ub9ac\uc9c0\uc5d0\uc11c \uc5d4\ud130\ud504\ub77c\uc774\uc988 \uc560\ud50c\ub9ac\ucf00\uc774\uc158(\uc608: Salesforce, Google Analytics, Marketo)\uae4c\uc9c0 \ubaa8\ub4e0 \uacf3\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc27d\uac8c \uc218\uc9d1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud074\ub9ad \ud55c \ubc88\uc774\uba74 \ub429\ub2c8\ub2e4. \ub610\ud55c, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \ub0b4\uc7a5\ub41c ETL \uae30\ub2a5\uc73c\ub85c \uac04\ub2e8\ud558\uac8c \uc885\uc18d\uc131\uc744 \uad00\ub9ac\ud558\uace0 \uc800\uc7a5\ub41c \ub370\uc774\ud130\ub97c \ubcc0\ud658\ud558\uac70\ub098 Databricks SQL\uc5d0\uc11c dbt \ub4f1\uc758 \uc790\uc8fc \uc0ac\uc6a9\ud558\ub294 \ub3c4\uad6c\ub97c \ud1b5\ud574 \ucd5c\uc801\uc758 \uc131\ub2a5\uc744 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u00a0\"Databricks\uc640 Fivetran\uc744 \ud568\uaed8 \uc0ac\uc6a9\ud55c \ub355\ubd84\uc5d0 \ub9e4\uc6b0 \uc9e7\uc740 \uc2dc\uac04\uc5d0 \uac15\ub825\ud558\uace0 \ud604\ub300\uc801\uc778 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \u0000\u0000\uad6c\ucd95\ud560 \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. Fivetran\uc740 \uc6b0\ub9ac\uc5d0\uac8c \ud544\uc694\ud55c \ucee4\ub125\ud130\uc640 \ud1b5\ud569 \uae30\ub2a5\uc744 \ubaa8\ub450 \uac16\ucd94\uace0 \uc788\uc5c8\uc2b5\ub2c8\ub2e4.\"\u2014 Kreg Tool \uc778\uc0ac\uc774\ud2b8 \ubc0f \ubd84\uc11d \ubd80\ubb38 \ucc45\uc784\uc790\uc790\uc138\ud788\uc6d0\ud558\ub294 \ub3c4\uad6c\ub97c \uc0ac\uc6a9\ud55c \ucd5c\uc2e0 \ubd84\uc11d \ubc0f BITableau, Power BI, Looker \ub4f1\uc758 \uac00\uc7a5 \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ud558\ub294 BI \ub3c4\uad6c\ub97c \uc6d0\ud65c\ud558\uac8c \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \uc774\uc81c \uc560\ub110\ub9ac\uc2a4\ud2b8\ub294 \uc790\uc8fc \uc0ac\uc6a9\ud558\ub294 \ub3c4\uad6c\uc5d0\uc11c \uac00\uc7a5 \uc644\uc804\ud55c \ucd5c\uc2e0 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \uc0c8\ub85c\uc6b4 \ube44\uc988\ub2c8\uc2a4 \uc778\uc0ac\uc774\ud2b8\ub97c \ubc1c\uacac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uadf8\ubfd0\ub9cc \uc544\ub2c8\ub77c Databricks SQL\uc740 \uae30\ubcf8 \ub0b4\uc7a5\ub41c SQL \ud3b8\uc9d1\uae30, \uc2dc\uac01\ud654, \ub300\uc2dc\ubcf4\ub4dc\ub97c \uc0ac\uc6a9\ud574 \ubaa8\ub4e0 \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 \ud568\uaed8 \ud611\ub825\ud558\uc5ec \uc778\uc0ac\uc774\ud2b8\ub97c \ucffc\ub9ac\ud558\uace0 \ucc3e\uc544\uc11c \uacf5\uc720\ud560 \uc218 \uc788\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\u00a0\"\ub370\uc774\ud130\ub97c \uc190\uc27d\uac8c \ud655\ubcf4\ud560 \uc218 \uc788\uac8c \ub418\uba74\uc11c Power BI \ub300\uc2dc\ubcf4\ub4dc \ubc0f \ubcf4\uace0\uc11c\uc5d0 \uac00\uc7a5 \ucd5c\uc2e0\uc758 \uc644\uc804\ud55c \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uace0 \uc788\ub2e4\ub294 \uc0ac\uc2e4\uc5d0 \ud6e8\uc52c \ub354 \ud070 \uc790\uc2e0\uac10\uc744 \uac16\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\"\u2014 Jake Stone, ButcherBox \ube44\uc988\ub2c8\uc2a4 \ubd84\uc11d \ubd80\ubb38 \uc218\uc11d \uad00\ub9ac\uc790\uc790\uc138\ud788\uc11c\ubc84\ub9ac\uc2a4 \ucef4\ud4e8\ud305\uc73c\ub85c \ub9ac\uc18c\uc2a4 \uad00\ub9ac \uc81c\uac70Databricks SQL \uc11c\ubc84\ub9ac\uc2a4\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ud074\ub77c\uc6b0\ub4dc \uc778\ud504\ub77c\ub97c \uad00\ub9ac, \uad6c\uc131\ud558\uac70\ub098 \ud655\uc7a5\ud560 \ud544\uc694\uac00 \uc5c6\uc5b4\uc11c \ub370\uc774\ud130\ud300\uc774 \uc790\uc2e0\uc758 \uc77c\uc5d0 \ucd5c\uc120\uc744 \ub2e4\ud560 \uc218 \uc788\ub294 \uc5ec\uc720\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. Databricks SQL \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub294 \uc2a4\ud1a0\ub9ac\uc9c0\uc640\ub294 \ubd84\ub9ac\ud558\uc5ec \uc989\uac01\uc801\uc774\uace0 \ud0c4\ub825\uc801\uc778 SQL \ucef4\ud4e8\ud305\uc744 \uc81c\uacf5\ud558\uba70, \ub3d9\uc2dc\uc131\uc774 \ub192\uc740 \uc0ac\uc6a9 \uc0ac\ub840\uc5d0 \ub300\ud574 \uc790\ub3d9 \ud655\uc7a5\ud558\uc5ec \uc81c\ud55c \uc5c6\ub294 \ub3d9\uc2dc\uc131\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\u00a0\"Databricks SQL Serverless\uc5d0\uc11c Databricks SQL\uc758 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\uba74\uc11c \uc778\ud504\ub77c\ub97c \ud6e8\uc52c \ub354 \ud6a8\uc728\uc801\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\"\u2014 R. Tyler Croy, Scribd \ud50c\ub7ab\ud3fc \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubd80\ubb38 \ucc45\uc784\uc790\uc790\uc138\ud788\ucd5c\uace0\uc758 \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\ub3c4\ub85d \uc124\uacc4Databricks SQL\uc5d0\ub294 \uc218\ucc9c \uac00\uc9c0 \ucd5c\uc801\ud654\uac00 \ud3ec\ud568\ub418\uc5b4 \uc788\uc5b4 \uac01\uc885 \ub3c4\uad6c, \ucffc\ub9ac \ud0c0\uc785 \ubc0f \uc2e4\uc81c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ubaa8\ub450 \ucd5c\uc120\uc758 \uc131\ub2a5\uc744 \uc81c\uacf5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc5d0\ub294 \ucc28\uc138\ub300 \ubca1\ud130\ud654 \ucffc\ub9ac \uc5d4\uc9c4 Photon\uc774 \ud3ec\ud568\ub418\uba70, SQL \uc5d4\ub4dc\ud3ec\uc778\ud2b8\uc640 \ud568\uaed8 \uc0ac\uc6a9\ud558\uba74 \ub2e4\ub978 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 \ucd5c\ub300 12\ubc30 \uac00\uaca9-\uc131\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\u00a0\"Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ubd84\uc11d\uc744 \uc2e4\ud589\ud558\uc5ec \ud0c0\uac9f \ud589\ub3d9\uc5d0\uc11c \uc778\uc0ac\uc774\ud2b8\ub97c \ub3c4\ucd9c\ud558\ub294 \ub370 \ud544\uc694\ud55c \uc2dc\uac04\uc744 \uba87 \uc8fc\uc5d0\uc11c \uba87 \ubd84\uc73c\ub85c \ub2e8\ucd95\ud588\uc2b5\ub2c8\ub2e4.\"\u2014 Stephane Caron, CBC\/Radio-Canada \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4 \ubd80\ubb38 \uc218\uc11d \uc774\uc0ac\uc790\uc138\ud788\ud45c\uc900 SQL\ub85c \ud55c \uacf3\uc5d0\uc11c \ubaa8\ub4e0 \ub370\uc774\ud130 \uc800\uc7a5 \ubc0f \uad00\ub9ac\uac1c\ubc29\uc801 \ud615\uc2dd Delta Lake\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \ub370\uc774\ud130\uc5d0 \ud558\ub098\uc758 \uc0ac\ubcf8\uc744 \uc124\uc815\ud568\uc73c\ub85c\uc368 \ub370\uc774\ud130 \uc885\uc18d\uc744 \ud53c\ud558\uace0, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc14\ub85c \ubd84\uc11d\uacfc ETL\/ELT\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130\ub97c \uc774\ub3d9\ud558\uac70\ub098, \uc11c\ub85c \ubd84\ub9ac\ub41c \uc2dc\uc2a4\ud15c\uc5d0 \uc0ac\ubcf8\uc744 \uc800\uc7a5\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4. \uadf8\ub7f0 \ub2e4\uc74c, Databricks Unity Catalog\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc138\ubd84\ud654\ub41c \uac70\ubc84\ub10c\uc2a4, \ub370\uc774\ud130 \ub9ac\ub2c8\uc9c0, \ud45c\uc900 SQL\ub85c \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \uc190\uc27d\uac8c \ubc1c\uacac, \ubcf4\ud638\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u00a0\"Databricks\ub294 \uc6b0\ub9ac \ube44\uc988\ub2c8\uc2a4\uc758 \ud575\uc2ec\uc774 \ub418\uc5c8\uace0, Databricks\uc758 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub294 \uc2e4\ud589 \uac00\ub2a5\ud55c \ub370\uc774\ud130\uc5d0 \uc561\uc138\uc2a4\ud558\uc5ec \uc774\ub97c \uc800\uc7a5\ud558\uace0 \uacf5\uc720\ud560 \uc218 \uc788\ub294 \ud1b5\ud569\ub41c \ubc29\uc2dd\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\u2014 Jagan Mangalampalli, Punchh \ube45\ub370\uc774\ud130 \ubd80\ubb38 \ucc45\uc784\uc790\uc790\uc138\ud788\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc9c0\uc6d0\ud558\ub294 \uacf5\ud1b5\uc801 \ub370\uc774\ud130 \uae30\ubc18 \uad6c\ucd95Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ubaa8\ub4e0 \ubd84\uc11d \ub370\uc774\ud130 \uc694\uad6c \uc0ac\ud56d \ub4f1\uc5d0 \uac00\uc7a5 \uc644\uc804\ud558\uace0 \uc804\uccb4\uc801\uc778 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5 \uc194\ub8e8\uc158\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 \ub9e4\uc6b0 \uc801\uc740 \ube44\uc6a9\uc73c\ub85c \uc138\uacc4 \ucd5c\uace0\uc758 \uc131\ub2a5\uc744 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub300\uaddc\ubaa8\ub85c \uc6d0\ubcf8 \ub370\uc774\ud130\uc5d0\uc11c \uc2e4\ucc9c \uac00\ub2a5\ud55c \ub370\uc774\ud130\ub97c \uc5bb\ub294 \uc18d\ub3c4\ub97c \ub192\uc774\uace0 \ubc30\uce58\uc640 \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \ud1b5\ud569\ud569\ub2c8\ub2e4. \ub610\ud55c, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \ud300\uc740 \uc124\uba85\uc801 \ubd84\uc11d\uc5d0\uc11c \uc608\uce21\uc801 \ubd84\uc11d\uae4c\uc9c0 \uc790\uc5f0\uc2a4\ub7fd\uac8c \uc774\ub3d9\ud558\uc5ec \uc0c8\ub85c\uc6b4 \uc778\uc0ac\uc774\ud2b8\ub97c \ubc1c\uacac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u00a0\"Databricks\ub294 \ub370\uc774\ud130 \ubc0f \ubd84\uc11d \ud300\uc774 ABN AMRO \uc804\ubc18\uc758 \ub370\uc774\ud130\uc5d0 \uc561\uc138\uc2a4\ud558\uace0 \uacf5\uc720\ud560 \uc218 \uc788\ub294 \ub2e8\uc77c \ud50c\ub7ab\ud3fc\uc744 \uc81c\uacf5\ud558\uc5ec \uc804\uc0ac\uc801\uc73c\ub85c \uc790\ub3d9\ud654\ub97c \ucd94\uc9c4\ud558\uace0 \uc778\uc0ac\uc774\ud2b8\ub97c \ub3c4\ucd9c\ud558\ub294 ML \uae30\ubc18 \uc194\ub8e8\uc158\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\u2014 Stefan Groot, ABN AMRO \ubd84\uc11d \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ucc45\uc784\uc790\uc790\uc138\ud788Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130 \uc0ac\uc77c\ub85c, \ub290\ub9b0 \uc131\ub2a5, Hadoop\uc774\ub098 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub192\uc740 \ube44\uc6a9\uc5d0 \uc9c0\uce58\uc168\ub098\uc694? \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc138\uc694.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud1b5\ud569\uc5d0\ucf54\uc2dc\uc2a4\ud15c\uacfc \ub9e4\ub044\ub7fd\uac8c \ud1b5\ud569\ub418\ubbc0\ub85c \ub370\uc774\ud130 \ud300\uc758 \uc720\uc5f0\uc131\uc774 \uadf9\ub300\ud654\ub429\ub2c8\ub2e4. Fivetran\uc73c\ub85c \ube44\uc988\ub2c8\uc2a4\uc5d0 \uc911\uc694\ud55c \ub370\uc774\ud130\ub97c \uc785\ub825\ud558\uace0, dbt\ub85c \ubcc0\ud658\ud558\uace0, Power BI, Tableau \ub610\ub294 Looker\ub85c \uc0c8\ub85c\uc6b4 \uc778\uc0ac\uc774\ud2b8\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uacfc\uc815\uc5d0\uc11c \uc804\ud600 \uae30\uc874 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub85c \ub370\uc774\ud130\ub97c \uc774\ub3d9\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \uc218\uc9d1 \ubc0f ETL\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4BI \ubc0f \ub300\uc2dc\ubcf4\ub4dc+ \uc5ec\ud0c0 \ubaa8\ub4e0 Apache Spark\u2122\ufe0f \ud638\ud658 \ud074\ub77c\uc774\uc5b8\ud2b8\"\uc9c0\uae08\uc740 \uadf8 \uc5b4\ub290 \ub54c\ubcf4\ub2e4\ub3c4 \uae30\uc5c5 \uc870\uc9c1\uc5d0 \ubcc0\ud654\ud558\ub294 \uc0c1\ud669\uc5d0 \uc801\uc751\ud558\uae30 \uc704\ud55c \uc18d\ub3c4\uc640 \ubbfc\ucca9\uc131\uc744 \uc9c0\uc6d0\ud560 \ub370\uc774\ud130 \uc804\ub7b5\uc774 \uc808\uc2e4\ud55c \uc2dc\uae30\uc785\ub2c8\ub2e4. \uae30\uc5c5\ub4e4\uc774 \uc11c\ub458\ub7ec \ub370\uc774\ud130\ub97c \ud074\ub77c\uc6b0\ub4dc\ub85c \uc62e\uae30\uba74\uc11c, \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c \ubd84\uc11d\uc744 \uc218\ud589\ud558\ub294 \ubc29\uc2dd\uc5d0 \uad00\ud55c \uad00\uc2ec\uc774 \ub192\uc544\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. Databricks SQL\ub294 \uace0\uac1d\uc5d0\uac8c \ud544\uc694\ud55c \uc131\ub2a5, \uc548\uc815\uc131\uacfc \ud655\uc7a5\uc131\uc744 \uc644\ube44\ud55c \ub300\ub7c9\uc758 \ub370\uc774\ud130\uc5d0\uc11c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uac8c \ub418\ub294 \uc644\uc804\ud788 \uc0c8\ub85c\uc6b4 \uacbd\ud5d8\uc744 \uc81c\uace0\ud569\ub2c8\ub2e4. Databricks\uc640 \uc190\uc744 \uc7a1\uace0 \uadf8\ub7f0 \uae30\ud68c\ub97c \uc2e4\ud604\ud558\uac8c \ub418\uc5b4 \ubfcc\ub4ef\ud55c \uae30\ubd84\uc785\ub2c8\ub2e4.\"\u2014Francois Ajenstat, \ucd5c\uace0 \uc81c\ud488 \ucc45\uc784\uc790, Tableau\uace0\uac1d \uc0ac\ub840\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30Delta LakePartner ConnectUnity CatalogDelta Live \ud14c\uc774\ube14\uad00\ub828 \ucf58\ud150\uce20\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uc7a5\uc810\uc5d0 \ub300\ud55c eBook\uacfc \ub3d9\uc601\uc0c1\uc744 \ucc3e\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0 Bill Inmon\uc774 \uad6c\ucd95\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucc28\uc138\ub300 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc778 \uc774\uc720\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 Big Book\uc655\ucd08\ubcf4\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc774\ubca4\ud2b8Data + AI World Tour\ub85c \ubcf4\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ub0b4\ubd80 \uad6c\uc870\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uc131\ub2a5 \ud29c\ub2dd \ubaa8\ubc94 \uc0ac\ub840 \uc6e8\ube44\ub098 \u2013 \ucffc\ub9ac\uc758 \uc218\uba85 \ub0b4\uc5d0\uc11cDatabricks SQL \ubb34\ub8cc \uad50\uc721 \u2013 \uc628\ub514\ub9e8\ub4dc\ucd5c\uace0\uc758 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ube14\ub85c\uadf8Databricks, \uacf5\uc2dd \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5 \uc131\ub2a5 \uc2e0\uae30\ub85d \ub2ec\uc131Databricks SQL \uc815\uc2dd \ucd9c\uc2dcDatabricks\uc5d0\uc11c SQL \uc5b8\uc5b4\uc758 \ubc1c\uc804: Ansi \ud45c\uc900 \uae30\ubcf8 \uc9c0\uc6d0, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \uac04\ud3b8\ud55c \uc9c0\uc6d0Databricks\uc5d0\uc11c \ub354\uc6b1 \uac04\ub2e8\ud558\uac8c dbt \ubc30\ud3ecDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5 \ubaa8\ub378\ub9c1 \uae30\uc220 \ubc0f \uad6c\ud604Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c Fivetran \ubc0f dbt\ub97c \ud65c\uc6a9\ud558\uc5ec \ub9c8\ucf00\ud305 \ubd84\uc11d \uc194\ub8e8\uc158\uc744 \uc218\ucd95\ud558\ub294 \ubc29\ubc95\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ucee4\ubba4\ub2c8\ud2f0 \uac00\u0000\uc785\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/teach","text":"Databricks University | DatabricksDatabricks University AllianceMore educator resourcesIf you are new to the Databricks University community, the following resources may be helpful in getting you started teaching Databricks in both in-person and virtual classrooms:\u00a0Try Databricks for freeTo begin the sign-up process for a full-featured 14-day trial (bring a credit card and your own cloud resources) or to sign up for the Community Edition which is focused on students and educational institutions who are just getting started with Apache Spark.Free community edition\u00a0Learn the basic concepts behind Spark using Databricks in this tutorialYou will learn the basics of creating Spark jobs, loading data, and working with data. You\u2019ll also get an introduction to running machine learning algorithms and working with streaming data. Databricks lets you start writing Spark queries instantly so you can focus on your data problems.Learn more\u00a0Access free self-paced trainings available through Databricks AcademyDatabricks Academy is the training and certification organization at Databricks (must sign up with email address given to you by your educational institution).Learn more\u00a0View Databricks use cases and industry solutionsUse case solutionsIndustry solutions\u00a0Watch content on the Databricks YouTube channelFeaturing videos and live streams of\u00a0tech talks and online meet-ups as well as introductory workshops for college students\u00a0hosted by key Databricks engineers.See all our videosJoin the Databricks University AllianceProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/timothy-ahrens\/#","text":"Timothy Ahrens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTimothy AhrensMessaging Design Division Chief at Department of StateBack to speakersTim Ahrens is a civil service employee with the U.S. Department of State and currently serves as the Division Chief for the Information Resource Management Operations Messaging Systems Office, Messaging Design Division. As MD Division Chief, he leads business process re-engineering, design, development, agile delivery, and tier 3 operational support for five enterprise products: SMART, eRecords, FOIA technology stack, CDS, and the CfA Data.State technology platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/legal\/privacynotice","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. 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It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. 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We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. 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We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. 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You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/09\/22\/extracting-oncology-insights-from-real-world-clinical-data-with-nlp.html","text":"Extracting Oncology Insights from Real-World Clinical Data with NLP - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorExtracting Oncology Insights From Real-World Clinical Data With NLPby Amir Kermany, Moritz Steller, David Talby and Michael SankySeptember 22, 2021 in Engineering BlogShare this postPreview the solution accelerator notebooks referenced in this blog online or get started right away by downloading and importing the notebooks into your Databricks account.Cancer is the leading cause of death and disease in the U.S., and\u00a0 the numbers are staggering with nearly 2 million new cases of cancer expected to be diagnosed in the U.S. this coming year. Cancer also represents a significant portion of total U.S. healthcare spending, estimated at more than $200B in 2020. As such, the biopharmaceutical industry is heavily focused on oncology drug development. Nearly 40 new cancer drugs were approved by the FDA in 2019 and 2020 alone, and more than 1300 new medications and vaccines are in clinical development.Measuring the efficacy of oncology interventions is critical to matching patients with the right intervention. Oncology data, and related real-world evidence, have the potential to inform clinical research, trial design, regulatory decisions, safety assessments, treatment pathways and more.\u00a0 Unfortunately, given the highly specialized nature of oncology care, disease criteria and endpoints typically are not available in structured formats and remain locked in data silos, making them hard to aggregate and analyze.In oncology, pathology reports (often captured in PDF format and siloed in EMR systems), contain critical information, such as tumor size, grade, stage and histology. These variables, once extracted with a natural language processing (NLP) system, can be used to define disease cohorts, assess disease severity and create a baseline for disease progression, which then can be applied to the aforementioned use cases, ranging from clinical trial matching to treatment pathways. But extracting this information from unstructured clinical text data is often a huge pain point for data teams.John Snow Labs, the leader in healthcare NLP, and Databricks are tackling these challenges head-on and working with many customers across the healthcare ecosystem to translate unstructured oncology data into actionable evidence.Clinical natural language processing at scale with Databricks & John Snow LabsThe path forward begins with the Databricks Lakehouse Platform, a modern data platform that combines the best elements of a data warehouse\u2014such as data management and performance \u2014with the low cost, flexibility and scale of a cloud data lake. This new, simplified architecture enables health systems to unify all their data\u2014structured (e.g. diagnoses and procedure codes found in EHR databases), semi-structured (e.g. HL7, FHIR messages) and unstructured (e.g. free-text notes and images)\u2014 into a single, high-performance platform for both traditional analytics and data science.At the core of the Databricks Lakehouse Platform is Delta Lake, an open-source storage layer that brings performance (via Apache Spark\u2122), reliability and governance to a data lake. Healthcare organizations can land all of their data \u2013 including raw provider notes, radiology reports and PDF pathology reports \u2013 into Delta Lake. This preserves the original source of truth before applying any data transformations. By contrast, with a traditional data warehouse, transformations occur prior to loading the data, which means that all structured variables extracted from unstructured text are disconnected from the native text.Building on this foundation is John Snow Labs' Spark NLP for Healthcare, the most widely-used NLP library in the healthcare and life science industries. Optimized to run on Databricks, Spark NLP for Healthcare seamlessly extracts, classifies and structures clinical and biomedical text data with state-of-the-art accuracy at scale. It is the only native distributed open-source text processing library for Python, Java and Scala, and since every Spark NLP pipeline is a Spark ML pipeline, it is particularly well suited to building unified NLP and machine learning pipelines. Spark NLP provides Python, Java and Scala libraries with the full functionality of traditional NLP libraries (like spaCy, nltk, Stanford CoreNLP and Open NLP) and adds additional functionality, such as spell-checking, sentiment analysis and document classification. You can learn more about the joint Databricks and John Snow Labs solution in our previous blog, Applying Natural Language Processing to Health Text at Scale.Real-world oncology data abstraction in actionTo demonstrate the power of Databricks and John Snow Labs, we created a Solution Accelerator for abstracting real-world data from oncology notes. The solution accelerator contains sample data, prebuilt code and step-by-step instructions for ingesting and preparing oncology reports for downstream analytics and real-world evidence generation. The solution is ready to go in a Databricks notebook and to help you get started, we've included a brief walkthrough of the solution below.For this solution we used the MT ONCOLOGY NOTES dataset. It offers resources primarily in the form of transcribed sample medical reports across medical specialties and common medical transcription words\/phrases encountered in specific sections that form part of a medical report\u00a0 \u2013 sections such as physical examination or PE, review of systems or ROS, laboratory data and mental status exam, among others.We chose 50 de-identified oncology reports from the MT Oncology notes dataset as the source of the unstructured text and landed the raw text data into the Delta Lake bronze layer. For demonstration purposes, we limited the number of samples to 50, but the framework presented in this solution accelerator can be scaled to accommodate millions of clinical notes and text files.The first step in our accelerator is to extract variables using various models for Named-Entity Recognition (NER). To do that, we first set up our NLP pipeline, which contains annotators such as documentAssembler and sentenceDetector and tokenizer\u00a0 that are trained specifically for healthcare-related NER. In the example below, we combined bionlp_ner, which is a clinical NER model, and jsl_ner, which is a pre-trained deep NER model for clinical terminology. We see that the mesothelioma patient is experiencing symptoms such as coughing.Extracting named entities from texts is a great example of AI-assisted ETL: pre-trained deep learning (DL) models enable us to transform unstructured data into a structured format that can be used for downstream clinical analysis.Once we have the symptoms extracted, we can map to ICD-10 codes, which can be used for coding automation and improving Hierarchical Condition Category (HCC) coding accuracy for Medicare Risk Adjustment. We can further use this data to analyze treatment patterns and analyze the association between symptoms and oncological entities.Figure 1: Average risk indication for coded symptoms in the clinical datasetFigure 2: A visualization of symptom enrichment among most frequent conditions in the datasetWe can also generate a chart to study the assertion status of these symptoms as being present, absent or associated with someone else (for example, a family member).Continuing with the same note set, we run descriptive and visual statistics to display the most common oncology entities (example below) stratified by their assertion status.Figure 3: Assertion Status Of Most Common Symptoms.Next, we can look at treatments, including drug frequency and duration, which form the basis of oncology regimens. Below is a screenshot of the NLP model included in our solution notebook extracting drug treatment and duration information.We can then associate symptoms in relation to treatments, as well as disease statuses such as relapse, with confidence scores.This data is critical for ensuring both the quality of individual patient care and population-level research, which can help determine the efficacy and safety of interventions in the real world.Using the Databricks Lakehouse Platform, we can also easily create a database of conditions, symptoms and procedures, along with other relevant extracted information from the unstructured notes, which can then be used for downstream analysis, clinical decision support and research.With this solution accelerator, Databricks and John Snow Labs have opened the door to extract oncology data at scale with the quality required for real-world evidence generation.Get started extracting RWD from oncology notes with NLPTo use this solution, preview the notebooks online or get started right away by downloading and importing the notebooks into your Databricks account. The notebooks include guidance for installing the related John Snow Labs NLP libraries and license keys.You can also visit our industry pages to learn more about our Healthcare and Life Sciences solutions.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=new%20york%20city%2C%20new%20york","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thet-ko","text":"Thet Ko - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThet KoPrincipal Data Engineer at SEEKBack to speakersThet Ko has 10+ years experience working across the full stack from cloud infrastructure, databases, backend systems to front end development. He is currently a Principal Engineer at SEEK responsible for supporting over 165 engineers and scientists scale their analysis on Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jun-rong-lau","text":"Jun Rong Lau - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJun Rong LauData Engineer\/Analyst at GrabTaxi Holding Pte LtdBack to speakersFrom the Analytics Data Platform and Finance Data + AI transformation TeamLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/danica-fine","text":"Danica Fine - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDanica FineSenior Developer Advocate at ConfluentBack to speakersDanica Fine is a Senior Developer Advocate at Confluent where she helps others get the most out of their event-driven pipelines. In her previous role as a software engineer on a streaming infrastructure team, she predominantly worked on Kafka Streams- and Kafka Connect-based projects. She can be found on Twitter, tweeting about tech, plants, and baking @TheDanicaFine.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-hayes-0","text":"Matthew Hayes - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew HayesSoftware Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/a-new-approach-to-data-sharing","text":"\n\n\n\n\n\n\n\nA New Approach To Data Sharing\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/kr\/product\/data-lakehouse","text":"Databricks\uc758 \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc - \uc9c0\uae08 \ub370\ubaa8\ub97c \uc608\uc57d\ud558\uc138\uc694! | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5 \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \ud558\ub098\uc758 \ud50c\ub7ab\ud3fc\uc5d0 \ud1b5\ud569\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister now\ub2e8\uc21c\ud55c \uc624\ud508 \uba40\ud2f0\ud074\ub77c\uc6b0\ub4dcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc640 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc7a5\uc810\ub9cc\uc744 \uacb0\ud569\ud558\uc5ec \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc548\uc815\uc131, \uac15\ub825\ud55c \uac70\ubc84\ub10c\uc2a4, \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\uba74\uc11c\ub3c4 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uac1c\ubc29\uc131, \uc720\uc5f0\uc131, \uba38\uc2e0 \ub7ec\ub2dd \uae30\ub2a5\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\uc774\ub7ec\ud55c \ud1b5\ud569\uc801 \uc811\uadfc\ubc95\uc740 \uc9c0\uae08\uae4c\uc9c0 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ubd84\uc11d, BI, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4, \uba38\uc2e0 \ub7ec\ub2dd\uc744 \uad6c\ubd84\ud558\uace0 \ubcf5\uc7a1\ud558\uac8c \ud558\ub358 \ub370\uc774\ud130 \uc0ac\uc77c\ub85c\ub97c \uc81c\uac70\ud558\uc5ec \ud604\ub300\uc801 \ub370\uc774\ud130 \uc2a4\ud0dd\uc744 \uac04\uc18c\ud654\ud569\ub2c8\ub2e4. \uc624\ud508 \uc18c\uc2a4\uc640 \uac1c\ubc29\ud615 \ud45c\uc900 \uae30\ubc18\uc73c\ub85c \uad6c\ucd95\ud558\uc5ec \uc720\uc5f0\uc131\uc744 \uadf9\ub300\ud654\ud569\ub2c8\ub2e4. \ub370\uc774\ud130 \uad00\ub9ac, \ubcf4\uc548 \ubc0f \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\uc5d0 \uacf5\ud1b5\uc801 \ubc29\uc2dd\uc744 \uc801\uc6a9\ud568\uc73c\ub85c\uc368, \ud6a8\uc728\uc740 \ud5a5\uc0c1\ud558\uace0 \ud601\uc2e0\uc740 \ub192\uc774\ub294 \ud6a8\uacfc\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc2ec\ud50c\uc774 \ud1b5\ud569\uc801 \uc811\uadfc\ubc95\uc740 \uae30\uc874\uc5d0 \ubd84\uc11d, \ub370\uc774\ud130 \uacfc\ud559\uacfc \uba38\uc2e0 \ub7ec\ub2dd\uc744 \uad6c\ubd84\ud558\ub358 \ub370\uc774\ud130 \uc0ac\uc77c\ub85c\ub97c \uc5c6\uc560 \ub370\uc774\ud130 \uc544\ud0a4\ud14d\ucc98\ub97c \uac04\uc18c\ud654\ud569\ub2c8\ub2e4. \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \uc0ac\uc6a9\ud558\uba74 \ubd84\uc11d\uacfc AI \uc774\ub2c8\uc154\ud2f0\ube0c\uc758 \ubaa8\ub4e0 \uc7a0\uc7ac\ub825\uc744 \uc2e4\ud604\ud558\ub294 \ub370 \ubc29\ud574\uac00 \ub418\ub294 \ubcf5\uc7a1\uc131\uacfc \ube44\uc6a9 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc624\ud508Delta Lake\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0 \uc800\uc7a5\ub41c \ub370\uc774\ud130\uc5d0 \uc9c1\uc811 \uc548\uc815\uc131\uacfc \uc138\uacc4 \ucd5c\uace0 \uc218\uc900\uc758 \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\uc5ec \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uc624\ud508\ud615 \uae30\ubc18\uc744 \uad6c\uc131\ud569\ub2c8\ub2e4. \ubc30\ud0c0\uc801\uc73c\ub85c \uad6c\ud68d\uc744 \uad6c\ubd84\ud560 \ud544\uc694 \uc5c6\uc774 \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uacf5\uc720\ud558\uace0, \uc624\ud508 \uc18c\uc2a4 \ub370\uc774\ud130 \ud504\ub85c\uc81d\ud2b8\uc640 \uad11\ubc94\uc704\ud55c Databricks \ud30c\ud2b8\ub108 \ub124\ud2b8\uc6cc\ud06c\ub85c \uad6c\uc131\ub41c \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc5d0 \uc5b8\uc81c\ub4e0 \uc561\uc138\uc2a4\ud558\uc5ec \ud604\ub300\uc801 \ub370\uc774\ud130 \uc2a4\ud0dd\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \ud658\uacbd \uc804\ubc18\uc758 450+ \ud30c\ud2b8\ub108\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30\ub354 \uc54c\uc544\ubcf4\uc138\uc694\uba40\ud2f0\ud074\ub77c\uc6b0\ub4dcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0 \uc77c\uad00\uc801\uc778 \uad00\ub9ac, \ubcf4\uc548 \ubc0f \uac70\ubc84\ub10c\uc2a4 \ud658\uacbd\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc0ac\uc6a9\ud558\ub358 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc \ud50c\ub7ab\ud3fc\uc5d0 \ub300\ud55c \ud504\ub85c\uc138\uc2a4\ub97c \uc0c8\ub86d\uac8c \uac1c\ubc1c\ud558\uc9c0 \uc54a\uc544\ub3c4 \ub370\uc774\ud130\uc640 AI 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Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \ud65c\uc6a9\ud558\ub294 \uc7a5\uc810\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\ucd08\ubcf4\uc790\ub97c \uc704\ud55c \uac1c\ub860\uc11c: \ucd5c\uc2e0 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud328\ub7ec\ub2e4\uc784\uc758 \ubd80\uc0c1\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ubd80\uc0c1 by \ube4c \uc778\ubaac, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0Delta Lake\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 Big BookDelta Lake: \uc644\uc804 \uc815\ubcf5 \uac00\uc774\ub4dc(\uae00: O\u2019Reilly)Delta Lake \uc644\uc804 \uc815\ubcf5 \uac00\uc774\ub4dcDelta Lake: \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ucd08\uba38\uc2e0 \ub7ec\ub2ddeBook: ML \uc218\uba85 \uc8fc\uae30 \ud45c\uc900\ud654\uac00\uc0c1 \uc774\ubca4\ud2b8: \uba38\uc2e0 \ub7ec\ub2dd \ud50c\ub7ab\ud3fc \ube4c\ub4dc\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/trust\/privacy","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueOverview\n\u00a0Databricks takes privacy seriously. We understand that the data you analyze using Databricks is important both to your organization and your customers, and may be subject to a variety of privacy laws and regulations.\n\u00a0\nTo help you understand how Databricks fits into regulatory frameworks that may apply to you, we\u2019ve prepared Privacy FAQs and documents that transparently set forth how Databricks approaches privacy.ResourcesPrivacy PolicyPrivacy FAQsDatabricks SubprocessorsData Processing AddendumSecurity AddendumProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lindsey-woodland","text":"Lindsey Woodland - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLindsey WoodlandExecutive Vice President, Client Data Science at 605Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chunxu-tang","text":"Chunxu Tang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChunxu TangResearch Scientist at AlluxioBack to speakersDr. Chunxu Tang is a Research Scientist at Alluxio and a committer of PrestoDB. Prior to Alluxio, he served as a Senior Software Engineer in Twitter\u2019s data platform team, where he gained extensive experience with a wide range of data systems, including Presto, Zeppelin, BigQuery, and Druid. He received his Ph.D. from Syracuse University, where he conducted research on distributed collaboration systems and machine learning applications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zachary-huang","text":"Zachary Huang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZachary HuangPhD at Columbia UniversityBack to speakersZachary Huang is a PhD student at Columbia University. His research interests are in novel data management systems over large join graphs. His research works have been applied to data exploration, machine learning, and data market.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/austin-ford","text":"Austin Ford - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAustin FordStaff Product Manager at DatabricksBack to speakersAustin is a product leader and former mathematician from Columbus, Mississippi. He is currently a Sr. Product Manager at Databricks in San Francisco and is responsible for the Databricks Notebook and the data science development experience in Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/session_na20\/rapid-response-to-hospital-operations-using-data-and-ai-during-covid-19","text":"AboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLCDatabricks - YouTube"}
{"source":"https:\/\/www.databricks.com\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/events-policy\/#","text":"Events Policy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEvents PolicyPaymentsIn-person conference tickets and both in-person and virtual training will be assessed a fee and must be purchased with a credit card. Payment will be accepted in US dollars only. All registration fees must be paid in full prior to attending the conference. You will receive a payment confirmation and receipt via email once your credit card is processed and payment is complete. In order to receive the prices listed online you must complete and submit the online registration form by midnight (PST) on the deadline date. Any registration completed online after midnight (PST) will be processed at the next deadline price.\nPromo CodesIf you have a promo code, you must apply it at the time of your registration. Only one (1) promo code can be applied per registration.\nTransfers, Cancellation, and RefundsSubstitutions\/Registration Transfer\nSubstitution requests can be processed in person onsite or via written request at [email\u00a0protected]\u00a0 If requested in writing, please provide the names and emails of both the original and substitute registrants with both parties copied in the email. All requests for substitutions must be received no later than 5:00 p.m. (Pacific) on June 23, 2023. \u00a0 Onsite substitutions will incur a US $50 processing fee.\n\u00a0\nCancellations\nThe Databricks Registration Team must receive all cancellation requests in writing via email at [email\u00a0protected] by June 21, 2023.\n\u00a0\nPayment Information\nPayment accepted in US dollars only.\n\u00a0\nRefunds\nAll paid items (such as training or in person registration packages) will be refunded to the original form of payment.\n\u00a0\nWe will issue a full refund, less a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PT.\u00a0 Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PT, will be issued a 50% refund, less a 10% cancellation fee.\u00a0 No refunds will be offered for paid items after May 26, 2023.\n\u00a0\nRefunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record.\u00a0 If you have not received a refund by July 1, 2023, please contact the Databricks Registration Team at [email\u00a0protected]\n\u00a0\nPlease note: Any requests to change the payment method used for a completed registration will incur a $50 change fee. If you need to make a change, please contact the Databricks Registration Team at: [email\u00a0protected]\u00a0 Databricks reserves the right to deny registration to any individual or entity for any reason, in Databricks\u2019s sole discretion, including for past or present failure to meet Databricks\u2019s standards of conduct (including, but not limited to, engaging in violent, illegal, threatening, or discriminatory conduct).\u00a0 \u00a0 Payment terms are Net 30.\u00a0 Payment must be received in full to print attendee badge on-site.\nRegistration ConfirmationRegistration will be confirmed by email. You\u2019ll receive a message as soon as payment has been received and your registration has been processed.\nSpeakers & SessionsThe speakers listed on this website are leading professionals in their respective fields. Should a speaker be unable to attend the conference, all efforts will be made to replace him or her with one of comparable experience and qualifications. We are constantly working on improving the quality of our conference products. If the opportunity arises we may, at our discretion, add conference sessions and workshops to the posted line-up to enhance the schedule.\nPhoto Release & Privacy InformationFrom time to time Databricks may choose to photograph and record certain portions of the conference and may capture conference participants. Databricks may choose such photographs and recordings in our promotional materials. By virtue of your attendance at Data + AI Summit you consent to, Databricks\u2019 use of your likeness in such materials and you hereby waive \u201cmoral rights\u201d in such photos, recordings, or other digital content. You agree that any personal data you provide us will be handled in accordance with this Event Policy and our Privacy Policy.\n\u00a0\nYou may not record any sessions or sessions at Data + AI Summit without prior approval from Databricks.\n\nTerms of Use. Privacy Policy. Code of Conduct.\n\u00a0\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=people%20and%20hr","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/avanade-cpg-control-tower","text":"CPG Control Tower by Avanade | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionCPG Control Tower by AvanadeIndustry-specific solution developed by Avanade and powered by the Databricks Lakehouse PlatformGet startedGet control of your supply chainCustomer needs are shifting faster than ever before, and organizations in the consumer packaged goods (CPG) industry need better insights to outpace change across their business. Avanade\u2019s solution, the CPG Control Tower, gives you unprecedented oversight of your supply chain and manufacturing operations. The solution can help you find valuable insights through a direct view of the data impacting your business, empowering smarter business decisions surrounding financial performance, operational excellence, risk and more. Use the Control Tower to produce a resilient, profitable and customer-centric supply chain.Ability to model scenarios and impact on supply chain 2\u20133x fasterReduction in idle \u201ctrapped\u201d cash, adjusted use of credit lines, reduction of bank fees, and a more concentrated cash positionAvanade clients using CPG Control Tower have seen a greater than 10% return on investment as well as a 10%\u201312% sales increaseGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks - Unifica tutti i carichi di lavoro di analisi e AI | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWAzure DatabricksServizi di gestione dei dati e AI di Databricks, forniti attraverso Microsoft Azure, per conservare tutti i dati su un semplice lakehouse aperto e per unificare tutti i carichi di lavoro di analisi e AI.CominciaProgramma una demoAzure Databricks \u00e8 ottimizzato per Azure e strettamente integrato con Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI e altri servizi Azure per conservare tutti i dati su un semplice lakehouse aperto e unificare tutti i carichi di lavoro di analisi e AI.Semplice\nUnifica dati, analisi e AI\nsu una piattaforma comune per tutti i casi di utilizzo dei datiAperta\nUnifica l'ecosistema di dati\ncon open source, standard e formatiCollaborativa\nUnifica i team di dati\nper collaborare lungo tutto il flusso di lavoro di gestione dei dati e AIPerch\u00e9 Azure DatabricksPrestazioni 50 volte superiori per carichi di lavoro Apache Spark\u2122\nImplementa cluster di calcolo auto-scalabili con Spark altamente ottimizzato che offrono prestazioni fino a 50 volte pi\u00f9 veloci.Maggiori informazioniMilioni di ore-server al giorno\nAzure Databricks ha conquistato la fiducia di migliaia di clienti che ogni giorno eseguono milioni di ore di lavoro sui server in oltre 34 regioni Azure.Maggiori informazioniFacilit\u00e0 d'uso\nComincia con un solo clic nel portale di Azure, effettua l'integrazione nativa con i servizi di sicurezza e dati di Azure e aumenta la produttivit\u00e0 fino al 25% grazie ad attivit\u00e0 collaborative di data engineering e data science.Maggiori informazioniCasi d'uso per settoreServizi finanziariSwiss Re\nAnalisi dei dati unificata per data engineering, data science e analisti.HSBC\nHa costruito una piattaforma di pagamento digitale utilizzando Azure Databricks.ABN AMROHa migliorato i flussi di lavoro di analisi grazie a collaborazione, approfondimenti AI e funzionalit\u00e0 avanzate di machine learning automatizzato.Maggiori informazioniretailSanit\u00e0 e bioscienzePartecipa a un evento Azure DatabricksDatabricks, Microsoft e i rispettivi partner sono entusiasti di ospitare questi eventi dedicati ad Azure Databricks. Unisciti a noi partecipando a un evento nella tua zona per conoscere meglio il servizio Dati + AI che cresce pi\u00f9 velocemente su Azure! Il programma e il formato sono diversi per ogni evento, consulta la pagina dedicata per conoscere tutti i dettagli.\u00a0Maggiori informazioniOttimizzato per AzureIntegrazione diretta con data store e servizi di Azure tramite connettori specifici, per un accesso veloce ai dati e una gestione semplificata in tutto l'ambiente. Con questo approccio risulta facile impostare i controlli di sicurezza, gestire gli ambienti ed elaborare tutti i dati su Azure.Maggiori informazioniIntegrazioni disponibiliAzure Active DirectorySingle Sign-On (accesso unico) con Azure Active Directory \u00e8 il modo migliore per accedere ad Azure Databricks. Azure Databricks supporta anche il provisioning automatizzato degli utenti con Azure AD per creare nuovi utenti, fornire loro il livello di accesso appropriato ed eliminare utenti per disabilitare l'accesso.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultRisorseWhitepaperAzure Databricks per data engineeringAzure Databricks: la piattaforma migliore per ML e AITre casi d'uso pratici con Azure DatabricksPrimi passi con Apache Spark su Azure DatabricksVideoAli Ghodsi e Rohan Kumar (CVP, Microsoft), conversazione davanti al caminetto al Keynote Data + AI Summit NA 2021Demo integrazione in cloud di Databricks su AzureIngestione di dati in Delta Lake su Azure DatabricksEsplorazione di dati con Databricks SQLeBookGartner Magic Quadrant 2021 per piattaforme di data science e machine learningPiattaforme moderne per la gestione di dati in cloud per principianti8 passi per gli sviluppatori che vogliono imparare a usare Apache Spark\u2122 con Delta LakeApache Spark\u2122 visto da dentro: introduzione all'architettura e ai concetti chiavePronto per cominciare?CominciaProgramma una demoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stefania-leone","text":"Stefania Leone - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStefania LeoneSr. Manager Product Management at DatabricksBack to speakersStefania is a product manager at Databricks working on the Databricks Runtime. She holds a PhD in Computer Science from ETH Zurich.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/corey-zumar\/#","text":"Corey Zumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCorey ZumarSoftware Engineer at DatabricksBack to speakersCorey has been working as a Software Engineer at Databricks for the last 4 years and has been an active contributor to and maintainer of MLflow since its first release.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hari-shankar\/#","text":"Hari Shankar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHari ShankarSenior Director, R&D at VizioBack to speakersHari Shankar is the Senior Director of R&D, Data Engineering, for Vizio, the connected home and entertainment leader. At Vizio, Hari was responsible for leading their Databricks and lakehouse migration, as well as managing their AdTech platform strategy. Prior to Vizio, Hari worked at Samsung, NetApp, and Sun Microsystems in technical leadership roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ioannis-papadopoulos\/#","text":"Ioannis Papadopoulos - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIoannis PapadopoulosCloud Technologist at DatabricksBack to speakersIoannis is a Cloud Technologist at Databricks, working in collaboration with the technical fields of AWS, Azure, and GCP.\nHe started his career at CERN as a research physicist and then moved to Apple to lead the business development of the research markets in EMEA.\nBefore joining Databricks, Ioannis had co-founded 3 startups, where he championed the development of serverless architectures on the cloud. \nIoannis holds a Ph.D. in Physics, an MBA, and an Executive Master in digital transformation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/retail-industry-solutions","text":"La soluzione di data lakehouse per commercio al dettaglio e largo consumo - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWScopri Lakehouse for RetailLa piattaforma unificata per dati, analisi e AI utilizzata dalle aziende retail per ottimizzare l'offerta in ogni fase del percorso del clienteRegistratiContattiPrestazioni migliori, portata pi\u00f9 ampia, costi di gestione (TCO) minoriLakehouse per il retailUnifica i carichi di lavoro di dati e AI con condivisione e governance integrate, in modo che i team interni ed esterni abbiano accesso ai dati di cui hanno bisogno, quando ne hanno bisognoImpatto su tutta la catena del valoreCoinvolgimento del clientePertinenza e iper-personalizzazione in ogni punto di contattoGrazie a viste dei clienti a 360\u00b0, precise e in tempo reale, le aziende di commercio al dettaglio hanno tutto ci\u00f2 che serve per instaurare relazioni personalizzate con ciascun cliente, grazie alla capacit\u00e0 di intercettare il sentiment su tutti i canali e personalizzare le raccomandazioni. Risultato: maggiore redditivit\u00e0 e fidelizzazione.Efficienza operativaProduttivit\u00e0 dei dipendentiPrestazioni dei prodottiSoluzioni e partner nel settore retailSoluzioni di analisi dei dati e AI senza compromessi realizzate appositamente per il tuo settoreGli Acceleratori Databricks sono guide specifiche \u2014 notebook con funzionalit\u00e0 complete e best practice \u2014 che velocizzano il raggiungimento di risultati nel commercio al dettaglio. Risparmia tempo nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo per casi d'uso come punteggi di propensione agli acquisti, valore del ciclo di vita del cliente (CLV), ottimizzazione del prelievo di ordini e altro ancora.Previsioni granulariGenerare previsioni su larga scala in meno tempo\nGenera previsioni granulari a livello di singolo negozio-articolo in modo efficiente, sfruttando la potenza di calcolo distribuita della Databricks Lakehouse Platform.CominciaSegmentazione clientiSegmentare i clienti per indirizzare meglio le iniziative\nCrea categorie di clienti avanzate utilizzando dati di vendita, campagne, sistemi promozionali e altri strumenti per migliorare le previsioni di acquisto in base ai comportamenti.CominciaAnalisi del punto vendita in tempo realeCalcolare in tempo reale gli inventari di molteplici negozi per migliorare i margini di guadagno nel commercio al dettaglio\nAcquisisci rapidamente tutte le sorgenti e le tipologie di dati dei punti vendita, su larga scala, per ricavare dati approfonditi in tempo reale che soddisfano il fabbisogno pressante di informazioni sui negozi.CominciaScopri gli acceleratori per il commercio al dettaglioAbbiamo collaborato con le principali societ\u00e0 di consulenza per fornire soluzioni innovative per settori specifici. Le soluzioni Databricks Brickbuilder aiutano a ridurre i costi e aumentare il valore generato dai dati. Con decenni di competenze settoriali alle spalle \u2014 e specificamente costruite per la Databricks Lakehouse Platform \u2014 le soluzioni Brickbuilder sono ritagliate su misura per le tue esigenze.Vista unificata della domandaMassimizzare la precisione, la granularit\u00e0 e la puntualit\u00e0 con un piano della domanda che attinge a un'unica \"fonte della verit\u00e0\".Maggiori informazioniGestione della crescita dei ricaviEseguire rapidamente l'analisi di dati di fatturazione, dati di mercato esterni, notizie e web scraping (estrazione di dati da siti web) per analizzare modalit\u00e0 e schemi ricorrenti del commercio al dettaglio.Maggiori informazioniTrellisRisolvere problematiche di previsione della domanda, rifornimenti, approvvigionamenti, prezzi e servizi promozionali.Maggiori informazioniScopri le soluzioni Brickbuilder\u201cOra riusciamo a combinare, per ogni singolo cliente, le informazioni sugli acquisti online e offline, un'attivit\u00e0 che in passato era molto complessa. Questa vista omnicanale ci consente di creare un motore di raccomandazioni online pi\u00f9 completo, che favorisce un notevole coinvolgimento\u201d.\n\u2014 Wendell Kuling, Manager of Data Science and Analytics, Jumbo\n\u201cDatabricks ci consente di avere le prestazioni migliori e offrire al cliente esperienze best-in-class in ogni settore. Grazie alla Lakehouse Platform, i nostri responsabili e sviluppatori possono lavorare in modo pi\u00f9 collaborativo, individuando le tendenze principali e acquisendo le informazioni approfondite e dettagliate necessarie per servire i nostri oltre 180 milioni di clienti\u201d.\n\u2014 Sergiy Tkachuk, Head of Data Science, Reckitt\nSempre pi\u00f9 reparti utilizzano la piattaforma con una modalit\u00e0 self-service che in passato non era possibile. Non esistono parole adeguate per descrivere l'impatto positivo di Databricks su Columbia\u201d.\n\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear\nRisorseTour autoguidatoTutte le risorse di cui hai bisogno per conoscere Lakehouse for RetailWebinarPrendere decisioni in tempo reale nel commercio al dettaglioeBookIl grande libro dei casi d'uso nel commercio al dettaglioProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speakers?itm_data=hp-featured-speakers-dais23","text":"Speakers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpeakersBrowse the roster to find new and familiar faces alike. The Data + AI Summit draws experts from all over the globe across a wide array of fields.\nFeatured speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAll speakersAayush PatelData & Platform EngineerSkywatchAbhishek PatelHead of Databricks COELTIMindtreeAdam WilsonCo-Founder, Chief of ProductDivirod, Inc.Adi PolakData & AI TechnologistTechnologistAdriana IspasStaff Product ManagerDatabricksAikaterini KalouPrincipal Data ScientistCitrixAjali SenSenior ManagerAccentureAjmal AzizSolutions ArchitectDatabricksAkira AjisakaSenior Software Development EngineerAmazon Web ServicesAlain BrianconVP Data Science Profiles by KantarKantar GroupAlbert HuSenior Analytics EngineerRec RoomAlessandro GaravagliaLead ML EngineerGucciAlexander BoothAssistant Director of Research & DevelopmentTexas Rangers Baseball Club, LLCAlexander VanadioPrincipal ConsultantOptivAli GhodsiCo-founder and CEODatabricksAlon GubkinCo-Founder & CTOAporiaAman KapoorHead of Data PlatformPetronasAmanda MilbergSenior Partner Sales EngineerDataikuAmine BenhamzaLead Solutions ArchitectDatabricksAmir SkovronikDistinguished Software EngineerAkamaiAmrinder Singh OberaiEMR Migrations LeadDatabricksAnanya GhoshBusiness Application Owner for DatabricksNationwide InsuranceAndrew BlanceInnovation ConsultantWaterstonsAndria FuquenTechnical Program ManagerImmutaAndy HanksSenior Data Architect, Analytics PlatformCRISP Shared ServicesAnfisa KaydakVP, Data Product & EngineeringHealthverityAngela ChuSenior Solution ArchitectDatabricksAnil PuliyerilSenior ArchitectHabuAnindita MahapatraLead Solutions ArchitectDatabricksAnindya SahaML Platform Software EngineerAnkit MathurTech Lead, Model Serving GPUsDatabricksAnna RussoGlobal Director of Data ScienceGucciAnton OkolnychyiSoftware EngineerAppleAntoni BaumSoftware EngineerAnyscaleAntonio CasteloCollibraAnup SeguCo-Head of Data EngineeringYipitDataArtem MeshcheryakovConsultantORAYLIS GmbHArthur LiSenior Software EngineerInstacartArujit PradhanSoftware EngineerCoinbaseArun PamulapatiSr. Staff Security Field EngineerDatabricksAshwin GangadharSenior Solutions ArchitectMongoDBAtiyah CurmallyPrincipal Environmental SpecialistInternational Finance CorporationAustin FordStaff Product ManagerDatabricksAvinash SooriyarachchiSenior Solutions ArchitectDatabricksBalaji RamanujamAVP - Senior Principal Technology ArchitectInfosysBasak EskiliML EngineerAhold DelhaizeBehzad BordbarLead Data ScientistMarks & SpencerBeinan WangSenior Staff Software EngineerAlluxioBen CoppersmithSr. Manager, Data PlatformDisney StreamingBen WilsonPrincipal Specialist Solutions ArchitectDatabricksBeth MattsonSenior Data EngineerOur Family WizardBin MuVice President and Head of Data & AnalyticsAdobeBinwei Yangsoftware engineerintelBlaise SandwidiLead Data Scientist, As. ESG Officer, PhDInternational Finance Corporation (IFC)\u2013World Bank GroupBob ZhangSenior Technical Program ManagerMicrosoftBrad CorwinChief Data ScientistBooz Allen HamiltonBradley AxenMachine Learning EngineerBlockBrendan BarsnessData and Analytics ArchitectDeloitteBrooke WenigDirector, Machine Learning PracticeDatabricksCan ElfeogluStaff Product ManagerDatabricksCelia KungEngineering ManagerDatabricksChang SheCEOLanceDBChao SunSoftware EngineerAppleChen GuoStaff Software EngineerCoinbaseChris StevensSenior Staff Software EngineerDatabricksChris VoLead Member of Tech StaffAT&TChris InkpenSolutions architectHoneywellChris HechtDatabricksChris MantzData ArchitectSlalomChristian Acu\u00f1aSenior Data EngineerGrammarlyChristian HamiltonDirector, Data Science Technology84.51Christina TaylorData EngineerToptalChristina TaylorSenior Staff Data EngineerCatalyst SoftwareChristopher LocklinEngineer Manager, Data PlatformGrammarlyChunxu TangResearch ScientistAlluxioCody FergusonData & AI Management Branch ChiefChief Digital and Artificial Intelligence Office - AdvanaCorey ZumarSoftware EngineerDatabricksCorey ZwartChief Technology OfficerPumpJack DataworksCort LunkeData & Analytics Lead - TruterraLand O'LakesCraig WileySr. Director of Product, Lakehouse AIDatabricksCyrielle SimeonePrincipal Product Marketing ManagerDatabricksDael WilliamsonField CTODatabricksDan HoustonManager, Data Science and Exploration Advanced AnalyticsUSPSDan SmithHead of Technology Data & AnalyticsPerenti GroupDanica FineSenior Developer AdvocateConfluentDaniel TenedorioSr. Staff Software EngineerDatabricksDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL)MITDarshana SivakumarStaff Product ManagerDatabricksDarth VaderSith LordThe Galactic EmpireDatin Ts. Habsah Binti NordinChief Data OfficerPETRONASDavid SkinnerChief Strategy OfficerAcxiomDavid TempelmanResident Solutions ArchitectDatabricksDawn SongProfessor, Department of Electrical Engineering and Computer ScienceUC BerkeleyDeepa ParanjpeDirector of EngineeringDiscoveryDeepak SekarSr. Solution ArchitectDatabricksDenny LeeSr. Staff Developer AdvocateDatabricksDerek SlagerCTOAmperityDerek SugdenAd Measurement Lead \u2013 Measurement & AttributionEffectvDevlina DasSenior Software EngineerInstacartDeylo WooData Engineer ArchitectProvidence Health ServicesDilip BiswalSenior ArchitectAdobeDillon BostwickSolutions ArchitectDatabricksDipankar MazumdarDeveloper AdvocateDremioDon ScottVP, New Product DevelopmentHitachi Solutions AmericaDon Bosco DuraiCofounder and CTOPrivaceraDonghwa KimSr. Director of IT ArchitectureOntada, a McKesson CompanyDouglas MooreLead Specialist Solutions ArchitectDatabricksDurga KalaSr. DirectorVisa Inc.Egor GryaznovCTO and Co-founderBigeyeEllen SulcsDirector, Data Products & EngineeringT-MobileEllie HajarianSnr IT ManagerTD BankElliot ShmuklerCo-Founder & CEOAnomaloEmad MostaqueCEOstability.aiEric PeterSr Staff Product ManagerDatabricksEric SchmidtFormer CEO and Chairman, Google; Co-FounderSchmidt FuturesErika EhrliSenior Director of Product MarketingDatabricksErin BoelkensVP of ProductLiveRampErni DurdevicSpecialist Solutions Architect (Geospatial)DatabricksFabian JakobsSr Staff Software EngineerDatabricksFabien CochetIT Expert on Data and AnalyticsMichelinFabio Luis Correia da SilvaArchitecture SpecialistBradescoFaraz YasrobiSoftware EngineerGrammarlyFrancisco RiusHead of Data Science and Data EngineeringMinecraft at MicrosoftFranco PatanoProduct SpecialistDatabricksFrank MunzPrincipal Technical Marketing EngineerDatabricksGanesh DeivarayanSr ManagerAmerican AirlinesGaurav SarafProduct ManagerDatabricksGavita RegunathPrincipal Data ScientistAdvancing AnalyticsGeoffrey FreemanSolutions ArchitectT-MobileGidon GershinskyLead Systems ArchitectAppleGilad AsulinBig Data Engineer Team LeaderAkamai Technologies, IncGreg NelsonVP of Data OperationsHighmark HealthGreg KroleskiProduct ManagementDatabricksGregory LittleDCDAO for Enterprise Platforms and Business OptimizationDoD CFO Transformation OfficeHannes M\u00fchleisenCo-Founder and CEODuckDB LabsHao ZhuSenior ManagerNVIDIAHari ShankarSenior Director, R&DVizioHari RajaramSr Director \/ Principal Data ArchitectProcoreHarrison ChaseCEOLangChainHarsh MishraLead Enterprise ArchitectAustralian Rail Track CorporationHeiko UdluftChief Technology OfficerDivirod, Inc.Himanshu AroraResident Solutions ArchitectDatabricksHimanshu RajaDatabricksHitesh SahniHead of Cloud Data Platforms and Data Engineering SolutionsDeutsche Post DHLHolly SmithSenior Resident Solutions ArchitectDatabricksHuaxin GaoSoftware EngineerAppleHyukjin KwonStaff Software EngineerDatabricksIan SotnekDirector of ProductAI Squared, IncIan GallowaySenior Director, ApplicationsCollins AerospaceIfigeneia DerekliField Engineering Manager & Unity Catalog SpecialistDatabricksIoannis PapadopoulosCloud TechnologistDatabricksItai YaffeSenior Big Data ArchitectAkamaiIvan PengSoftware EngineerDoorDashJacek LaskowskiIT Freelancerjapila.plJackie BrosamerDirector of Software EngineeringBlockJacob RennChief TechnologistAI Squared, IncJacolon WalkerCo-founder & CTOMonadJaison DominicSenior Manager Information SystemsAmgenJames DemmelDr. Richard Carl Dehmel Distinguished ProfessorUniversity of California, BerkeleyJames NormanPrincipal Software EngineerNikeJamie BakerDirector of ProductMatillionJason ShiverickData Platform ManagerRivianJay BhankhariaSenior Director, Data PartnershipsDatabricksJay YangPrincipal Data EngineerProcoreJeff Breeding-AllisonSenior Data ScientistMars PetcareJeff MrozTechnical SME for Cloud and Big DataWoolpert \/ US Army Corps of EngineersJeffrey HessLead TechnologistBooz Allen HamiltonJeffrey ParkinsonVP, Core Data EngineeringNorthwestern MutualJeffrey ChouCo-Founder, CEOSync ComputingJegadeesan PugazhenthiLead Big Data EngineerAT&TJeremy LewallenProduct ManagerDatabricksJiajun YaoSoftware EngineerAnyscaleJim HibbardSenior Developer AdvocateDatabricksJim ThorstadSolutions ArchitectDatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchUniversity of California at BerkeleyJoanna GurryExecutive, Data DeliveryNational Australia Bank (NAB)Joe WalshDirector of Measurement & AttributionEffectvJohn RousselCIOCalifornia Department of Public Health (CDPH)John ThompsonGlobal Head, Artificial IntelligenceEYJohn KutayDirector of Product ManagementStriimJon OsbornField CTOAscend.ioJonathan KellerSr. Director, Product ManagementDatabricksJonathan HollanderVP, Enterprise Data Technology PlatformsTD BankJonathan NeoData EngineerCanvaJordan PeckPrincipal Technical Account ManagerSnowplowJordan DonmoyerManager, Customer Data SolutionsThe Hershey CompanyJoseph SarsfieldMachine Learning EngineerMarks & SpencerJoseph BradleyLead Product SpecialistDatabricksJules DamjiLead Developer AdvocateAnyscaleJulie FerrisVice President, Commercial OptimizationDefinitive HealthcareJulien Le DemChief ArchitectAstronomerJun Rong LauData Engineer\/AnalystGrabTaxi Holding Pte LtdJunta NakaiRVP, Industry Solutions, Financial Services and SustainabilityDatabricksJustin BreeseSr. Product ManagerDatabricksJustin DeBrabantSVP of ProductActionIQJustin LaiDistinguished Data ArchitectBlackBerryJustin ThompsonDirector, IT Data and AnalyticsJetBlueKarthik RamasamyHead of StreamingDatabricksKasey UhlenhuthStaff Product ManagerDatabricksKeith AndersonSolution PrincipalHitachi SolutionsKeshav SanthanamPhD StudentStanford UniversityKetan GanatraSolution ArchitectDatabricksKieran TaylorSenior Software Engineer IIInstacartKrishti BikalSenior Executive - Director BI & AnalyticsEmeraldKyle HaleProduct SpecialistDatabricksKylie TaylorData ScientistMars PetcareLakhan PrajapatiDirector of Architecture and EngineeringZS associatesLarry FeinsmithHead of Global Tech Strategy, Innovation and PartnershipsJP Morgan Chase & Co.Lee YangSr. Principal SW EngineerNVIDIALeena DalviAssistant Vice President, Enterprise Data & AnalyticsNavy Federal Credit UnionLeo DuncanSr. Solutions ArchitectKyvos Insights Inc.Leon EllerSolutions ArchitectDatabricksLewis MbaeHead of Customer EngineeringRudderStackLin QiaoCo-creator of PyTorch, Co-founder and CEOFireworksLindsay MicoHead of Data ScienceProvidence HealthLindsey WoodlandExecutive Vice President, Client Data Science605Lior GavishCTO and Co-founderMonte Carlo DataLiping HuangSenior Solutions ArchitectDatabricksLorenzo De TomasiData Architect, Data Platforms Lead at BarillaBarilla G. e R. Fratelli S.p.A.Lucas dos Santos CelestinoPlatform Product ManagerAB InbevLuk VerhelstData ArchitectVolvo Group (consultant)Luyang WangLead Distinguished ScientistVerizonMacGregor WinegardAssociate Data EngineerKPMGMaciej SzpakowskiCo-founderProphecyMadalina TanasieChief Technology OfficerCollibraMaggie DavisPrincipal, Data EngineeringSlalomMahesh PrakriyaDirector in Intelligence PlatformMicrosoftMalav ShahSenior Data ScientistDIRECTVManbir PaulVP of Engineering, Data Insights and MarTechSephoraMani KandasamyTech FellowDeloitte Consulting LLPManu SharmaCEOLabelboxMarcel KramerHead of Data EngineeringABN AMRO Bank N.VMaria VechtomovaML EngineerAhold DelhaizeMaria DaibertData Platform Product ManagerAB InbevMarianna CervinoGlobal Data ScientistGucciMarius PangaSolutions ArchitectDatabricksMark LeeSenior Specialist Solutions ArchitectDatabricksMark D'AndreaGlobal Chief Revenue OfficerAccuweatherMartin GrundSenior Staff Software EngineerDatabricksMat KeepSenior Director, MongoDB Products TeamMongoDBMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflowDatabricksMatt McKenzieGM, TechnologyTabcorpMatteo QuattrocchiDirector, Policy-EMEABSAMatthew HayesVice President of SAP BusinessQlikMatthew PowersDeveloper AdvocateDatabricksMatthew HayesSoftware EngineerDatabricksMatthew DoxeySenior EpidemiologistWashington State Department of HealthMatthew KarasickChief Product OfficerHabuMaxime AgostiniCEOSarus Technologies IncMeena RamSr Director, Enterprise Data and Records Management OfficeCIBCMegan FogalSolutions ArchitectDatabricksMenglei SunSenior Software EngineerDatabricksMiao WangSenior Engineering ManagerAdobeMichael ShtelmaLead Specialist Solutions ArchitectDatabricksMichael ArmbrustDistinguished EngineerDatabricksMichael GreenSenior Data ScientistHitachi Solutions AmericaMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious DiseasesCalifornia Department of Public Health (CDPH)Michael SankyRVP, Industry Solutions, Healthcare and Life SciencesDatabricksMike ConoverSoftware EngineerDatabricksMike TangAssociate Director, Responsible AIVerizonMike Del BalsoCo-founder + CEOTectonMilos ColicTech Lead EMEA Public Sector - Sr. Solutions ArchitectDatabricksMiranda LunaProduct ManagementDatabricksMitch ErtlePartner Solutions EngineerSigma ComputingMohan KolliIT DirectorLabCorpMorgan HsuDirector, Data and ML EngineeringFanDuelMostafa MokhtarPrincipal Software EngineerDatabricksMurali MadireddiArchitectAccentureNabil RaadSVP of Data and AnalyticsGM FinancialNadine FarahHead of Dev RelOnehouseNaresh YegireddiStaff Data EngineerIndigo AGNat FriedmanCreator of Copilot; Former CEOGithubNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North AmericaHitachi Solutions America Ltd.Naveen ZutshiChief Information OfficerDatabricksNeil PatelLead Specialist Solutions ArchitectDatabricksNic JansmaSenior Principal Lead EngineerAkamaiNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, TechnologyGlaxoSmithKlineNick KingFounder & CEOData KineticNicolas PelaezTechnical MarketingDatabricksNihar ShethSenior Product ManagerAWS - AmazonNitu NiveditaManaging DirectorAccentureNoam BresslerML Team LeadDeepchecksNoritaka SekiyamaPrincipal Big Data ArchitectAmazon Web ServicesOliver DykstraData EngineerTexas RangersOnik KurktchianHead of S&P Global Marketplace WorkbenchS&P GLOBALOri ZoharPrincipal Product Marketing ManagerDatabricksOz KatzCTO @ Treeverse, co-creator of lakeFSTreeverse LTDPakshal Kumar H DhelariaSenior Software Engineer 1CitrixPamela PettitSolutions ArchitectDatabricksParth ChandraSoftware EngineerApplePascal van BellenSenior ConsultantORAYLIS GmbHPatrick HallPrincipal Scientist | Visiting FacultyBNH.AI | GWUPaul RoomeStaff Product ManagerDatabricksPaul MracekSenior Solutions ArchitectDatabricksPaul WellmanVP, Executive Product Owner, Data-as-a-ServiceTD BankPaul MarshSenior Director Application DevelopmentNew York JetsPaula MartinezCEO & CofounderMarvikPearl UbaruSr. Technical Marketing EngineerDatabricksPedro BoaretoChapter Leader of Analytics EngineeringBradescoPercy LiangProfessor of Computer ScienceStanfordPhilippe LeonhartDigital Transformer, Corporate Business ServicesMichelinPieter NoordhuisSr. Staff Software EngineerDatabricksPouya Barrach-YousefiData Pro and Director Strategic AccountsProphecyPrashanth BabuLead Product SpecialistDatabricksPrateek ChawlaFounding EngineerMonte CarloPraveen VemulapalliDirector- TechnologyAT&TPravin DarbareVice President of Data AnalyticsWorkdayPritesh PatelPublic Sector Leader, UK&IDatabricksPulkit ChadhaSr. Solutions ArchitectDatabricksRafael BarcelosSoftware ArchitectMicrosoft CorporationRafi KurlansikLead Solutions ArchitectDatabricksRaghu JayachandranSenior Manager Enterprise DataRaceTrac Inc.Rahil BhatnagarDevelopment Lead, LOLAAnheuser BuschRahul PandeySolution ArchitectadidasRajesh IyerVice President Financial Services Insights & DataCapgeminiRakesh KumarStaff Software EngineerLyft IncRakesh SinghLead ArchitectABN AMRO Bank N.VRashmi KansakarDirector, Data & Cloud Architect84.51Rekha BachwaniEngineering Director, ML EngineeringThe Walt Disney CompanyReynold XinCo-founder and Chief ArchitectDatabricksRicardo PortillaPrincipal Solution ArchitectDatabricksRisha RavindranathSr Manager, Data GovernanceComcast AdvertisingRob SakerGlobal VP, Retail and ManufacturingDatabricksRobin SutaraField CTODatabricksRobinson CreightonPrincipal Analyst, Enterprise Data OpsComcast AdvertisingRodrigo BeceiroCTO & CofounderMarvikRoger DunnCo-founder, CTOExponamRoie Schwaber-CohenStaff Developer AdvocatePineconeRomit JadhwaniSr. Director, Data Analytics, Engineering and IntegrationsDatabricksRong MaSoftware EngineerintelRuifeng ZhengSenior Software EngineerDatabricksRyan BoydCo-founderMotherDuckRyan HarrisPrincipal Cybersecurity EngineerHSBCRyan JohnsonSenior Staff EngineerDatabricksSaad AnsariSenior Staff Product ManagerDatabricksSachin Balgonda PatilSolutions ArchitectDatabricksSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSamrat RaySenior Staff Product ManagerDatabricksSanjeev KumarVice President, Data Analytics and AIGainwell TechnologiesSanket AminSenior Manager of CAS Data Science and AnalyticsCollins AerospaceSarah PollittGroup Product ManagerMatillionSatish GarlaSr Solutions ArchitectDatabricksSatya NadellaChairman and CEOMicrosoft, Live Virtual GuestScott MeierDirector, Data Analytics Service, Financial Services CenterU.S. Department of Veterans AffairsScott StarbirdGeneral Counsel, Public Affairs and Strategic PartnershipsDatabricksScott BellPrincipal Consultant and Databricks SMERapidDataScott CastleChief Strategy OfficerSisenseSean KnappFounder & CEOAscend.ioSean OwenPrincipal Product SpecialistDatabricksSeth BabcockHead of Connected Aviation Tech Ops Solutions and AnalyticsCollins AerospaceShasidhar ErantiSpecialist Solutions ArchitectDatabricksShawn GilleranPrincipal Cloud Solutions LeadLiveRampShawn BenjaminData and Business Intelligence ChiefU.S. Department of Homeland Security - USCISShir ChorevCTODeepchecksShiv TrisalGTM Director, Manufacturing & EnergyDatabricksSiddharth BhaiSr. Manager, Product ManagementDatabricksSidharth KunnathPrincipal ArchitectAmerican Airlines, IncSimon WhiteleyCTOAdvancing AnalyticsSirui SunDatabricksSlava FridCTOWorldQuant PredictiveSneh KakiletiVice President, Product ManagementZoomInfoSpencer CookSenior Solutions Architect - Financial ServicesDatabricksSreekanth RatakondaPrincipal Solutions ArchitectLabcorpSridhar DevarapalliSenior Director, Product ManagementDatabricksSrinivasa KanamathaSenior ManagerBlackBerryStan LinSenior Software EngineerMicrosoft CorporationStefania LeoneSr. Manager Product ManagementDatabricksStephen SheltonVice President, Business IntelligencePluto TVSteve MahoneySr Manager, Product ManagementDatabricksSteve SobelGlobal Lead - Communications, Media & EntertainmentDatabricksSteven YuPrincipal Solutions ArchitectDatabricksSumesh NairDirector of Engineering, Data and Cloud StrategyOptum, United HealthGroupSuneel KonidalaSr. ManagerAccentureSunil RanganathanDirector, MLOPsTredenceSuresh MatlapudiLead Solutions Architect and Specialist SME, MigrationsDatabricksSurya TuragaSr. Solutions ArchitectDatabricksSuze HowseHead of Enterprise DataMarks and SpencerTanmay KumarSenior ManagerDeloitte Consulting LLPTathagata DasDatabricksTaylor HosbachData ScientistDIRECTVTeja TangedaPrincipal Data EngineerAmerican AirlinesTEST BecknerTESTTESTTest1 TestCFP1102testThet KoPrincipal Data EngineerSEEKThomas La PianaSenior Software EngineerEthycaThomas RoachSr. Solutions ArchitectDatabricksThorsten JacobsSr. Solutions ArchitectDatabricksTianyu LiuLead Data Scientist (Analytics)GrabTimothy AhrensMessaging Design Division ChiefDepartment of StateTodd GreensteinProduct ManagerDatabricksTomer PatelSoftware Engineering ManagerAkamai TechnologiesTony WangPhD studentStanfordUri MayHuntersVadivel SelvarajStaff Software EngineerRivianVarun SharmaPrincipal Data EngineerVisa Inc.Vicky AndonovaManager, Applied Machine LearningAnomaloVika SmilanskyDirector of Product MarketingThoughtSpotVikas Reddy AravabhumiStaff Backline EngineerDatabricksVincent ChenDirect of Product \/ Founding EngineerSnorkel AIVinit DoshiSenior ManagerTredenceVinod MarurSVP of EngineeringDatabricksVolker TjadenManager Solution ArchitectsDatabricksVuong NguyenSenior Solutions ArchitectDatabricksWassym BensaidSr. Vice President, Software DevelopmentRivianWeston HutchinsProduct ManagerDatabricksWill GirtenSr. Specialist Solutions ArchitectDatabricksWilliam ZanineHead of Data Management, Channel and Specialty North AmericaIQVIAWilly LulciucSr. Software EngineerAstronomerXiao LiSenior Engineering ManagerDatabricksXuefu WangSr. Data ScientistThe Trade DeskYali SassoonCPOSnowplowYang YouPresidential Young ProfessorNational University of SingaporeYaniv KundaSenior Software ArchitectAkamaiYaron SingerCEO & Co-FounderRobust IntelligenceYeshwanth VijayakumarSr Engineering Manager\/ArchitectAdobeYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and TechnologyU.S. ArmyYuki SaitoTechnical EvangelistNTT DATA CorporationZachary BannorData Engineering ManagerCond\u00e9 NastZachary HuangPhDColumbia UniversityZaheera ValaniSenior Director of EngineeringDatabricksZeashan PappaSenior Product Specialist - Data GovernanceDatabricksZoe DurandSenior Product ManagerDatabricksSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/hp-inc","text":"Customer Case Study: HP, Inc. | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYReal-time IoT device management at scale Vertical Use Case: IoT,Real-time device management,Process optimization Technical Use Case: Ingest\/ETL,Machine Learning\"Databricks\u2019 unified platform has helped foster collaboration across our data science and engineering teams which has impacted innovation and productivity.\"\n\u2014 John Landry, Distinguished Technologist at HP, Inc.HP Inc. was created in 2015 when Hewlett-Packard was split into two separate companies, HP Enterprise, and HP Inc. HP Inc. creates technology that makes life better for everyone, everywhere. Through a portfolio of printers, PCs, mobile devices, solutions, and services, their stated mission is to engineer experiences that amaze.The ChallengesSiloed data:\u00a0Data stored in multiple systems, in multiple places, that was hard to access and analyzeExisting tools difficult to manage:\u00a0Reliance on old data warehousing technologies and tooling resulting in heavy DevOps work, which typically fell on the data science teamThe SolutionDatabricks provides HP Inc. with a scalable, affordable, unified analytics platform that allows them to predict product issues and uncover new customer services:Simplified management of Apache Spark\u2122:\u00a0Turnkey unified platform removed infrastructure complexity and empowered the data scientists to focus on the data and not DevOpsAnalysis of high volume data in flight:\u00a0Analyze data from more than 20 million devices with a seamless workflowImproved collaboration and productivity:\u00a0a unified platform for business analysts, data scientists, and subject matter expertsReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/daniela-rus\/#","text":"Daniela Rus - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MITBack to speakersDaniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. Rus\u2019s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering, and the American Academy for Arts and Science. She earned her PhD in Computer Science from Cornell University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-vo","text":"Chris Vo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris VoLead Member of Tech Staff at AT&TBack to speakersChris Vo has 25+ years of software development experience. He has multiple Azure and Databricks certifications. He earned a Master's Degree in Computer Science at the University of Texas at Dallas (UTD) and a Bachelor's Degree in Computer Science at the University of Texas at Arlington (UTA).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hyukjin-kwon\/#","text":"Hyukjin Kwon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHyukjin KwonStaff Software Engineer at DatabricksBack to speakersHyukjin is a Databricks software engineer as the tech-lead in OSS PySpark team, Apache Spark PMC member and committer, working on many different areas in Apache Spark such as PySpark, Spark SQL, SparkR, infrastructure, etc. He is the top contributor in Apache Spark, and leads efforts such as Project Zen, Pandas API on Spark, and Python Spark Connect.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/geoffrey-freeman","text":"Geoffrey Freeman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeoffrey FreemanSolutions Architect at T-MobileBack to speakersGeoffrey Freeman has spent most of his career working in massive scale online data delivery services. He is currently a solution architect for T-Mobile's procurement division.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aman-kapoor","text":"Aman Kapoor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAman KapoorHead of Data Platform at PetronasBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arthur-li","text":"Arthur Li - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArthur LiSenior Software Engineer at InstacartBack to speakersArthur Li is a software engineer who has been working at Instacart for the past two years focusing on batch data processing infrastructure. He has contributed to the company's data platform team by implementing data collection and management strategies that have streamlined the company's data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/extract-transform-load","text":"What is ETL?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWExtract Transform Load (ETL)All>Extract Transform Load (ETL)What is ETL?As the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to prioritize these initiatives puts increasing pressure on the data engineering teams because processing the raw, messy data into clean, fresh, reliable data is a critical step before these initiatives can be pursued. ETL, which stands for extract, transform, and load, is the process data engineers use to extract data from different sources, transform the data into a\u00a0 usable and trusted resource, and load that data into the systems end-users can access and use downstream to solve business problems.How Does ETL Work?ExtractThe first step of this process is extracting data from the target sources that are usually heterogeneous such as business systems, APIs, sensor data, marketing tools, and transaction databases, and others. As you can see, some of these data types are likely to be the structured outputs of widely used systems, while others are semi-structured JSON server logs.There are different ways to perform the extraction: Three Data Extraction methods:Partial Extraction \u2013 The easiest way to obtain the data is if the if the source system notifies you when a record has been changedPartial Extraction (with update notification) - Not all systems can provide a notification in case an update has taken place; however, they can point to those records that have been changed and provide an extract of such records.Full extract \u2013 There are certain systems that cannot identify which data has been changed at all. In this case, a full extract is the only possibility to extract the data out of the system. This method requires having a copy of the last extract in the same format so you can identify the changes that have been made.TransformThe second step consists of transforming the raw data that has been extracted from the sources into a format that can be used by different applications. In this stage, data gets cleansed, mapped and transformed, often to a specific schema, so it meets operational needs. This process entails several types of transformation that ensure the quality and integrity of data Data is not usually loaded directly into the target data source, but instead it is common to have it uploaded into a staging database. This step ensures a quick roll back in case something does not go as planned. During this stage, you have the possibility to generate audit reports for regulatory compliance, or diagnose and repair any data issues.LoadFinally, the load function is the process of writing converted data from a staging area to a target database, which may or may not have previously existed. Depending on the requirements of the application, this process may be either quite simple or intricate. Each of these steps can be done with ETL tools or custom code.What is an ETL pipeline?An ETL pipeline (or data pipeline) is the mechanism by which ETL processes occur. Data pipelines are a set of tools and activities for moving data from one system with its method of data storage and processing to another system in which it can be stored and managed differently. Moreover, pipelines allow for automatically getting information from many disparate sources, then transforming and consolidating it in one high-performing data storage.Challenges with ETLWhile ETL is essential, with this exponential increase in data sources and types, building and maintaining reliable data pipelines has become one of the more challenging parts of data engineering. From the start, building pipelines that ensure data reliability is slow and difficult. Data pipelines are built with complex code and limited reusability. A pipeline built in one environment cannot be used in another, even if the underlying code is very similar, meaning data engineers are often the bottleneck and tasked with reinventing the wheel every time. Beyond pipeline development, managing data quality in increasingly complex pipeline architectures is difficult. Bad data is often allowed to flow through a pipeline undetected, devaluing the entire data set. To maintain quality and ensure reliable insights, data engineers are required to write extensive custom code to implement quality checks and validation at every step of the pipeline. Finally, as pipelines grow in scale and complexity, companies face increased operational load managing them which makes data reliability incredibly difficult to maintain. Data processing infrastructure has to be set up, scaled, restarted, patched, and updated - which translates to increased time and cost. Pipeline failures are difficult to identify and even more difficult to solve - due to lack of visibility and tooling. Regardless of all of these challenges, reliable ETL is an absolutely critical process for any business that hopes to be insights-driven. Without ETL tools that maintain a standard of data reliability, teams across the business are required to blindly make decisions without reliable metrics or reports. To continue to scale, data engineers need tools to streamline and democratize ETL, making the ETL lifecycle easier, and enabling data teams to build and leverage their own data pipelines in order to get to insights faster.Automate reliable ETL on Delta LakeDelta Live Tables (DLT) makes it easy to build and manage reliable data pipelines that deliver high quality data on Delta Lake. DLT helps data engineering teams simplify ETL development and management with declarative pipeline development, automatic testing, and deep visibility for monitoring and recovery.Additional ResourcesDelta Live Tables DemoDelta Lake: The Foundation of Your Lakehouse WebinarData Management: The Good The Bad The Ugly WebinarGetting Started with Delta Live TablesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tianyu-liu","text":"Tianyu Liu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTianyu LiuLead Data Scientist (Analytics) at GrabBack to speakersFrom the Analytics Data Platform and Finance Data + AI Transformation Team at Grab.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/pricing?itm_data=hp-hamburger-pricing-dais23","text":"Pricing - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPricingConference\n\n\n\n\n\n\n\n\n\n\n\nFull Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1795 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nGroup DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1295 IN-PERSONEACH\n\n\n\n\n\n\n\n\n\n\n\nGOV\/EDU\/NFPDiscounted pass for Government\/Education\/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1395 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\nVirtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event.\n $0 VIRTUALTraining\n\n\n\n\n\n\n\n\n\n\nTwo-Day CourseThis includes a two-day course and the certification exam.\n$1125 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nFull-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic.\n$750 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nHalf-Day TrainingA 4-hour, in-depth session covering your chosen topic.\n$375 IN-PERSONCertification\n\n\n\n\n\n\n\n\n\n\n\nCertification ExamRegister for training and take a certification exam onsite for free.\n$0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sanjeev-kumar","text":"Sanjeev Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSanjeev KumarVice President, Data Analytics and AI at Gainwell TechnologiesBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/data-engineering","text":"Data Engineering | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWData EngineeringDezenas de milh\u00f5es de cargas de trabalho produtivas s\u00e3o executadas diariamente no DatabricksIntrodu\u00e7\u00e3oAssista \u00e0 demonstra\u00e7\u00e3o\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowIngira e transforme facilmente dados em batch e streaming na Plataforma Databricks Lakehouse. Orquestre fluxos de trabalho de produ\u00e7\u00e3o confi\u00e1veis enquanto a Databricks gerencia automaticamente sua infraestrutura em escala. Aumente a produtividade de suas equipes com testes de qualidade de dados integrados e suporte \u00e0s melhores pr\u00e1ticas de desenvolvimento de software.Unifique batch e streamingElimine silos em uma plataforma com uma API unificada para ingerir, transformar e processar dados em batch e streaming de forma incremental em escala.Foque em extrair valor dos dadosA Databricks gerencia automaticamente sua infraestrutura e os componentes operacionais de seus fluxos de trabalho de produ\u00e7\u00e3o para que voc\u00ea possa se concentrar no valor, n\u00e3o nas ferramentas.Conecte suas ferramentas de escolhaUma Plataforma Lakehouse aberta para se conectar e usar suas ferramentas preferidas de engenharia de dados para ingest\u00e3o de dados, ETL\/ELT e orquestra\u00e7\u00e3o.Conte com a Plataforma LakehouseA Plataforma Lakehouse fornece a melhor funda\u00e7\u00e3o para construir e compartilhar ativos de dados confi\u00e1veis que s\u00e3o governados centralmente, confi\u00e1veis e extremamente r\u00e1pidos.\"A Databricks est\u00e1 se tornando o recurso completo para todo o nosso trabalho de ETL. Quanto mais trabalhamos com a Plataforma Lakehouse, mais f\u00e1cil \u00e9 para os usu\u00e1rios e administradores.\"\u2014 Hillevi Crognale, gerente de engenharia da YipitDataComo funciona?Ingest\u00e3o simplificada de dadosProcessamento automatizado de ETLOrquestra\u00e7\u00e3o confi\u00e1vel de fluxos de trabalhoMonitoramento e observabilidade de ponta a pontaMotor de processamento de dados de \u00faltima gera\u00e7\u00e3oFunda\u00e7\u00e3o de governan\u00e7a, confiabilidade e desempenhoIngest\u00e3o simplificada de dadosConsuma dados em sua Plataforma Lakehouse e potencialize suas an\u00e1lises, IA e aplica\u00e7\u00f5es de streaming de um s\u00f3 lugar.\u00a0O Auto Loader processa de forma incremental e autom\u00e1tica os arquivos que chegam ao armazenamento de nuvem, sem a necessidade de gerenciar informa\u00e7\u00f5es de estado, em jobs programados ou cont\u00ednuos. Ele rastreia com efici\u00eancia novos arquivos (escalando para bilh\u00f5es) sem ter que list\u00e1-los em um diret\u00f3rio e tamb\u00e9m pode inferir automaticamente o esquema dos dados de origem e evolu\u00ed-lo conforme as mudan\u00e7as ao longo do tempo. O comando COPY INTO facilita para analistas operarem a ingest\u00e3o de arquivos em batch para o Delta Lake com SQL.\"Vimos um aumento de 40% na produtividade da engenharia de dados - reduzindo o tempo que leva para desenvolver novas id\u00e9ias de dias para minutos e aumentando a disponibilidade e a precis\u00e3o de nossos dados.\"\u2014 Shaun Pearce, diretor de tecnologia,\u00a0GoustoSaiba maisProcessamento automatizado de ETLUma vez ingeridos, os dados brutos precisam ser transformados para que fiquem prontos para an\u00e1lise e IA. A Databricks fornece poderosos recursos ETL para times de engenharia, ci\u00eancia e an\u00e1lise de dados com Delta Live Tables (DLT). DLT \u00e9 a primeira estrutura que utiliza uma abordagem declarativa simples para construir pipelines ETL e ML em batch ou streaming de dados, enquanto automatiza complexidades operacionais tais como gerenciamento de infraestrutura, orquestra\u00e7\u00e3o de tarefas, tratamento e recupera\u00e7\u00e3o de erros, e otimiza\u00e7\u00e3o de desempenho. Com as DLTs, a equipe de engenharia tamb\u00e9m pode tratar seus dados como c\u00f3digo e aplicar as melhores pr\u00e1ticas de engenharia de software como testes, monitoramento e documenta\u00e7\u00e3o para criar pipelines confi\u00e1veis em escala.Saiba maisOrquestra\u00e7\u00e3o de fluxos de trabalho confi\u00e1velOs fluxos de trabalho Databricks s\u00e3o o servi\u00e7o de orquestra\u00e7\u00e3o totalmente gerenciado para todos os seus dados, an\u00e1lises e IA nativos da sua Plataforma Lakehouse. Organize cargas de trabalho diversas em todo o ciclo de vida, incluindo Delta Live Tables e Jobs para SQL, Spark, notebooks, dbt, modelos de ML e muito mais. A integra\u00e7\u00e3o profunda com a Plataforma Lakehouse garante que voc\u00ea crie e execute cargas de trabalho de produ\u00e7\u00e3o confi\u00e1veis em qualquer nuvem e, ao mesmo tempo, forne\u00e7a monitoramento profundo e centralizado com simplicidade para usu\u00e1rios finais.\u201cNossa miss\u00e3o \u00e9 transformar a forma como alimentamos o planeta. Nossos clientes do setor de energia precisam de dados, consultoria e pesquisas para alcan\u00e7ar essa transforma\u00e7\u00e3o. O Databricks Workflows nos d\u00e1 a velocidade e a flexibilidade para fornecer os insights de que nossos clientes precisam.\u201d\u2014 Yanyan Wu, vice-presidente de dados,\u00a0Wood MackenzieSaiba maisMonitoramento e observabilidade de ponta a pontaA Plataforma Lakehouse oferece visibilidade em todo o ciclo de vida de dados e IA para que equipes de engenharia de dados e de opera\u00e7\u00f5es possam ver a integridade de seus fluxos de trabalho de produ\u00e7\u00e3o em tempo real, gerenciar a qualidade dos dados e entender tend\u00eancias hist\u00f3ricas. Nos Fluxos de trabalho da Databricks, voc\u00ea pode acessar gr\u00e1ficos de fluxo de dados e pain\u00e9is que rastreiam a integridade e o desempenho de seus jobs produ\u00e7\u00e3o e pipelines de Delta Live Tables. Os logs de eventos tamb\u00e9m s\u00e3o expostos como tabelas do Delta Lake para que voc\u00ea possa monitorar e visualizar m\u00e9tricas de desempenho, qualidade dos dados e confiabilidade de qualquer \u00e2ngulo.Motor de processamento de dados de \u00faltima gera\u00e7\u00e3oA engenharia de dados da Databricks \u00e9 alimentada pelo Photon, o motor de \u00faltima gera\u00e7\u00e3o compat\u00edvel com as APIs do Apache Spark, oferecendo pre\u00e7o\/desempenho recordes enquanto escala automaticamente para milhares de n\u00f3s.\u00a0O Spark Structured Streaming oferece uma API unificada para processamento em batch e stream, facilitando a ado\u00e7\u00e3o do streaming no lakehouse sem alterar o c\u00f3digo ou aprender novas habilidades.Saiba maisGovernan\u00e7a, confiabilidade e desempenho de dados de \u00faltima gera\u00e7\u00e3oA engenharia de dados na Databricks significa que voc\u00ea se beneficia dos componentes fundamentais da\u00a0Plataforma Lakehouse\u00a0\u2014 Unity Catalog e Delta Lake. Seus dados brutos s\u00e3o otimizados com o\u00a0Delta Lake, um formato de armazenamento de c\u00f3digo aberto que fornece confiabilidade por meio de transa\u00e7\u00f5es ACID e tratamento escal\u00e1vel de metadados com desempenho extremamente r\u00e1pido. Isso se combina com o\u00a0Unity Catalog\u00a0para oferecer uma governan\u00e7a granular para todos os seus dados e ativos de IA, simplificando a forma como voc\u00ea governa, com um modelo consistente para descobrir, acessar e compartilhar dados entre as nuvens. O Unity Catalog tamb\u00e9m fornece suporte nativo para\u00a0Delta Sharing, o primeiro protocolo aberto da ind\u00fastria para compartilhamento de dados f\u00e1cil e seguro com outras organiza\u00e7\u00f5es.Migre para a DatabricksN\u00e3o aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, an\u00e1lises e IA.Migre para a DatabricksIntegra\u00e7\u00f5esOfere\u00e7a o m\u00e1ximo de flexibilidade \u00e0s suas equipes de dados \u2014 aproveite o Partner Connect e um ecossistema de parceiros de tecnologia para se integrar perfeitamente a ferramentas populares de engenharia de dados. Por exemplo, voc\u00ea pode ingerir dados cr\u00edticos de neg\u00f3cios com o Fivetran, transform\u00e1-los no lugar com dbt e orquestrar seus pipelines com o Apache Airflow.Ingest\u00e3o de dados e ETL+ qualquer outro cliente compat\u00edvel com Apache Spark\u2122Hist\u00f3ria de clienteDescubra maisDelta LakeFluxos de trabalhoDelta Live TablesDelta SharingConte\u00fado relacionado\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre os benef\u00edcios da data engineering no Databricks.\nExplorar recursose-booksBuilding the Data Lakehouse, de Bill Inmon, pai do data warehouseData, Analytics and AI governanceGerenciamento de dados 101e-book: The Big Book of Data EngineeringExplore a nova solu\u00e7\u00e3o de Delta SharingLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosGerencie a transforma\u00e7\u00e3o de dados com Delta Live TablesS\u00e9rie de webinars sobre ingest\u00e3o de dados sem complica\u00e7\u00f5esData + AI Summit 2022Modernize seu data warehouseBlogsAnunciando disponibilidade geral de Delta Live Tables (DLT) da DatabricksApresentando os fluxos de trabalho da DatabricksUma vis\u00e3o geral de todos os novos recursos estruturados de streaming desenvolvidos em 2021 para Databricks e Apache Spark10 recursos poderosos para simplificar o gerenciamento de dados semiestruturados no Databricks LakehouseTudo pronto para come\u00e7ar?Experimente gratuitamenteJunte-se \u00e0 comunidadeAWSAzureGCPProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/murali-madireddi\/#","text":"Murali Madireddi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMurali MadireddiArchitect at AccentureBack to speakersMurali is an accomplished architect with strong expertise in ETL, DW and Data lakes.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/teja-tangeda","text":"Teja Tangeda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTeja TangedaPrincipal Data Engineer at American AirlinesBack to speakersTeja Tangeda is a Principal Data Engineer at American Airlines. He has over a decade of experience as a Data Engineer. His love for aviation, travel, and data led him to American Airlines. Teja enjoys using his skills to solve complex data issues. He is inspired daily by his wife and two kids. In his free time, Teja likes to garden and take long walks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mohan-kolli\/#","text":"Mohan Kolli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMohan KolliIT Director at LabCorpBack to speakersIT professional with 23 years of experience as Application Developer, Data Engineer, Data Architect, Data Warehouse lead and leadership roles. Currently working as Director of Enterprise Analytics Platform with portfolio of Data Platform, Data Modeling, Data Integration, Data Engineering and Data Governance. I am the visionary in data engineering and data platform space to develop data driven organization(s) to empower users make decision(s) timely with high confidence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/fr\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/don-scott","text":"Don Scott - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon ScottVP, New Product Development at Hitachi Solutions AmericaBack to speakersDon, is the VP of New Product Development at Hitachi Solutions. With 10 years in emerging technology, and a background in high-performance compute, he currently drives success for clients by leading the Empower Analytics Platform. Passionate about cloud solutions, Don's mission is to address historic labor shortages through automation in the data and AI space.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/p\/ebook\/standardizing-the-ml-lifecycle?itm_data=lakehouse-link-standardmllifecycle","text":"Standardizing the ML Lifecycle | DatabrickseBookStandardizing the ML LifecycleFind out how to successfully build, deploy and reproduce ML models at scale. And learn engineering best practices, discover why MLflow has emerged as a leader in automating the end-to-end ML lifecycle with over 2 million monthly downloads and get an introduction to MLflow\u2019s newest component \u2014 Model Registry. The eBook covers:Key challenges organizations face when managing ML models throughout their lifecycleHow MLflow addresses these challenges, including experiment tracking, project reproducibility, and model deployment and managementHow Managed MLflow provides a fully managed, integrated experience with enterprise reliability, security and scale on DatabricksGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/philippe-leonhart","text":"Philippe Leonhart - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPhilippe LeonhartDigital Transformer, Corporate Business Services at MichelinBack to speakersFormer Sales Rep, moving to business analysis and later project management. My passionate about solving issues using digital tools! I believe that a true digital transformation relies on a better symbiosis between Information System actors and Business actors. For this, 2 core levers : making the expression of requirements a core competency and shift the roles in the delivery with citizen development. I\u2019m looking forward to share this perspective with you!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/getting-started-with-delta-lake-tech-talks?itm_data=deltalake-link-deltalaketechtalks","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/how-to-simplify-data-and-ai-governance-with-unity-catalog","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sai-ravuru-0","text":"Sai Ravuru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSai RavuruSenior Manager of Data Science & Analytics at JetBlueBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Sharing\uff1a\u30c7\u30fc\u30bf\u8cc7\u7523\u306e\u30bb\u30ad\u30e5\u30a2\u306a\u5171\u6709\u306e\u305f\u3081\u306e\u30aa\u30fc\u30d7\u30f3\u30b9\u30bf\u30f3\u30c0\u30fc\u30c9\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e\u7236\u3067\u3042\u308b\u30d3\u30eb\u30fb\u30a4\u30f3\u30e2\u30f3\u306b\u3088\u308b\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u53f0\u982d\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u306e\u3054\u76f8\u8ac7\u3092\u627f\u3063\u3066\u304a\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks 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{"source":"https:\/\/www.databricks.com\/terms-of-service","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/product\/machine-learning","text":"Machine learning de Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWMachine learningAcc\u00e9l\u00e9rez vos projets d'IA gr\u00e2ce \u00e0 une approche du machine learning ax\u00e9e sur les donn\u00e9esEssai gratuitPlanifier une d\u00e9mo\nConstruisez votre propre mod\u00e8le de grande langue comme Dolly\n26 April, 2023 | 9:00AM BST I 10AM CEST\nS'inscrirePlongez dans le machine learning sur DatabricksMlflow administr\u00e9Registre des mod\u00e8lesRuntime MLNotebooks collaboratifsMagasin de fonctionnalit\u00e9sAutoMLL'IA explicableR\u00e9f\u00e9rentielsSupervision des mod\u00e8lesMise \u00e0 disposition de mod\u00e8lesBas\u00e9e sur une architecture ouverte de lakehouse, Databricks Machine Learning permet aux \u00e9quipes en charge du ML de pr\u00e9parer et de traiter les donn\u00e9es, de rationaliser la collaboration \u00e0 travers l'entreprise et de standardiser l'ensemble du cycle de vie du ML, depuis l'exp\u00e9rimentation jusqu'\u00e0 la production.Plus de 6 millions de dollars d'\u00e9conomiesCONA Services utilise Databricks pour un cycle de vie ML complet afin d'optimiser la Supply Chain pour des centaines de milliers de magasins.En savoir plus3,9 millions de R$ d'\u00e9conomiesVia s'appuie sur l'apprentissage automatique pour pr\u00e9voir avec pr\u00e9cision la demande, r\u00e9duisant ainsi les co\u00fbts de calcul de 25 %.En savoir plusPlus de 50 millions de dollars de r\u00e9duction des co\u00fbtsAmgen am\u00e9liore la collaboration en mati\u00e8re de science des donn\u00e9es pour acc\u00e9l\u00e9rer la d\u00e9couverte de m\u00e9dicaments et r\u00e9duire les co\u00fbts op\u00e9rationnels.En savoir plusSimplifier toutes les donn\u00e9es pour le MLPuisque Databricks ML repose sur une base ouverte de lakehouse gr\u00e2ce \u00e0 Delta Lake, vous permettez \u00e0 vos \u00e9quipes de ML d'acc\u00e9der \u00e0 tout type de donn\u00e9es, de les explorer et de les pr\u00e9parer et ce, \u00e0 n'importe quelle \u00e9chelle. Transformez des fonctionnalit\u00e9s en pipelines de production disponibles en libre-service sans d\u00e9pendre du support de l'ing\u00e9nierie des donn\u00e9es.Automatiser le suivi et la gouvernance des exp\u00e9riencesManaged MLflow suit automatiquement les param\u00e8tres de vos tests et journaux, les m\u00e9triques, le contr\u00f4le de versions des donn\u00e9es et du code, ainsi que les artefacts de mod\u00e8le \u00e0 chaque ex\u00e9cution d'entra\u00eenement. Vous pouvez rapidement voir les ex\u00e9cutions pr\u00e9c\u00e9dentes, comparer les r\u00e9sultats et reproduire un r\u00e9sultat pr\u00e9c\u00e9demment obtenu selon vos besoins. Une fois que vous avez identifi\u00e9 la meilleure version d'un mod\u00e8le pour la production, enregistrez-la dans le registre des mod\u00e8les pour simplifier les transferts tout au long du cycle de d\u00e9ploiement.G\u00e9rez l'int\u00e9gralit\u00e9 du cycle de vie des mod\u00e8les, des donn\u00e9es \u00e0 la production \u2013 et inversement.Une fois que les mod\u00e8les entra\u00een\u00e9s sont enregistr\u00e9s, vous pouvez les g\u00e9rer de mani\u00e8re collaborative tout au long de leur cycle de vie \u00e0 l'aide du registre des mod\u00e8les. Les mod\u00e8les peuvent \u00eatre versionn\u00e9s et passer par diff\u00e9rentes \u00e9tapes, comme l'exp\u00e9rimentation, la pr\u00e9-production, la production et l'archivage. La gestion du cycle de vie s'int\u00e8gre aux workflows d'approbation et de gouvernance selon des contr\u00f4les d'acc\u00e8s bas\u00e9s sur les r\u00f4les. Les commentaires et les notifications par e-mail offrent un environnement de collaboration riche aux \u00e9quipes charg\u00e9es des donn\u00e9es.D\u00e9ployer des mod\u00e8les de ML \u00e0 faible latence et \u00e0 grande \u00e9chelleD\u00e9ployez des mod\u00e8les en un seul clic sans vous inqui\u00e9ter de la gestion des serveurs ou des contraintes d'\u00e9chelle. Avec Databricks, vous pouvez d\u00e9ployer vos mod\u00e8les en tant que points de terminaison d\u2019API REST n\u2019importe o\u00f9. Et toujours avec une disponibilit\u00e9 de niveau entreprise.Les composants du produitNotebooks collaboratifsLes notebooks Databricks prennent nativement en charge Python, R, SQL et Scala. Les utilisateurs peuvent ainsi travailler avec les langages et biblioth\u00e8ques de leur choix pour extraire, visualiser et partager des informations.En savoir plusRuntime de machine learningAcc\u00e8s en un clic \u00e0 des clusters ML pr\u00e9configur\u00e9s, optimis\u00e9s et bas\u00e9s sur une distribution \u00e9volutive et fiable des frameworks ML les plus populaires (tels que PyTorch, TensorFlow et scikit-learn), avec des optimisations int\u00e9gr\u00e9es pour des performances in\u00e9gal\u00e9es dans toute l'entreprise.En savoir plusMagasin de fonctionnalit\u00e9sFacilitez la r\u00e9utilisation des fonctionnalit\u00e9s gr\u00e2ce \u00e0 une recherche de fonctionnalit\u00e9s bas\u00e9e sur le lignage de donn\u00e9es exploitant les sources de donn\u00e9es enregistr\u00e9es automatiquement. Rendez vos fonctionnalit\u00e9s disponibles pour l'apprentissage gr\u00e2ce \u00e0 un d\u00e9ploiement de mod\u00e8le simplifi\u00e9 ne n\u00e9cessitant pas de modification de l'application client.En savoir plusAutoMLOffrez \u00e0 chacun, des experts du ML aux data scientists, une approche \u00ab\u00a0Glass box\u00a0\u00bb de l'AutoML fournissant non seulement le mod\u00e8le le plus performant mais g\u00e9n\u00e9rant aussi un code qui sera par la suite affin\u00e9 par des experts.En savoir plusMlflow administr\u00e9Con\u00e7u \u00e0 partir de MLflow - la premi\u00e8re plateforme open source au monde pour le cycle de vie du ML - Managed MLflow aide les mod\u00e8les ML \u00e0 passer rapidement de la phase de test \u00e0 la production, avec un haut niveau de s\u00e9curit\u00e9, de fiabilit\u00e9 et d'\u00e9volutivit\u00e9 \u00e0 l'\u00e9chelle de l'entreprise.En savoir plusMise \u00e0 disposition de mod\u00e8les de niveau productionDiffusez des mod\u00e8les \u00e0 n'importe quelle \u00e9chelle et en un clic gr\u00e2ce \u00e0 l'option de calcul serverless.En savoir plusSupervision des mod\u00e8lesSurveillez les performances des mod\u00e8les et leur incidence sur les indicateurs de l\u2019entreprise en temps r\u00e9el. Databricks offre une visibilit\u00e9 et une tra\u00e7abilit\u00e9 de bout en bout, des mod\u00e8les en production aux syst\u00e8mes de donn\u00e9es source. La plateforme permet d'analyser le mod\u00e8le et la qualit\u00e9 des donn\u00e9es tout au long du cycle de vie du machine learning, et donc d'identifier les probl\u00e8mes avant qu'ils n'aient un impact.En savoir plusR\u00e9f\u00e9rentielsRepos permet aux ing\u00e9nieurs de suivre les workflows Git dans Databricks. Ainsi, les \u00e9quipes data peuvent exploiter les workflows de CI \/ CD automatis\u00e9s et la portabilit\u00e9 du code.En savoir plusMigrer vers DatabricksVous en avez assez des silos de donn\u00e9es, de la lenteur des performances et des co\u00fbts \u00e9lev\u00e9s associ\u00e9s aux anciens syst\u00e8mes comme Hadoop et aux entrep\u00f4ts de donn\u00e9es d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de donn\u00e9es, d'analyses et d'IA.Migrer vers DatabricksRessources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez la biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur la data science et le machine learning.\nExplorer les ressourcesEbooksLe Grand Livre des MLOpsD\u00e9couvrez la nouvelle solution de Delta SharingGuide de migration : Hadoop vers DatabricksD\u00e9mos et blogsPlongez dans les solutions de machine learning DatabricksCinq \u00e9tapes cl\u00e9s pour r\u00e9ussir la migration de Hadoop vers l'architecture Lakehouse\u00c9v\u00e8nements virtuelsAutML\u00a0: le machine learning rapide et accessible \u00e0 tous\u00c9v\u00e9nement virtuel MLOps\u00a0: standardisation des MLOps \u00e0 grande \u00e9chelleAutomatiser le cycle de vie du ML avec Databricks Machine Learning\u00c9v\u00e9nement virtuel MLOps \"\u00a0Op\u00e9rationnalisation du Machine Learning \u00e0 grande \u00e9chelle\u00a0\"Cr\u00e9er des plateformes de Machine LearningDelta Lake\u00a0: la fondation de votre LakehouseGuide \u00e9tape par \u00e9tape de la migration HadoopPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deylo-woo\/#","text":"Deylo Woo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeylo WooData Engineer Architect at Providence Health ServicesBack to speakersDeylo Woo attended University of Alaska Anchorage (Computer Science) and is an experienced IT professional with 22 years of experience and 12 years with Providence Health Services. He specializes in Software and Data Engineering, and has worked with various technologies such as Java, .Net (C#), Javascript, Python, SQL, Data Warehouses, ETL development, and cloud architectures. Deylo is originally from Brazil but grew up in the US (Alaska) where his favorite past time is camping and fishing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/09\/22\/introducing-new-partner-integrations-partner-connect.html","text":"Introducing New Partner Integrations in Partner Connect - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing New Partner Integrations in Partner ConnectFive validated partner solutions extend the power of your lakehouseby Riley Maris, Zaheera Valani, Maraki Ketema and Hiral JasaniSeptember 22, 2022 in Company BlogShare this postWe are delighted to introduce five new integrations in Databricks Partner Connect, a one-stop portal that makes it easy to discover and integrate data, analytics and AI solutions with your lakehouse. These validated solutions help users establish a semantic data layer for their lakehouse, sync mission-critical data to strategic destinations, and connect to powerful BI and analytics platforms to help your organization become more data-driven.Notably, we have added three partner integrations to the BI and visualization category, as well as the first integrations for both the reverse ETL and semantic layer categories. This continues our mission of bringing innovative partner integrations to our customers through Partner Connect.Take a look at what's new!BI and visualizationPresetPreset is a modern cloud data visualization and exploration platform powered by Apache Superset, the leading open source business intelligence platform. Preset makes it easy to build interactive charts and dashboards on top of your Databricks Lakehouse using its no-code chart builder that generates queries on the analyst's behalf. Charts and dashboards can be managed as code or embedded externally in third-party applications.Qlik Sense\nQlik Sense, a complete data analytics solution, is now integrated with Databricks Partner Connect. With this integration, you can now automatically connect to Qlik Sense directly from within the Databricks Lakehouse Platform through an existing Qlik tenant or a free trial. This makes it easier to combine data from hundreds of sources and generate insights using Qlik's interactive dashboards. Learn more about the integration here.ThoughtSpot\nThoughtSpot's mission is to create a more fact-driven world with the easiest-to-use analytics platform. With ThoughtSpot, anyone can leverage natural language search and AI to find data insights and tap into the most cutting-edge innovations the cloud data ecosystem offers, including the Databricks Lakehouse Platform. Learn more about Databricks and ThoughtSpot here.Reverse ETLHightouch\nThe world's leading Data Activation platform, Hightouch empowers Databricks users to easily send data to strategic destinations by syncing the business rules defined in the lakehouse directly into SaaS tools. All business teams, from sales and marketing to support and customer success, need relevant, accurate, and real-time customer data to add critical context inside the software they already use. Hightouch supports more integrations than any other tool available today \u2014 all with SQL and no scripts. Learn how easy it is to launch your own Hightouch workspace from directly within Partner Connect here.Semantic layerStardogStardog is the ultimate semantic data layer to get better and more accurate insights faster. The Stardog Enterprise Knowledge Graph platform operates with your lakehouse to unite your data, unleash insight, and accelerate returns from your investment. By connecting enterprise data and overlaying business semantics, knowledge graphs facilitate more agile data operations, reduce the cost of data integration, and help generate powerful insights answering complex business questions. Data and analytics teams can quickly establish a data fabric that evolves with their organization's growing needs. Learn more about how to get started with Stardog on Databricks.Customer spotlightFlyr grows their business with live analytics on their lakehouse dataIn an industry filled with unpredictability, European airline Flyr takes a data-first approach leveraging Databricks and ThoughtSpot to make informed decisions, provide the best customer experience and scale their company. With self-service search and Liveboards, anyone at Flyr can search across all their lakehouse data in ThoughtSpot in a matter of seconds to create actionable insights. The new ThoughtSpot integration in Databricks Partner Connect allows users at Flyr to jump right into asking questions and deriving insights from their lakehouse data. Flyr can now respond more quickly to ever-changing customer demands and shifts in costs and strategically plan its flight routes to maximize cost-effectiveness with granular, in-the-moment insights. As a result, Flyr has saved on fuel prices, expanded its routes to serve customer demand, and improved decision-making on all platforms, from sales to distribution.\"We were really excited to learn about ThoughtSpot and the opportunity to leverage the data we built in Databricks.\" - Martin Stangeland, VP Data and Analytics, FlyrNauto uses predictive AI on the lakehouse to make roads saferNauto delivers AI-powered fleet management software that coaches drivers to reduce collisions and save lives. For years, Nauto relied on fragile point-to-point integrations as it took new orders, processed payments, shipped hardware to customers, and managed customer subscriptions to its cloud data processing services. With Hightouch and Databricks, Nauto established a single source of truth in the lakehouse and syncs data to Salesforce and Netsuite, eliminating the complex series of scripts and spreadsheets it previously used to track data changes. With the Hightouch integration in Databricks Partner Connect, data workers at Nauto can sync data from multiple sources with ease, helping stakeholders across Nauto make strategic decisions that drive the company forward.Learn more in the full customer spotlight, here.\"Hightouch allows us to throw away all of the complexity and simply write SQL to move our data out of Databricks. I don't have to go through all the hoops of adding a new field in Netsuite or Salesforce and make sure there isn't a conflict somewhere else.\" - Ernest Prabhakar, Business Data Lead, NautoGet started with Partner ConnectSign up for a free trial of Databricks to try Partner Connect at no additional cost, and stay tuned as we announce more integrations in the coming months.Try Databricks for freeGet StartedRelated postsAnnouncing New Partner Integrations in Partner ConnectJune 15, 2022 by Hiral Jasani, Bilal Aslam, Zaheera Valani and Katie Cummiskey in Company Blog\nWe are excited to announce six new integrations in Databricks Partner Connect. Our expanding partnerships enable our users to integrate the freshest data...\nLaunching dbt Cloud in Databricks Partner ConnectApril 14, 2022 by Bilal Aslam, Hiral Jasani, Shant Hovsepian, Dave Eyler, Daniel Rosenthal and Bemnet Merha in Partners\nWe are delighted to announce that dbt Cloud, the fastest and most reliable way to build, manage and monitor dbt projects, is now...\nDeploy Fully Managed Change Data Capture Pipelines With Arcion and Databricks Partner ConnectJune 21, 2022 by Prasad Kona and Rajkumar Sen in News\nThis is a collaborative post between Databricks and Arcion. We thank Rajkumar Sen, Founder & CTO of Arcion, for their contribution. We are...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sirui-sun\/#","text":"Sirui Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSirui Sun DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/virtual-experience","text":"Virtual Experience - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVirtual ExperienceTune in, June 28-29, from anywhere in the world.\n*Asia Pacific & Japan Keynotes Rebroadcast\u00a0\nEnglish,\u00a0Japanese,\u00a0Korean\u00a0and\u00a0Mandarin\nJune 29 and June 30\n8.30 AM IST | 11 AM SGT | 12 PM JST | 12 PM KST | 1 PM AEST\nRegister nowThis year\u2019s Data + AI Summit Virtual Experience brings you a host of live content including major industry and product announcements, expert keynotes, curated breakout sessions, exclusive interviews with guest speakers and Databricks founders, as well as 250+ breakouts available on demand after the event.Featured speakersCheck back in mid May to see the full speaker lineup for our virtual event.\nDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAgendaWednesday, June 28*8:15 AM \u2013 11:00 AM | Keynote Day 1\n1:00 PM - 5:40 PM | Breakout Sessions 1-6\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nThursday, June 29*8:30 AM \u2013 11:00 AM |\u00a0 Keynote Day 2\n12:00 PM - 4:40 PM | Breakout Sessions 7-11\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nOn DemandAll 250+ breakout sessions delivered onsite in San Francisco will be recorded and available on demand soon after the event. More updates coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/eric-peter\/#","text":"Eric Peter - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEric PeterSr Staff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/technology","text":"Parcerias de tecnologia Databricks - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWParcerias de tecnologia DatabricksConecte-se com as parcerias de tecnologia Databricks para integrar recursos de ingest\u00e3o de dados, business intelligence e governan\u00e7a na Plataforma Databricks Lakehouse.\u201cCom Databricks e Fivetran, melhoraremos significativamente os insights de marketing no futuro. Do ponto de vista t\u00e9cnico, as duas ferramentas interagem com harmonia e a integra\u00e7\u00e3o \u00e9 totalmente perfeita.\u201d\u2014 Jan-Niklas M\u00fchlenbrock, L\u00edder de Equipe de Business Intelligence e ERP na Paul HewittAs parcerias de tecnologia Databricks integram suas solu\u00e7\u00f5es com a Databricks para fornecer recursos complementares para ETL, ingest\u00e3o de dados, business intelligence, machine learning e governan\u00e7a.Essas integra\u00e7\u00f5es permitem que os clientes aproveitem a confiabilidade e a escalabilidade da Plataforma Databricks Lakehouse para inovar mais rapidamente, obtendo valiosos insights de dados.Conex\u00e3o de parceirosRe\u00fana todos os seus dados, an\u00e1lises e ferramentas de IA em uma \u00fanica plataforma aberta. Com o Partner Connect, a Databricks oferece uma maneira r\u00e1pida e f\u00e1cil de conectar suas ferramentas existentes ao seu lakehouse usando integra\u00e7\u00f5es validadas. Tamb\u00e9m ajuda voc\u00ea a descobrir e experimentar novas solu\u00e7\u00f5es.Comece uma parceriaSaiba maisLoading...ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brad-corwin","text":"Brad Corwin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrad CorwinChief Data Scientist at Booz Allen HamiltonBack to speakersBrad Corwin is a Chief Data Scientist at Booz Allen Hamilton with over a decade of professional experience in software engineering, data engineering and data science. He has a focus on innovative techniques and operationalizing data science solutions. He provides thought leadership to maximize the outcome and has a passion for building data-driven solutions in a rapid Agile environment. He currently leads Advana\u2019s Data Science and Data Engineering team to accelerate data and AI delivery.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-shtelma","text":"Michael Shtelma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael ShtelmaLead Specialist Solutions Architect at DatabricksBack to speakersMichael Shtelma is a Lead Specialist Solutions Architect at Databricks. Michael focuses on developing and operationalizing large-scale Machine Learning use cases on the Databricks platform. Before Databricks, Michael worked for Teradata, helping Teradata customers build data and machine learning solutions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anton-okolnychyi\/#","text":"Anton Okolnychyi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnton OkolnychyiSoftware Engineer at AppleBack to speakersAnton is an Apache Iceberg PMC member and Apache Spark contributor at Apple. He has been working on various internals of Big Data systems for the last six years. Anton's recent focus is on building secure, efficient and reliable data lakes. Before joining Apple, he optimized and extended a proprietary distribution of Apache Spark at SAP. Anton holds a Master\u2019s degree in Computer Science from RWTH Aachen University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adam-wilson\/#","text":"Adam Wilson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdam WilsonCo-Founder, Chief of Product at Divirod, Inc.Back to speakersAdam is a serial entrepreneur. He co-founded Sphero in 2010, the robot company responsible for bringing joy and education to millions of kids through programmable robots and amazing educational content. He has a unique talent for product development, visionary ideas and relentless drive to focus on execution and is a contributor to over 15 technology patents. Adam\u2019s real passion is \u201cmaking,\u201d he has a full size R2-D2 in his living room, loves to judge kid\u2019s science fairs, sits on the NHS board of University of Northern Colorado where he graduated with a undergraduate degree in math and physics and you may have even seen some of his work as a spokesperson from past Microsoft commercials!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/noam-bressler\/#","text":"Noam Bressler - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNoam BresslerML Team Lead at DeepchecksBack to speakersNoam directs the development of algorithms and Machine Learning methodologies for validation of models and data at Deepchecks. Noam holds an MSc in physics and previously served as a Data Scientist and Algorithms Researcher, developing ML and analytical models in the domain of acoustic signal processing in the IDF.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mark-lee\/#","text":"Mark Lee - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMark LeeSenior Specialist Solutions Architect at DatabricksBack to speakersMark is a Senior Specialist Solutions Architect at Databricks. He brings with him over a decade of experience in Health Life Sciences and emerging high performance computing technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/consulting-and-si","text":"Partner di consulenza di Databricks - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks Consulting PartnerEntra in contatto con partner di Databricks in tutto il mondo che possono aiutarti a costruire, implementare o migrare alla Databricks Lakehouse PlatformI Databricks Consulting Partner sono esperti che offrono un'esperienza unica nell'implementazione e nella modulazione di progetti di data engineering, data science collaborativa, machine learning lungo tutto il ciclo di vita e business analytics.\nQueste aziende offrono competenze nell'ambito delle tecnologie, dei settori industriali e dei casi d'uso per ottenere il massimo dalla Databricks Lakehouse Platform. I servizi spaziano dalla definizione di una strategia di trasformazione dei dati specifica per ogni azienda, alla modernizzazione e migrazione dei dati, fino alla gestione e governance dei dati, e altro ancora.Loading...ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/product\/machine-learning-runtime?itm_data=product-link-MLRuntime","text":"ML Runtime \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMachine Learning RuntimeReady-to-use and optimized machine learning environmentTry for freeSchedule a demoThe Machine Learning Runtime (MLR) provides data scientists and ML practitioners with scalable clusters that include popular frameworks, built-in AutoML and optimizations for unmatched performance.BenefitsFrameworks of ChoiceML Frameworks are evolving at a frenetic pace and practitioners need to manage on average 8 libraries. The ML Runtime provides one-click access to a reliable and performant distribution of the most popular ML frameworks, and custom ML environments via pre-built containers.Augmented Machine LearningAccelerate machine learning from data prep to inference with built-in AutoML capabilities including hyperparameter tuning and model search using Hyperopt and MLflow.Simplified ScalingGo from small to big data effortlessly with an auto-managed and scalable cluster infrastructure. The Machine Learning Runtime also includes unique performance improvements for the most popular algorithms as well as HorovodRunner, a simple API for distributed deep learning.FeaturesFrameworks of ChoiceML Frameworks: The most popular ML libraries and frameworks are provided out-of-the-box including TensorFlow, Keras, PyTorch, MLflow, Horovod, GraphFrames, scikit-learn, XGboost, numpy, MLeap, and Pandas.Augmented MLAutomated Experiments Tracking:\u00a0Track, compare, and visualize hundreds of thousands of experiments using open source or Managed MLflow and the parallel coordinates plot feature.Automated Model Search (for Single-node ML):\u00a0Optimized and distributed conditional hyperparameter search across multiple model architectures with enhanced Hyperopt and automated tracking to MLflow.Automated Hyperparameter Tuning for Single-node Machine Learning:\u00a0Optimized and distributed hyperparameter search with enhanced Hyperopt and automated tracking to MLflow.Automated Hyperparameter Tuning for Distributed Machine Learning:\u00a0Deep integration with PySpark MLlib\u2019s Cross Validation to automatically track MLlib experiments in MLflow.Optimized for simplified scalingOptimized TensorFlow:\u00a0Benefit from TensorFlow CUDA-optimized version on GPU clusters for maximum performance.HorovodRunner:\u00a0Quickly migrate your single node deep learning training code to run on a Databricks cluster with HorovodRunner, a simple API that abstracts complications faced when using Horovod for distributed training.Optimized MLlib Logistic Regression and Tree Classifiers:\u00a0The most popular estimators have been optimized as part of the Databricks Runtime for ML to provide you with up to 40% speed-up compared to Apache Spark 2.4.0.Optimized GraphFrames:\u00a0Run GraphFrames 2-4 times faster and benefit from up to 100 times speed-up for Graph queries, depending on the workloads and data skew.Optimized Storage for Deep Learning Workloads:\u00a0Leverage high-performance solutions on\u00a0Azure,\u00a0AWS, and\u00a0GCP\u00a0for data loading and model checkpointing, both of which are critical to deep learning training workloads.How it worksThe Machine Learning Runtime is built on top and updated with every Databricks Runtime release. It is generally available across all Databricks product offerings including: Azure Databricks, AWS cloud, GPU clusters and CPU clusters.To use the ML Runtime, simply select the ML version of the runtime when you create your cluster.Databricks Runtime for Machine LearningCustomer StoryResourcesBlogsProductionizing Machine Learning: From Deployment to Drift DetectionDetecting Bias with SHAPHyperparameter Tuning with MLflow, Apache Spark MLlib and HyperoptIntroducing HorovodRunner for Distributed Deep Learning TrainingLoan Risk Analysis with XGBoost and Databricks Runtime for Machine LearningeBooksThe Big Book of Machine Learning Use CasesWebinarsAutoML Rapid, simplified machine learning for everyoneMLOps Virtual Event - Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningMLOps Virtual EventAutomated Hyperparameter Tuning, Scaling and Tracking on DatabricksSimple Steps to Distributed Deep LearningAccelerating Machine Learning on DatabricksNotebooksUse Keras with TensorFlow on a single node on DatabricksFrom single node to distributed training with PyTorch on DatabricksSimple Steps to Distributed Deep Learning Demo NotebookDocumentationDatabricks Runtime for Machine LearningApache Spark MLlibAutoMLDeep LearningHorovodRunner: Distributed Deep Learning with HorovodReady to get started?Follow the Quickstart GuideProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/databricks-on-aws-free-training-series?itm_data=awspage-awsstepbystep","text":"Databricks on AWS free training series - DatabricksFree TrainingDatabricks on AWS step-by-step trainingStart these newly refreshed lessons todayOn-demand trainingUnify all your analytics and AI workloads on a simple, open Lakehouse Platform. Databricks on AWS combines the best of data warehouses and data lakes to support your data analytics, data engineering, data science and machine learning activities. Get the foundation you need to start using the Databricks Lakehouse Platform in this free step-by-step training series.You\u2019ll learn how to:Ingest data and build a Lakehouse for analyzing customer product usageQuery your Lakehouse using SQL queriesTrain an ML customer model using your LakehouseSpeakersMina RaoAssociate Technical Curriculum Developer,DatabricksDave LeBlancStaff Technical Curriculum Developer, DatabricksDavid HarrisTechnical Curriculum Developer, DatabricksMark RoepkeSenior Technical Curriculum Developer, DatabricksWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/prateek-chawla\/#","text":"Prateek Chawla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPrateek ChawlaFounding Engineer at Monte CarloBack to speakersPrateek Chawla is a founding engineer and technical lead at Monte Carlo, where he drives the technical strategy for their data observability platform. Previously, he served as a technical lead at Barracuda, working on email fraud prevention technologies. He graduated Summa Cum Laude with a B.S. in Computer Science and Engineering from the University of California, Santa Cruz. In his free time, Prateek enjoys watching Broadway shows, flying airplanes, reading, and exploring new places.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/multi-touch-attribution","text":"Measure Advertising Effectiveness With Sales Forecasting and Attribution | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorMeasure Ad Effectiveness With Multi-Touch AttributionPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedOptimize marketing spend with better ad channel attributionConnect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.Fine-grain insights with real-time dashboardsEasily integrate new marketing channels to your modelOptimize your media mixDownload the notebookResourcesCase studyLearn moreWebinarRegister nowBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nicholas-woodbrige","text":"Nicholas Woodbrige - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, Technology at GlaxoSmithKlineBack to speakersTechnical Leader on Strategic Solutions \u2014 Data & Analytics, Cloud, AI\/ML \nI have spearheaded complex, large-scale, and business-critical technical programs at Amazon, Adobe, and now GlaxoSmithKline, bringing a combination of technology knowledge, business insight, and team leadership to deliver solutions and results. \nI partner with executive leaders and stakeholders to understand business needs and collaborate closely with engineering, product, and other functional leaders, as well as external vendors, to strategize and execute, achieving outcomes that move the business forward.\nThe consistent success of these programs depends on the caliber of the team, and I am passionate about managing, coaching, and mentoring talent to perform at the highest levels, even in rapidly changing and ambiguous situations. \nSelect skills include: Strategic Planning & Execution, Complex Program & Project Management, Product Development, Executive\/Stakeholder Engagement, Business Analysis\/Requirements Gathering, Vendor Management, Relationship Building, Change Management, Team LeadershipLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sunil-ranganathan\/#","text":"Sunil Ranganathan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSunil RanganathanDirector, MLOPs at TredenceBack to speakersSunil is an experienced product leader with over 18 years of experience in building data analytics and AI\/ML based products and solutions. In his current role at Tredence Analytics, he is responsible for leading the MLOPs practice and building out industry specific AI\/ML solutions. In his earlier role at 247.ai, Sunil was focused on building ML based products in the Conversational AI space.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jordan-donmoyer\/#","text":"Jordan Donmoyer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJordan DonmoyerManager, Customer Data Solutions at The Hershey CompanyBack to speakersJordan leads the Customer Data Solutions team at The Hershey Company, and in his role, he partners with key strategic\nCategory Management teams and retailer commercial data partners to develop and manage the multi-year strategic plans to enable and unlock organizational topline growth for Hershey. Jordan also partners with internal IS teams to drive the development of strategic policies impacting data sharing, maintaining data literacy, and cataloging key strategic retailer data. Jordan brings over 6 years of supply chain, logistics, reporting & analytics, and leadership\/management experience to his role within the Commercial Data team. Jordan currently resides with his family in Fayetteville, Arkansas, but was born and raised in Lititz, Pennsylvania, just forty minutes outside of Hershey, PA. He played baseball at Pennsylvania State University where he graduated with a Bachelor\u2019s in Supply Chain and Information Systems and a minor in Information Systems Management.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/datasentics-persona360","text":"Persona 360 by DataSentics and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionPersona 360: Financial Customer Data Platform by DataSenticsIndustry-specific solution developed by DataSentics and powered by the Databricks Lakehouse Platform\nGet startedUnify, understand and activate your customer data in financial servicesPersona 360 by DataSentics, an Atos company, was created specifically for retail banks and insurance companies to allow them to complete, unify and fully capture customer profiles in a smart data model. Built on the Databricks Lakehouse Platform and available on multiple clouds, Persona 360 supplements basic profile information with insights from digital behavior and unstructured data like call center recordings. With Persona 360, utilize pre-built banking and insurance customer 360\u00b0 data model information and 1,695 attributes to understand the differences between customer segments. You can also leverage insights from advertising, marketing and other platforms (e.g., Facebook, Google, Salesforce) utilizing ready-to-use connectors. Persona 360 helps you activate customer data and deliver better business performance and customer satisfaction. With Persona 360, you can:Get pre-built banking and insurance-specific customer 360\u00b0 data models and AI segmentation, including 1,695+ attributes and segmentsConnect the workflow of data scientists (via Databricks) and marketing specialists (via Persona 360), making it easy for data specialists to adopt the results of their work and nontechnical users to understand and activate dataHave the tools to grow engagement by 37% and conversion rates by 45% with personalized campaignsGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/azure","text":"Azure Databricks - Unify All Your Analytics and AI Workloads | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure DatabricksThe data and AI service from Databricks available through Microsoft Azure to store all your data on a simple open lakehouse and unify all your analytics and AI workloads.Get startedSchedule a demoAzure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI and other Azure services to store all your data on a simple, open lakehouse and unify all your analytics and AI workloads.Simple\nUnify your data, analytics and AI\non one common platform for all data use casesOpen\nUnify your data ecosystem\nwith open source, standards, and formatsCollaborative\nUnify your data teams\nto collaborate across the entire data and AI workflowWhy Azure Databricks?50x performance for Apache Spark\u2122 workloads\nDeploy auto-scaling compute clusters with highly optimized Spark that perform up to 50x faster.Learn moreMillions of server hours each day\nAzure Databricks is trusted by thousands of customers who run millions of server hours each day across more than 34\u00a0Azure regions.Learn moreEase of use\nStart with a single click in the Azure Portal, natively integrate with Azure security and data services, and boost productivity by up to 25% with collaborative data engineering and data science.Learn moreIndustry use casesFinancial servicesSwiss ReUnified\u00a0data analytics across data engineering, data science and analysts.HSBC\nBuilt a\u00a0digital payment platform\u00a0using Azure Databricks.ABN AMROImproved analytics workflows\u00a0by enabling collaboration, AI insights and advanced, automated machine learning capabilities.Learn moreRetailHealthcare and life sciencesJoin an Azure Databricks eventDatabricks, Microsoft and our partners are excited to host these events dedicated to Azure Databricks. Please join us at an event near you to learn more about the fastest-growing data and AI service on Azure! The agenda and format will vary, please see the specific event page for details.\u00a0Learn moreOptimized for AzureSeamlessly integrate to Azure data stores and services with specialized connectors for fast data access and\u00a0simplified management\u00a0across your environment. This makes it easy to set up\u00a0security controls,\u00a0manage environments, and\u00a0process\u00a0all your Azure data.Learn moreFeatured integrationsAzure Active DirectorySingle Sign-On\u00a0with Azure Active Directory is the best way to sign in to Azure Databricks. Azure Databricks also supports\u00a0automated user provisioning\u00a0with Azure AD to create new users, give them the proper level of access, and remove users to deprovision access.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultResourcesWhitepapersAzure Databricks for data engineeringAzure Databricks: The Best Platform to Run ML and AIThree Practical Use Cases with Azure DatabricksGetting Started With Apache Spark on Azure DatabricksVideosAli Ghodsi and Rohan Kumar (CVP, Microsoft) Fireside Chat at Keynote Data + AI Summit NA 2021Azure Databricks Cloud Integration DemoIngest data Into Delta Lake on Azure DatabricksExplore your data using Databricks SQLeBooks2021 Gartner Magic Quadrant for Data Science and Machine Learning PlatformsModern Cloud Data Platform for Dummies8 Steps for a Developer to Learn Apache Spark\u2122 With Delta LakeApache Spark\u2122 Under the Hood: Getting started with core architecture and basic conceptsReady to get started?Get startedSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/?itm_data=events-hp-nav-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leon-eller\/#","text":"Leon Eller - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeon EllerSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/weston-hutchins","text":"Weston Hutchins - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWeston HutchinsProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/08\/03\/how-to-build-a-marketing-analytics-solution-using-fivetran-and-dbt-on-the-databricks-lakehouse.html","text":"Marketing Analytics on the Databricks Lakehouse using Fivetran and dbt - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHow to Build a Marketing Analytics Solution Using Fivetran and dbt on the Databricks Lakehouseby Tahir Fayyaz, Bilal Aslam and Robert SaxbyAugust 3, 2022 in ProductShare this postMarketing teams use many different platforms to drive marketing and sales campaigns, which can generate a significant volume of valuable but disconnected data. Bringing all of this data together can help to drive a large return on investment, as shown by Publicis Groupe who were able to increase campaign revenue by as much as 50%.The Databricks Lakehouse, which unifies data warehousing and AI use cases on a single platform, is the ideal place to build a marketing analytics solution: we maintain a single source of truth, and unlock AI\/ML use cases. We also leverage two Databricks partner solutions, Fivetran and dbt, to unlock a wide range of marketing analytics use cases including churn and lifetime value analysis, customer segmentation, and ad effectiveness.Fivetran and dbt can read and write to Delta Lake using a Databricks cluster or Databricks SQL warehouseFivetran allows you to easily ingest data from 50+ marketing platforms into Delta Lake without the need for building and maintaining complex pipelines. If any of the marketing platforms' APIs change or break, Fivetran will take care of updating and fixing the integrations so your marketing data keeps flowing in.dbt is a popular open source framework that lets lakehouse users build data pipelines using simple SQL. Everything is organized within directories, as plain text, making version control, deployment, and testability simple. Once the data is ingested into Delta Lake, we use dbt to transform, test and document the data. The transformed marketing analytics data mart built on top of the ingested data is then ready to be used to help drive new marketing campaigns and initiatives.Both Fivetran and dbt are a part of Databricks Partner Connect, a one-stop portal to discover and securely connect data, analytics and AI tools directly within the Databricks platform. In just a few clicks you can configure and connect these tools (and many more) directly from within your Databricks workspace.How to build a marketing analytics solutionIn this hands-on demo, we will show how to ingest Marketo and Salesforce data into Databricks using Fivetran and then use dbt to transform, test, and document your marketing analytics data model.All the code for the demo is available on Github in the workflows-examples repository.dbt lineage graph showing data sources and modelsThe final dbt model lineage graph will look like this. The Fivetran source tables are in green on the left and the final marketing analytics models are on the right. By selecting a model, you can see the corresponding dependencies with the different models highlighted in purple.Data ingestion using FivetranFivetran has many marketing analytics data source connectorsCreate new Salesforce and Marketo connections in Fivetran to start ingesting the marketing data into Delta Lake. When creating the connections Fivetran will also automatically create and manage a schema for each data source in Delta Lake. We will later use dbt to transform, clean and aggregate this data.Define a destination schema in Delta Lake for the Salesforce data sourceFor the demo name the schemas that will be created in Delta Lake marketing_salesforce and marketing_marketo. If the schemas do not exist Fivetran will create them as part of the initial ingestion load.Select which data source objects to synchronize as Delta Lake tablesYou can then choose which objects to sync to Delta Lake, where each object will be saved as individual tables. Fivetran also makes it simple to manage and view what columns are being synchronized for each table:Fivetran monitoring dashboard to monitor monthly active rows synchronizedAdditionally, Fivetran provides a monitoring dashboard to analyze how many monthly active rows of data are synchronized daily and monthly for each table, among other useful statistics and logs.Data modeling using dbtNow that all the marketing data is in Delta Lake, you can use dbt to create your data model by following these stepsSetup dbt project locally and connect to Databricks SQLSet up your local dbt development environment in your chosen IDE by following the set-up instructions for dbt Core and dbt-databricks.Scaffold a new dbt project and connect to a Databricks SQL Warehouse using dbt init, which will ask for following information.\n$ dbt init\nEnter a name for your project (letters, digits, underscore): \nWhich database would you like to use?\n[1] databricks\n[2] spark\n\nEnter a number: 1\nhost (yourorg.databricks.com): \nhttp_path (HTTP Path): \ntoken (dapiXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX): \nschema (default schema that dbt will build objects in): \nthreads (1 or more) [1]: \nOnce you have configured the profile you can test the connection using:\n$ dbt debugInstall Fivetran dbt model packages for stagingThe first step in using the Marketo and Salesforce data is to create the tables as sources for our model. Luckily, Fivetran has made this easy to get up and running with their pre-built Fivetran dbt model packages. For this demo, let's make use of the marketo_source and salesforce_source packages.To install the packages just add a packages.yml file to the root of your dbt project and add the marketo-source, salesforce-source and the fivetran-utils packages:\npackages:\n  - package: dbt-labs\/spark_utils\n    version: 0.3.0\n  - package: fivetran\/marketo_source\n    version: [\">=0.7.0\", \"=0.4.0\", \"\n\nTo download and use the packages run\n\n\n$ dbt depsYou should now see the Fivetran packages installed in the packages folder.Update dbt_project.yml for Fivetran dbt modelsThere are a few configs in the dbt_project.yml file that you need to modify to make sure the Fivetran packages work correctly for Databricks.The dbt_project.yml file can be found in the root folder of your dbt project.spark_utils overriding dbt_utils macrosThe Fivetran dbt models make use of macros in the dbt_utils package but some of these macros need to be modified to work with Databricks which is easily done using the spark_utils package.It works by providing shims for certain dbt_utils macros which you can set using the dispatch config in the dbt_project.yml file and with this dbt will first search for macros in the spark_utils package when resolving macros from the dbt_utils namespace.\ndispatch:\n - macro_namespace: dbt_utils\n   search_order: ['spark_utils', 'dbt_utils']\nVariables for the marketo_source and salesforce_source schemasThe Fivetran packages require you to define the catalog (referred to as database in dbt) and schema of where the data lands when being ingested by Fivetran.Add these variables to the dbt_project.yml file with the correct catalog and schema names. The default catalog is hive_metastore which will be used if _database is left blank. The schema names will be what you defined when creating the connections in Fivetran.\nvars:\n marketo_source:\n   marketo_database: # leave blank to use the default hive_metastore catalog\n   marketo_schema: marketing_marketo\n salesforce_source:\n   salesforce_database: # leave blank to use the default hive_metastore catalog\n   salesforce_schema: marketing_salesforce\nTarget schema for Fivetran staging modelsTo avoid all the staging tables that are created by the Fivetran source models being created in the default target schema it can be useful to define a separate staging schema.In the dbt_project.yml file add the staging schema name and this will then be suffixed to the default schema name.\nmodels:\n marketo_source:\n   +schema: your_staging_name # leave blank to use the default target_schema\n salesforce_source:\n   +schema: your_staging_name # leave blank to use the default target_schema\nBased on the above, if your target schema defined in profiles.yml is mkt_analytics, the schema used for marketo_source and salesforce_source tables will be mkt_analytics_your_staging_name.Disable missing tablesAt this stage you can run the Fivetran model packages to test that they work correctly.\ndbt run \u2013select marketo_source\ndbt run \u2013select salesforce_sourceIf any of the models fail due to missing tables, because you chose not to sync those tables in Fivetran, then in your source schema you can disable those models by updating the dbt_project.yml file.For example if the email bounced and email template tables are missing from the Marketo source schema you can disable the models for those tables by adding the following under the models config:\nmodels:\n marketo_source:\n   +schema: your_staging_name \n   tmp:\n     stg_marketo__activity_email_bounced_tmp:\n       +enabled: false\n     stg_marketo__email_template_history_tmp:\n       +enabled: false\n   stg_marketo__activity_email_bounced:\n     +enabled: false\n   stg_marketo__email_template_history:\n     +enabled: false\nDeveloping the marketing analytics modelsdbt lineage graph showing the star schema and aggregate tables data modelNow that the Fivetran packages have taken care of creating and testing the staging models you can begin to develop the data models for your marketing analytics use cases which will be a star schema data model along with materialized aggregate tables.For example, for the first marketing analytics dashboard, you may want to see how engaged certain companies and sales regions are by the number of email campaigns they have opened and clicked.To do so, you can join Salesforce and Marketo tables using the Salesforce user email, Salesforce account_id and Marketo lead_id.The models will be structured under the mart folder in the following way.\nmarketing_analytics_demo\n|-- dbt_project.yml\n|-- packages.yml\n|-- models\n      |-- mart\n             |-- core\n             |-- intermediate\n             |-- marketing_analytics\nYou can view the code for all the models on Github in the \/models\/mart directory and below describes what is in each folder along with an example.Core modelsThe core models are the facts and dimensions tables that will be used by all downstream models to build upon.The dbt SQL code for the dim_user model\nwith salesforce_users as (\n   select\n       account_id,\n       email\n   from {{ ref('stg_salesforce__user') }}\n   where email is not null and account_id is not null\n),\nmarketo_users as (\n   select\n       lead_id,\n       email\n   from {{ ref('stg_marketo__lead') }}\n),\njoined as (\n   select\n     lead_id,\n     account_id\n   from salesforce_users\n     left join marketo_users\n     on salesforce_users.email = marketo_users.email\n)\n\nselect * from joined\nYou can also add documentation and tests for the models using a yaml file in the folder.There are 2 simple tests in the core.yml file that have been added\nversion: 2\n\nmodels:\n - name: dim_account\n   description: \"The Account Dimension Table\"\n   columns:\n     - name: account_id\n       description: \"Primary key\"\n       tests:\n         - not_null\n - name: dim_user\n   description: \"The User Dimension Table\"\n   columns:\n     - name: lead_id\n       description: \"Primary key\"\n       tests:\n         - not_null\nIntermediate modelsSome of the final downstream models may rely on the same calculated metrics and so to avoid repeating SQL you can create intermediate models that can be reused.The dbt SQL code for int_email_open_clicks_joined model:\nwith opens as (\n\tselect * \n\tfrom {{ ref('fct_email_opens') }} \n), clicks as (\n\tselect * \n\tfrom {{ ref('fct_email_clicks') }} \n), opens_clicks_joined as (\n\n    select \n      o.lead_id as lead_id,\n      o.campaign_id as campaign_id,\n      o.email_send_id as email_send_id,\n      o.activity_timestamp as open_ts,\n      c.activity_timestamp as click_ts\n    from opens as o \n      left join clicks as c \n      on o.email_send_id = c.email_send_id\n      and o.lead_id = c.lead_id\n\n)\n\nselect * from opens_clicks_joined\nMarketing Analytics modelsThese are the final marketing analytics models that will be used to power the dashboards and reports used by marketing and sales teams.The dbt SQL code for country_email_engagement model:\nwith accounts as (\n\tselect \n        account_id,\n        billing_country\n\tfrom {{ ref('dim_account') }}\n), users as (\n\tselect \n        lead_id,\n        account_id\n\tfrom {{ ref('dim_user') }} \n), opens_clicks_joined as (\n\n    select * from {{ ref('int_email_open_clicks_joined') }} \n\n), joined as (\n\n\tselect * \n\tfrom users as u\n\tleft join accounts as a\n\ton u.account_id = a.account_id\n\tleft join opens_clicks_joined as oc\n\ton u.lead_id = oc.lead_id\n\n)\n\nselect \n\tbilling_country as country,\n\tcount(open_ts) as opens,\n\tcount(click_ts) as clicks,\n\tcount(click_ts) \/ count(open_ts) as click_ratio\nfrom joined\ngroup by country\nRun and test dbt modelsNow that your model is ready you can run all the models using\n$ dbt runAnd then run the tests using\n$ dbt testView the dbt docs and lineage graphdbt lineage graph for the marketing analytics modelOnce your models have run successfully you can generate the docs and lineage graph using\n$ dbt docs generateTo then view them locally run\n$ dbt docs serveDeploying dbt models to productionOnce you have developed and tested your dbt model locally you have multiple options for deploying into production one of which is the new dbt task type in Databricks Workflows (private preview).Your dbt project should be managed and version controlled in a Git repository. You can create a dbt task in your Databricks Workflows job pointing to the Git repository.Using a dbt task type in Databricks Workflows to orchestrate dbtAs you are using packages in your dbt project the first command should be dbt deps followed by dbt run for the first task and then dbt test for the next task.Databricks Workflows job with two dependant dbt tasksYou can then run the workflow immediately using run now and also set up a schedule for the dbt project to run on a specified schedule.Viewing the dbt logs for each dbt runFor each run you can see the logs for each dbt command helping you debug and fix any issues.Powering your marketing analytics with Fivetran and dbtAs shown here using Fivetran and dbt alongside the Databricks Lakehouse Platform allows you to easily build a powerful marketing analytics solution that is easy to set-up, manage and flexible enough to suit any of your data modeling requirements.To get started with building your own solution visit the documentation for integrating Fivetran and dbt with Databricks and re-use the marketing_analytics_demo project example to quickly get started.The dbt task type in Databricks Workflows is in private preview. To try the dbt task type, please reach out to your Databricks account executive.Try Databricks for freeGet StartedRelated postsNow Generally Available: Simplify Data and Machine Learning Pipelines With Jobs OrchestrationNovember 1, 2021 by Roland F\u00e4ustlin in Platform Blog\nWe are excited to announce the general availability of Jobs orchestration, a new capability that lets Databricks customers easily build data and machine...\nDatabricks Ventures Partners With dbt Labs to Welcome Analytics Engineers to the LakehouseFebruary 24, 2022 by Bilal Aslam, Shant Hovsepian, Robert Saxby and Andrew Ferguson in Company Blog\nToday, we are thrilled to announce Databricks Ventures\u2019 investment in dbt Labs. With this investment, we are proud to support the growth of t...\n7 Reasons to Migrate From Your Cloud-Based Hadoop to the Databricks Lakehouse PlatformJune 9, 2022 by Chris Moon, Abhishek Dey and Ganesh Rajagopal in Platform Blog\nOver the past several years, many enterprises have migrated their legacy on-prem Hadoop workloads to cloud-based managed services like EMR, HDInsight, or DataProc...\nSee all Product postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/himanshu-raja\/#","text":"Himanshu Raja - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHimanshu Raja DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zachary-bannor\/#","text":"Zachary Bannor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZachary BannorData Engineering Manager at Cond\u00e9 NastBack to speakersDr. Zachary R. Bannor, PharmD, is a data engineering manager at Cond\u00e9 Nast. His team works to de-silo data and to build robust data pipelines to provide valuable datasets to stakeholders across myriad business verticals. He lives in Chicago with his wife, Nicole, and cats, Stuart and Samantha. His interests include cooking, cycling, weight lifting, and playing with his band, Five Step Drop.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lucas-dos-santos-celestino","text":"Lucas dos Santos Celestino - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLucas dos Santos CelestinoPlatform Product Manager at AB InbevBack to speakersCurrently working for Anheuser-Busch InBev (Brazil) as Platform Product Manager with expertise in software development, cloud architecture\/infrastructure, UX design, product operations and agile methods.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#fd8d8f948b9c9e84bd999c899c9f8f949e968ed39e9290","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c35893a119c36\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/customers\/all","text":"Customer All | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks CustomersDiscover how innovative companies across every industry are leveraging the Databricks Lakehouse Platform for successTry DatabricksSchedule a demoLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/diversity","text":"Diversit\u00e9 et inclusion | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWL'avenir des donn\u00e9es est ouvert \u00e0 tousDiversit\u00e9, \u00e9galit\u00e9 et inclusion chez DatabricksLa puissance des donn\u00e9es. L'\u00e9nergie des \u00e9quipes.Nous nous sommes donn\u00e9 pour mission de diversifier le monde des Big Data, en commen\u00e7ant par notre \u00e9quipe. Nous avons la conviction que la diversit\u00e9 des parcours, des exp\u00e9riences, des perspectives, des connaissances et des comp\u00e9tences stimulent l'innovation et renforcent les liens qui nous unissent \u00e0 nos clients. Nous encourageons activement une culture d'appartenance o\u00f9 chacun se sent pleinement en mesure de lib\u00e9rer tout son potentiel professionnel. Que ce soit en garantissant l'\u00e9galit\u00e9 salariale ou en mettant sur pied des programmes qui rendent hommage \u00e0 nos \u00e9quipes, les forment et les motivent, nous incorporons la diversit\u00e9, l'\u00e9galit\u00e9 et l'inclusion (DEI) \u00e0 tout ce que nous faisons.Certification Fair Pay Workplace\nNous sommes fiers d'\u00eatre l'une des six premi\u00e8res organisations \u00e0 recevoir la certification Fair Pay Workplace. Dans le cadre de nos efforts pour atteindre l'\u00e9galit\u00e9 salariale, Databricks a soumis ses donn\u00e9es et pratiques salariales \u00e0 une \u00e9valuation. Nous nous sommes \u00e9galement engag\u00e9s \u00e0 rendre des comptes en proc\u00e9dant \u00e0 des analyses r\u00e9guli\u00e8res de l'\u00e9galit\u00e9 salariale.Gaingels et Flucas Ventures\nNotre engagement envers la diversit\u00e9, l\u2019\u00e9galit\u00e9 et l\u2019inclusion englobe toute notre \u00e9quipe, des personnes qui travaillent avec nous \u00e0 celles qui investissent dans nos projets. C'est pourquoi nous sommes fiers d'\u00eatre les partenaires d'un \u00e9ventail d'investisseurs de classe mondiale, parmi lesquels Gaingels et Flucas Ventures qui ciblent en priorit\u00e9 les entreprises manifestant un engagement profond envers la DEI.\u00ab\u00a0Nous savons que la qualit\u00e9 de nos insights d\u00e9pend de la quantit\u00e9 de donn\u00e9es dont nous disposons. Il en va de m\u00eame pour la diversit\u00e9 et l'inclusion\u00a0: Databricks s'\u00e9panouit en accueillant la plus grande diversit\u00e9 possible de parcours, d'exp\u00e9riences et de points de vue.\u00a0\u00bb\u2014 Ali Ghodsi, Cofondateur et PDG de DatabricksNos communaut\u00e9sNous sommes convaincus que c'est en donnant de l'autonomie \u00e0 nos collaborateurs qu'ils pourront lib\u00e9rer tout leur potentiel. Nos groupes de ressources collaborateurs (ERG) sont des collectifs vivants et dynamiques qui jouent un r\u00f4le cl\u00e9 dans l'\u00e9laboration d'un environnement inclusif et bienveillant chez Databricks. Ces communaut\u00e9s diverses de salari\u00e9s et d'alli\u00e9s cr\u00e9ent des espaces d'\u00e9change et de c\u00e9l\u00e9bration, tout en nous sensibilisant \u00e0 des probl\u00e9matiques essentielles.R\u00e9seau Queeries\nR\u00e9seau de V\u00e9t\u00e9rans\nR\u00e9seau des Collaborateurs Noirs (Black Employee Network)\nR\u00e9seau de Femmes\nR\u00e9seau LatinX\nR\u00e9seau des Collaborateurs asiatiques\nNos exp\u00e9riences\u00ab\u00a0Chez Databricks, je cr\u00e9e des \u00e9quipes dont j'aurais envie de faire partie, des environnements o\u00f9 je pourrais \u00eatre pleinement moi-m\u00eame en toute s\u00e9curit\u00e9 et offrir le m\u00eame espace de confort \u00e0 tous ceux qui m'entourent. L'attention que nous portons les uns aux autres et notre engagement pour l'inclusion ont un impact consid\u00e9rable sur l'ensemble de notre communaut\u00e9.\u00a0\u00bb\u2014 Stacy Kerkela, Directrice de l\u2019ing\u00e9nierieEn savoir plus\u00ab\u00a0Le r\u00e9seau LatinX de Databricks me donne un fort sentiment d'appartenance \u00e0 la communaut\u00e9, une communaut\u00e9 ouverte. En effet, chez Databricks, nos groupes de ressources collaborateurs accueillent et informent toutes les personnes qui se pr\u00e9sentent, quel que soit leur parcours.\u00a0\u00bb\u2014 Miguel Peralvo, Senior Solutions ArchitectEn savoir plus\u00ab\u00a0Beaucoup d'entreprises s'attachent \u00e0 accro\u00eetre la diversit\u00e9 des genres, mais c\u2019est formidable de voir son employeur prendre activement des mesures pour faire bouger les choses.\u00a0\u00bb\u2014 Allie Emrich, Program Management, ProductEn savoir plusL'inclusion en actionRapportPartenariats avec ColorStack et Rewriting the CodeNotre \u00e9quipe de recrutement universitaire s\u2019associe \u00e0 ColorStack et \u00e0 Rewriting the Code pour aider les femmes ainsi que les \u00e9tudiants noirs et LatinX \u00e0 poursuivre une carri\u00e8re dans la technologie.En savoir plusRapportProgramme de mentorat Women in TechChez Databricks, nous savons \u00e0 quel point il est important d'offrir des opportunit\u00e9s de d\u00e9veloppement et d'avancement professionnel aux communaut\u00e9s historiquement sous-repr\u00e9sent\u00e9es.En savoir plusRapportPrix InHerSight 2021Nous avons le plaisir de figurer parmi les meilleurs lieux de travail pour les femmes dans le secteur du logiciel, selon une \u00e9valuation faite par des femmes. Pour en savoir plus, visitez notre profil InHerSight.En savoir plusB\u00e2tissons ensemble l'avenir des donn\u00e9esNous nous sommes donn\u00e9 pour mission de simplifier et d\u00e9mocratiser les donn\u00e9es et l'IA, et nous avons besoin de vous pour la mener \u00e0 bien.D\u00e9couvrez les opportunit\u00e9sProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/jp\/blog","text":"Databricks \u30d6\u30ed\u30b0Skip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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NOWLoading...\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"Solu\u00e7\u00f5es de parceiros - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWSolu\u00e7\u00f5es para parceirosSolu\u00e7\u00f5es especializadas em lakehouse e ferramentas de migra\u00e7\u00e3o desenvolvidas por nossos parceirosFazemos parceria com as principais empresas de consultoria para projetar solu\u00e7\u00f5es e ferramentas de migra\u00e7\u00e3o inovadoras para os casos de uso espec\u00edficos do seu setor. As solu\u00e7\u00f5es Databricks Brickbuilder s\u00e3o projetadas por nossos parceiros para ajudar voc\u00ea a reduzir custos e aumentar o valor dos seus dados. Com anos de experi\u00eancia da empresa no setor e forte envolvimento na Plataforma Databricks Lakehouse, voc\u00ea tem a garantia de receber solu\u00e7\u00f5es adequadas para o seu neg\u00f3cio.Buscar parcerias dispon\u00edveissearchSetor p\u00fablicoCloud Data Migration by Accenture - DatabricksSaiba maisVarejo e bens de consumoUnified View of Demand by AccentureSaiba maisTecnologia de Publicidade e MarketingCPG Control Tower by AvanadeSaiba maisTecnologia de Publicidade e MarketingIntelligent Healthcare on Azure Databricks by AvanadeSaiba maisTecnologia de Publicidade e MarketingIntelligent ManufacturingSaiba maisTecnologia de Publicidade e MarketingLegacy System Migration by AvanadeSaiba maisTecnologia de Publicidade e MarketingRisk Management by AvanadeSaiba maisTecnologia e softwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksSaiba maisTecnologia e softwareMigrate to Cloud and Databricks by Capgemini and DatabricksSaiba maisTecnologia e softwareCapgemini Revenue Growth ManagementSaiba maisTecnologia e softwareMigrate to Databricks by Celebal Technologies and DatabricksSaiba maisTecnologia e softwareCognizant Video Quality of ExperienceSaiba maisTecnologia de Publicidade e MarketingPersona 360 by DataSentics and DatabricksSaiba maisTecnologia de Publicidade e MarketingSAP Migration Accelerator by DataSentics - DatabricksSaiba maisTecnologia de Publicidade e MarketingPrecisionView\u2122 by DeloitteSaiba maisTecnologia de Publicidade e MarketingTrellis by DeloitteSaiba maisTecnologia de Publicidade e MarketingSmart Migration to Databricks by EPAMSaiba maisTecnologia de Publicidade e MarketingLeapLogic Migration Solution by ImpetusSaiba maisCarregue maisTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steve-sobel\/#","text":"Steve Sobel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteve SobelGlobal Lead - Communications, Media & Entertainment at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/survivorship-and-churn","text":"Analyzing Customer Attrition in Subscription Models | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorSubscriber Churn PredictionPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAnalyze and predict subscriber attritionPreempt churn with the Databricks Solution Accelerator for predicting subscriber attrition. Learn how to analyze behavioral data to identify subscribers with an increased risk of cancellation. Then use machine learning to quantify the likelihood to churn as well as indicate which factors explain that risk.Understand your customers to appropriately engage with themAccelerate data pipelines by 6x, enabling teams to make decisions fasterCreate more personalized experiences that drive subscriber engagementDownload notebookResourcesExplainer videoLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/volker-tjaden\/#","text":"Volker Tjaden - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVolker TjadenManager Solution Architects at DatabricksBack to speakersVolker leads a team of Solutions Architects at Databricks. His career in Data & AI started out as an economics student at university where he focused on statistical and computational methods working with large datasets. After completing a PhD, he held various consulting and management positions in different industries where he built data driven solutions to business problems such as dynamic pricing in banking, automated supply chains in retail and IoT platforms in manufacturing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/databricks-platform-demo","text":"Databricks Platform Demo: Unify Your Data & AI | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Platform DemoGet started for freeIn this demo, we walk through an overview of the Databricks Platform, including the platform architecture and the Databricks data science, engineering, machine learning and SQL environments.\nSee full list of demos \nVideo transcriptLet\u2019s take a look at the architecture of the Databricks platform. While understanding the details of all the components and how they\u2019re integrated falls under the responsibility of a platform administrator, as a data engineer, it\u2019s good to have a broad understanding of the structure and how it all comes together.\nThis diagram illustrates the Databricks architecture. The control plane consists of the backend services that Databricks manages in its own cloud account aligned with the cloud service and used by the customer \u2013 AWS Azure or GCP. Though the majority of your data does not live here, some elements, such as notebook commands and workspace configurations, are stored in the control plane and encrypted at rest. Through the control plane and the associated UI and APIs it provides, one can launch clusters, start jobs and get results, and interact with table metadata.\nCollapse full transcriptExpand full transcriptProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/product\/data-lakehouse","text":"Data Lakehouse Platform von Databricks \u2013 Jetzt eine Demo vereinbaren! | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDie Lakehouse-Plattform von DatabricksIhre Data Warehousing- und KI-Anwendungsf\u00e4lle auf einer einzigen Plattform vereinheitlichenKostenlos testen\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowEinfach. Offen. Multi-Cloud.Die Databricks Lakehouse Plattform kombiniert die besten Elemente von Data Lakes und Data Warehouses, um die Zuverl\u00e4ssigkeit, starke Governance und Leistung von Data Warehouses mit der Offenheit, Flexibilit\u00e4t und Unterst\u00fctzung f\u00fcr Machine Learning von Data Lakes zu verbinden.Dieser vereinheitlichte Ansatz vereinfacht Ihren modernen Daten-Stack, indem er die Datensilos beseitigt, die bisher Data Engineering, Analytics, BI, Data Science und Machine Learning trennen und verkomplizieren. Die Plattform fu\u00dft auf Open Source und offenen Standards und bietet so ein Maximum an Flexibilit\u00e4t. Und der gemeinsame Ansatz f\u00fcr Datenmanagement, Sicherheit und Governance hilft Ihnen, effizienter zu arbeiten und Innovationen schneller voranzutreiben.EinfachDer einheitliche Ansatz vereinfacht Ihre Datenarchitektur, indem Datensilos eliminiert werden, die beim herk\u00f6mmlichen Ansatz separate Analytics, BI, Data Science und Machine Learning voneinander trennen. Mit einem Lakehouse k\u00f6nnen Sie die Komplexit\u00e4t und die Kosten beseitigen, die es schwierig machen, das volle Potenzial Ihrer Analytics- und KI-Initiativen auszusch\u00f6pfen.OffenDelta Lake bildet das offene Fundament des Lakehouse, indem es Zuverl\u00e4ssigkeit und herausragende Leistung bei Daten direkt im Data Lake bietet. Sie k\u00f6nnen abgegrenzte Bereiche vermeiden, Daten problemlos austauschen und Ihren modernen Daten-Stack mit uneingeschr\u00e4nktem Zugang zum \u00d6kosystem der Open-Source-Datenprojekte und dem breiten Databricks-Partnernetzwerk entwickeln.Erfahren Sie mehr \u00fcber 450+ Partner in der gesamten DatenlandschaftWeitere InformationenMulti-CloudDie Databricks Lakehouse Plattform bietet Ihnen ein einheitliches Management-, Sicherheits- und Governance-Erlebnis in allen Clouds. Sie m\u00fcssen nicht in die Neuerfindung von Prozessen f\u00fcr jede Cloud-Plattform investieren, die Sie zur Unterst\u00fctzung Ihrer Daten- und KI-Bem\u00fchungen nutzen. Stattdessen k\u00f6nnen sich Ihre Datenteams einfach darauf konzentrieren, alle Daten zu nutzen, um neue Einblicke zu gewinnen.Weitere InformationenSch\u00f6pfen Sie das Potenzial Ihrer Daten \u2013 und Ihrer Datenteams ausErfahren Sie mehr dar\u00fcber, wie die Databricks Lakehouse-Plattform Ihre Daten- und KI-Workloads unterst\u00fctztData EngineeringDatabricks SQLMachine Learning\u00c4hnliche Inhalte\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu den Vorteilen von Data Engineering in Databricks.\nRessourcen erkundenLakehouseWas ist ein Lakehouse?Einsteigerbuch: \u201eThe Modern Cloud Data Platform\u201cDer Aufstieg des Lakehouse-ParadigmasRise of the Data Lakehouse von Bill Inmon, dem Vater des Data WarehouseDelta LakeDas gro\u00dfe Buch des Data Engineering\u201eDelta Lake: The Definitive Guide\u201c von O\u2019ReillyDer ultimative Leitfaden zu Delta LakeDelta Lake \u2013 die Grundlage f\u00fcr unser LakehouseMachine LearningE-Book: \u201eStandardizing the ML Lifecycle\u201cVirtuelle Veranstaltung: \u201eBuilding Machine Learning Platforms\u201cM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/albert-hu\/#","text":"Albert Hu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlbert HuSenior Analytics Engineer at Rec RoomBack to speakersAlbert is a Senior Analytics Engineer at Rec Room, a social UGC app you can play on multiple platforms. In this role, he is responsible for building out the infrastructure to enable analysis, experimentation, and product features. Prior to Rec Room, Albert held various roles in both startups and Fortune 500 companies including Head of Analytics at Ribbon and Data Product roles at Walmart. He holds a B.A., Economics and Mathematics from Northwestern University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mark-lee","text":"Mark Lee - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMark LeeSenior Specialist Solutions Architect at DatabricksBack to speakersMark is a Senior Specialist Solutions Architect at Databricks. He brings with him over a decade of experience in Health Life Sciences and emerging high performance computing technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-wisdom-of-transitioning-to-a-data-lakehouse-strategy","text":"The Wisdom of Transitioning to a Data Lakehouse Strategy \u2013 DatabrickseBookPlan your data lakehouse transitionWhat to know before you beginCloud modernization has become the rallying cry for organizations that want to take advantage of advanced analytics using ML and AI while they continue to support traditional data warehouse consumers.Meanwhile, data consumers have become more sophisticated in how they use analytics and data science tools, and have raised their expectations for data democratization.This TDWI Checklist explores how a data lakehouse approach can help you overcome the common limitations of existing data architecture strategies.In this eBook, you\u2019ll learn:The limitations of existing data architecture strategies in supporting emerging and future analytics needsThe benefits of a data lakehouse approach in addressing these limitationsSeven steps for transitioning to a data lakehouseGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-hayes-0\/#","text":"Matthew Hayes - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew HayesSoftware Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/scc-customers","text":"Amendment to Data Processing Addendum (SCC Amendment) | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAmendment to Data Processing Addendum (SCC Amendment)Dear Existing Databricks Customers -Databricks updated its Data Processing Addendum (DPA) to incorporate the 2021 Standard Contractual Clauses (SCCs). DPAs signed after September 24, 2021 will therefore include the 2021 SCCs.For Customers with DPAs executed before September 24, 2021, Databricks offers the following options:Enter into an Amendment to the DPA (Data Transfer Addendum for SCCs), available below, which replaces the existing SCCs and SCC specific terms with the 2021 SCCs and SCC specific terms. Your existing DPA will otherwise remain unaffected.Click here to sign an amendment to your existing DPA with Databricks to include the new SCCsClick here to download a sample of the Databricks DPA AmendmentEnter into a new DPA, available below, which will replace your existing DPA in its entirety;Click here to sign a new DPA with Databricks in its entiretyClick here to download a sample of the Databricks DPAFor both options, you can electronically sign the relevant documentation above. Upon completion, a copy of the executed DPA will be emailed to the address you designate during the process.If you have any questions or concerns, please contact [email\u00a0protected].ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/managed-mlflow","text":"Managed MLflow | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWManaged MLflowManaging the complete machine learning lifecycleTry for freeSchedule a demoWhat is Managed MLflow?Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete machine learning lifecycle with enterprise reliability, security and scale. The latest update to MLflow is packed with innovative features that broaden its ability to manage and deploy large language models (LLMs). This enhanced LLM support is delivered through three new model flavors: Hugging Face Transformers, OpenAI functions and LangChain.BenefitsModel developmentAccelerate and simplify machine learning lifecycle management with a standardized framework for developing production-ready ML models. With managed MLflow Recipes, you can bootstrap ML projects, perform rapid iteration with ease and ship high-quality models to production at scale.Experiment trackingRun experiments with any ML library, framework or language, and automatically keep track of parameters, metrics, code and models from each experiment. By using MLflow on Databricks, you can securely share, manage and compare experiment results along with corresponding artifacts and code versions \u2014 thanks to built-in integrations with the Databricks Workspace and notebooks.Model managementUse one central place to discover and share ML models, collaborate on moving them from experimentation to online testing and production, integrate with approval and governance workflows and CI\/CD pipelines, and monitor ML deployments and their performance. The MLflow Model Registry facilitates sharing of expertise and knowledge, and helps you stay in control.Model deploymentQuickly deploy production models for batch inference on Apache Spark\u2122 or as REST APIs using built-in integration with Docker containers, Azure ML or Amazon SageMaker. With Managed MLflow on Databricks, you can operationalize and monitor production models using Databricks Jobs Scheduler and auto-managed Clusters to scale based on the business needs.FeaturesMLflow Model Registry\nCENTRAL REPOSITORY: Register MLflow models with the MLflow Model Registry. A registered model has a unique name, version, stage, and other metadata.\nMODEL VERSIONING: Automatically keep track of versions for registered models when updated.\nMODEL STAGE: Assign preset or custom stages to each model version, like \u201cStaging\u201d and \u201cProduction\u201d to represent the lifecycle of a model.\nCI\/CD WORKFLOW INTEGRATION: Record stage transitions, request, review and approve changes as part of CI\/CD pipelines for better control and governance.\nMODEL STAGE TRANSITIONS: Record new registration events or changes as activities that automatically log users, changes, and additional metadata such as comments.\nMLflow Models\nMLFLOW MODELS: A standard format for packaging machine learning models that can be used in a variety of downstream tools \u2014 for example, real-time serving through a REST API or batch inference on Apache Spark.\nMODEL CUSTOMIZATION: Use Custom Python Models and Custom Flavors for models from an ML library that is not explicitly supported by MLflow\u2019s built-in flavors.\nBUILT-IN MODEL FLAVORS: MLflow provides several standard flavors that might be useful in your applications, like Python and R functions, Hugging Face, OpenAI and LangChain, PyTorch, Spark MLlib, TensorFlow, and ONNX.\nBUILT-IN DEPLOYMENT TOOLS: Quickly deploy on Databricks via Apache Spark UDF for a local machine, or several other production environments such as Microsoft Azure ML, Amazon SageMaker, and building Docker Images for Deployment.\nMLflow Recipes\nSIMPLIFIED PROJECT STARTUP: MLflow Recipes provides out-of-box connected components for building and deploying ML models.\nACCELERATED MODEL ITERATION: MLflow Recipes creates standardized, reusable steps for model iteration \u2014 making the process faster and less expensive.\nAUTOMATED TEAM HANDOFFS: Opinionated structure provides modularized production-ready code, enabling automatic handoff from experimentation to production.\nMLflow Projects\nMLFLOW PROJECTS: MLflow projects allow you to specify the software environment that is used to execute your code. MLflow currently supports the following project environments: Conda environment, Docker container environment, and system environment. Any Git repo or local directory can be treated as an MLflow project.\nREMOTE EXECUTION MODE: Run MLflow Projects from Git or local sources remotely on Databricks clusters using the Databricks CLI to quickly scale your code.\nMLflow Tracking\nMLFLOW TRACKING: Automatically log parameters, code versions, metrics, and artifacts for each run using Python, REST, R API, and Java API\nMLFLOW TRACKING SERVER: Get started quickly with a built-in tracking server to log all runs and experiments in one place. No configuration needed on Databricks.\nEXPERIMENT MANAGEMENT: Create, secure, organize, search, and visualize experiments from within the Workspace with access control and search queries.\nMLFLOW RUN SIDEBAR: Automatically track runs from within notebooks and capture a snapshot of your notebook for each run, so that you can always go back to previous versions of your code.\nLOGGING DATA WITH RUNS: Log parameters, data sets, metrics, artifacts and more as runs to local files, to a SQLAlchemy compatible database, or remotely to a tracking server.\nDELTA LAKE INTEGRATION: Track large-scale data sets that fed your models with Delta Lake snapshots.\nARTIFACT STORE: Store large files such as S3 buckets, shared NFS file system, and models in Amazon S3, Azure Blob Storage, Google Cloud Storage, SFTP server, NFS, and local file paths.\nSee our Product News from Azure Databricks and AWS to learn more about our latest features.Comparing MLflow offeringsHow it worksMLflow is a lightweight set of APIs and user interfaces that can be used with any ML framework throughout the Machine Learning workflow. It includes four components: MLflow Tracking, MLflow Projects, MLflow Models and MLflow Model RegistryMore about MLflowMLflow TrackingRecord and query experiments: code, data, config, and results.\nLearn moreMLflow ProjectsPackaging format for reproducible runs on any platform.\nLearn moreMLflow ModelsGeneral format for sending models to diverse deployment tools.\nLearn moreMLflow Model RegistryCentralized repository to collaboratively manage MLflow models throughout the full lifecycle.\nLearn moreManaged MLflow on DatabricksManaged MLflow on Databricks is a fully managed version of MLflow providing practitioners with reproducibility and experiment management across Databricks Notebooks, Jobs, and data stores, with the reliability, security, and scalability of the Databricks Lakehouse Platform.Read the docsLog your first run as an experimentExecute runs remotely as Databricks jobsDeploy a model for a batch interfaceResourcesBlogsDatabricks Extends MLflow Model Registry With Enterprise FeaturesHow to Display Model Metrics in Dashboards Using the MLflow Search APIAutomate Deployment and Testing With Databricks Notebook + MLflowIntroducing the MLflow Model RegistryA Guide to MLflow Talks at Spark + AI Summit 2019 EuropeProductionizing Machine Learning: From Deployment to Drift DetectionDetecting Bias With SHAPHyperparameter Tuning With MLflow, Apache Spark MLlib and HyperoptA Guide to MLflow Talks at Spark + AI Summit 2019MLflow On-Demand Webinar and FAQ Now AvailableIntroducing MLflow: An Open Source Machine Learning PlatformVideosComcast: How to Utilize MLflow and Kubernetes to Build an Enterprise ML PlatformGojek: Scaling Ride-Hailing With Machine Learning on MLflowShowtime: Data-Driven Transformation: Leveraging Big Data at Showtime With Apache SparkBest Practices for Hyperparameter Tuning With MLflowAdvanced Hyperparameter Optimization for Deep Learning With MLflowRStudio: Managing the Machine Learning Lifecycle With MLflow and RSplice Machine\u2019s Use of Apache Spark and MLflowKount: Moving a Fraud-Fighting Random Forest From scikit-learn to Spark With MLlibTutorialsDetecting Financial Fraud at Scale With Decision Trees and MLflow on DatabricksUsing Dynamic Time Warping and MLflow to Detect Sales Trends (Part 1)Using Dynamic Time Warping and MLflow to Detect Sales Trends (Part 2)How to Use MLflow to Experiment a Keras Network Model: Binary Classification for Movie ReviewsHow to Use MLflow, TensorFlow and Keras With PyCharmHow to Use MLflow to Reproduce Results and Retrain Saved Keras ML ModelsWebinarsAutoML Rapid, Simplified Machine Learning EveryoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningAutomated Hyperparameter Tuning, Scaling and Tracking on DatabricksWhat\u2019s New With MLflow? On-Demand Webinar and FAQs Now AvailableManaging the Complete Machine Learning Lifecycle: On-Demand Webinar Now AvailableUnderstanding MLflow: Ask the ExpertsMLOps Virtual EventeBooksStandardizing the Machine Learning LifecycleFour Real-Life Machine Learning Use CasesThe Big Book of Machine Learning Use CasesNotebooksMLflow Quick Start in PythonMLflow Quick Start in RMLflow Quick Start in ScalaFinancial Fraud Detection Using Decision Tree Machine Learning ModelsUsing Dynamic Time Warping and MLflow to Detect Sales Trends (dbc format)DocumentationTracking Training RunsSaving and Deploying ModelsReproducible RunsManaging ModelsReady to get started?Try Databricks for freeQuick Start GuideProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jiajun-yao\/#","text":"Jiajun Yao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJiajun YaoSoftware Engineer at AnyscaleBack to speakersJiajun works on the Engineering team for Ray core at Anyscale. Prior to working at AnyScale, he was at LinkedIn where he worked on Liquid, an in-memory graph database.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-mlops","text":"The Big Book of MLOps | DatabrickseBookA new data-centric approach to building robust MLOps practicesDiscover the fastest path to get machine learning models to production. The Big Book of MLOps will show you how data engineers, data scientists, and machine learning engineers can build and collaborate on a common platform, using powerful and open frameworks such as Delta Lake for data pipelines, MLflow for model management and Databricks Workflows for automation.In this eBook, you\u2019ll learn:The essential components of an MLOps reference architectureThe key stakeholders to involve as you build and deploy machine learning applicationsHow to leverage the same platform for data and models and get to production fasterHow to monitor data and models through the complete ML lifecycle with end-to-end lineageBest practices to guide your MLOps planning and decision-makingDownload your copyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deepa-paranjpe\/#","text":"Deepa Paranjpe - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeepa ParanjpeDirector of Engineering at DiscoveryBack to speakersDeepa Paranjpe is director of engineering in WBD.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/data-ingestion","text":"Data ingestion | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData ingestionEasily load your data into Delta LakeTry for freeWatch a demoWith Databricks, you can ingest data from hundreds of data sources incrementally and efficiently into your Delta Lake to ensure your\u00a0lakehouse\u00a0always contains the most complete and up-to-date data available for data science, machine learning and business analytics.Data ingestion, simplifiedAuto LoaderUse Auto Loader to ingest any file that can land in a data lake into Delta Lake. Point Auto Loader to a directory on cloud storage services like Amazon S3, Azure Data Lake Storage or Google Compute Storage, and Auto Loader will incrementally process new files with exactly once semantics.Tracking and monitoringLet Auto Loader track which files have been processed, discover late arriving data, infer your data schema, monitor schema changes over time and rescue data with data quality problems. Auto Loader can ingest data continuously within seconds or can be scheduled to run at your expected data arrival rate \u2014 whether it is once an hour, once a day or once a month.Copy intoThe SQL command COPY INTO allows you to perform batch file ingestion into Delta Lake. COPY INTO is a command that ingests files with exactly once semantics, best used when the input directory contains thousands of files or fewer, and the user prefers SQL. COPY INTO can be used over JDBC to push data into Delta Lake at your convenience.Efficient data processingWith Databricks, you can pull data from popular message queues, such as\u00a0Apache Kafka, Azure Event Hubs or AWS Kinesis at lower latencies. By ingesting your data from these sources into your Delta Lake, you don\u2019t have to worry about losing data within these services due to retention policies. You can reprocess data cheaper and more efficiently as business requirements evolve, and you can keep a longer historical view of your data to power machine learning as well as business analytics applications.Unify your data from other enterprise applicationsLeverage a vast data ingestion network of partners like Azure Data Factory, Fivetran, Qlik, Infoworks, StreamSets and Syncsort to easily ingest data from applications, data stores, mainframes, files and more into Delta Lake from an easy-to-use gallery of connectors. Utilize an ecosystem of partners to realize the full potential of combining big data and data from cloud-based applications, databases, mainframes and file systems.Ingesting change data capture from application databases in Delta LakeYour business relies on your application databases. Leveraging them directly in data analytics use cases can cause interruptions in your business applications due to too much load on the database. By replicating these data sets to your lakehouse, you ensure that your business applications can operate without hiccups as you leverage the valuable information in your analytics use cases. You can ingest data from these data stores by leveraging services like Azure Data Factory, AWS DMS and Auto Loader or partners like Fivetran.CustomersRelated contentWebinarWatch the webinar serieseBookLearn moreeBookLearn moreReady to get started?Try Databricks for freeData ingestion documentationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/viacom18","text":"Customer Story: Viacom18 \u2013 DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYConnecting with viewers in a personalized way26%Increase in operational efficiency lowers overall costs INDUSTRY: Media and entertainment SOLUTION: Customer segmentation,recommendation engines,subscriber churn prediction,customer lifetime value PLATFORM USE CASE: Delta Lake,data science,machine learning,ETL CLOUD: Azure\"Moving from Hadoop to Databricks has unlocked significant business value. We are able to process more data faster, build reliable ETL pipelines, and make it easier for our analysts to build models that viewing experiences that our customers want.\u201d\n\u2013 Parijat Dey, Assistant Vice President \u2013 Digital Transformation and Technology at Viacom18Viacom18 Media Pvt. Ltd. is one of India\u2019s fastest-growing entertainment networks with 40x growth over the past decade, they offer a multi-platform, multi-generational, and multicultural brand experiences to 600+ million monthly viewers. In order to deliver more engaging experiences for their millions of viewers, Viacom18 migrated from their Hadoop environment due to its inability to process data at scale efficiently. With Databricks, they have streamlined their infrastructure management, increased data pipeline speeds, and increased productivity among their data teams. Today, Viacom18 is able to deliver more relevant viewing experiences to their subscribers, while identifying opportunities to optimize the business and drive greater ROI.Growth in subscribers and TBs of viewing data pushes Hadoop to its limitsViacom18, a joint venture between Network18 and ViacomCBS, is focused on providing its audiences with highly personalized viewing experiences. The core of this strategy requires implementing an enterprise data architecture that enables the building of powerful customer analytics on daily viewer data. But with millions of consumers across India, the sheer amount of data was tough to wrangle: they were tasked with ingesting and processing over 45,000 hours of daily content on VOOT (Viacom18\u2019s on-demand video subscription platform) which easily generated 700GB to 1TB data per day.\u201cContent is at the heart of what we do,\u201d explained Parijat Dey, Viacom18\u2019s Assistant Vice President of Digital Transformation and Technology. \u201cWe deliver personalized content recommendations across our audiences around the world based on individual viewing history and preferences in order to increase viewership and customer loyalty.\u201dViacom18\u2019s data lake, which was leveraging on-premises Hadoop for operations, wasn\u2019t able to optimally process 90 days of rolling data within their management\u2019s defined SLAs, limiting their ability to deliver on their analytics needs which impacted not only the customer experience but also overall costs.To meet this challenge head-on, Viacom18 needed a modern data warehouse with the ability to analyze data trends for a longer period of time instead of daily snapshots. They also needed a platform that simplified infrastructure by allowing their team to easily provision clusters with features like auto-scaling to help reduce compute costs.Rapid data processing for analytics and ML with DatabricksTo enable the processing power and data science capabilities they required, Viacom18 partnered with Celebal Technologies, a premier Salesforce, data analytics, and big data consulting organization based in India. The team at Celebal leveraged Azure Databricks to provide Viacom18 with a unified data analytics platform that modernizes its data warehousing capabilities and accelerates data processing at scale.The ability to cache data within Delta Lake resulted in the much-needed acceleration of queries, while cluster management with auto-scaling and the decoupling of storage and compute simplified Viacom18\u2019s infrastructure management and optimized operational costs. \u201cDelta Lake has created a streamlined approach to the management of data pipelines,\u201d explained Dey. \u201cThis has led to a decrease in operational costs while speeding up time-to-insight for downstream analytics and data science.\u201dThe notebooks feature was an unexpected bonus for Viacom18, as a common workspace gave data teams a way to collaborate and increase productivity on everything from model training to ad hoc analysis, dashboarding, and reporting via PowerBI.Leveraging viewer data to power personalized viewing experiencesCelebal Technologies and Databricks have enabled Viacom18 to deliver innovative customer solutions and insights with increased cross-team collaboration and productivity. With Databricks, Viacom18\u2019s data team is now able to seamlessly navigate their data while better serving their customers.\u201cWith Databricks, Viacom18\u2019s engineers can now slice and dice large volumes of data and deliver customer behavioral and engagement insights to the analysts and data scientists,\u201d said Dey.In addition to performance gains, the faster query times have also lowered the overall cost of ownership, even with daily increases in data volumes. \u201cAzure Databricks has greatly streamlined processes and improved productivity by an estimated 26%,\u201d concluded Dey.Overall, Dey cites the migration from Hadoop to Databricks has delivered significant business value \u2014 reducing the cost of failure, accelerating processing speeds at scale, and simplifying ad hoc analysis for easier data exploration and innovations that deliver highly engaging customer experiences.Related ContentCase StudyBuilding a Real-time Analytics PlatformVideoScaling Self Service Analytics with Databricks and Apache SparkBuilding a Just-in-Time Data WarehouseArticleHow MTV and Nickelodeon use DatabricksReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jay-yang\/#","text":"Jay Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJay YangPrincipal Data Engineer at ProcoreBack to speakersJay Yang is a Principal Data Engineer at Procore, where he leads the Data and Analytics Platform team. With more than 17 years of industry experience, Jay excels in creating high-performance data platforms designed to support the company's reporting, analytics, and machine-learning applications. As a strong advocate for data accessibility, he is committed to unlocking the potential of data and generating value for businesses.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/company\/partners\/cloud-partners","text":"Databricks \u30af\u30e9\u30a6\u30c9\u30b5\u30fc\u30d3\u30b9\u30d7\u30ed\u30d0\u30a4\u30c0\u30d1\u30fc\u30c8\u30ca\u30fc | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/resources\/google-cloud-free-trial?itm_data=gcp-bottomppromo-gcpfreetrial","text":"Google Cloud Free Trial \u2013 DatabricksTry Databricks on Google Cloud for FreeGet Started with a Free 14-day Trial of Databricks on Google Cloud.One open lakehouse platform to store and manage all of your data for data engineering, data science, and analytics.What you get:Databricks account on Google CloudSingle Sign-on into Databricks with Google Cloud IdentitySingle-click cluster set up running on Google Kubernetes Engine (GKE), processing data in your own accountBuilt-in integration with Google Cloud Storage, Big Query, Pub\/Sub and LookerAbility to run production ELT\/ETL pipelines at massive scaleFully collaborative notebooks with multi-language supportOut-of-the-box native support for ML frameworks like MLflow, scikit-learn, TensorFlow and KerasPlease tell us about yourselfProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ajmal-aziz\/#","text":"Ajmal Aziz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAjmal AzizSolutions Architect at DatabricksBack to speakersAjmal Aziz is a Solutions Architect at Databricks based in Melbourne. He is passionate about helping customers scale their machine learning and analytics applications. Ajmal received his MPhil from the University of Cambridge where he learned the art of punting. In his spare time, he likes to go hiking and bouldering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/oliver-dykstra","text":"Oliver Dykstra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOliver DykstraData Engineer at Texas RangersBack to speakersOliver Dykstra is a data engineer with the Texas Rangers. He builds scalable, future-proof data pipelines to support\nanalytics and machine learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-data-teams-guide-to-the-databricks-lakehouse-platform","text":"The Data Team\u2019s Guide to the Databricks Lakehouse Platform | DatabrickseBookIntro to the Databricks Lakehouse PlatformSupport modern data and AI workloadsLearn the full capabilities of the data lakehouse architecture. With the Databricks Lakehouse Platform, organizations of all sizes \u2014 from enterprises to startups in every industry \u2014 can manage all their data, analytics, AI and machine learning use cases on one platform.Download this eBook to learn:The data lakehouse architectureThe top 3 reasons why enterprises struggle with data, analytics and AIThe Databricks Lakehouse Platform, its key benefits, core workloads and productsData governance, security, instant compute and serverless for modern data solutionsSimplified data, analytics and AI workloads on one platform: data warehousing, data engineering, data streaming, data science and machine learningHow to get unrestricted access to the ecosystem of open source data projects and the broad Databricks partner networkHow to get started with the Databricks Lakehouse PlatformGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zaheera-valani","text":"Zaheera Valani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZaheera ValaniSenior Director of Engineering at DatabricksBack to speakersZaheera Valani is a Senior Director of Engineering at Databricks for the Partner and Dev Ecosystem teams, and Site Lead for Databricks Seattle area offices. Prior to Databricks, Zaheera was at Tableau for 6 years leading the Data Management organization. She started out her career as a software engineer on Microsoft Excel. She is passionate about data, analytics, engineering and has grown teams and shipped widely adopted data and analytics products during her ~20 year career in technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maria-daibert\/#","text":"Maria Daibert - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaria DaibertData Platform Product Manager at AB InbevBack to speakersData Platform Product Manager at Anheuser-Busch InBev (Brazil), with 5+ years of expertise in product management, business development and agile frameworks. Passionate about Big Data, strategy and agility. A Data Mesh enthusiast.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/industries\/federal-government","text":"Analisi dei dati e AI per agenzie federali | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWAnalisi dei dati e AI per agenzie federaliFavorire l'innovazione per fornire servizi pubblici migliori con l'analisi dei dati e il machine learningDalla Federal Data Strategy all'AI Executive Order, \u00e8 chiaro che il Governo federale americano punta a modernizzare le sue capacit\u00e0 di analisi dei dati e di data warehousing.Con Databricks Lakehouse Platform, le agenzie federali possono sfruttare tutto il potenziale dei loro dati per realizzare gli obiettivi della loro missione e servire meglio i cittadini.Mettere a disposizione delle agenzie federali dati\u00a0e AI per portare a termine le missioniScelto dalle principali agenzie del settore pubblico+ Qualsiasi altro client compatibile con Apache Spark\u2122\ufe0fScopri come i leader utilizzano Databricks per migliorare l'esperienza dei cittadini con tutti i servizi pubbliciBlog, webinar e case study pi\u00f9 recentiPerch\u00e9 Databricks per il governo federaleModernizzare l'analisi dei dati130 car. Rinnovare la dotazione tecnologica per migliorare l'esperienza di pazienti e medici con la pipeline DNASeq pi\u00f9 veloce su larga scala.Realizzare gli obiettivi della missione in modo efficace ed efficiente130 car. Rinnovare la dotazione tecnologica per migliorare l'esperienza di pazienti e medici con la pipeline DNASeq pi\u00f9 veloce su larga scala.Creare esperienze migliori per i cittadini130 car. Rinnovare la dotazione tecnologica per migliorare l'esperienza di pazienti e medici con la pipeline DNASeq pi\u00f9 veloce su larga scala.Maggiori informazioniConformit\u00e0 estesa per ottenere le approvazioni operative (ATO) in modo semplice e veloceDatabricks ha ottenuto le approvazioni operative (ATO) per le regioni, le reti e i controlli di conformit\u00e0 che supportano gli obiettivi della tua missioneCloudC2S\nSC2S\nGovCloud\nCloud pubblico\nRetiPubbliche\nNIPR\nSIPR\nJWICS\nControlli di conformit\u00e0FedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICD-503\nDatabricks sostiene l'innovazione del Governo federaleSanit\u00e0Migliorare la fornitura e la qualit\u00e0 dei servizi sanitari per i cittadini con analisi avanzata e una vista a 360\u00b0 dei pazienti.\nPatient 360\u00a0\nOttimizzazione della supply chain\u00a0\nGestione delle assicurazioni\u00a0Genomica\u00a0\nScoperta e somministrazione di farmaciDifesaApplicare la potenza dell'analisi predittiva a dati geospaziali, IoT e di sorveglianza per migliorare le attivit\u00e0 operative e proteggere la nazione.\u00a0\nLogistica\nManutenzione predittiva\u00a0\nSorveglianza e riconoscimento\u00a0\nForze dell'ordine e pronto interventoHomeland Security (sicurezza nazionale)Individuare e prevenire attivit\u00e0 criminali e minacce nazionali con analisi in tempo reale e decisioni guidate dai dati.\u00a0\nDogane e protezione dei confini\u00a0\nImmigrazione e cittadinanza\u00a0\nAntiterrorismo\u00a0\nProtezione civile e gestione delle emergenzeAutorit\u00e0 pubblica\/CommercioRilevare proattivamente le anomalie con il machine learning per mitigare il rischio e prevenire attivit\u00e0 fraudolente.\u00a0\nFrodi fiscali e riscossione\u00a0\nGestione di processi e attivit\u00e0 operative\u00a0\nGestione dei finanziamenti\u00a0\nCustomer 360EnergiaMigliorare la gestione energetica con informazioni ricavate dai dati che garantiscono la resilienza e la sostenibilit\u00e0 energetica.\u00a0\nSicurezza dell'infrastruttura energetica\u00a0\nGestione intelligente dell'energia\u00a0\nEsplorazione energetica\u00a0\nAffidabilit\u00e0 della rete elettricaIntelligence CommunitySfruttare informazioni in tempo reale per prendere decisioni informate che possono incidere sulla sicurezza dei cittadini e del mondo.\u00a0\nRilevamento di minacce\u00a0\nNeutralizzazione di attacchi informatici\u00a0\nSorveglianza e riconoscimento per attivit\u00e0 di intelligence\u00a0\nAnalisi dei social mediaRisorseReferenzePazienti al primo posto in CMS con la trasformazione digitaleBest practice di governance dei dati - L'esempio dei centri per i servizi Medicare e MedicaidLezioni imparate dalla modernizzazione della piattaforma di analisi dei dati USCISModernizzare l'aeronautica militare con Big Data e AIWebinarRisposta rapida ad attivit\u00e0 ospedaliere utilizzando dati e AI durante la pandemia di COVID-19Analisi e AI geospaziale nel settore pubblicoModerna architettura di analisi dei dati per la pubblica amministrazioneMigliorare il rilevamento di minacce con Big Data e AINotizieAzure Databricks ottiene l'autorizzazione FedRAMP di alto livello per Microsoft Azure Government (MAG)Sicurezza governativa su AWS CloudAnalisi unificata per clienti governativiDotare l'Intelligence statunitense di capacit\u00e0 critiche di analisi e AIDibattitiAutomatizzare l'acquisizione e l'analisi dei dati nel sistema di gestione informatica (SWIM) della Federal Aviation Administration (FAA)Analisi geospaziale su larga scala: analizzare i modelli di spostamento delle persone durante una pandemiaPronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e capire come il nostro team di servizi potrebbe aiutarti a realizzarli.\u00a0Prova gratuitaContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=recruiting","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabien-cochet","text":"Fabien Cochet - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabien CochetIT Expert on Data and Analytics at MichelinBack to speakersWorking at Michelin for a decade, mainly around data. Inspiring and helping others and transforming our ways of doing all the things that drive Fabien Cochet every day. He likes racking his brains and thinking out of the box, especially about the solutions we design. Fabien is always curious and willing to explore new approaches and technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud30c\ud2b8\ub108\uac00 \uac1c\ubc1c\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc6a9 \uc0b0\uc5c5 \ubc0f \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uc194\ub8e8\uc158Databricks\ub294 \uc8fc\uc694 \ucee8\uc124\ud305 \ud30c\ud2b8\ub108\uc640 \ud611\ub825\ud558\uc5ec \uc0b0\uc5c5 \ubc0f \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uc0ac\uc6a9 \uc0ac\ub840\uc5d0 \ub300\ud55c \ud601\uc2e0\uc801 \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud588\uc2b5\ub2c8\ub2e4. Databricks Brickbuilder Solutions\ub294 \ub2f9\uc0ac \ud30c\ud2b8\ub108\uac00 \uace0\uac1d\uc758 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uace0 \ub370\uc774\ud130\uc5d0\uc11c \ub354 \ub9ce\uc740 \uac00\uce58\ub97c \ucc3d\ucd9c\ud558\ub3c4\ub85d \ub3c4\uc6b8 \uc218 \uc788\ub3c4\ub85d \uc124\uacc4\ud588\uc2b5\ub2c8\ub2e4. \uc624\ub7ab\ub3d9\uc548 \ucd95\uc801\ub41c \uc5c5\uacc4 \uacbd\ud5d8\uc744 \ub178\ud558\uc6b0 \uc0bc\uc544 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uae30\ubc18\uc73c\ub85c \uac1c\ubc1c\ud55c \ub9de\ucda4\ud615 \uc194\ub8e8\uc158\uc744 \uc548\uc2ec\ud558\uace0 \ud65c\uc6a9\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc774\uc6a9 \uac00\ub2a5\ud55c \ud30c\ud2b8\ub108 \uac80\uc0c9search\uacf5\uacf5 \ubd80\ubb38Cloud Data Migration by Accenture - Databricks\uc790\uc138\ud788\uc18c\ub9e4 \ubc0f \uc18c\ube44\uc7acUnified View of Demand by Accenture\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220CPG Control Tower by Avanade\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Intelligent Healthcare on Azure Databricks by Avanade\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Intelligent Manufacturing\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Legacy System Migration by Avanade\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Risk Management by Avanade\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4Migrate Legacy Cards and Core Banking Portfolios by Capgemini and Databricks\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4Migrate to Cloud and Databricks by Capgemini and Databricks\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4Capgemini Revenue Growth Management\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4Migrate to Databricks by Celebal Technologies and Databricks\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4Cognizant Video Quality of Experience\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Persona 360 by DataSentics and Databricks\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220SAP Migration Accelerator by DataSentics - Databricks\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220PrecisionView\u2122 by Deloitte\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Trellis by Deloitte\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220Smart Migration to Databricks by EPAM\uc790\uc138\ud788\uad11\uace0 \ubc0f \ub9c8\ucf00\ud305 \uae30\uc220LeapLogic Migration Solution by Impetus\uc790\uc138\ud788\uc790\uc138\ud788 \ubcf4\uae30\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/de\/product\/data-science","text":"Data Science | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWData ScienceKollaborative Data Science im gro\u00dfen Ma\u00dfstabKostenlos testenPlanen Sie eine DemoTauchen Sie tiefer in Data Science auf Databricks einDatabricks NotebooksIDE IntegrationReposMachine LearningOptimieren Sie den gesamten Data-Science-Workflow\u00a0\u2013 von der Datenaufbereitung \u00fcber die Modellierung bis hin zum Austausch von Erkenntnissen\u00a0\u2013 mit einer kollaborativen und einheitlichen Data-Science-Umgebung, die auf ein offenes Lakehouse aufsetzt. Erhalten Sie schnellen Zugriff auf saubere und zuverl\u00e4ssige Daten, vorkonfigurierte Datenverarbeitungsressourcen,\u00a0IDE-Integrationen, Unterst\u00fctzung mehrerer Sprachen und integrierte fortschrittliche Visualisierungstools, um Datenanalyseteams maximale Flexibilit\u00e4t zu geben.Zusammenarbeit im gesamten Data-Science-WorkflowSchreiben Sie mit Databricks Notebooks Code in Python, R, Scala und SQL, analysieren Sie Daten mit interaktiven Visualisierungen und gewinnen Sie neue Erkenntnisse. Geben Sie Ihren Code sicher und ohne Bedenken frei\u00a0\u2013 mit Co-Authoring, Kommentaren, automatischer Versionierung, Git-Integrationen und rollenbasierter Zugriffssteuerung.Schwerpunktlegung auf Data Science (statt der Infrastruktur)K\u00fcnftig sind Sie nicht mehr auf die Datenspeicherkapazit\u00e4t Ihres Laptops oder die Ihnen zur Verf\u00fcgung stehende Compute-Leistung beschr\u00e4nkt. Migrieren Sie Ihre lokale Umgebung schnell in die Cloud und verbinden Sie Notebooks mit Ihren eigenen, pers\u00f6nlichen Compute- und automatisch verwalteten Clustern.Ihre bevorzugte lokale IDE \u2013 mit skalierbarer RechenleistungDie Wahl einer IDE ist eine sehr pers\u00f6nliche Angelegenheit und hat erheblichen Einfluss auf die Produktivit\u00e4t.Verbinden Sie Ihre bevorzugte IDE mit Databricks, um k\u00fcnftig von unbegrenztem Datenspeicher und unbeschr\u00e4nkter Rechenleistung zu profitieren. Alternativ verwenden Sie RStudio oder JupyterLab einfach direkt innerhalb von Databricks. So wird das Nutzungserlebnis nahtlos.Daten f\u00fcr Data Science aufbereitenBereinigen und katalogisieren Sie alle Ihre Daten \u2013 seien es Batch-, Streaming-, strukturierte oder unstrukturierte Daten \u2013 mit Delta Lake an einem einzigen Ort und machen Sie sie mithilfe eines zentralen Datenspeichers unternehmensweit auffindbar. Automatische Qualit\u00e4tspr\u00fcfungen sorgen daf\u00fcr, dass eingehende Daten den Erwartungen entsprechen und bereit zur Analyse sind. Wenn sich Daten durch das Erg\u00e4nzen neuer Daten und weitere Transformationen fortentwickeln, stellt die Datenversionierung sicher, dass Sie alle Compliance-Anforderungen erf\u00fcllen k\u00f6nnen.Visuelle Low-Code-Tools f\u00fcr die DatenerkundungVerwenden Sie native visuelle Tools aus den Databricks-Notebooks heraus, um Ihre Daten aufzubereiten, zu transformieren und zu analysieren, sodass Teams unabh\u00e4ngig vom jeweiligen Kenntnisstand mit Daten arbeiten k\u00f6nnen. Sobald Datentransformationen und Visualisierungen abgeschlossen sind, k\u00f6nnen Sie den Code generieren, der im Hintergrund ausgef\u00fchrt wird. So sparen Sie Zeit beim Schreiben von Boilerplate-Code, sodass Sie mehr Zeit f\u00fcr hochwertige Arbeit haben.Neue Einblicke schnell entdecken und teilenVerwandeln Sie Ihre Analyse im Handumdrehen in ein dynamisches Dashboard, um Ergebnisse schnell und einfach weiterzugeben und zu exportieren. Die Dashboards sind immer auf dem neuesten Stand und k\u00f6nnen auch interaktive Abfragen durchf\u00fchren. Zellen, Visualisierungen oder Notebooks k\u00f6nnen mit rollenbasierter Zugriffssteuerung geteilt und in verschiedenen Formaten wie HTML oder IPython Notebook exportiert werden.Zu Databricks migrierenSind die Datensilos, die langsame Leistung und die hohen Kosten f\u00fcr Altsysteme wie Hadoop und Enterprise Data Warehouses m\u00fcde? Holen Sie sich eine einzige moderne Plattform f\u00fcr alle Ihre Daten-, Analytics- und KI-Anwendungsf\u00e4lle.Zu Databricks migrierenRessourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nErkunden Sie die Ressourcenbibliothek, um E-Books und Videos zu Themen Datenwissenschaft und Machine Learning zu finden.\nRessourcen erkundenBerichte und E-BooksDas Big Book of Data ScienceDie Kunst der kollaborativen Datenwissenschaft in jeder Gr\u00f6\u00dfenordnungEine moderne ClouddatenplattformMLflow: eine Open-Source-Plattform f\u00fcr Machine LearningDie neue Delta-Sharing-L\u00f6sung erkundenDatabricks von Gartner\u00ae im Magic Quadrant\u2122 2021 als Leader in den Bereichen DBMS und DSML benanntTakeda migrierte von On-Premises-Hadoop zu DatabricksBlogs5 wichtige Schritte f\u00fcr eine erfolgreiche Migration von Hadoop zur Lakehouse-ArchitekturVirtuelle VeranstaltungenSchritt-f\u00fcr-Schritt-Anleitung zur Hadoop-MigrationM\u00f6chten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/br\/glossary","text":"Glossaries Archive | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGlossaryA-ZsearchACID Transactions What is a transaction?\nIn the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a cons{...}AdaGrad Gradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.\nTypes of Gradient Descent\nThere are three primary types of gradient descent {...}Alternative Data What is Alternative Data?\nAlternative data is information gathered by using alternative sources of data that others are not using; &nbsp;non-traditional information sources. Analysis of alternative data can provide insights beyond that which an in{...}Anomaly Detection Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like{...}Apache Hive What is Apache Hive?\nApache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.\nWith exten{...}Apache Kudu What is Apache Kudu?\nApache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows to{...}Apache Kylin What is Apache Kylin?\nApache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/S{...}Apache Spark What Is Apache Spark?\nApache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.&nbsp;Apache Spark started in 2009 as a research project at {...}Apache Spark as a Service What is Apache Spark as a Service?\nApache Spark is an open source cluster computing framework for fast real-time large-scale data processing.&nbsp;Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently ra{...}Artificial Neural Network What is an Artificial Neural Network?\nAn artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.\nHow Do Artificial Neural Networks Work?\nArtificial Neural Networks can be best viewed{...}Automation Bias What is Automation Bias?\nAutomation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, {...}Bayesian Neural Network What Are Bayesian Neural Networks?\nBayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology {...}Big Data Analytics The Difference Between Data and Big Data Analytics\nPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relat{...}Bioinformatics Bioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.\nBioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data.{...}Catalyst Optimizer At the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional program{...}Complex Event Processing What is Complex Event Processing [CEP]?\nComplex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being s{...}Continuous Applications Continuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate{...}Convolutional Layer In deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language {...}Data Analysis Platform What is a Data Analysis Platform?\nA data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visua{...}Data Governance What is Data Governance?\nData governance is the oversight to ensure data brings value and supports the business strategy. Data governance is more than just a tool or a process. It aligns data-related requirements to the business strategy using a f{...}Data Lakehouse What is a Data Lakehouse?\nA data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business int{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Data Sharing What is data sharing?\nData sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or external{...}Data Vault What is a data vault?\nA data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.\nHubs represent core business concepts, {...}Data Warehouse What is a data warehouse?\nA data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business i{...}Databricks Runtime Databricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of {...}DataFrames What is a DataFrame?\nA DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are {...}Datasets Datasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recal{...}Deep Learning What is Deep Learning?\nDeep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referre{...}Demand Forecasting What is demand forecasting?\nDemand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.\nRet{...}Dense Tensor Dense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software prod{...}Digital Twin What is a Digital Twin?\nThe classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers {...}DNA Sequence What is a DNA Sequence?\nThe DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). &nbsp;Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine {...}Extract Transform Load (ETL) What is ETL?\nAs the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to pr{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Genomics Genomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DN{...}Hadoop Cluster What Is a Hadoop Cluster?\nApache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by{...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hadoop Ecosystem What is the Hadoop Ecosystem?\nApache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of{...}Hash Buckets In computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from whic{...}Hive Date Function What is a Hive Date Function?\nHive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditi{...}Hosted Spark What is Hosted Spark?\nApache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Py{...}Jupyter Notebook What is a Jupyter Notebook?\nA Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.\nWhat are Jupyter Notebooks used fo{...}Keras Model What is a Keras Model?\nKeras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.&nbsp;Keras has become one of {...}Lakehouse for Retail What is Lakehouse for Retail?\nLakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.\nLakehouse fo{...}Lambda Architecture What is Lambda Architecture?\nLambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solv{...}Machine Learning Library (MLlib) Apache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and mod{...}Machine Learning Models What is a machine learning Model?\nA machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recogni{...}Managed Spark What is Managed Spark?\nA managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, m{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}Materialized views Delta Pipelines \/ Materialized Views in Databricks Delta\nIntro\nDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve dat{...}Medallion Architecture What is a medallion architecture?\nA medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through ea{...}ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and c{...}MLOps What is MLOps?\nMLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. M{...}Model Risk Management Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and{...}Neural Network What is a Neural Network?\nA neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an outpu{...}Open Banking What is Open Banking?\nOpen banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of custo{...}Orchestration What is Orchestration?\nOrchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of {...}Overall Equipment Effectiveness What is Overall Equipment Effectiveness?\nOverall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to{...}pandas DataFrame \nWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as ef{...}Parquet What is Parquet?\nApache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in {...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}Predictive Analytics What is Predictive Analytics?\nPredictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.\nHow Does Predictive Analytics Work?\nPredictive analytics {...}Predictive Maintenance What is predictive maintenance?\nPredictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rath{...}PyCharm PyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to crea{...}PySpark What is PySpark?\nApache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface wi{...}Real-Time Retail What is real-time data for Retail?\nReal-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. {...}Resilient Distributed Dataset (RDD) \nRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API {...}Snowflake Schema What is a snowflake schema?\nA snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and re{...}Spark API If you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDs\nWhat are Resilient Distributed Datasets?\nRDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are {...}Spark Applications Spark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; res{...}Spark Elasticsearch What is Spark Elasticsearch?\nSpark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and r{...}Spark SQL Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can al{...}Spark Streaming Apache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Stre{...}Spark Tuning What is Spark Performance Tuning?\nSpark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also preven{...}Sparklyr What is Sparklyr?\nSparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little l{...}SparkR SparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follow{...}Sparse Tensor Python offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library. Sptensor is a class that represents the sparse tensor. A spa{...}Star Schema What is a star schema?\nA star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The st{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a stre{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API What is the Tensorflow Estimator API?\nEstimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow {...}Transformations What Are Transformations?\nIn Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d {...}Tungsten What is the Tungsten Project?\nTungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance{...}Unified AI Framework Unified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute r{...}Unified Data Analytics Unified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it e{...}Unified Data Analytics Platform Databricks' Unified Data Analytics Platform&nbsp;helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at mass{...}Unified Data Warehouse What is a Unified Data Warehouse?\nA unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in {...}What Is Hadoop? Apache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them{...}ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/jp\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks\u3001\u30ac\u30fc\u30c8\u30ca\u30fc \u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u7ba1\u7406\u30b7\u30b9\u30c6\u30e0\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u306e\u30ea\u30fc\u30c0\u30fc\u306e 1 \u793e\u306b | Databricks2022\u5e74\u30ac\u30fc\u30c8\u30ca\u30fc\u3000\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8Databricks\u3001\u30ac\u30fc\u30c8\u30ca\u30fc \u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u7ba1\u7406\u30b7\u30b9\u30c6\u30e0\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u306e\u30ea\u30fc\u30c0\u30fc\u306e 1 \u793e\u306bDatabricks\u3001\u30ac\u30fc\u30c8\u30ca\u30fc 2022 \u5e74\u300cCDBMS \u90e8\u9580\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u300d\u306e\u30ea\u30fc\u30c0\u30fc\u306e 1 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\u304c\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u306e\u30ea\u30fc\u30c0\u30fc\u306e 1 \u793e\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u305f\u7406\u7531\u304a\u3088\u3073\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u304c\u3082\u305f\u3089\u3059\u30e1\u30ea\u30c3\u30c8\u306b\u3064\u3044\u3066\u3001\u672c\u30ec\u30dd\u30fc\u30c8\u3067\u8a73\u3057\u304f\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9 \u300cGartner 2022 Cloud Database Management Systems\u300dHenry Cook\u3001Merv Adrian\u3001Rick Greenwald\u3001Xingyu Gu \u5171\u8457\u30012022\u5e7412\u670813\u65e5\nGARTNER \u306f\u3001Gartner, Inc. \u307e\u305f\u306f\u7c73\u56fd\u5185\u5916\u306e\u540c\u793e\u95a2\u9023\u4f1a\u793e\u306e\u767b\u9332\u5546\u6a19\u304a\u3088\u3073\u30b5\u30fc\u30d3\u30b9\u30de\u30fc\u30af\u3067\u3042\u308a\u3001MAGIC QUADRANT 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{"source":"https:\/\/www.databricks.com\/blog\/2021\/08\/30\/announcing-databricks-serverless-sql.html","text":"Announcing Databricks Serverless SQL: Instant, Managed, Secured and Production-ready Platform for SQL Workloads - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing serverless compute for Databricks SQLInstant compute with minimal management and lower costs for BI and SQLby Nikhil Jethava and Kevin ClugageAugust 30, 2021 in Platform BlogShare this postDatabricks SQL already provides a first-class user experience for BI and SQL directly on the data lake, and today, we are excited to announce another step in making data and AI simple with serverless compute for Databricks SQL. This new capability for Databricks SQL provides instant compute to users for their BI and SQL workloads, with minimal management required and capacity optimizations that can lower overall cost by an average of 40%. This makes it even easier for organizations to expand adoption of the lakehouse for business analysts who are looking to access the rich, real-time datasets of the lakehouse with a simple and performant solution.Under the hood of this capability is an active server fleet, fully managed by Databricks, that can transfer compute capacity to user queries, typically in about 15 seconds. The best part? You only pay for serverless compute when users start running reports or queries.Organizations with business analysts who want to analyze data in the data lake with their favorite BI tools will benefit from this capability. First, connecting BI tools to Databricks SQL Serverless is easy, especially with built-in connectors using optimized JDBC\/ODBC drivers for easy authentication support and high performance.Second, Serverless SQL was built for the modern business analyst, who works on their own schedules and wants instant compute available to process their queries without waiting for clusters to start up or scale out. Administrators are the ones battling to stay ahead of these user workloads with manual configurations and cluster startups\/shutdown schedules, but it\u2019s imperfect at best and incurs extra costs for over-provisioning and excess idle time.This is where Serverless SQL shines with instant compute availability for all users. It only takes one click to enable, there is no performance tuning, and patching and upgrades are managed automatically. By default, if at any point the cluster is idle for 10 minutes, Serverless SQL will automatically shut it down, remove the resources and prepare to start the instant compute process over again for the next query. This is how Serverless SQL helps lower overall costs \u2013 by matching capacity to usage that avoids over-provisioning and idle capacity when users are inactive.Customers have already started using Serverless SQL and seen the benefits:\n\u201cHaving the ability to fetch data ad-hoc with compute available within seconds helps our teams get answers quickly. Being able to autoscale up and down aggressively given the fast startup time makes our spiky workloads with BI and reporting tools easier to manage.\u201d\nAnup Segu, Data Engineering Tech Lead, YipitData\n\n\u201cServerless SQL is easy to use and allows us to unlock more performance at the same price point. We already see improved query performance and lower costs using this feature for our spiky BI workloads.\u201d\nBen Thwaites, Sr. Data Engineer, Intelematics\nInside Serverless SQL ComputeAt the core of Serverless SQL is a compute platform that operates a pool of servers, located in Databricks\u2019 account, running Kubernetes containers that can be assigned to a user within seconds.Serverless SQL compute platformWhen many users are running reports or queries at the same time, the compute platform adds more servers to the cluster (again, within seconds) to handle the concurrent load. Databricks manages the entire configuration of the server and automatically performs the patching and upgrades as needed.Each server is running a secure configuration and all processing is secured by three layers of isolation \u2013 the Kubernetes container hosting the runtime, the virtual machine (VM) hosting the container and the virtual network for the workspace. Each layer is isolated to one workspace with no sharing or cross-network traffic allowed. The containers use hardened configurations, VMs are shut down and not reused, and network traffic is restricted to nodes in the same cluster.Comparing startup time, execution time and costWe ran a set of internal tests to compare Databricks SQL Serverless to the current Databricks SQL and several traditional cloud data warehouses. We found Serverless SQL to be the most cost-efficient and performant environment to run SQL workloads when considering cluster startup time, query execution time and overall cost.2021 Cloud Data Warehouse Benchmark Report: Databricks researchGetting startedDatabricks SQL Serverless is another step in making BI and SQL on the Lakehouse simple. Customers benefit from the instant compute, minimal management and lower cost from a high-performance platform that is accessible to their favorite BI and SQL tools. Users will love the boost to their productivity, while administrators have peace of mind knowing their users are productive without blowing the budget from over-provisioning capacity or wasted idle compute. Everybody wins!Serverless SQL is available today in public preview on AWS; customers should contact their account team to request access.Try Databricks for freeGet StartedRelated postsAnnouncing serverless compute for Databricks SQLAugust 30, 2021 by Nikhil Jethava and Kevin Clugage in Platform Blog\nDatabricks SQL already provides a first-class user experience for BI and SQL directly on the data lake, and today, we are excited to...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/product\/delta-lake-on-databricks","text":"Delta Lake na Databricks - Agende uma demonstra\u00e7\u00e3o!Skip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDelta LakeConfiabilidade, seguran\u00e7a e desempenho para seu data lakeExperimente gratuitamenteAssista \u00e0 demonstra\u00e7\u00e3oO que \u00e9 Delta Lake?Delta Lake \u00e9 uma camada de armazenamento em formato aberto que oferece confiabilidade, seguran\u00e7a e desempenho ao seu data lake, para opera\u00e7\u00f5es de\u00a0streaming\u00a0e em batch. Ao substituir os silos de dados por um \u00fanico local dedicado a dados estruturados, semiestruturados e n\u00e3o estruturados, o Delta Lake \u00e9 a base para um lakehouse econ\u00f4mico e altamente escal\u00e1vel.Dados confi\u00e1veis e de alta qualidadeUma \u00fanica fonte confi\u00e1vel da verdade para todos os seus dados, incluindo streams\u00a0em tempo real,\u00a0. Suas equipes de dados sempre trabalhar\u00e3o com os dados mais atualizados. Com suporte para transa\u00e7\u00f5es ACID e valida\u00e7\u00e3o de esquema, o Delta Lake fornece a confiabilidade que falta aos data lakes tradicionais. Isso permite que voc\u00ea obtenha insights confi\u00e1veis em toda a organiza\u00e7\u00e3o e execute an\u00e1lises e outros projetos relacionados a dados diretamente em seu data lake, para ter insights at\u00e9 50 vezes mais r\u00e1pido.Compartilhamento aberto e seguro de dadosO Delta Sharing\u00a0\u00e9 o primeiro protocolo aberto para compartilhamento seguro de dados. Ele facilita a troca de dados com outras organiza\u00e7\u00f5es, independentemente de onde esses dados estejam. A integra\u00e7\u00e3o nativa com o\u00a0Unity Catalog\u00a0permite gerenciar e auditar centralmente os dados compartilhados entre organiza\u00e7\u00f5es. Ela tamb\u00e9m permite que voc\u00ea compartilhe com confian\u00e7a ativos de dados com fornecedores e parceiros para uma melhor coordena\u00e7\u00e3o dos seus neg\u00f3cios, atendendo aos crit\u00e9rios de seguran\u00e7a e conformidade. As integra\u00e7\u00f5es com as principais ferramentas e plataformas facilitam ainda mais a visualiza\u00e7\u00e3o, query, enriquecimento e governan\u00e7a de dados compartilhados a partir das ferramentas de sua escolha.Desempenho extremamente r\u00e1pidoAlavancando o Apache Spark\u2122, o Delta Lake oferece escalabilidade e velocidade impressionantes. Gra\u00e7as a recursos como indexa\u00e7\u00e3o, que otimizam seu desempenho, o Delta Lake permite que seus usu\u00e1rios\u00a0executem ETLs at\u00e9 48 vezes mais r\u00e1pido.Aberto e \u00e1gilTodos os dados no Delta Lake s\u00e3o armazenados no formato Apache Parquet aberto, podendo ser lidos por qualquer leitor compat\u00edvel. As APIs s\u00e3o abertas e compat\u00edveis com o Apache Spark. Com o Delta Lake na Databricks, voc\u00ea tem acesso a um grande ecossistema de c\u00f3digo aberto e evita qualquer bloqueio de dados em formatos propriet\u00e1rios.Data engineering automatizada e confi\u00e1velSimplifique sua engenharia de dados com\u00a0Delta Live Tables,\u00a0uma maneira f\u00e1cil de criar e gerenciar facilmente pipelines de dados para obter dados novos e de alta qualidade no Delta Lake. As Delta Live Tables ajudam as equipes de data engineering a simplificar o desenvolvimento e o gerenciamento de\u00a0ETL\u00a0por meio da cria\u00e7\u00e3o de pipelines declarativos, que aumentam a confiabilidade dos dados facilitam o estabelecimento de opera\u00e7\u00f5es de produ\u00e7\u00e3o em escala de nuvem, auxiliando na constru\u00e7\u00e3o da funda\u00e7\u00e3o do lakehouse.Seguran\u00e7a e governan\u00e7a em escalaO Delta Lake reduz o risco pois permite uma governan\u00e7a de dados com base em controles de acesso refinados, o que, tipicamente, n\u00e3o \u00e9 poss\u00edvel em data lakes. Voc\u00ea pode atualizar com rapidez e precis\u00e3o os dados em seu data lake para cumprir regulamentos como a GDPR e manter uma melhor governan\u00e7a de dados por meio de logs de auditoria. Esses recursos s\u00e3o integrados nativamente e aprimorados no Databricks como parte do\u00a0Unity Catalog, o primeiro cat\u00e1logo de dados multi-cloud para o Lakehouse.Casos de usoBI nos seus dadosForne\u00e7a aos seus analistas novos dados em tempo real e obtenha insights imediatos sobre sua empresa gra\u00e7as \u00e0s cargas de trabalho de Business Intelligence executadas diretamente no seu data lake. O Delta Lake permite que voc\u00ea aproveite uma arquitetura de lakehouse multi-cloud que oferece desempenho de armazenamento de dados com custos pr\u00f3ximos do data lake para uma rela\u00e7\u00e3o pre\u00e7o\/desempenho at\u00e9 6 vezes melhor para cargas de trabalho SQL do que data warehouses tradicionais em nuvem.Saiba maisUnifique batch e streamingExecute opera\u00e7\u00f5es em batch e streaming em uma arquitetura simplificada, evitando sistemas complexos e redundantes e problemas operacionais. No Delta Lake, uma tabela \u00e9 uma tabela em batch, mas tamb\u00e9m uma fonte de streaming e um coletor de dados. A ingest\u00e3o de dados de streaming, o preenchimento hist\u00f3rico em batch e as queries interativas funcionam sem nenhum esfor\u00e7o extra, integrando-se diretamente ao Spark Structured Streaming.Atenda \u00e0s necessidades regulat\u00f3riasO Delta Lake elimina desafios na ingest\u00e3o de dados mal formados, a dificuldade na exclus\u00e3o de dados por motivos de conformidade e os problemas na opera\u00e7\u00e3o de captura de dados de altera\u00e7\u00e3o. Com suporte a transa\u00e7\u00f5es ACID em seu data lake, o Delta Lake garante que todas as opera\u00e7\u00f5es sejam totalmente bem-sucedidas ou canceladas para novas tentativas posteriores, sem exigir a cria\u00e7\u00e3o de novos pipelines de dados. Al\u00e9m disso, o Delta Lake registra todas as transa\u00e7\u00f5es anteriores em seu data lake, facilitando assim o acesso a vers\u00f5es anteriores de seus dados para atender de maneira confi\u00e1vel aos padr\u00f5es de conformidade, como GDPR e CCPA.Rede de ingest\u00e3o de dadosOs conectores nativos facilitam a ingest\u00e3o de dados no Delta Lake de forma r\u00e1pida e confi\u00e1vel a partir de todos os seus armazenamentos de arquivos, aplicativos e bancos de dados.Clientes\u201cA Databricks nos ajudou a diminuir nosso tempo de ida ao mercado, melhorar a utiliza\u00e7\u00e3o de analytics e de nossa opera\u00e7\u00e3o para atender \u00e0s novas demandas do setor de sa\u00fade.\u201d\n\u2013 Peter James, arquiteto-chefe, Healthdirect AustraliaSaiba mais\u201cAproveitando o Databricks e o Delta Lake, j\u00e1 conseguimos democratizar os dados em escala e, ao mesmo tempo, reduzir o custo de execu\u00e7\u00e3o de cargas de trabalho de produ\u00e7\u00e3o em 60%. Isso nos poupou milh\u00f5es de d\u00f3lares.\u201d\n\u2014 Steve Pulec, diretor de tecnologia, YipitDataSaiba mais\u201cO Delta Lake prov\u00ea as transa\u00e7\u00f5es ACID que simplificam as opera\u00e7\u00f5es de pipeline para melhorar a confiabilidade e a consist\u00eancia dos dados. Ao mesmo tempo, recursos como cache e indexa\u00e7\u00e3o autom\u00e1tica permitem acesso eficiente e de alto desempenho aos dados.\u201d\n\u2014 Lara Minor, gerente s\u00eanior de dados empresariais, Columbia SportswearSaiba mais\u201cO Delta Lake criou uma abordagem simplificada para gerenciar pipelines de dados. Isso nos levou a reduzir custos operacionais e, ao mesmo tempo, acelerar a produ\u00e7\u00e3o de insights e an\u00e1lises em nossos processos de data science.\u201d\n\u2014 Parijat Dey, vice-presidente assistente de transforma\u00e7\u00e3o e tecnologia digital, Viacom18Saiba maisRecursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre os benef\u00edcios da data engineering no Databricks.\nExplorar recursose-booksThe Big Book of Data Engineering: Casos de usoData, Analytics and AI governanceData Management 101 on DatabricksBuilding the Data Lakehouse, de Bill Inmon, pai do data warehousePalestras e treinamentos t\u00e9cnicosIntrodu\u00e7\u00e3o ao Delta Lake \u2013 S\u00e9rie Tech TalkWebinarsO bom, o mau e o feioMergulhe no lakehouse com Delta LakeTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteDocumenta\u00e7\u00e3o do Delta LakeProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/it\/company\/leadership-team","text":"Gruppo direttivo | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLeadershipCon una visione di lungo termine, il nostro gruppo dirigente sfrutta decenni di esperienza per tracciare nuove rotte nel mondo dei dati e dell'intelligenza artificialeConosci il nostro teamGruppo dirigenteFondatoriConsiglio direttivoAli GhodsiCofondatore e Chief Executive OfficerAndy KofoidPresidente, Global Field OperationsDavid ConteChief Financial OfficerAmy ReichanadterChief People OfficerTr\u00e2m PhiSVP and General CounselRon GabriskoChief Revenue OfficerRick SchultzChief Marketing OfficerHatim ShafiqueChief Operating OfficerFerm\u00edn SernaChief Security OfficerNaveen ZutshiChief Information OfficerVinod MarurSVP of EngineeringDavid MeyerSVP of ProductsAdam ConwaySVP of ProductsArsalan Tavakoli-ShirajiCofondatore e SVP of Field EngineeringProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/de\/solutions","text":"Skip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks f\u00fcr die IndustrieKompromisslose Data Analytics- und KI-L\u00f6sungen, die speziell f\u00fcr Ihre Branche entwickelt wurdenErste SchrittePlanen Sie eine DemoDas Lakehouse f\u00fcr Ihre Branche entdeckenKommunikation, Medien und UnterhaltungF\u00fcr mehr Aufmerksamkeit sorgen, mehr Fantasie anregenWeitere InformationenFinanzdienstleistungenMehr Vertrauen aufbauen, Unbesorgtheit sicherstellenWeitere InformationenGesundheitswesen und BiowissenschaftenBessere Pflege entdecken und anbietenWeitere InformationenEinzelhandel und Konsumg\u00fcterKunden bei ihrer Produktnutzung begleiten und Ihre Marke vertretenWeitere InformationenAlle Branchen durchsuchensearchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listBranchenl\u00f6sungenVon der Idee zum Machbarkeitsnachweis in nur zwei WochenDatabricks Solution Accelerators sind speziell entwickelte Leitf\u00e4den, voll funktionsf\u00e4hige Notebooks und Best Practices, die Ergebnisse beschleunigen. Databricks-Kunden sparen Stunden beim Entdecken, Entwerfen, Entwickeln und Testen, wobei viele in nur zwei Wochen von der Idee zum Machbarkeitsnachweis gelangen.Accelerators erkundenBereit zu starten?Erkunden Sie, was Databricks f\u00fcr Sie tun kann, indem Sie mit einer kostenlosen Testversion beginnen.Kostenlose Testversion startenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/mcsa","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/discover\/champions-of-data-and-ai\/s2-e9-the-role-of-data-ai-in-healthcare-equity","text":"Champions of Data + AI Series | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWChampions of Data + AIData leaders powering data-driven innovationSee all episodesDive into the world of data leadersIn each episode we salute Champions of Data + AI, the change agents who are shaking up the status quo. These mavericks are rethinking how data and AI can enhance the human experience. We\u2019ll dive into their challenges \u2014 and celebrate their successes \u2014 all while getting to know these leaders a little more personally.Episode 25The Impact of Analytics and AI on the Future of InsuranceDr. Michael ZimmerCDO and Head of AI, Zurich Insurance GermanyEpisode 23How Data and AI Are Revolutionizing TelecomsAndy MarkusChief Data Officer, AT&TEpisode 22Democratizing Data to the Front LinesThom KennyFormer CDO, U.S. Special Operations CommandEpisode 21The Power of Data FusionYanyan WuVP, Data and Data Analytics, Wood Mackenzie, a Business of VeriskEpisode 20Cloud-Powered InnovationMichael O'RourkeSVP, Head of Artifical Intelligence and Data Services Technology, NasdaqEpisode 19Data for the PeopleJack BerkowitzChief Data Officer, ADPEpisode 18AI in RetailVimal KohliVP, Data Science and Analytics, Gap Inc.Episode 17Solving Business Problems With DataSanjeeva FernandoSenior Vice President, AI products and Platforms, Optum LabsEpisode 16Data Veracity and DiversityYao MorinChief Data Officer, JLLEpisode 15Wall Street to Hollywood and the Role of DataDuan PengSVP of Data and AI, WarnerMediaEpisode 14Representation Matters in Data + AIJeffrey ReidVP, Chief Data Officer, Regeneron Genetics CenterEpisode 13Making the Case for Digital TransformationJohn IrvinChief Data Officer - Information Technology Services, DeloitteEpisode 12Scaling Data MarketplacesWarren BreakstoneManaging Director and Chief Product Officer, Data Management Solutions, S&P GlobalEpisode 11Failing Fast with Data Science and MLDan JeavonsVP for Digital Innovation and Computational Science, ShellEpisode 10Next-Gen Customer 360 With Data + AIDon VuChief Data Officer, Northwestern MutualEpisode 9The Role of Data + AI in Healthcare EquitySlawek KiernerSVP, Chief Data and Analytics Officer, HumanaEpisode 8The Critical Job of Building a Data CultureYao Morin, Ph.D., CDO at JLL, Don Vu, Chief Data Officer at Northwestern Mutual, Patrick Baginski, Sr. Director of Data Analytics at McDonald\u2019s, Sherman Cooper, VP of Data Management and Strategy at Mastercard, Randy Bean, CEO, NewVantage PartnersEpisode 7Why AI Starts with Effective Data ManagementHabsah NordinHead of Enterprise Data, Group Digital, PETRONASEpisode 6The Role of the Data Platform in Transforming BusinessPallaw SharmaChief Data Science Officer, Supply Chain, Johnson and JohnsonEpisode 5Ethical Use of Data for AIJoAnn StonierChief Data Officer, MastercardEpisode 4How Education Rewrote the Book on Virtual LearningKate CarruthersChief Data and Insights Officer, University of New South Wales, StarbucksEpisode 3Improving Human Experiences With DataJon FrancisChief Analytics Officer, StarbucksEpisode 2The Evolving Data LeaderSol RashidiChief Analytics Officer, Est\u00e9e LauderEpisode 1Democratizing Data Starts at the TopStuart HughesChief Information and Digital Officer, Rolls-RoyceHosted byChris D\u2019AgostinoGlobal Field CTODatabricksFrom 2014 to 2020, Chris was responsible for leading Capital One\u2019s enterprise data transformation initiative. Chris managed a 1,000 person data engineering team with a budget of $120 million-plus to develop cloud-native solutions and platforms for streaming data, data lake, on-demand compute, data warehouse, data management, data governance, business intelligence and machine learning. He was also responsible for migrating Capital One from on-prem versions of Teradata, SAS, Hadoop and Ab Initio to the new AWS-based Modern Cloud Data Architecture leveraging Databricks and Snowflake for various workloads.\n\u00a0\nPrior to Capital One, Chris founded, led and successfully exited a software company after serving as its president and CEO from 2002 through 2014. He served as an adjunct professor at George Mason University and the University of Virginia and is a frequent presenter at major technology conferences. Chris holds B.S. and M.S. degrees in Electrical Engineering with a concentration in Computer Science from Virginia Tech.Alexandra MysakDirector of Sales, Financial ServicesDatabricksAlex leads the dedicated sales team for financial services at Databricks. Before her career in big data, Alex led Americas sales and accounts for the collaboration software company, Symphony Communication. Prior to that, Alex was in finance, spending 15-plus years in equity advisory, capital markets and corporate banking at Goldman Sachs and Standard Chartered. Alex holds a bachelor\u2019s degree in Japanese and management from Durham University in the UK.ResourceseBookTransform and Scale Your Organization with Data and AIProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andy-hanks\/#","text":"Andy Hanks - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndy HanksSenior Data Architect, Analytics Platform at CRISP Shared ServicesBack to speakersA trained physician, Andy leads the Data Analytics team at CRISP Shared Services. CRISP is the designated health information exchange in Maryland and the District of Columbia and supports other affiliate States.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/industries\/retail-industry-solutions","text":"Solution de Data Lakehouse pour le retail et les biens de consommation courante \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWD\u00e9couvrez Lakehouse pour la vente au d\u00e9tailLa plateforme unifi\u00e9e de donn\u00e9es, d'analytique et d'IA utilis\u00e9e par les d\u00e9taillants pour optimiser toutes les phases du parcours clientS'inscrireNous contacterDes performances sup\u00e9rieures \u00e0 grande \u00e9chelle, pour un TCO plus faibleLakehouse for RetailUnifiez vos charges de travail de donn\u00e9es et d'IA gr\u00e2ce \u00e0 l'int\u00e9gration du partage et de la gouvernance\u00a0: les \u00e9quipes externes ont acc\u00e8s \u00e0 toutes les donn\u00e9es utiles \u00e0 tout momentUn impact sur toute la cha\u00eene de valeurEngagement des clientsPertinence et hyper-personnalisation \u00e0 chaque point de contactEn s'appuyant sur des vues \u00e0 360\u00b0 pr\u00e9cises et temps r\u00e9el de leurs clients, les d\u00e9taillants peuvent interpr\u00e9ter le sentiment qui se d\u00e9gage de l'ensemble des canaux et personnaliser les recommandations. Ils ont ainsi toutes les cartes en main pour cr\u00e9er des relations selon les pr\u00e9f\u00e9rences de chaque client. Les r\u00e9sultats Davantage de rentabilit\u00e9 et de fid\u00e9lit\u00e9.Efficacit\u00e9 op\u00e9rationnelleProductivit\u00e9 des collaborateursPerformance des produitsSolutions et partenaires pour la vente au d\u00e9tailDes solutions d\u2019analytique et d\u2019IA sans compromis sp\u00e9cialement pens\u00e9es pour votre secteur d\u2019activit\u00e9Les acc\u00e9l\u00e9rateurs de solutions Databricks sont des guides sp\u00e9cialis\u00e9s con\u00e7us pour acc\u00e9l\u00e9rer les r\u00e9sultats dans la vente au d\u00e9tail, \u00e0 l'aide de notebooks enti\u00e8rement fonctionnels et de bonnes pratiques. Gagnez du temps sur la d\u00e9couverte, la conception, le d\u00e9veloppement et les tests de multiples cas d'usage\u00a0: score de propension, valeur vie client, optimisation de la pr\u00e9paration de commandes et bien plus encore.Pr\u00e9visions granulairesG\u00e9n\u00e9rez rapidement des pr\u00e9visions \u00e0 grande \u00e9chelle\nEffectuez des pr\u00e9visions fine \u00e0 l'\u00e9chelle de l'article en magasin avec une grande efficacit\u00e9 gr\u00e2ce \u00e0 la puissance informatique distribu\u00e9e de la plateforme lakehouse de Databricks.D\u00e9marrerSegmentation des clientsSegmentez vos clients pour optimiser le ciblage\nCr\u00e9ez des segments de clients sophistiqu\u00e9s \u00e0 l'aide des donn\u00e9es issues des ventes, des campagnes, des syst\u00e8mes de promotion et d'autres informations pour produire de meilleures pr\u00e9visions d'achat sur la base des comportements.D\u00e9marrerAnalytique des points de vente en temps r\u00e9elCalculez des inventaires en temps r\u00e9el sur plusieurs boutiques pour am\u00e9liorer les marges de la vente au d\u00e9tail\nImportez rapidement tous les types de sources de donn\u00e9es de point de vente pour g\u00e9n\u00e9rer des insights en temps r\u00e9el et r\u00e9pondre aux besoins urgents d'information en boutique.D\u00e9marrerD\u00e9couvrez les acc\u00e9l\u00e9rateurs pour la vente au d\u00e9tailNous nous sommes associ\u00e9s \u00e0 des cabinets de conseil de premier plan pour proposer des solutions innovantes d\u00e9di\u00e9es \u00e0 chaque secteur d'activit\u00e9. Les solutions Databricks Brickbuilder vous aident \u00e0 r\u00e9duire les co\u00fbts et \u00e0 optimiser la valeur de vos donn\u00e9es. Les solutions Brickbuilder s'appuient sur des d\u00e9cennies d\u2019expertise sectorielle et sont pens\u00e9es pour la plateforme Databricks Lakehouse, pour r\u00e9pondre \u00e0 vos besoins exacts.Vue unifi\u00e9e de la demandeMaximisez la pr\u00e9cision, la granularit\u00e9 et la rapidit\u00e9 avec un plan de requ\u00eate bas\u00e9 sur une source unique de v\u00e9rit\u00e9.En savoir plusGestion de la croissance des revenusAcc\u00e9l\u00e9rez l\u2019analyse des donn\u00e9es de facturation, des donn\u00e9es de march\u00e9 externes, des actualit\u00e9s et des donn\u00e9es scrap\u00e9es sur Internet pour explorer les tendances du retail.En savoir plusTrellisRelevez les d\u00e9fis associ\u00e9s \u00e0 la pr\u00e9vision de la demande, au r\u00e9approvisionnement, \u00e0 l'approvisionnement, \u00e0 la tarification et aux services de promotion.En savoir plusSolutions Brickbuilder\u00ab\u00a0Nous parvenons maintenant \u00e0 combiner, \u00e0 l'\u00e9chelle du client, des informations sur les achats effectu\u00e9s en ligne et en boutique, ce qui \u00e9tait auparavant un v\u00e9ritable d\u00e9fi. Gr\u00e2ce \u00e0 cette vue omnicanal, nous avons mis au point un moteur de recommandation en ligne plus complet qui suscite un engagement sans pr\u00e9c\u00e9dent.\u00a0\u00bb\n\u2014 Wendell Kuling, Responsable Data science et analytique, Jumbo\n\u00ab\u00a0Avec Databricks, nous devan\u00e7ons la concurrence gr\u00e2ce \u00e0 des exp\u00e9riences client exceptionnelles sur tous les march\u00e9s. Avec la plateforme lakehouse, nos parties prenantes et nos d\u00e9veloppeurs collaborent plus \u00e9troitement\u00a0: ils r\u00e9v\u00e8lent des tendances et des insights strat\u00e9giques pour mieux servir nos 180\u00a0millions de clients.\u00a0\u00bb\n\u2014 Sergiy Tkachuk, Directeur Data Science, Reckitt\nDe plus en plus d'unit\u00e9s commerciales utilisent la plateforme en self-service, ce qui \u00e9tait impossible auparavant. \u00ab\u00a0Je suis extr\u00eamement impressionn\u00e9e par l'impact positif qu'a eu Databricks sur Columbia.\u00a0\u00bb\n- Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear\nRessourcesVisite libreToutes les ressources dont vous avez besoin pour explorer le lakehouse pour la vente au d\u00e9tailWebinairesFaciliter la prise de d\u00e9cision en temps r\u00e9el dans la vente au d\u00e9taile-bookLe Grand Livre des cas d'usage de la vente au d\u00e9tailProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/glossary\/alternative-data","text":"What is Alternative Data?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAlternative DataAll>Alternative DataTry Databricks for freeGet StartedWhat is Alternative Data?Alternative data is information gathered by using alternative sources of data that others are not using; \u00a0non-traditional information sources. Analysis of alternative data can provide insights beyond that which an industry's regular data sources are capable of providing. However, what exactly is considered to be alternative data varies from one industry to another as it depends on the traditional data sources that you and your competitors are already using.Typical Alternative Data TypesWhen we talk about alternative data, there are a couple of data types that are mainly used:satellite data,mobile datasensor dataweb data.However, alternative data can also include:Geolocation (foot traffic)Credit card transactionsEmail receiptsPoint-of-sale transactionsSocial media postsOnline browsing activityShipping container receiptsProduct reviewsPrice TrackersWeather and micro-climatesFlight and shipping trackersIn recent years, the increase in data coming from mobile devices, satellites, sensors, and websites has led to vast amounts of structured, semistructured and unstructured data, that we refer under the generic term of big data. Using alternative data allows you to gain unique insights, competitive industry advantage, and boosted profits. \u00a0You can combine data sets from different sources to get a clear overview of company-specific, competitive market landscapes. There are three main ways that can be used to access alternative data:Acquisition of Raw dataThird-party LicensingWeb scraping (or web harvesting, or web data extraction). A web scraper is an Application Programming Interface(API) that extract data from a web site and is capable of gathering key insights on the desired topic necessary to thrive in your industry. Newer forms of web scraping involve listening to data feeds from web servers. For example, JSON is commonly used as a transport storage mechanism between the client and the web server.Automated Scraping TechniquesHTML Parsing: HTML parsing is done using Java scripts, and targets linear or nested HTML pages.DOM Parsing: Document Object Model, or DOM, defines the style, structure and the contents contained within the XML files.Vertical Aggregation: Vertical aggregation platforms are created by organizations featuring a huge computing power which are targeting specific verticals.XPath: XML Path Language or XPath is a query language that can be used on XML documents.Google Docs: Google sheets can be used pretty much the same as if you were writing a scraper in a programming language like Python or Ruby, as a result, it is a good and quick way to introduce the basics of certain types of scrapers.Text Pattern Matching: This is a regular expression-matching technique that uses the UNIX grep command, and clubbed with popular programming languages like Perl or Python.Additional ResourcesSupercharging Your Data Lake with Alternative Data WebinarLeveraging Alternative and Third-Party Data in Financial Services eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vikas-reddy-aravabhumi\/#","text":"Vikas Reddy Aravabhumi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVikas Reddy AravabhumiStaff Backline Engineer at DatabricksBack to speakersVikas Reddy Aravabhumi is an experienced Staff Backline engineer with over 12 years of industry experience. He specializes in resolving Big data problems for customers through the use of Structured Streaming, spark SQL, Delta Lake and DLT. Additionally, he has extensive expertise in implementing Structured Streaming frameworks. Prior to joining Databricks, he worked as a technical lead assisting consulting and R&D companies in deploying their big data ETL pipelines using Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/trust?itm_data=menu-item-securitytrustcenter","text":"Centro de seguran\u00e7a e confian\u00e7a - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueSabemos que os dados s\u00e3o um de seus ativos mais valiosos e t\u00eam que ser protegidos sempre. \u00c9 por isso que a seguran\u00e7a est\u00e1 integrada em cada camada da Plataforma Databricks Lakehouse. Nossa transpar\u00eancia permite que voc\u00ea atenda \u00e0s suas necessidades regulamentares enquanto tira proveito da nossa plataforma.Sabemos que os dados s\u00e3o um de seus ativos mais valiosos e t\u00eam que ser protegidos sempre. \u00c9 por isso que a seguran\u00e7a est\u00e1 integrada em cada camada da Plataforma Databricks Lakehouse. Nossa transpar\u00eancia permite que voc\u00ea atenda \u00e0s suas necessidades regulamentares enquanto tira proveito da nossa plataforma.Plataforma confi\u00e1velA confian\u00e7a vem atrav\u00e9s da transpar\u00eancia. Veja como protegemos a plataforma por meio de pr\u00e1ticas l\u00edderes do setor, incluindo testes de penetra\u00e7\u00e3o, gerenciamento de vulnerabilidades e desenvolvimento de software seguro para proteger a Plataforma Databricks Lakehouse.Saiba maisCaracter\u00edsticas de seguran\u00e7aFornecemos recursos de seguran\u00e7a abrangentes para proteger seus dados e workloads, como criptografia, controles de rede, auditoria, integra\u00e7\u00e3o de identidade, controles de acesso e governan\u00e7a de dados.Saiba maisConformidadeClientes de todo o mundo e de todos os setores dependem da Plataforma Databricks Lakehouse. Temos as certifica\u00e7\u00f5es e os atestados para atender \u00e0s necessidades exclusivas de conformidade de setores altamente regulamentados.Saiba maisPrivacidadeValorizamos a privacidade dos seus dados e entendemos que \u00e9 importante tanto para a sua organiza\u00e7\u00e3o quanto para os seus clientes. Os dados podem ajudar voc\u00ea a cumprir as leis de privacidade e atender aos requisitos regulamentares.Saiba maisRealize sua pr\u00f3pria an\u00e1lise de seguran\u00e7a de autoatendimento da Databricks usando nosso pacote de due diligence, que inclui documenta\u00e7\u00e3o e materiais de conformidade.Pacote de due diligenceProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=datastreaming-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/sponsors?itm_data=hp-hamburger-sponsors-dais23","text":"Sponsors - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricing2023 SponsorsBecome a sponsorIf you are interested in sponsoring Data + AI Summit 2023, please contact our Sponsorship Management Team.\nOrganizing SponsorPrivacyPlatinum SponsorPrivacyPrivacyPrivacyDiamond SponsorsPrivacyPrivacyPrivacyPrivacyGold + SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyGold SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacySilver SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyBronze SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-green","text":"Michael Green - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael GreenSenior Data Scientist at Hitachi Solutions AmericaBack to speakersMichael holds a doctorate in artificial intelligence from NYU's Tandon School of Engineering. He's been researching artificial intelligence for more than 6 years, with successful projects using tree-search, evolutionary optimization, deep learning, and reinforcement learning techniques, with more than 25 peer-reviewed papers. \nToday, Michael works as a product manager and senior data scientist at Hitachi Solutions America, leading the AI initiative for the Empower Platform team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/building-machine-learning-platforms?itm_data=machinelearning-link-buildingmlplatforms","text":"Building Machine Learning Platforms | DatabricksBuilding Machine Learning PlatformsHear Matei Zaharia\u2019s keynote on MLOps and ML Platforms State of the Industry \u2014 now available on-demand. Learn about managing the end-to-end ML lifecycle at scale from Databricks\u2019 chief technology officer and co-founder. Topics covered:Product demos: How to operationalize data science and ML on Databricks with MLflowReal-world use cases: Analytics experts at Blue Cross, Atlassian, Quby and OutreachQ&A panel: Hosted by Ben Lorica, Chief Data Scientist, DatabricksFeatured SpeakersMatei ZahariaCo-founder and Chief Technology OfficerDatabricksBen LoricaChief Data ScientistDatabricksClemens MewaldDirector, Product Management, Data Science and MLDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/reputation-risk","text":"How to build: Reputation Risk | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: A reputation risk engineTo enable financial services institutions to measure brand perception\nCreate superior customer experiences by tracking customer feedback\nHarness the Databricks Lakehouse Platform to build a risk engine that can analyze customer feedback \u2014 securely and in real-time to power an early assessment of reputation risks. Read the full write-up\nNOTEBOOK 1Using Delta Lake for ingesting anonymized customer complaints in real-timeDownload NotebookNOTEBOOK 2Exploring complaints data at scale using KoalasDownload NotebookNOTEBOOK 3Leverage AI to better operate customer complaintsDownload NotebookNOTEBOOK 4Supercharge your BI reports with augmented intelligenceDownload NotebookBenefits and business valueGain a holistic viewApply new sources of data, such as social media, direct customer feedback and other unstructured sources to gauge reputationMove fast and earlyPreempt issues with an early assessment of reputational risksCollaborate at scaleEnable data teams to collaborate and iterate quickly on building reputation risk platforms that can scale as data volume growsReference ArchitectureAdditional resourcesLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/06\/16\/solution-accelerator-toxicity-detection-in-gaming.html","text":"Build a Real-time AI Model to Detect Toxic Behavior in Gaming - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorSolution Accelerator: Toxicity Detection in Gamingby Dan Morris and Duncan DavisJune 16, 2021 in Engineering BlogShare this postCheck out the\u00a0solution accelerator\u00a0to download the notebooks referred throughout this blog.\u00a0Across massively multiplayer online video games (MMOs), multiplayer online battle arena games (MOBAs) and other forms of online gaming, players continuously interact in real time to either coordinate or compete as they move toward a common goal -- winning.\u00a0 This interactivity is integral to gameplay dynamics, but at the same time, it\u2019s a prime opening for toxic behavior -- an issue pervasive throughout the online video gaming sphere.Toxic behavior manifests in many forms, such as the varying degrees of griefing, cyberbullying and sexual harassment that are illustrated in the matrix below from Behaviour Interactive, which lists the types of interactions seen within the multiplayer game, Dead by Daylight.Fig. 1: Matrix of toxic interactions that players experienceIn addition to the personal toll that toxic behavior can have on gamers and the community -- an issue that cannot be overstated -- it is also damaging to the bottom line of many game studios. For example, a study from Michigan State University revealed that 80% of players recently experienced toxicity, and of those, 20% reported leaving the game due to these interactions. Similarly, a study from Tilburg University showed that having a disruptive or toxic encounter in the first session of the game led to players being over three times more likely to leave the game without returning. Given that player retention is a top priority for many studios, particularly as game delivery transitions from physical media releases to long-lived services, it\u2019s clear that toxicity must be curbed.Compounding this issue related to churn, some companies face challenges related to toxicity early in development, even before launch. For example, Amazon\u2019s Crucible was released into testing without text or voice chat due in part to not having a system in place to monitor or manage toxic gamers and interactions. This illustrates that the scale of the gaming space has far surpassed most teams\u2019 ability to manage such behavior through reports or by intervening in disruptive interactions. Given this, it\u2019s essential for studios to integrate analytics into games early in the development lifecycle and then design for the ongoing management of toxic interactions.Toxicity in gaming is clearly a multifaceted issue that has become a part of video game culture and cannot be addressed universally in a single way.\u00a0 That said, addressing toxicity within in-game chat can have a huge impact given the frequency of toxic behavior and the ability to automate detection of it using natural language processing (NLP).Introducing the Toxicity Detection in Gaming Solution Accelerator from DatabricksUsing toxic comment data from Jigsaw and Dota 2 game match data, this solution accelerator walks through the steps required to detect toxic comments in real time using NLP and your existing lakehouse. For NLP, this solution accelerator uses Spark NLP from John Snow Labs, an open-source, enterprise-grade solution built natively on Apache Spark \u2122.The steps you will take in this solution accelerator are:Load the Jigsaw and Dota 2 data into tables using Delta LakeClassify toxic comments using multi-label classification (Spark NLP)Track experiments and register models using MLflowApply inference on batch and streaming dataExamine the impact of toxicity on game match dataDetecting toxicity within in-game chat in productionWith this solution accelerator, you can now more easily integrate toxicity detection into your own games. For example, the reference architecture below shows how to take chat and game data from a variety of sources, such as streams, files, voice or operational databases, and leverage Databricks to ingest, store and curate data into feature tables for machine learning (ML) pipelines, in-game ML, BI tables for analysis and even direct interaction with tools used for community moderation.Fig. 2: Toxicity detection reference architectureHaving a real-time, scalable architecture to detect toxicity in the community allows for the opportunity to simplify workflows for community relationship managers and the ability to filter millions of interactions into manageable workloads. Similarly, the possibility of alerting on severely toxic events in real-time, or even automating a response such as muting players or alerting a CRM to the incident quickly, can have a direct impact on player retention. Likewise, having a platform capable of processing large datasets, from disparate sources, can be used to monitor brand perception through reports and dashboards.Getting startedThe goal of this solution accelerator is to help support the ongoing management of toxic interactions in online gaming by enabling real-time detection of toxic comments within in-game chat. Get started today by importing this solution accelerator directly into your Databricks workspace.Once imported you will have notebooks with two pipelines ready to move to production.ML Pipeline using Multi-Label Classification with training on real-world English datasets from Google Jigsaw. The model will classify and label the forms of toxicity in text.Real-time streaming inference pipeline leveraging the toxicity model. The pipeline source can be easily modified to ingest chat data from all the common data sources.With both of these pipelines, you can begin understanding and analyzing toxicity with minimal effort. This solution accelerator also provides a foundation to build, customize and improve the model with relevant data to game mechanics and communities.Check out the\u00a0solution accelerator\u00a0to download the notebooks referred throughout this blog.\u00a0Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/announcing-public-preview-databricks-marketplace","text":"Announcing Public Preview of Databricks Marketplace - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing Public Preview of Databricks MarketplaceAn open marketplace for all your data, analytics, and AIby Zaheera Valani, Steve Mahoney, Jay Bhankharia, Erika Ehrli, Sachin Thakur, Darshana Sivakumar and Cassie MiaoApril 27, 2023 in Platform BlogShare this postWe are excited to announce the public preview of Databricks Marketplace, an open marketplace for all your data, analytics, and AI, powered by the open-source Delta Sharing\u00a0standard. The Databricks Marketplace brings together a vast ecosystem of data consumers and data providers to share and collaborate across a wide array of data assets including data sets, notebooks, ML models, and more, without any platform dependencies, complicated ETL or expensive replication. Data consumers can innovate and advance their organizations\u2019 AI, ML, and analytics initiatives and deliver faster insights with no vendor lock-in. Data providers can expand their businesses, reach new users, and unlock revenue.Exploring an embedded notebook on Databricks MarketplaceIn this blog post, we discuss our vision for an open marketplace that enables data consumers and providers to discover, share and monetize complete solutions on a secure platform - not just data, but notebooks, models, dashboards, applications, and more to deliver insights and innovation faster.Databricks Marketplace for Data ProvidersData providers need an open marketplace where they can grow their business by monetizing new types of assets and reach users on any platform securely.But data providers also face major roadblocks with current marketplaces:Limited opportunities to monetize new types of assets: A data-only approach means that organizations are limited to monetizing anything beyond a dataset and have more friction to create new revenue opportunities with non-compatible platforms.Difficulty reaching users securely across platforms: Most data solutions limit the number of users data providers can reach. Data providers frequently have to replicate data for different recipients across platforms, clouds, and regions. Data providers have to choose between forgoing business or incurring the expense to replicate data.Lack of secure technology and unified governance: As modern data requirements become more stringent, homegrown and legacy technologies have become more difficult to secure and govern. Data providers have to use multiple tools to govern and secure access to the scattered data, leading to inconsistent governance and security issues.The Databricks Marketplace expands businesses and unlocks new revenue opportunities for data providers. Built on open standards, the Marketplace connects providers with the widest array of data tools across every cloud to uniquely allow data providers to monetize both their data sets and data assets - like models, notebooks, and dashboards - without any platform dependence, ETL, or replication to ensure that their data consumers obtain the fastest and simplest time to insight.Monetize more than just data: Monetize the broadest set of data assets including data sets, notebooks, ML models, and more with the broadest set of data consumers.Reach users on any platform: Expand your reach across platforms and to new personas. Connect with a vast ecosystem beyond walled gardens that includes any cloud or region, customers and partners both inside and outside of Databricks, as well as native integrations with many tools and platforms, such as Excel, PowerBI, pandas, and more. Our cloud-neutral strategy supports AWS, GCP, and Azure and our users include data analysts, ML practitioners, as well as data engineers and business users. Streamline delivery of simple and secure data sharing to any cloud or region, without replication.Share data securely: Share all your data sets, notebooks, ML models, dashboards and more securely across clouds, regions and data platforms.\nWith Nasdaq data now discoverable on the Databricks Marketplace and accessible via Delta Sharing, we will enable customers to access data in an open way across their tools of choice and accelerate their time. \u2014 Bill Dague, Vice-president and Head of data product at Nasdaq\n\nAccuWeather\u2019s Superior Weather Intelligence plus Databricks Marketplace enables our customers to get from data access to business impact quickly, saving them time and money \u2014 Mark D\u2019Andrea, CRO AccuWeather\n\nThe Databricks Marketplace is a key channel for co-developing and delivering real-world data sets and analytics with our customers, which helps TriNetX with reducing barriers to data access, and ultimately enables our customers to accelerate the generation of real-world evidence. \u2014 Jeffrey Graham, Vice President, Real-World Data and Innovation, TriNetX, LLC.\n\nLiveRamp is excited to launch data and identity solutions within Databricks Marketplace, enabling brands to connect securely with customers on a more personalized level while maintaining a privacy-centric approach. These solutions offer industry-leading person-based and household-based identity solutions, attribute enrichments, and identity translation solutions for partner data connectivity to accelerate Lakehouse ML and advanced analytics use cases.\u201d \u2014 Erin Boelkens, VP of Product, LiveRamp\nDatabricks Marketplace for Data ConsumersData consumers need an open marketplace where they can find, evaluate, and discover a broader set of data assets and solutions to innovate with data, analytics, and AI and deliver faster insights with no vendor lock-in.But data consumers today still face major roadblocks with current marketplaces:Focus on data only or simple applications: Data only means that organizations looking to take advantage of ML\/AI need to look elsewhere or start from scratch, causing delays in business insights.Lengthy discovery and evaluation: The tools most marketplaces provide for data consumers to evaluate data are simply descriptions and example SQL statements. Minimal evaluation tools mean it takes more time to figure out if a data product is right for you, which might include more time in back-and-forth messages with a provider or searching for a new provider altogether.Delayed time-to-insights with vendor lock-in: Delivery through proprietary sharing technologies or FTP means either vendor lock-in or lengthy ETL processes to get the data where you need to work with it.The Databricks Marketplace dramatically expands the opportunity for data consumers to deliver innovation and advance all their analytics and AI initiatives. Data consumers can uniquely obtain data sets, as well as AI and analytical assets - such as ML models, notebooks, applications, and dashboards - without proprietary platform dependencies, complicated ETL, or expensive replication. This open approach allows you to put your data to work more quickly in every cloud with your tools of choice.Discover more than just data: Unlock innovation and advance your organization's AI, ML, and analytics initiatives. Access more than just data sets, including ML models, notebooks, applications, and solutions.Evaluate data products faster: Pre-built notebooks and sample data help you quickly evaluate and have much greater confidence that a data product is right for your AI, ML, or analytics initiatives.Avoid vendor lock-in: Substantially reduce the time to deliver insights and avoid lock-in with open and seamless sharing and collaboration across clouds, regions, or platforms. Directly integrate with your tools of choice and right where you work.\nDatabricks Marketplace simplifies the process of discovering and evaluating external data with pre-built notebooks, without locking us into a single vendor or prolonging procurement cycles. With just a few clicks, we can access the data within our Databricks workspaces. We also look forward to leveraging the notebooks, dashboards, and ML models through the marketplace to enhance our analytics and AI initiatives \u2014 Greg Rokita, AVP Technology, Edmunds\n\nThe Databricks Marketplace is a game-changer when it comes to accessing third-party data through Delta Sharing. The platform allows us to seamlessly browse a range of data products, evaluate them using a variety of tools like notebooks and dashboards, and put the data into production-ready use cases. This ease of use and flexibility is truly transformative \u2014 David Mariani | Chief Technology Officer, Founder, AtScale\nGet started with Databricks MarketplaceWatch a demo below to discover the ease of use of Databricks Marketplace for data consumers and data providers:To play this video, click here and accept cookiesThis is just the beginning. We are working on exciting new features to realize our vision with Databricks Marketplace for data consumers and data providers. Don\u2019t miss more exciting updates about data sharing and collaboration and register for our sessions at\u00a0Data and AI Summit.If you are interested in becoming a data provider on the marketplace, sign-up and please choose \"Marketplace\" as the program of interest.Try Databricks for freeGet StartedRelated postsIntroducing Databricks MarketplaceJune 28, 2022 by Matei Zaharia, Zaheera Valani, Jay Bhankharia, Sachin Thakur, Itai Weiss and Steve Mahoney in Announcements\nWe're pleased to announce Databricks Marketplace, an open marketplace for exchanging data products such as datasets, notebooks, dashboards, and machine learning models. To...\nAnnouncing General Availability of Delta SharingAugust 26, 2022 by Matei Zaharia, Celia Kung, Xiaotong Sun, Steve Mahoney, Itai Weiss, Sachin Thakur and Jay Bhankharia in Announcements\nToday we are excited to announce that Delta Sharing is generally available (GA) on AWS and Azure. With the GA release, you can...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/discover\/introduction-to-data-analysis-workshop-series","text":"Overview - Data Analysis Workshop SeriesSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIntroduction to Data Analysisfor Aspiring Data ScientistsOverviewIntroduction to PythonData Analysis with pandasIntroduction to Apache SparkOverviewJoin us for a four-part learning series: Introduction to Data Analysis for Aspiring Data Scientists. This self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Each workshop page contains the session video recording, transcripts, speaker info, and a GitHub link to access the notebooks and resources. We suggest you\u00a0start with Part One, Introduction to Python, and continue from there in order because each workshop builds upon the last.If you\u2019d like to follow along, please\u00a0Sign Up for your free Community Edition account\u00a0or\u00a0download the Delta Lake library.Sign up for Community editionIntroduction to PythonIn this workshop, we will show you the simple steps needed to program in Python using a notebook environment on the free Databricks Community Edition.This workshop covers major foundational concepts necessary for you to start coding in Python, with a focus on data analysis. No prior programming knowledge is required.Watch videoData Analysis with PandasThis workshop is on pandas, a powerful open-source Python package for data analysis and manipulation. In this workshop, you will learn how to read data, compute summary statistics, check data distributions, conduct basic data cleaning and transformation, and plot simple visualizations. Although no prep work is required, we do recommend basic python knowledge. Watch Part One, Introduction to Python to learn about Python.Watch videoIntroduction to Apache SparkThis workshop covers the fundamentals of Apache Spark, the most popular big data processing engine. In this workshop, you will learn how to ingest data with Spark, analyze the Spark UI, and gain a better understanding of distributed computing. No prior knowledge of Spark is required, but Python experience is highly recommended.Watch videoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/azure\/security-and-compliance","text":"Azure Databricks Security and Compliance | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure Databricks security and complianceEnable the true potential of your data with cloud native security, deeply integrated with Azure\nTry for freeSchedule a demoFederal, state and local government agencies, such as the U.S. Department of Veterans Affairs (VA), Centers for Medicare and Medicaid Services (CMS), Department of Transportation (DOT), the City of Spokane and DC Water, trust Azure Databricks for their critical data and AI needs. Databricks maintains the highest level of data security by incorporating industry-leading best practices into our security program.\nBenefits of securing a lakehouse on Azure\nAs organizations move to break down data silos, Azure Databricks enables them to implement policy-governed controls that enable data engineers, data scientists and business analysts to process and query data from many sources in a single data lake. Different classes of data can be protected and isolated to ensure proper access and auditability.\n\u00a0\nAn integrated and consistent approach to data governance and access simplifies the lakehouse architecture and gives organizations the ability to rapidly scale from a single use case to operationalizing a data and AI platform across many distributed data teams.\nSecure access to the lakehouseAppropriate user accessLakehouse auditabilityPolicy-based access controlsAzure Databricks security and compliance features\nIn addition to core Databricks security features, Azure Databricks provides native integration with Azure security features to safeguard your most sensitive data and enhance compliance.\nCloud-native controls for core security\nSimplify data lakehouse access with Azure Active Directory (Azure AD) credential pass-through. Control who has access to what data by using seamless identity federation with Azure AD.Data security\nAzure storage automatically encrypts your data, and Azure Databricks provides tools to safeguard data to meet your organization\u2019s security and compliance needs, including column-level encryption.Manage your secrets, such as keys and passwords, with integration to Azure Key Vault. By default, all Azure Databricks notebooks and results are encrypted at rest with a different encryption key. If you want to own and manage the key used for encrypting your notebooks and results yourself, you can bring your own key (BYOK).Isolated environments\nThe default deployment of Azure Databricks is a fully managed service on Azure that includes a virtual network (VNet). Azure Databricks also supports deployment in your own virtual network (sometimes called VNet injection or bring your own VNet) that enables full control of network security rules.Azure Private Link encrypts all traffic between your users and their Azure Databricks notebooks and compute resources using Azure\u2019s network backbone that is inaccessible to the outside world. This mitigates against data exfiltration, preventing users from sending data externally.Audit\nGet cloud-native visibility into who is processing the data and when, using Azure Storage Explorer.Compliance standards\nGDPR and CCPA\nDelta Lake brings data reliability and performance optimizations to your cloud lakehouse. Azure Databricks can help you comply with applicable data protection laws, like GDPR and CCPA.HIPAA\nCompliance with HIPAA is available through Microsoft Azure BAA. Learn more about the Databricks Compliance and Assurance Program.HITRUSTAzure Databricks is HITRUST CSF Certified to meet the required level of security and risk controls to support the regulatory requirements of our customers.FedRAMP HighAzure Databricks has received a Federal Risk and Authorization Management Program (FedRAMP) High Authority to Operate (ATO) in two Azure Government regions: US Gov Arizona and US Gov Virginia. Azure Databricks is Federal Risk and Authorization Management Program (FedRAMP) authorized at the High Impact level, enabling data and AI use cases across the public sector on the dedicated Microsoft Azure Government (MAG) cloud. See the list of Azure services by FedRAMP and DoD CC SRG audit scope. Learn more about FedRAMP by reading this Microsoft documentation.Department of Defense Impact Level 5 (DoD IL5)Azure Databricks has received a Provisional Authorization (PA) by the Defense Information Systems Agency (DISA) at Impact Level 5 (IL5) in two Azure Government regions: US Gov Arizona and US Gov Virginia, as published in the Department of Defense Cloud Computing Security Requirements Guide (DoD CC SRG).Policy-based access controls\nAzure Databricks supports cloud-native access control for ADLS Gen 2 for seamless access management controls, including role-based access controls.Documentation and resourcesBlogsAzure Databricks Security Best PracticesSecurity Cluster Connectivity Is Generally Available on Azure DatabricksFeatures and informationDatabricks Security FeaturesMicrosoft Trust CenterDocsAzure Databricks product pageAzure Databricks Platform SecurityAzure Databricks Security and privacyAzure Databricks Administration GuideMicrosoft FedRAMP documentationDelta lake documentationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/douglas-moore\/#","text":"Douglas Moore - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDouglas MooreLead Specialist Solutions Architect at DatabricksBack to speakersSince 2011 Douglas Moore been making Big Data Analytics a lot easier for customers. His current role is that of an HLS Lead Specialist Solutions Architect with Databricks. Douglas brings a long tenure in enterprise data architecture and building data analytics platforms. Past roles have included: Solutions Architect, Data Architect, CTO, Engineer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/external-user-terms","text":"External User Terms | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesExternal User TermsThese External User Terms (\u201cExternal User Terms\u201d) are entered into by and between the individual or organization accessing the External User Workspace, as defined below (\u201cYou\u201d) and Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d). These External User Terms are a Schedule to the\u00a0Master Cloud Service Agreement\u00a0(\"MCSA\"). Together, these External User Terms and MCSA comprise the \u201cAgreement\u201d governing Your use of the Platform Services as an External User. Capitalized terms used but not defined in these External User Terms have the meaning assigned to them in the MCSA. You hereby agree to the Agreement by clicking \u201cAccept\u201d or through any other indication of agreement to these External User Terms, or by accessing any External User Workspace made available to You by Databricks on behalf of the named Customer paying Databricks for such Workspace.Use of the Platform Services as an External User.\u00a0Generally. \u00a0Unless otherwise indicated in this Schedule, the terms of the MCSA apply to Your use of the Platform Services as an External User of a Customer. \u00a0Where the MCSA uses the term \u201cCustomer\u201d, it shall be deemed to refer to You unless stated otherwise in this Schedule. \u00a0Where this Schedule uses the term \u201cCustomer\u201d, it shall refer to the Customer who invited You to use the External User Workspace.Additional Definitions for External Users. The following terms are added to the MCSA and (to the extent of a conflict) supersede the MCSA where a term is already defined within the MCSA:\n\u201cCustomer Services\u201d means services which Customer offers to External User, which requires use of the Platform Services.\u201cExternal User\u201d means an Authorized User of the Platform Services who has been invited to join a Workspace set up by Customer.\u201cExternal User Workspace\u201d means a Workspace operated by Customer which has had one or more External Users added to it.Limited Use of the Platform Services; No Support. External User may use the External User Workspace as an Authorized User of Customer, subject at all times to the Agreement and to any restrictions Customer places on the use of the External User Workspace. \u00a0Without limiting the foregoing,\nCustomer may use the External User Workspace solely to receive the Customer Services and for no other purposes, and that accordingly, Customer may not make available more Customer Data to the External User Workspace than is necessary to permit External User to receive the Customer Services;External User may only use the External User Workspace while External User is under written agreement with the Customer to receive the Customer Services and for so long as Customer has an active Order with Databricks for the use of the Platform Services;Customer, and not External User, is Databricks\u2019 \u2018customer\u2019 with respect to the use of the External User Workspace and accordingly Databricks shall have no obligations directly to External User related to the use of the External User Workspace (including, for example, Databricks will not be responsible for providing Support to External User);External User acknowledges Customer is responsible for managing the External User Workspace and will therefore have access to any Customer Content made available to the External User Workspace by External User; andWithout limiting the foregoing, External User may not use the External User Workspace to replace its use of the Platform Services under any Order or other agreement External User executes or has executed with Databricks for the direct use of the Platform Services by External User as a \u2018Customer\u2019.Platform Deployment. You, the External User, acknowledge that External User Workspaces will be deployed based on configurations determined between External User and Customer. Databricks may rely on instructions from either the External User or Customer regarding External User Workspaces.\u00a0Additional Authorized Users. \u00a0If Customer permits External User to add additional Authorized Users, such Authorized Users must be (i) employees or agents of External User, and (ii) designated as External Users (if provided an option within the Platform Services to designate an Authorized User as an \u2018Internal User\u2019 or \u2018External User\u2019 or similar). \u00a0For the avoidance of doubt, External User is not permitted to provide access to the Platform Services to third parties for such third parties\u2019 own uses.Last Updated October 10, 2022. For earlier versions, please send a request to\u00a0[email\u00a0protected]\u00a0(with \u201cExternal User Terms Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/accelerators","text":"Databricks \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130 - \ub370\uc774\ud130 \ubc0f AI \uac00\uce58 \ucc3d\ucd9c \uc2dc\uac04 \ub2e8\ucd95 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, 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\uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 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Databricks\uc5d0\uc11c\ub294 \uc801\uc808\ud55c \ub9ac\uc18c\uc2a4(\ub178\ud2b8\ubd81, \uac80\uc99d\ub41c \ud328\ud134, \ubaa8\ubc94 \uc0ac\ub840)\ub97c \uc81c\uacf5\ud574 \ub370\uc774\ud130\uc640 AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \ube60\ub974\uac8c \uc2dc\uc791\ud558\ub3c4\ub85d \ub3d5\uace0\uc790 \ud569\ub2c8\ub2e4. 2\uc8fc \uc774\ub0b4\uc5d0 \uad6c\uc0c1\uc5d0\uc11c \uac1c\ub150 \uc99d\uba85(PoC) \ub2e8\uacc4\uae4c\uc9c0 \uc644\ub8cc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc2e4\uc81c \uace0\uac1d\uc758 Databricks \uc0ac\uc6a9 \uc0ac\ub840\uace0\uac1d \uc0ac\ub840 \ub458\ub7ec\ubcf4\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jegadeesan-pugazhenthi\/#","text":"Jegadeesan Pugazhenthi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJegadeesan PugazhenthiLead Big Data Engineer at AT&TBack to speakersWorking as Lead Big Data Engineer at AT&T. Have been at the forefront of adoption of new technologies at AT&T including successful adoption of Big Data platform as part of AT&T Big Data COE. Currently leading the effort on adoption of cloud technologies and migration of on-prem applications to cloud platforms like Databricks. Instrumental in migrating petabytes of data to the cloud. Leading continuous cloud optimization efforts resulting in significant cloud cost savings.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suresh-matlapudi\/#","text":"Suresh Matlapudi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuresh MatlapudiLead Solutions Architect and Specialist SME, Migrations at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ananya-ghosh\/#","text":"Ananya Ghosh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnanya GhoshBusiness Application Owner for Databricks at Nationwide InsuranceBack to speakersAnanya Ghosh has over 15 years of experience in DW\/DI\/BI tools and technologies. Currently she plays the role of Business Application Owner for Capture & Curate platforms including Databricks. Prior to that, she worked as a Databricks Data Engineer and Workspace Administrator for about 2 yrs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/tensorflow-estimator-api","text":"What is the Tensorflow Estimator API?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTensorflow Estimator APIAll>Tensorflow Estimator APITry Databricks for freeGet StartedWhat is the Tensorflow Estimator API?Estimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow provides a programming stack consisting of multiple API layers like in the below image:There are two types of estimators; you can either choose the pre-made Estimators, alternatively, you can write your own custom Estimators. Estimators-based models can be run on local hosts as well as on distributed multi-server environment without changing your model. In addition, you can run Estimators-based models on CPUs, GPUs, or TPUs without having to record your model.Estimators Encapsulate Four Main Features:Training- they will train a model on a given input for a fixed number of stepsEvaluation- they will evaluate the model based on a test set.Prediction- \u00a0estimators will run inference using the trained model.Export your model for serving.On top of that, the Estimator includes default behavior common to training jobs, such as saving and restoring checkpoints, creating summaries, etc. An Estimator will require you to write a model_fn and an input_fn that correspond to the model and input portions of your TensorFlow graph.Estimators Come with Numerous Benefits:Estimators simplify sharing implementations between model developers.You can develop a great model with high-level intuitive code, as they usually are easier to use if you need to create models compared to the low-level TensorFlow APIs.Estimators are themselves built on tf.keras.layers, that makes customization a lot easier.Estimators will make your life easier by building the graph for you.Estimators provide a safely distributed training loop that controls how and when to:\nbuild the graphinitialize variablesload datahandle exceptionscreate checkpoint files and recover from failuressave summaries for TensorBoard\u00a0Additional ResourcesTensorFlow PlaceholdersEnd-to-End Spark\/TensorFlow\/PyTorch Pipelines with Databricks DeltaBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/spencer-cook","text":"Spencer Cook - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpencer CookSenior Solutions Architect - Financial Services at DatabricksBack to speakersSpencer Cook, M.S., is a data professional with experience delivering end-to-end analytics solutions in the cloud to iconic brands. Since 2021, Spencer has been a financial services solutions architect at Databricks focused on revolutionizing the industry with lakehouse architecture.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/09\/17\/timeliness-and-reliability-in-the-transmission-of-regulatory-reports.html","text":"Timeliness and Reliability in the Transmission of Regulatory Reports - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorTimeliness and Reliability in the Transmission of Regulatory Reportsby Antoine Amend and Fahmid KabirSeptember 17, 2021 in Engineering BlogShare this postManaging risk and regulatory compliance is an increasingly complex and costly endeavour. Regulatory change has increased 500% since the 2008 global financial crisis and boosted the regulatory costs in the process. Given the fines associated with non-compliance and SLA breaches (banks hit an all-time high in fines of $10 billion in 2019 for AML), processing reports has to proceed even if data is incomplete. On the other hand, a track record of poor data quality is also \"fined\" because of \"insufficient controls.\" As a consequence, many Financial Services Institutions (FSIs) are often left battling between poor data quality and strict SLAs, balancing between data reliability and data timeliness.In this regulatory reporting solution accelerator, we demonstrate how Delta Live Tables can guarantee the acquisition and processing of regulatory data in real time to accommodate regulatory SLAs. With Delta Sharing and Delta Live Tables combined, analysts gain real-time confidence in the quality of regulatory data being transmitted. In this blog post, we demonstrate the benefits of the Lakehouse architecture to combine financial services industry data models with the flexibility of cloud computing to enable high governance standards with low development overhead. We will now explain what a FIRE data model is and how DLT can be integrated to build robust data pipelines.FIRE data modelThe Financial Regulatory data standard (FIRE) defines a common specification for the transmission of granular data between regulatory systems in finance. Regulatory data refers to data that underlies regulatory submissions, requirements and calculations and is used for policy, monitoring and supervision purposes. The FIRE data standard is supported by the European Commission, the Open Data Institute and the Open Data Incubator FIRE data standard for Europe via the Horizon 2020 funding programme. As part of this solution, we contributed a PySpark module that can interpret FIRE data models into Apache Spark\u2122 operating pipelines.Delta Live TablesDatabricks recently announced a new product for data pipelines orchestration, Delta Live Tables, which makes it easy to build and manage reliable data pipelines at enterprise scale. With the ability to evaluate multiple expectations, discard or monitor invalid records in real time, the benefits of integrating the FIRE data model on Delta Live Tables are obvious. As illustrated in the following architecture, Delta Live Table will ingest granular regulatory data landing onto cloud storage, schematize content and validate records for consistency in line with the FIRE data specification. Keep reading to see us demo the use of Delta Sharing to exchange granular information between regulatory systems in a safe, scalable, and transparent manner.Enforcing schemaEven though some data formats may \"look\" structured (e.g. JSON files), enforcing a schema is not just a good engineering practice; in enterprise settings, and especially in the space of regulatory compliance, schema enforcement guarantees any missing field to be expected, unexpected fields to be discarded and data types to be fully evaluated (e.g. a date should be treated as a date object and not a string). It also proof-tests your systems for eventual data drift. Using the FIRE pyspark module, we programmatically retrieve the Spark schema required to process a given FIRE entity (collateral entity in that example) that we apply on a stream of raw records.\nfrom fire.spark import FireModel\nfire_model = FireModel().load(\"collateral\")\nfire_schema = fire_model.schema\nIn the example below, we enforce schema to incoming CSV files. By decorating this process using @dlt annotation, we define our entry point to our Delta Live Table, reading raw CSV files from a mounted directory and writing schematized records to a bronze layer.\n@dlt.create_table()\ndef collateral_bronze():\n  return (\n    spark\n      .readStream\n      .option(\"maxFilesPerTrigger\", \"1\")\n      .option(\"badRecordsPath\", \"\/path\/to\/invalid\/collateral\")\n      .format(\"csv\")\n      .schema(fire_schema)\n      .load(\"\/path\/to\/raw\/collateral\")\nEvaluating expectationsApplying a schema is one thing, enforcing its constraints is another. Given the schema definition of a FIRE entity (see example of the collateral schema definition), we can detect if a field is required or not. Given an enumeration object, we ensure its values are consistent (e.g. currency code). In addition to the technical constraints from the schema, the FIRE model also reports business expectations, such as minimum, maximum, monetary and maxItems. All these technical and business constraints will be programmatically retrieved from the FIRE data model and interpreted as a series of Spark SQL expressions.\nfrom fire.spark import FireModel\nfire_model = FireModel().load(\"collateral\")\nfire_constraints = fire_model.constraints\nWith Delta Live Tables, users have the ability to evaluate multiple expectations at once, enabling them to drop invalid records, simply monitoring data quality or abort an entire pipeline. In our specific scenario, we want to drop records failing any of our expectations, which we later store to a quarantine table, as reported in the notebooks provided in this blog.\n@dlt.create_table()\n@dlt.expect_all_or_drop(fire_constraints)\ndef collateral_silver():\n  return dlt.read_stream(\"collateral_bronze\")\nWith only a few lines of code, we ensured that our silver table is both syntactically (valid schema) and semantically (valid expectations) correct. As shown below, compliance officers have full visibility around the number of records being processed in real time. In this specific example, we ensured our collateral entity to be exactly 92.2% complete (quarantine handles the remaining 7.8%).Operations data storeIn addition to the actual data stored as delta files, Delta Live Tables also stores operation metrics as \"delta\" format under system\/events. We follow a standard pattern of the Lakehouse architecture by \"subscribing\" to new operational metrics using AutoLoader, processing system events as new metrics unfold -- in batch or in real time. Thanks to the transaction log of Delta Lake that keeps track of any data update, organizations can access new metrics without having to build and maintain their own checkpointing process.\ninput_stream = spark \\\n    .readStream \\\n    .format(\"delta\") \\\n    .load(\"\/path\/to\/pipeline\/system\/events\")\n      \noutput_stream = extract_metrics(input_stream)\n    \noutput_stream \\\n    .writeStream \\\n    .format(\"delta\") \\\n    .option(\"checkpointLocation\", \"\/path\/to\/checkpoint\") \\\n    .table(metrics_table)\nWith all metrics available centrally into an operation store, analysts can use Databricks SQL to create simple dashboarding capabilities or more complex alerting mechanisms to detect data quality issues in real time.The immutability aspect of the Delta Lake format coupled with the transparency in data quality offered by Delta Live Tables allows financial institutions to \"time travel\" to specific versions of their data that matches both volume and quality required for regulatory compliance. In our specific example, replaying our 7.2% of invalid records stored in quarantine will result in a different Delta version attached to our silver table, a version that can be shared amongst regulatory bodies.\nDESCRIBE HISTORY fire.collateral_silver\nTransmission of regulatory dataWith full confidence in both data quality and volume, financial institutions can safely exchange information between regulatory systems using Delta Sharing, an open protocol for enterprise data exchange. Not constraining end users to a same platform nor relying on complex ETL pipelines to consume data (accessing data files through a SFTP server for instance), the open source nature of Delta Lake makes it possible for data consumers to access schematized data natively from Python, Spark or directly through MI\/BI dashboards (such as Tableau or PowerBI).Although we could be sharing our silver table as-is, we may want to use business rules that only share regulatory data when a predefined data quality threshold is met. In this example, we clone our silver table at a different version and to a specific location segregated from our internal networks and accessible by end users (demilitarized zone, or DMZ).\nfrom delta.tables import *\n\ndeltaTable = DeltaTable.forName(spark, \"fire.collateral_silver\")\ndeltaTable.cloneAtVersion(\n  approved_version, \n  dmz_path, \n  isShallow=False, \n  replace=True\n)\n\nspark.sql(\n  \"CREATE TABLE fire.colleral_gold USING DELTA LOCATION '{}'\"\n    .format(dmz_path)\n)\nAlthough the Delta Sharing open source solution relies on a sharing server to manage permission, Databricks leverages Unity Catalog to centralize and enforce access control policies, provide users with full audit logs capability and simplify access management through its SQL interface. In the example below, we create a SHARE that includes our regulatory tables and a RECIPIENT to share our data with.\n-- DEFINE OUR SHARING STRATEGY\nCREATE SHARE regulatory_reports;\n\nALTER SHARE regulatory_reports ADD TABLE fire.collateral_gold;\nALTER SHARE regulatory_reports ADD TABLE fire.loan_gold;\nALTER SHARE regulatory_reports ADD TABLE fire.security_gold;\nALTER SHARE regulatory_reports ADD TABLE fire.derivative_gold;\n\n-- CREATE RECIPIENTS AND GRANT SELECT ACCESS\nCREATE RECIPIENT regulatory_body;\n\nGRANT SELECT ON SHARE regulatory_reports TO RECIPIENT regulatory_body;\nAny regulator or user with granted permissions can access our underlying data using a personal access token exchanged through that process. For more information about Delta Sharing, please visit our product page and contact your Databricks representative.Proof test your complianceThrough this series of notebooks and Delta Live Tables jobs, we demonstrated the benefits of the Lakehouse architecture in the ingestion, processing, validation and transmission of regulatory data. Specifically, we addressed the need for organizations to ensure consistency, integrity and timeliness of regulatory pipelines that could be easily achieved using a common data model (FIRE) coupled with a flexible orchestration engine (Delta Live Tables). With Delta Sharing capabilities, we finally demonstrated how FSIs could bring full transparency and confidence to the regulatory data exchanged between various regulatory systems while meeting reporting requirements,reducing operation costs and adapting to new standards.Get familiar with the FIRE data pipeline using the attached notebooks and visit our Solution Accelerators Hub to get up to date with our latest solutions for financial services.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/discover\/demos","text":"Prodotto Databricks & Partner Demo Hub - Solution Accelerator Demo | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDemo HubScopri in prima persona Databricks da una prospettiva pratica con questi semplici video. Ogni demo descritta di seguito \u00e8 accompagnata da materiali quali notebook, video ed eBook, che consentono di provare a utilizzare Databricks in prima persona.Comincia gratisDemo di prodottoDatabricks PlatformQuesta demo offre una panoramica della Lakehouse Platform di Databricks, spiegando come progetti open-source quali Apache Spark\u2122, Delta Lake, MLflow e Koalas si inseriscono nell'ecosistema Databricks.Maggiori informazioniDatabricks SQLDatabricks WorkflowsUnity CatalogData science e machine learningDelta SharingDelta LakeDelta Live TablesDelta Lake Data Integration (Auto Loader e COPY INTO)Demo dei partnerIntegrazione in cloud di Azure DatabricksLa Lakehouse Platform Azure Databricks offre il meglio di data lake e data warehouse su una piattaforma semplice, aperta e collaborativa che si integra in maniera sicura con i servizi Azure esistenti. Questa demo illustra molte delle integrazioni Azure Databricks pi\u00f9 comuni, fra cui Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI e altre.Maggiori informazioniIntegrazione di Databricks sul cloud AWSImplementazione di Databricks su Google CloudPartner ConnectSoluzioni per settori specificiDall'idea al progetto concettuale (Proof of Concept) in sole due settimaneGli Acceleratori Databricks sono guide specifiche \u2014 notebook con funzionalit\u00e0 complete e best practice \u2014 che velocizzano l'ottenimento di risultati. I clienti di Databricks risparmiano molte ore nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo, e molti di loro vanno dall'idea al \"proof of concept\" in sole due settimane.Scopri gli AcceleratoriCrea il tuo account Databricks1\/2NomeCognomeE-mail aziendaleAziendaTitolo professionaleTelefono (Optional)Si prega di selezionareNazioneCominciaProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/it\/trust?itm_data=menu-item-securitytrustcenter","text":"Security and Trust Center - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueSappiamo che i dati sono una delle risorse pi\u00f9 preziose e devono essere sempre protetti: per questo la sicurezza viene integrata in ogni livello della Databricks Lakehouse Platform. La nostra trasparenza consente di rispettare le normative, sfruttando nel contempo i vantaggi della piattaforma.Sappiamo che i dati sono una delle risorse pi\u00f9 preziose e devono essere sempre protetti: per questo la sicurezza viene integrata in ogni livello della Databricks Lakehouse Platform. La nostra trasparenza consente di rispettare le normative, sfruttando nel contempo i vantaggi della piattaforma.Piattaforma affidabileLa fiducia nasce dalla trasparenza. Scopri come proteggiamo la piattaforma con best practice di settore quali test di penetrazione, gestione delle vulnerabilit\u00e0 e sviluppo software sicuro per proteggere la Databricks Lakehouse Platform.Maggiori informazioniFunzionalit\u00e0 di sicurezzaForniamo funzionalit\u00e0 di sicurezza complete per proteggere dati e carichi di lavoro, ad esempio crittografia, controlli di rete, revisioni, integrazione di identit\u00e0, controllo di accessi e governance dei dati.Maggiori informazioniConformit\u00e0Clienti in tutto il mondo e in tutti i settori si affidano alla piattaforma lakehouse di Databricks. Abbiamo certificazioni e attestati che soddisfano le richieste di conformit\u00e0 specifiche dei settori pi\u00f9 regolamentati.Maggiori informazioniRiservatezzaDiamo valore alla riservatezza dei dati e sappiamo quanto sia importante per ogni organizzazione e per i suoi clienti. Databricks aiuta a rispettare le leggi sulla privacy e i requisiti normativi.Maggiori informazioniEsegui autonomamente una verifica di sicurezza di Databricks utilizzando il nostro pacchetto di due diligence, che comprende documentazione e materiali di conformit\u00e0.Pacchetto Due DiligenceProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
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{"source":"https:\/\/www.databricks.com\/glossary\/what-are-dataframes","text":"What are DataFrames?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDataFramesAll>DataFramesTry Databricks for freeGet StartedWhat is a DataFrame?A DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are a flexible and intuitive way of storing and working with data.Every DataFrame contains a blueprint, known as a schema, that defines the name and data type of each column. Spark DataFrames can contain universal data types like StringType and IntegerType, as well as data types that are specific to Spark, such as StructType. Missing or incomplete values are stored as null values in the DataFrame.A simple analogy is that a DataFrame is like a spreadsheet with named columns. However, the difference between them is that while a spreadsheet sits on one computer in one specific location, a DataFrame can span thousands of computers. In this way, DataFrames make it possible to do analytics on big data, using distributed computing clusters.The reason for putting the data on more than one computer should be intuitive: either the data is too large to fit on one machine or it would simply take too long to perform that computation on one machine.The concept of a DataFrame is common across many different languages and frameworks. DataFrames are the main data type used in pandas, the popular Python data analysis library, and DataFrames are also used in R, Scala, and other languages.Additional ResourcesDataFrames DocumentationBuilding a Feature Store around Dataframes and Apache SparkAnalyzing Your MLflow Data with DataFramesBack to GlossaryLearn what\u2019s driving the Lakehouse pattern.REGISTER NOWProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maxime-agostini\/#","text":"Maxime Agostini - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaxime AgostiniCEO at Sarus Technologies IncBack to speakersMaxime Agostini is cofounder and CEO of Sarus, a privacy company backed by YCombinator. Sarus lets organizations leverage confidential data for analytics and machine learning with privacy guarantees. Prior to Sarus, he was cofounder and CEO of AlephD, a marketing-tech company that he led until a successful acquisition by Verizon Media.\nMaxime graduated from Ecole Polytechnique in computer science and physics and has been developing and building data-driven businesses during his whole career.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sai-ravuru-0\/#","text":"Sai Ravuru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSai RavuruSenior Manager of Data Science & Analytics at JetBlueBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/avanade-intelligent-health","text":"Intelligent Healthcare on Azure Databricks by Avanade | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionIntelligent Healthcare on Azure Databricks by AvanadeIndustry-specific solution developed by Avanade and powered by the Databricks Lakehouse PlatformGet startedEnd-to-end solution built around the HL7 FHIR specification on AzureThe Databricks Lakehouse Platform lets health providers map and interact with patients throughout the entire patient lifecycle. Intelligent Health on Azure Databricks, created by Avanade, enables providers to meet current patient trends while improving efficiencies to overcome resource constraints. With Intelligent Health, you can:Improve patient experiences and health outcomes with personalized patient journeys and access to careEnhance care team productivity with continuous and coordinated care team collaborationAccess rich data, gathered across the patient lifecycle, to drive interoperability and provide enhanced insights at scale using analytics and AIGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vadivel-selvaraj","text":"Vadivel Selvaraj - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVadivel SelvarajStaff Software Engineer at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-harris","text":"Ryan Harris - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan HarrisPrincipal Cybersecurity Engineer at HSBCBack to speakersRyan Harris is a Principal Cybersecurity Engineer on the Global Cybersecurity Science & Analytics Team at HSBC, focusing on transforming cybersecurity into a data-driven organization by designing and building a secure cloud-native environment to analyze petabytes of security data. For over 20 years he has leveraged data to disrupt financial services threat actors, preventing $100M+ in fraud. He served as a Captain in the USAF, and has a degree in Cognitive Science & Computer Science from UVa.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rekha-bachwani\/#","text":"Rekha Bachwani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRekha BachwaniEngineering Director, ML Engineering at The Walt Disney CompanyBack to speakersRekha Bachwani is an Engineering Director at Disney Streaming. She leads the ML Engineering team that drives the strategy for ML infrastructure, platform and applications for the services and engineering organization. She has a PhD in Computer Science from Rutgers University, and worked at Netflix and Intel Labs prior to joining Disney.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rakesh-singh\/#","text":"Rakesh Singh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRakesh SinghLead Architect at ABN AMRO Bank N.VBack to speakersLead Solution Architect and responsible for designing a future-proof data platform for ABN AMRO BankLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/simon-whiteley\/#","text":"Simon Whiteley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSimon WhiteleyCTO at Advancing AnalyticsBack to speakersSimon is a Databricks Beacon, Microsoft MVP and owner of Advancing Analytics. A deep techie with a focus on emerging cloud technologies and applying \u201cbig data\u201d thinking to traditional analytics problems, Simon also has a passion for bringing it back to the high level and making sense of the bigger picture. When not tinkering with tech, Simon is a death-dodging London cyclist, a sampler of craft beers, an avid chef, and a generally nerdy person.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/databricks-sql","text":"Databricks SQL Demo: Lightning-Fast Analytics | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks SQL DemoGet started for freeDatabricks SQL is the serverless data warehouse on the Lakehouse, providing up to 12x better price\/performance than other cloud data warehouses.See full list of demosTake a deeper dive on Databricks SQLLearn moreLearn moreVideo transcriptDatabricks SQL demo overview\nHello everyone, as you heard, the lakehouse is the best data warehouse because it combines data warehouse\u2019s speeds with the data lake\u2019s scale and flexibility. In this demo, I\u2019ll show you how data teams can use Databricks SQL, a serverless data warehouse on the Databricks Lakehouse Platform to analyze revenue trends for a large multinational company.Collapse full transcriptExpand full transcriptCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/contact","text":"Contact Us - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContact usNeed assistance with training or support? See these additional resources.DocumentationRead technical documentation for Databricks on AWS, Azure or Google CloudDatabricks CommunityDiscuss, share and network with Databricks users and expertsTrainingMaster the Databricks Lakehouse Platform with instructor-led and self-paced training or become a certified developerSupportAlready a customer? Click here if you are encountering a technical or payment issueOur office locationsSee all our office locations globally and get in touchKnowledge baseFind quick answers to the most frequently asked questions about Databricks products and servicesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-thompson\/#","text":"Justin Thompson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin ThompsonDirector, IT Data and Analytics at JetBlueBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/about-us","text":"\u00dcber Databricks, ein von den urspr\u00fcnglichen Entwicklern von Apache Spark\u2122 gegr\u00fcndetes UnternehmenSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks ist das Lakehouse-UnternehmenDatabricks hat seinen Ursprung im akademischen Umfeld und in der Open-Source-Community und wurde 2013 von den Originalentwicklern von Apache Spark\u2122, Delta Lake und MLflow gegr\u00fcndet. Als weltweit erste und einzige Lakehouse-Plattform in der Cloud kombiniert Databricks das Beste aus Data Warehouses und Data Lakes und stellt eine offene und einheitliche Plattform f\u00fcr Daten und KI zur Verf\u00fcgung.\n\u00a0Lakehouse-Plattform kennenlernenZurzeit nehmen mehr als 7.000\u00a0Unternehmen weltweit \u2013 darunter ABN AMRO, Cond\u00e9 Nast, Regeneron und Shell \u2013 die Leistungen von Databricks in Anspruch, um Data Engineering in riesigen Ausma\u00dfen, kollaborative Data Science, den gesamten Lebenszyklus des Machine Learning und Business Analytics zu implementieren.\nMit seinem Hauptsitz in San Francisco, Niederlassungen auf der ganzen Welt und gemeinsam mit Hunderten internationaler Partner wie etwa Microsoft, Amazon, Tableau, Informatica, Cap Gemini und Booz Allen Hamilton verfolgt Databricks das Ziel, Daten und KI zu vereinfachen und zu demokratisieren und so Datenteams bei der L\u00f6sung der schwierigsten Probleme der Menschheit zu unterst\u00fctzen.Kundenberichte erkundenPartner anzeigenUnsere KundenAlle Kunden anzeigen\nUnsere Gesch\u00e4ftsleitungLeitungsteamF\u00fchrungskr\u00e4fte kennenlernenGr\u00fcnderUnsere Gr\u00fcnder kennenlernenVorstandUnseren Vorstand kennenlernenUnsere AnlegerProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ashwin-gangadhar\/#","text":"Ashwin Gangadhar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAshwin GangadharSenior Solutions Architect at MongoDBBack to speakersAshwin is a Senior Solutions architect with MongoDB based in Bangalore India. He has 7+ years of experience in building data driven applications, involving complex architectural and scalability requirements in diverse industries. He has worked extensively in providing solutions for Search relevancy building and delivering solutions in ML \/ NLP modeling, data processing\/data mining pipelines.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/partnerconnect","text":"Partner Connect | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner ConnectEasily discover and integrate data, analytics and AI solutions with your lakehouseWatch demosPartner Connect makes it easy for you to discover data, analytics and AI tools directly within the Databricks platform \u2014 and quickly integrate the tools you already use today. With Partner Connect, you can simplify tool integration to just a few clicks and rapidly expand the capabilities of your lakehouse.Connect your data and AI tools to the lakehouseEasily connect your preferred data and AI tools to the lakehouse and power any analytics use caseDiscover validated data and AI solutions for new use casesA one-stop portal for validated partner solutions so you can build your next data application fasterSet up in a few clicks with pre-built integrationsPartner Connect simplifies your integrations by automatically configuring resources \u2014 including clusters, tokens and connection files \u2014 to connect with partner solutionsGet started as a partnerDatabricks partners are uniquely positioned to deliver faster analytics insights for customers. Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partner\u201cBuilding on our longtime partnership, Partner Connect enables us to design an integrated experience between our companies and customers. With Partner Connect, we\u2019re delivering a streamlined experience that makes it easier than ever for the thousands of Databricks customers, whether they use Fivetran today or discover us through Partner Connect, to unlock insights in their data, discover more analytics use cases, and get value from their lakehouse faster by easily connecting hundreds of data sources to their lakehouse.\u201d\u2014 George Fraser, CEO at FivetranDemosFivetranConnect data from 180+ popular apps, including SaaS apps (Salesforce, Google Analytics, etc.) into the lakehousedbtGet started with dbt Cloud and Databricks to build data transformationsPower BIBring the advantages of Databricks Lakehouse performance and technology to all your usersTableauEmpower all users with a data lakehouse for modern analytics by connecting Tableau Desktop to Databricks SQLRiverySimplify the data journey from ingestion to transformation and delivery into Delta LakeLabelboxEasily prepare unstructured data for AI and Analytics in the LakehouseProphecyBuild and deploy Spark and Delta pipelines using a visual drag-and-drop interfaceArcionConnect data sources to the lakehouse with a distributed CDC-based replication platformTry for freeResourcesBlogFeb 2023 \u2013 Announcing New Partner Integrations in Partner ConnectSept 2022 \u2013 Introducing New Partner Integrations in Partner ConnectJune 2022 \u2013 Announcing New Partner Integrations in Partner ConnectBuild Your Business on Databricks With Partner ConnectDocumentationDatabricks Partner Connect guideReady to learn more?Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partnerContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mani-kandasamy","text":"Mani Kandasamy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMani KandasamyTech Fellow at Deloitte Consulting LLPBack to speakersMani is a technology executive with Deloitte Consulting LLP and leads @Scale cloud data modernization and analytics solutions for a global portfolio of Deloitte's clients. \nHe is a highly sought and trusted technical advisor, conference speaker, and passionate about helping the clients transform continually leveraging emerging and niche technologies to achieve greater business benefits.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/acid-transactions","text":"What are ACID Transactions?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWACID TransactionsAll>ACID TransactionsWhat is a transaction?In the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a consistent state. The classic example of a transaction is what occurs when you withdraw money from your bank account. Either the money has left your bank account, or it has not \u2014 there cannot be an in-between state. A.C.I.D. properties: Atomicity, Consistency, Isolation, and DurabilityACID is an acronym that refers to the set of 4 key properties that define a transaction: Atomicity, Consistency, Isolation, and Durability. If a database operation has these ACID properties, it can be called an ACID transaction, and data storage systems that apply these operations are called transactional systems. ACID transactions guarantee that each read, write, or modification of a table has the following properties:Atomicity - each statement in a transaction (to read, write, update or delete data) is treated as a single unit. Either the entire statement is executed, or none of it is executed. This property prevents data loss and corruption from occurring if, for example, if your streaming data source fails mid-stream.Consistency - ensures that transactions only make changes to tables in predefined, predictable ways. Transactional consistency ensures that corruption or errors in your data do not create unintended consequences for the integrity of your table.Isolation - when multiple users are reading and writing from the same table all at once, isolation of their transactions ensures that the concurrent transactions don't interfere with or affect one another. Each request can occur as though they were occurring one by one, even though they're actually occurring simultaneously.Durability - ensures that changes to your data made by successfully executed transactions will be saved, even in the event of system failure.Why are ACID transactions a good thing to have?ACID transactions ensure the highest possible data reliability and integrity. They ensure that your data never falls into an inconsistent state because of an operation that only partially completes. For example, without ACID transactions, if you were writing some data to a database table, but the power went out unexpectedly, it's possible that only some of your data would have been saved, while some of it would not. Now your database is in an inconsistent state that is very difficult and time-consuming to recover from.Delta Lake: Reliable, consistent data with the guarantees of ACID transactionsACID transactions have long been one of the most enviable properties of data warehouses, but Delta Lake has now brought them to data lakes. They allow users to see consistent views of their data even while new data is being written to the table in real-time, because each write is an isolated transaction that is recorded in an ordered transaction log. [Delta Lake employs the highest level of isolation possible (serializable isolation), ensuring that reads and writes to a single table are consistent and reliable.] By implementing ACID transactions, Delta Lake effectively solves for several of the previously listed criticisms of Lambda architecture: its complexity, incorrect views of data, and the rework and reprocessing needed after Lambda pipelines inevitably break. Users can perform multiple concurrent transactions on their data, and in the event of an error with a data source or a stream, Delta Lake cancels execution of the transaction to ensure that the data is kept clean and intact. The beauty of ACID transactions is that users can trust the data that is stored in Delta Lake. A data analyst making use of Delta Lake tables to perform ETL on his or her data to ready it for dashboarding can count on the fact that the KPIs he or she is seeing represent the actual state of the data. A machine learning engineer using Delta Lake tables to perform feature engineering can be 100% confident that all of his or her transformations and aggregations either executed exactly as intended, or didn't execute at all (in which case, he or she would be notified). The value of knowing that the mental model you have of your data is actually reflective of its true underlying state cannot be overstated.Additional ResourcesDelta Lake on Databricks DemoACID Transactions on Data Lakes Tech Talks: Getting Started with Delta LakeDelta Lake Product PageDelta Lake Cheat SheetBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dawn-song\/#","text":"Dawn Song - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDawn SongProfessor, Department of Electrical Engineering and Computer Science at UC BerkeleyBack to speakersDawn Song is a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley and co-Director of Berkeley Center on Responsible Decentralized Intelligence. Her research interest lies in AI and deep learning, security and privacy, and blockchain. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, ACM SIGSAC Outstanding Innovation Award, and numerous Test-of-Time Awards and Best Paper Awards from top conferences in Computer Security and Deep Learning. She is an ACM Fellow and an IEEE Fellow. She is ranked the most cited scholar in computer security (AMiner Award). She obtained her Ph.D. degree from UC Berkeley. She is also a serial entrepreneur and has been named on the Female Founder 100 List by Inc. and Wired25 List of Innovators.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lindsay-mico\/#","text":"Lindsay Mico - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLindsay MicoHead of Data Science at Providence HealthBack to speakersLindsay Mico is the Head of Data Science for Providence, with a focus on enterprise scale AI solutions and cloud native architectures. Originally trained as a cognitive neuroscientist and statistician, he has worked across industries including natural resource management, telecom, and healthcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-keller\/#","text":"Jonathan Keller - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan KellerSr. Director, Product Management at DatabricksBack to speakersJonathan leads Product Management for data governance at Databricks, including Unity Catalog and Delta Sharing. He was previously Director of Product Management for Google Cloud\u2019s BigQuery team, after almost 20 years at Microsoft in various roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/05\/26\/introducing-delta-sharing-an-open-protocol-for-secure-data-sharing.html","text":"Introducing Delta Sharing: an Open Protocol for Secure Data Sharing - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Delta Sharing: An Open Protocol for Secure Data Sharingby Matei Zaharia, Michael Armbrust, Steve Weis, Todd Greenstein and Cyrielle SimeoneMay 26, 2021 in AnnouncementsShare this postUpdate:\u00a0Delta Sharing is now generally available on AWS and Azure.Get an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake.\u00a0Data sharing has become critical in the modern economy as enterprises look to securely exchange data with their customers, suppliers and partners. For example, a retailer may want to publish sales data to its suppliers in real time, or a supplier may want to share real-time inventory. But so far, data sharing has been severely limited because sharing solutions are tied to a single vendor. This creates friction for both data providers and consumers, who naturally run different platforms.Today, we\u2019re launching a new open source project that simplifies cross-organization sharing: Delta Sharing, an open protocol for secure real-time exchange of large datasets, which enables secure data sharing across products for the first time. We\u2019re developing Delta Sharing with partners at the top software and data providers in the world.To see why today\u2019s data sharing solutions create friction, consider a retailer that wants to share data with an analyst at one of its suppliers. Today, the retailer could use one of several cloud data warehouses that offer data sharing, but then the analyst would need to work with their IT, security, and procurement teams to deploy the same warehouse product at their company, a process that can take months. Furthermore, once the warehouse is deployed, the first thing the analyst would do is export the data from it into their favorite data science tool, such as pandas or Tableau.With Delta Sharing, data users can directly connect to the shared data through pandas, Tableau, or dozens of other systems that implement the open protocol, without having to deploy a specific platform first. This reduces their access time from months to minutes, and greatly reduces work for data providers who want to reach as many users as possible.We\u2019re working with a vibrant ecosystem of partners on Delta Sharing, including product teams at the leading cloud, BI and data vendors:In this post, we\u2019ll explain how Delta Sharing works and why we\u2019re so excited about an open approach to data sharing.Delta Sharing goalsDelta Sharing is designed to be easy for both providers and consumers to use with their existing data and workflows. We designed it with four goals in mind:Share live data directly without copying it: We want to make it easy to share existing data in real time. Today, the majority of enterprise data is stored in cloud data lake and lakehouse systems. Delta Sharing works over these; in particular, it lets you securely share any existing dataset in the Delta Lake or Apache Parquet formats.Support a wide range of clients: Recipients should be able to directly consume data from their tools of choice without installing a new platform. The Delta Sharing protocol is designed to be easy for tools to support directly. It\u2019s based on Parquet, which most tools already support, so implementing a connector for it is easy.Strong security, auditing and governance: The protocol is designed to help you meet privacy and compliance requirements. Delta Sharing lets you grant, track and audit access to shared data from a single point of enforcement.Scale to massive datasets: Data sharing increasingly needs to support terabyte-scale datasets, such as fine-grained industrial or financial data, a challenge for legacy solutions. Delta Sharing leverages the cost and elasticity of cloud storage systems to share massive datasets economically and reliably.How does Delta Sharing work?Delta Sharing is a simple REST protocol that securely shares access to part of a cloud dataset. It leverages modern cloud storage systems, such as S3, ADLS or GCS, to reliably transfer large datasets. There are two parties involved: Data Providers and Recipients.As the Data Provider, Delta Sharing lets you share existing tables or parts thereof (e.g., specific table versions of partitions) stored on your cloud data lake in Delta Lake format. A Delta Lake table is essentially a collection of Parquet files, and it's easy to wrap existing Parquet tables into Delta Lake if needed. The data provider decides what data they want to share and runs a sharing server in front of it that implements the Delta Sharing protocol and manages access for recipients. We\u2019ve open sourced a reference sharing server; and we provide a hosted one on Databricks, as we imagine other vendors will.As a Data Recipient, all you need is one of the many Delta Sharing clients that supports the protocol. We\u2019ve released open source connectors for pandas, Apache Spark, Rust and Python, and we\u2019re working with partners on many more.The actual exchange is carefully designed to be efficient by leveraging the functionality of cloud storage systems and Delta Lake. The protocol works as follows:The recipient\u2019s client authenticates to the sharing server (via a bearer token or other method) and asks to query a specific table. The client can also provide filters on the data (e.g. \u201ccountry=US\u201d) as a hint to read just a subset of the data.The server verifies whether the client is allowed to access the data, logs the request, and then determines which data to send back. This will be a subset of the data objects in S3 or other cloud storage systems that actually make up the table.To transfer the data, the server generates short-lived pre-signed URLs that allow the client to read these Parquet files directly from the cloud provider, so that the transfer can happen in parallel at massive bandwidth, without streaming through the sharing server. This powerful feature available in all the major clouds makes it fast, cheap and reliable to share very large datasets.Benefits of the designThe Delta Sharing design provides many benefits for both providers and consumers:Data Providers can easily share an entire table, or just one version or partition of the table, because clients are only given access to a specific subset of the objects in it.Data Providers can update data reliably in real time using the ACID transactions on Delta Lake, and recipients will always see a consistent view.Data Recipients don\u2019t need to be on the same platform as the provider, or even in the cloud at all -- sharing works across clouds and even from cloud to on-premise users.The Delta Sharing protocol is very easy for clients to implement if they already understand Parquet. Most of our prototype implementations with open source engines and BI tools only took 1-2 weeks to build.Transfer is fast, cheap, reliable and parallelizable using the underlying cloud system.An open ecosystemAs previously mentioned, we are excited about establishing an open approach to data sharing. Data providers, like Nasdaq, have uniformly told us that it is too hard to deliver data to diverse consumers, all of which use different analytics tools.\n\"We support Delta Sharing and its vision of an open protocol that will simplify secure data sharing and collaboration across organizations. Delta Sharing will enhance the way we work with our partners, reduce operational costs and enable more users to access a comprehensive range of Nasdaq\u2019s data suite to discover insights and develop financial strategies,\u201d said Bill Dague, Head of Alternative Data, Nasdaq.\nWith Delta Sharing, dozens of popular systems will be able to connect directly to shared data so that any user can use it, reducing friction for all participants. We are working with dozens of partners to define the Delta Sharing standard, and we invite you to participate.\nMany of these companies extended their support for today\u2019s launch:BI Tools: Tableau, Qlik, Power BI, LookerAnalytics: AtScale, Dremio, Starburst, Microsoft Azure, Google BigQueryGovernance: Collibra, Immuta, Alation, PrivaceraData Providers: FactSet, Nasdaq, Precisely, Safegraph, Atlassian, AWS, Foursquare, ICE, Qandl, S&P, SequenceBioDelta Sharing on DatabricksDatabricks customers will have a native integration of Delta Sharing in our Unity Catalog, providing a streamlined experience for sharing data both within and across organizations. Administrators will be able to manage shares using a new CREATE SHARE SQL syntax or REST APIs and audit all accesses centrally. Recipients will be able to consume the data from any platform. Sign up to join our waitlist for preview access and updates.RoadmapThis first version of Delta Sharing is just a start. As we develop the project, we plan to extend it to sharing other objects, such as streams, SQL views or arbitrary files like machine learning models. We believe that the future of data sharing is open, and we are thrilled to bring this approach to other sharing workflows.Getting started with Delta SharingTo try the open source Delta Sharing release, follow the instructions at delta.io\/sharing. Or, if you are a Databricks customer, sign up for updates on our service. We are very excited to hear your feedback!To play this video, click here and accept cookiesTry Databricks for freeGet StartedRelated postsIntroducing Delta Sharing: An Open Protocol for Secure Data SharingMay 26, 2021 by Matei Zaharia, Michael Armbrust, Steve Weis, Todd Greenstein and Cyrielle Simeone in Announcements\nUpdate: Delta Sharing is now generally available on AWS and Azure. Get an early preview of O'Reilly's new ebook for the step-by-step guidance...\nSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/unity-catalog","text":"Unity Catalog | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWUnity CatalogGovernance unificata per dati, analisi e AI\n\u00a0CominciaGuarda la demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowUnity Catalog \u00e8 una soluzione di governance unificata per tutte le risorse di dati, inclusi file, tabelle, modelli di machine learning e dashboard, presenti nel lakehouse aziendale su qualsiasi cloud.Governance centralizzata per dati e AIUn modello di governance comune basato su ANSI SQL consente di gestire centralmente file, tabelle, dashboard e modelli ML su qualsiasi cloud.Ricerca e scoperta di dati incorporateGli utenti possono ricercare, comprendere e fare riferimento ai dati presenti in tutta l'organizzazione, aumentando la produttivit\u00e0.Prestazioni e scalabilit\u00e0Le prestazioni delle query vengono migliorate grazie alla fornitura di dati con bassa latenza e al perfezionamento automatico (auto-tuning) delle tabelle.Provenienza automatizzata di tutti i carichi di lavoroCrea una vista unificata e trasparente dell'intero ecosistema di dati, con la provenienza automatizzata e dettagliata di tutti i carichi di lavoro in SQL, R, Python, Scala e per tutti i tipi di risorse: tabelle, notebook, flussi di lavoro e dashboard.Integrazione con strumenti esistentiPredisponi la governance di dati e AI per il futuro, con la flessibilit\u00e0 di poter sfruttare le soluzioni esistenti di catalogazione e governance dei dati.Come funzionaGestione e governance centralizzate del patrimonio di datiUn modello di governance comune basato sullo standard aperto ANSI SQL consente di semplificare la governance di file, tabelle, dashboard e modelli ML su qualsiasi cloud. Le politiche di accessi possono essere definite una sola volta a livello di account e poi applicate a tutti i carichi e gli spazi di lavoro. Unity Catalog consente inoltre revisioni granulari centralizzate attraverso l'acquisizione di un registro delle operazioni svolte sui dati, aiutando a rispettare i requisiti di conformit\u00e0 e audit.\u00a0Gestire il controllo granulare degli accessiL'uso di funzioni SQL standard consente di definire filtri e maschere di colonne per controllare in modo granulare l'accesso a righe e colonne. Mentre Databricks continua a sviluppare funzionalit\u00e0 per migliorare la scalabilit\u00e0 e l'integrazione, i controlli di accesso basati su attributi, che verranno introdotti a breve, consentiranno di definire politiche di accesso basate su tag personalizzati (attributi).Esperienza di ricerca dei dati unificata e sicuraGli utenti possono trovare, comprendere e fare riferimento a dati rilevanti su tutto il patrimonio di dati, con un'esperienza di ricerca unificata per analisti, data engineer e data scientist. La ricerca di dati in Unity Catalog \u00e8 sicura per definizione, poich\u00e9 i risultati delle ricerche sono limitati in base ai privilegi di accesso di ciascun utente, con un ulteriore livello di sicurezza per la privacy.Prestazioni di query migliorate per qualsiasi volume di datiUnity Catalog migliora le prestazioni delle query grazie alla fornitura di dati con bassa latenza e al perfezionamento automatico (auto-tuning) delle tabelle, velocizzando l'esecuzione delle query su qualsiasi volume di dati. La compattazione automatica asincrona dei dati ottimizza le dimensioni dei file e riduce automaticamente la latenza di input\/output (I\/O) in background.Provenienza dei dati automatizzata in tempo realeOttieni visibilit\u00e0 a 360 gradi sui flussi di dati in ingresso nel lakehouse, con provenienza automatizzata in tempo reale per tutti i carichi di lavoro in SQL, Python, Scala e R. Esegui velocemente controlli di qualit\u00e0 dei dati e analisi complete dell'impatto delle modifiche ai dati, e correggi eventuali errori nelle pipeline di dati. Sfrutta i vantaggi della provenienza dei dati su tabelle, colonne, notebook, flussi di lavoro e dashboard. I grafici della provenienza in Unity Catalog tengono conto dei privilegi, limitando l'accesso in base alle autorizzazioni di ciascun utente. La provenienza pu\u00f2 essere recuperata anche attraverso API REST per supportare integrazioni con altri cataloghi.Condivisione dei dati protetta fra diverse organizzazioniUnity Catalog supporta in modo nativo Delta Sharing, il primo protocollo aperto al mondo per la condivisione sicura di dati, che consente di condividere facilmente dati esistenti nei formati Delta Lake e Apache Parquet con qualsiasi piattaforma di calcolo. I consumatori non devono operare necessariamente sulla piattaforma Databricks o sullo stesso cloud, e nemmeno su un cloud. I dati possono essere condivisi direttamente, senza bisogno di replicarli o copiarli su altri sistemi. Le integrazioni native con Power BI, Tableau, Spark, pandas e Java consentono ai destinatari di consumare dati condivisi direttamente dai loro strumenti preferiti. L'utilizzo dei dati condivisi pu\u00f2 essere gestito, governato, revisionato e tracciato centralmente su un'unica piattaforma.Integrazioni perfette con gli strumenti esistentiUnity Catalog funziona con i cataloghi di dati, i sistemi di archiviazione dei dati e le soluzioni di governance esistenti in modo da poter sfruttare gli investimenti esistenti e creare un modello di governance a prova di futuro senza costosi costi di migrazione.Stoccaggio dati e cloudPartner di governance e catalogazione dei datiClientela\u201cUnity Catalog ci ha aiutato a semplificare la gestione dei dati e i controlli di accesso in tutta l'azienda. Il team di gestione dei dati di Compass ha portato a bordo in piena sicurezza oltre 100 sorgenti di dati, ha migrato tutti gli spazi di lavoro su Unity Catalog e ha creato un livello Gold a cui tutte le figure interessate possono accedere, attingendo a informazioni approfondite su clienti, utilizzo, ricavi e altro ancora: un'unica fonte della verit\u00e0 con controlli di accesso completi per tutta l'azienda.\u201d\u2014 Rajesh Nagpal, Senior Director of Data Engineering\u201cUnity Catalog ha semplificato notevolmente l'implementazione del controllo degli accessi per ruoli, consentendoci di proteggere i dati a livello di catalogo, database, tabella e colonna. Offriamo il livello di accesso adeguato a ogni utente e possiamo gestire e proteggere l'accesso ai dati nel rispetto delle nostre rigorose politiche di conformit\u00e0 e riservatezza.\u201d\u2014 Chris Locklin, Engineering Manager of Data Platforms, Grammarly\u201cUnity Catalog ha consentito a Milliman di mettere a disposizione di tutti i suoi utenti il suo patrimonio di dati in continua espansione, semplificando la gestione degli accessi e riducendo la complessit\u00e0 dello storage. Grazie a Unity Catalog, Milliman pu\u00f2 rispettare rigorosi standard sanitari, esplorare i dati in modo collaborativo e ridurre la complessit\u00e0 dello storage. Con Unity Catalog possiamo dimensionare velocemente il sistema in base alle esigenze dei nostri clienti.\u201d\u2014 Dan McCurley, Cloud Solutions Architect, Milliman\u201cUnity Catalog ci consente di costruire una piattaforma di prossima generazione che sfrutta tutto il potenziale di veicoli definiti da software, che si evolvono e migliorano accumulando chilometri, migliorando l'esperienza di guida dei clienti e massimizzando i benefici ambientali della mobilit\u00e0 elettrica. Abbiamo centralizzato il data catalog e la gestione degli accessi per diversi team e spazi di lavoro, aprendoci opportunit\u00e0 di collaborazione e innovazione senza precedenti.\"\u2014 Venkat Sivasubramanian, Senior Director, Big Data\u201cUnity Catalog ha rappresentato una vera e propria svolta. I nostri analisti possono accedere a tabelle esterne AWS in tempo reale negli spazi di lavoro di Databricks e unirle con tabelle Delta Lake. In questo modo possiamo avere i vantaggi in termini di prestazioni di Databricks SQL senza dover migrare le tabelle Glue. Con Unity Catalog, diversi team possono collaborare senza spostare i dati da un posto all'altro.\u201d\u2014 Rajat Gupta, Engineering Manager, Warner Bros. DiscoveryRisorseIntervento principale e webinar[Intervento principale]Governance e condivisione dei dati sul lakehouse al Data + AI Summit 2022[Webinar on-demand]Come semplificare la governance di dati e AIe-book e blog[e-book] Governance di dati, analisi e AIAnnuncio della disponibilit\u00e0 generale della provenienza dei dati in Unity CatalogAnnuncio della disponibilit\u00e0 della provenienza dei dati in Unity CatalogPresentazione del catalogo di Databricks Unity: governance finanziaria per i dati e l'IA sul LakehouseDocumentazioneDocumentazione AWSDocumentazione AzurePronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/jp\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Databricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb | DatabricksDatabricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebDatabricks \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u5168\u6a5f\u80fd\u3092 14 \u65e5\u9593\u7121\u6599\u3067\u304a\u8a66\u3057\u3044\u305f\u3060\u3051\u307e\u3059\u3002AWS\u3001Microsoft Azure\u3001Google Cloud \u306e\u3044\u305a\u308c\u304b\u3092\u304a\u9078\u3073\u304f\u3060\u3055\u3044\u3002\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3001ETL \u3092\u81ea\u52d5\u5316\u6570\u767e\u306b\u304a\u3088\u3076\u30bd\u30fc\u30b9\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3068\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308b\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u4efb\u610f\u306e\u8a00\u8a9e\u3067\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032Python\u3001R\u3001Scala\u3001SQL \u306b\u3088\u308b\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u304c\u53ef\u80fd\u3067\u3059\u3002\u5171\u540c\u7de8\u96c6\u3001\u81ea\u52d5\u30d0\u30fc\u30b8\u30e7\u30f3\u7ba1\u7406\u3001Git \u7d71\u5408\u3001RBAC \u3082\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e 12 \u500d\u306e\u4fa1\u683c\u6027\u80fdDatabricks \u306f\u3001\u4e16\u754c 7000 \u793e\u4ee5\u4e0a\u306e\u304a\u5ba2\u69d8\u306b\u63a1\u7528\u3055\u308c\u3001BI \u3084 AI \u306e\u3042\u3089\u3086\u308b\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002Databricks \u30a2\u30ab\u30a6\u30f3\u30c8\u3092\u4f5c\u6210\u3059\u308b1\/2\u304a\u540d\u524d\uff08\u59d3)\u304a\u540d\u524d\uff08\u540d)\u696d\u52d9\u7528\u30e1\u30fc\u30eb\u30a2\u30c9\u30ec\u30b9\u4f01\u696d\uff0f\u56e3\u4f53\u540d\u5f79\u8077\u540d\u96fb\u8a71\u756a\u53f7\uff08\u4efb\u610f)\u9078\u629e\u3057\u3066\u304f\u3060\u3055\u3044\u56fd\u540d\u9001\u4fe1\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5 (\u66f4\u65b0)\u5229\u7528\u898f\u7d04\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/todd-greenstein","text":"Todd Greenstein - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTodd GreensteinProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/corey-zwart\/#","text":"Corey Zwart - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCorey ZwartChief Technology Officer at PumpJack DataworksBack to speakersCorey is an accomplished DevOps Engineer and Cloud Architect, consistently recognized for his reliability, dependability, & integrity in achieving technical outcomes. Corey serves as the Chief Technology Officer for Pumpjack Dataworks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=home-navmenu-platform-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jon-osborn\/#","text":"Jon Osborn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJon OsbornField CTO at Ascend.ioBack to speakersJon Osborn is an experienced technology executive (CDAO, VP) with deep management & development experience using cloud native solutions for agile data delivery. He is passionate about building high performance teams & zero impedance paths to production for both data & apps. With his background and track record of success, he excels at defining the combinations of business justification, executive support, mindset shift, & cultural changes required to drive a winning data modernization strategy.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/audience\/digital-native","text":"Digital Native Business and Applications | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLakehouse for companies born in the cloudBuild and scale data, analytics and AI capabilities faster on one high-performing data platform\nGet startedWatch demosThe faster you grow, the more complex your data gets. Innovate faster on the Databricks Lakehouse Platform \u2014 a simple, cost-efficient approach to data, analytics and AI making thousands of digital native businesses and startups more productive.Innovate with open source flexibility\nUse your data however and wherever you want \u2014 no vendor lock-in. Apache Spark\u2122 developers created the lakehouse with open formats and APIs.\nSee open source projectsBuild scalable data workloads\nEnsure reliable, lightning-fast performance on ETL workloads \u2014 for streaming and batch data \u2014 while Databricks automatically manages your infrastructure.\nSee data engineeringAccess data insights faster\nIngest, transform and query all your data in one place. Stop managing servers and scale on demand with serverless. Up to 12x better price\/performance.\nSee Databricks SQLDevelop next-gen apps with ML\nSpeed up your ML lifecycle from experimentation to production. Boost productivity with tools like collaborative notebooks, MLflow and MLOps.\nSee ML capabilitiesGetting started with DatabricksTry Databricks\nStart your 14-day free trial with Databricks on AWS in a few easy steps. Find resources for you and your entire data team.\nGet started freeBuild your skills\nAccess training and certification tailored to your needs, including data analytics, data engineering, data science and machine learning.\nGet trainingOptimize costs\nReduce infrastructure costs by up to 40% and increase productivity with a managed service. Check out our pay-as-you-go billing and discounted plans.\nSee pricingTechnical support\nFind answers faster with help from our Databricks experts. Plus, you can develop your data solution quickly with our self-service notebooks.\nSee notebooksBuilt on ProgramsBuild your data-driven applications on the lakehouse and accelerate your business growth with DatabricksDatabricks for StartupsGet started quickly with the startup program. Discover how to get free credits, expert advice and go-to-market support.Learn moreBuilt on Partners\u00a0Become a built on partner to gain access to technical, go-to-market, and co-marketing benefits to help scale your reach and grow your business.Learn moreNext-generation businesses built on DatabricksSolution architectures for digital native businessesHigh-performing, scalable ETL pipelinesBuild an end-to-end data engineering and ETL platform that lets you focus on delivering valuable insights on any cloud. No more building and maintaining pipelines or running ETL workloads.Leverage production-ready tools including Delta Live Tables, Unity Catalog and Workflows.Enjoy robust Git integration, orchestration and data quality controls.Unify batch and streaming operations on a simplified architecture, and streamline data pipeline development and testing.Ensure data quality and enhanced data skipping with Delta Lake \u2014 an open source file protocol usable by Apache Spark, Trino, Presto, Flink and more.Get startedSQL analytics and data warehousingEasily ingest, transform and query all your data in one place to deliver real-time business insights faster.Run all your SQL and BI applications at scale with up to 12x better price\/performance. Ensure data governance and security.Handle high concurrency with fully managed load balancing and scaling of compute resources.Leverage open formats and APIs, and the ingestion, transformation and BI tools of your choice with custom-built connectors.Reduce resource management overhead with serverless compute.Get startedInnovative machine learningAccelerate ML and data science by improving productivity and collaboration on the lakehouse.Leverage collaboration tools and options for glass-box AutoML.Prepare, process and manage data and features in a self-service manner \u2014 as well as manage models \u2014 and with a hosted Feature Store.Standardize the ML lifecycle from experimentation to production through MLflow to track model parameter, metrics and iterations over time.Deploy models in a batch or with serverless real-time REST endpoints.Get startedTechnology partners\nDiscover and integrate your favorite data and AI tools and services directly from the Databricks platform\nExplore Partner ConnectIndustry solutionsNext-generation industry leaders are building their data analytics and AI solutions with DatabricksExplore solutions by industryRetail and Consumer Goods\nDrive real-time decisions and stronger customer experiences.\nLearn moreFinancial Services\nPower your data and AI\u2013driven financial services for the future.\nLearn moreGaming\nHarness the power of data and AI to unlock next-level gaming experiences.\nLearn moreCommunications, Media & Entertainment\u00a0\nBuild data and AI-driven media for next-level user experience.\nLearn moreTechnology and Software\nDevelop next-generation solutions with advanced data and ML capabilities.\nLearn moreHealthcare Technology\nDeliver better patient outcomes with the power of data and AI.\nLearn moreTechnical guideSolving Common Data ChallengesFor Startups and Digital Native BusinessesLearn how to support data use cases as you scale while boosting cost efficiency and productivity. You\u2019ll benefit from architecture diagrams, step-by-step solutions and quickstart guides. You\u2019ll also find real-life use cases from leading companies such as Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable and Zipline.Get your copyResourceseBooksWhat Is a Lakehouse?The Big Book of Data EngineeringThe Big Book of Machine Learning Use CasesDefinitive Guide to Delta LakeDelta Lake: The Foundation to Your LakehouseThe Big Book of MLOpsThe Data Team\u2019s Guide to the Databricks Lakehouse PlatformQuickstart GuidesRun ETL WorkloadsData Pipelines With Delta Live TablesSQL Guide: Queries and DashboardsData Science QuickstartMachine Learning QuickstartBlogsAnnouncementsOpen SourceIndustry InsightsSolutionsReady to get started?Get free trialProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-rdd","text":"What is a Resilient Distributed Dataset (RDD)?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResilient Distributed Dataset (RDD)All>Resilient Distributed Dataset (RDD)Try Databricks for freeGet StartedRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API that offers transformations and actions.5 Reasons on When to use RDDsYou want low-level transformation and actions and control on your dataset;Your data is unstructured, such as media streams or streams of text;You want to manipulate your data with functional programming constructs than domain specific expressions;You don\u2019t care about imposing a schema, such as columnar format while processing or accessing data attributes by name or column; andYou can forgo some optimization and performance benefits available with DataFrames and Datasets for structured and semi-structured data.What happens to RDDs in Apache Spark 2.0?Are RDDs being relegated as second class citizens? Are they being deprecated? The answer is a resounding NO! What\u2019s more is you can seamlessly move between DataFrame or Dataset and RDDs at will\u2014by simple API method calls\u2014and DataFrames and Datasets are built on top of RDDs.To play this video, click here and accept cookiesAdditional ResourcesA Tale of Three Apache Spark APIs: RDDs vs DataFrames and DatasetsResilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing Research PaperBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pritesh-patel","text":"Pritesh Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPritesh PatelPublic Sector Leader, UK&I at DatabricksBack to speakersSales leader with years of experience in Public Sector and with passion to deliver citizen and social value through data and AI.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ryan-boyd","text":"Ryan Boyd - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan BoydCo-founder at MotherDuckBack to speakersRyan Boyd (LinkedIn) is a Boulder-based software engineer, data + authNZ geek and technology executive. He's currently a co-founder at MotherDuck, where they're making data analytics fun, frictionless and ducking awesome. He previously led developer relations teams at Databricks, Neo4j and Google Cloud. He's the author of O'Reilly's Getting Started with OAuth 2.0.Ryan advises B2B SaaS startups on growth marketing and developer relations as a Partner at Hypergrowth Partners. Prior to leading the Google Cloud Developer Relations team, he spent 7 years at Google working on 20+ different developer products and was the co-founder of Google Code Labs which aimed to improve quality and stability of Google's developer products.Ryan graduated with a degree in Computer Science from Rochester Institute of Technology (RIT) where he later worked full-time building web applications + APIs and architecting the central web hosting platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/diversity","text":"Diversit\u00e4t und Inklusion | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDie Zukunft der Daten steht allen offenDiversit\u00e4t, Gleichstellung und Inklusion bei DatabricksGesteuert von Daten. Umgesetzt durch Menschen.Wir haben es uns zum Ziel gesetzt, den Bereich Big Data zu diversifizieren\u00a0\u2013 angefangen bei unserem Team. Wir glauben, dass unterschiedliche Hintergr\u00fcnde, Erfahrungen, Perspektiven, Erkenntnisse und F\u00e4higkeiten Innovationen vorantreiben und unsere Verbindung untereinander und zu unseren Kunden vertiefen. Wir bem\u00fchen uns um eine Kultur der Zugeh\u00f6rigkeit, in der jeder in der Lage ist, beste Arbeit zu leisten. Diversit\u00e4t, Gleichstellung und Inklusion sind in allem, was wir tun, eingebunden: angefangen bei gleicher Bezahlung f\u00fcr gleiche Arbeit bis hin zur Entwicklung von Programmen, die alle unsere Teammitglieder willkommen hei\u00dfen, anerkennen, weiterbilden und f\u00f6rdern.Von Fair Pay Workplace zertifiziert\nWir sind stolz darauf, eine der ersten sechs von Fair Pay Workplace zertifizierten Unternehmen zu sein. Im Rahmen unserer Bem\u00fchungen um Lohngleichheit lie\u00df Databricks seine Lohndaten und -praktiken gr\u00fcndlich untersuchen und verpflichtete sich dazu, durch laufende Lohngleichstellungsanalysen weiterhin ein fairer Arbeitgeber zu bleiben.Gaingels und Flucas Ventures\nUnser Engagement f\u00fcr Diversit\u00e4t, Gleichstellung und Inklusion umfasst unser gesamtes Team\u00a0\u2013 von den Menschen, die mit uns zusammenarbeiten, bis hin zu den Menschen, die in uns investieren. Deshalb sind wir stolz darauf, mit einer Reihe von Weltklasse-Investoren zusammenzuarbeiten, darunter Gaingels und Flucas Ventures, die sich auf die Finanzierung von Unternehmen konzentrieren, die ein starkes Engagement f\u00fcr diese drei Aspekte zeigen.\u201eWir wissen, dass unsere Einblicke umso besser sind, je mehr Daten wir haben. Das Gleiche gilt f\u00fcr Diversit\u00e4t und Inklusion\u00a0\u2013 Databricks lebt davon, die gr\u00f6\u00dftm\u00f6gliche Vielfalt an Hintergr\u00fcnden, Erfahrungen und Sichtweisen einzubeziehen.\u201c\u2013 Ali Ghodsi, Mitbegr\u00fcnder und CEO von DatabricksUnsere CommunitysWir glauben, dass die M\u00f6glichkeiten unserer Mitarbeiter wesentlich dazu beitragen, unser volles Potenzial zu entfalten. Unsere dynamischen Employee Resource Groups (ERGs) sind von Mitarbeitern gef\u00fchrte Kollektive, die eine entscheidende Rolle f\u00fcr ein integratives und unterst\u00fctzendes Umfeld bei Databricks spielen. Diese diversen Communitys von Mitarbeitern und B\u00fcndnispartnern schaffen Raum f\u00fcr Verbindungen und vorbehaltlose Annahme. Au\u00dferdem sensibilisieren sie f\u00fcr wichtige Themen.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\nMeinungen unserer Mitarbeiter\u201eBei Databricks baue ich Teams auf, denen ich angeh\u00f6ren m\u00f6chte. Das bedeutet, die Sicherheit zu haben, mein authentisches Ich zu sein und allen um mich herum dieselbe Komfortzone zu bieten. Die Auswirkungen unserer F\u00fcrsorge f\u00fcreinander und unseres Engagements f\u00fcr Inklusion sind f\u00fcr unsere gesamte Community enorm.\u201c\u2013 Stacy Kerkela, Director of EngineeringWeiterlesen\u201eDas LatinX-Netzwerk bei Databricks gibt mir ein st\u00e4rkeres Community-Gef\u00fchl, das einer offenen Community, denn bei Databricks werden alle Menschen von unseren Employee Resource Groups (ERGs) willkommen gehei\u00dfen und weitergebildet\u00a0\u2013 unabh\u00e4ngig von ihrer Herkunft.\u201c\u2013 Miguel Peralvo, Senior Solutions ArchitectWeiterlesen\u201eViele Unternehmen bem\u00fchen sich um mehr geschlechtsspezifische Diversit\u00e4t, aber Teil eines Unternehmens zu sein, das sichtbar Ma\u00dfnahmen ergreift, um Worten auch Taten folgen zu lassen, ist gro\u00dfartig.\u201c\u2013 Allie Emrich, Program Management, ProductWeiterlesenInklusion in der PraxisBerichtPartnerschaften mit ColorStack und Rewriting the CodeUnser University Recruiting-Team arbeitet mit ColorStack und Rewriting the Code zusammen, um mehr Frauen sowie Black- und LatinX-Studierenden dabei zu helfen, eine Karriere in der Technologiebranche zu verfolgen.WeiterlesenBerichtWomen in Tech Mentorship ProgramWir bei Databricks wissen, wie wichtig es ist, historisch unterrepr\u00e4sentierten Communitys berufliche Wachstums- und Aufstiegschancen zu bieten.WeiterlesenBerichtInHerSight Award 2021Wir freuen uns, laut Frauen zu den besten Computersoftware-Arbeitspl\u00e4tzen f\u00fcr Frauen zu geh\u00f6ren. Erfahren Sie mehr in unserem InHerSight-Profil.WeiterlesenLassen Sie uns gemeinsam die Zukunft der Daten gestaltenWir haben es uns zur Aufgabe gemacht, Daten und KI zu vereinfachen und zu demokratisieren\u00a0\u2013 und ohne Sie k\u00f6nnen wir das nicht schaffen.M\u00f6glichkeiten auslotenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/data-teams-guide","text":"\n\n\n\n\n\n\n\nThe Data Team\u2019s Guide to the Data Lakehouse Platform\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/durga-kala","text":"Durga Kala - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDurga KalaSr. Director at Visa Inc.Back to speakersManaging Visa's global fraud detection and decisioning products, such as Visa Risk Manager. Responsible for strategy and development of new risk Fraud products that optimize consumer experience while minimizing fraud losses. Extensive experience with developing innovative products and increasing adoption of open source software.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/feed","text":"\n\nDatabricks\n\nhttps:\/\/www.databricks.com\n          Making big data simple.\nThu, 11 May 2023 16:49:14 GMT\nen\nhourly\t\n1\t\nhttps:\/\/wordpress.org\/?v=5.8.3\n\nhttps:\/\/www.databricks.com\/wp-content\/uploads\/2019\/12\/cropped-databricks-icon-32x32.png\nDatabricks \u2013 Databricks\nhttps:\/\/www.databricks.com\n          32\n32\n\nFleet optimization with CARTO & Databricks\nThu, 11 May 2023 13:12:25 GMT\nhttps:\/\/www.databricks.com\/blog\/fleet-optimization-carto-databricks\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Effective delivery has become increasingly important for businesses in recent years, particularly for logistics companies and those in the consumer packaged goods (CPG)...<\/div>\n      \nPlatform BlogPartners\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Effective delivery has become increasingly important for businesses in recent years, particularly for logistics companies and those in the consumer packaged goods (CPG)...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6008\n\n\nCluster Policy Onboarding Primer\nThu, 11 May 2023 09:35:03 GMT\nhttps:\/\/www.databricks.com\/blog\/cluster-policy-onboarding-primer\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Introduction This blog is part of our Admin Essentials series, where we'll focus on topics important to those managing and maintaining Databricks environments...<\/div>\n      \nIndustriesFinancial Services\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Introduction This blog is part of our Admin Essentials series, where we'll focus on topics important to those managing and maintaining Databricks environments...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6045\n\n\nIntroducing Databricks Fleet Clusters for AWS\nWed, 10 May 2023 13:53:39 GMT\nhttps:\/\/www.databricks.com\/blog\/introducing-databricks-fleet-clusters-aws\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We're excited to announce the general availability of Databricks Fleet clusters on AWS. What are Fleet clusters? Databricks Fleet clusters unlock the potential...<\/div>\n      \nPlatform BlogAnnouncements\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We're excited to announce the general availability of Databricks Fleet clusters on AWS. What are Fleet clusters? Databricks Fleet clusters unlock the potential...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6012\n\n\nActioning Customer Reviews at Scale with Databricks SQL AI Functions\nWed, 10 May 2023 11:00:08 GMT\nhttps:\/\/www.databricks.com\/blog\/actioning-customer-reviews-scale-databricks-sql-ai-functions\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Every morning Susan walks straight into a storm of messages, and doesn't know where to start! Susan is a customer success specialist at...<\/div>\n      \nEngineering BlogData Science and ML\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Every morning Susan walks straight into a storm of messages, and doesn't know where to start! Susan is a customer success specialist at...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6007\n\n\nUsing Structured Streaming with Delta Sharing in Unity Catalog\nTue, 09 May 2023 13:00:48 GMT\nhttps:\/\/www.databricks.com\/blog\/using-structured-streaming-delta-sharing-unity-catalog\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce that support for using Structured Streaming with Delta Sharing is now generally available (GA) in Azure, AWS, and...<\/div>\n      \nPlatform BlogProduct\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce that support for using Structured Streaming with Delta Sharing is now generally available (GA) in Azure, AWS, and...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5999\n\n\nUnifying Your Data Ecosystem with Delta Lake Integration\nTue, 09 May 2023 10:00:14 GMT\nhttps:\/\/www.databricks.com\/blog\/integrating-delta-lakehouse-other-platforms\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">As organizations are maturing their data infrastructure and accumulating more data than ever before in their data lakes, Open and Reliable table formats...<\/div>\n      \nEngineering BlogData Engineering\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">As organizations are maturing their data infrastructure and accumulating more data than ever before in their data lakes, Open and Reliable table formats...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5959\n\n\nUnify Data and Business Teams with Sigma on Databricks\nMon, 08 May 2023 10:36:35 GMT\nhttps:\/\/www.databricks.com\/blog\/unify-data-and-business-teams-sigma-databricks\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Data analytics has revolutionized the way businesses operate and compete, enabling them to make informed decisions and innovate their products and services. As...<\/div>\n      \nPlatform BlogPartners\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Data analytics has revolutionized the way businesses operate and compete, enabling them to make informed decisions and innovate their products and services. As...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5997\n\n\nThe Hitchhiker's Guide to data privilege model and access control in Unity Catalog\nFri, 05 May 2023 12:53:33 GMT\nhttps:\/\/www.databricks.com\/blog\/hitchhikers-guide-data-privilege-model-and-access-control-unity-catalog\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">As the volume, velocity and variety of data grows, organizations are increasingly relying on staunch data governance practices to ensure their core business...<\/div>\n      \nPlatform BlogSolutions\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">As the volume, velocity and variety of data grows, organizations are increasingly relying on staunch data governance practices to ensure their core business...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5933\n\n\nStrengthening the Lakehouse Governance Ecosystem: Databricks Ventures Invests in Immuta\nThu, 04 May 2023 12:47:48 GMT\nhttps:\/\/www.databricks.com\/blog\/strengthening-lakehouse-governance-ecosystem-databricks-ventures-invests-immuta\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Databricks Ventures is excited to announce our investment in Immuta's Series E funding round, marking the latest step in our six-year partnership with...<\/div>\n      \nNews\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Databricks Ventures is excited to announce our investment in Immuta's Series E funding round, marking the latest step in our six-year partnership with...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6018\n\n\nEmpowered to Raise the Bar\nThu, 04 May 2023 12:27:34 GMT\nhttps:\/\/www.databricks.com\/blog\/empowered-raise-bar\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We\u2019re excited to feature an in-depth interview with Brickster, \u00d6zge Bekleyen! Based in Zurich, she leads a team of Specialist Solutions Architects. In th...<\/div>\n      \nCompany BlogCulture\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We\u2019re excited to feature an in-depth interview with Brickster, \u00d6zge Bekleyen! Based in Zurich, she leads a team of Specialist Solutions Architects. In th...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5962\n\n\nAnnouncing Terraform Databricks modules\nThu, 04 May 2023 10:37:14 GMT\nhttps:\/\/www.databricks.com\/blog\/announcing-terraform-databricks-modules\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The Databricks Terraform provider reached more than 10 million installations, significantly increasing adoption since it became generally available less than one year ago...<\/div>\n      \nEngineering BlogData Engineering\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The Databricks Terraform provider reached more than 10 million installations, significantly increasing adoption since it became generally available less than one year ago...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5926\n\n\nUnderstanding Caching in Databricks SQL: UI, Result, and Disk Caches\nThu, 04 May 2023 06:38:40 GMT\nhttps:\/\/www.databricks.com\/blog\/understanding-caching-databricks-sql-ui-result-and-disk-caches\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Caching is an essential technique for improving the performance of data warehouse systems by avoiding the need to recompute or fetch the same...<\/div>\n      \nPlatform BlogProduct\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Caching is an essential technique for improving the performance of data warehouse systems by avoiding the need to recompute or fetch the same...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5952\n\n\nWelcome Okera: Adopting an AI-centric approach to governance\nWed, 03 May 2023 12:10:00 GMT\nhttps:\/\/www.databricks.com\/blog\/welcome-okera-adopting-ai-centric-approach-governance\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">For a decade, Databricks has focused on democratizing data and AI for organizations around the world. And since the debut of ChatGPT last...<\/div>\n      \nCompany Blog\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">For a decade, Databricks has focused on democratizing data and AI for organizations around the world. And since the debut of ChatGPT last...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/6002\n\n\nThe Executive\u2019s Guide to Data, Analytics and AI Transformation, Part 4: Democratize access to quality data with governance\nWed, 03 May 2023 11:50:10 GMT\nhttps:\/\/www.databricks.com\/blog\/executives-guide-data-analytics-and-ai-transformation-part-4-democratize-access-quality-data\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">This is part four of a multi-part series to share key insights and tactics with Senior Executives leading data and AI transformation initiatives...<\/div>\n      \nData StrategyData Leader\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">This is part four of a multi-part series to share key insights and tactics with Senior Executives leading data and AI transformation initiatives...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5932\n\n\nFive Reasons to Build your Modern Data Stack on the Lakehouse with Databricks, dbt Labs and Fivetran\nWed, 03 May 2023 10:52:26 GMT\nhttps:\/\/www.databricks.com\/blog\/five-reasons-build-your-modern-data-stack-lakehouse-databricks-dbt-labs-and-fivetran\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The Modern Data Stack (MDS) appeared several years ago as cloud-based modern data platforms put analytics - and the tools that power it...<\/div>\n      \nPlatform BlogPartners\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The Modern Data Stack (MDS) appeared several years ago as cloud-based modern data platforms put analytics - and the tools that power it...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5998\n\n\nUnlocking the Power of Retail Media Networks: How Data-Driven Advertising is Changing the Retail Promotions Landscape\nTue, 02 May 2023 12:15:04 GMT\nhttps:\/\/www.databricks.com\/blog\/unlocking-power-retail-media-networks-how-data-driven-advertising-changing-retail-promotions\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">With razor thin margins and increasing competition for the customer, retailers are always looking for new ways to monetize and stay ahead of...<\/div>\n      \nIndustriesRetail\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">With razor thin margins and increasing competition for the customer, retailers are always looking for new ways to monetize and stay ahead of...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5920\n\n\nMulti-cloud Architecture for Portable Data and AI Processing in Financial Services\nTue, 02 May 2023 11:03:21 GMT\nhttps:\/\/www.databricks.com\/blog\/multi-cloud-architecture-portable-data-and-ai-processing-financial-services\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Many financial institutions are developing a multi-cloud strategy to reduce operational risk, adhere to regulatory requirements, and also to benefit from a choice...<\/div>\n      \nIndustriesFinancial Services\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Many financial institutions are developing a multi-cloud strategy to reduce operational risk, adhere to regulatory requirements, and also to benefit from a choice...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5931\n\n\nFind what you seek with the new navigation UI\nTue, 02 May 2023 09:33:50 GMT\nhttps:\/\/www.databricks.com\/blog\/find-what-you-seek-new-navigation-ui\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce that we will be releasing a new UI that will make it easier for you to navigate Databricks...<\/div>\n      \nPlatform BlogProduct\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce that we will be releasing a new UI that will make it easier for you to navigate Databricks...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5243\n\n\nSecuring Databricks cluster init scripts\nTue, 02 May 2023 05:20:00 GMT\nhttps:\/\/www.databricks.com\/blog\/securing-databricks-cluster-init-scripts\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">This blog was co-authored by Elia Florio, Sr. Director of Detection &amp; Response at Databricks and Florian Roth and Marius Bartholdy, security researchers...<\/div>\n      \nEngineering Blog\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">This blog was co-authored by Elia Florio, Sr. Director of Detection &amp; Response at Databricks and Florian Roth and Marius Bartholdy, security researchers...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5968\n\n\nAcceleration Unlocked: DS3_v2 Instance Types on Azure now supported by Photon\nMon, 01 May 2023 07:24:39 GMT\nhttps:\/\/www.databricks.com\/blog\/acceleration-unlocked-ds3v2-instance-types-azure-now-supported-photon\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">At Databricks, we offer maximal flexibility for choosing compute for ETL and ML\/AI workloads. Staying true to the theme of flexibility, we announce...<\/div>\n      \nPlatform BlogProduct\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">At Databricks, we offer maximal flexibility for choosing compute for ETL and ML\/AI workloads. Staying true to the theme of flexibility, we announce...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5916\n\n\nEnroll in our New Expert-Led Large Language Models (LLMs) Courses on edX\nMon, 01 May 2023 05:06:14 GMT\nhttps:\/\/www.databricks.com\/blog\/enroll-our-new-expert-led-large-language-models-llms-courses-edx\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Enroll in the introductory course on edX today! The course will begin Summer 2023. New Large Language Model Courses with edX As Large...<\/div>\n      \nNews\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Enroll in the introductory course on edX today! The course will begin Summer 2023. New Large Language Model Courses with edX As Large...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5924\n\n\nApplying software development & DevOps best practices to Delta Live Table pipelines\nFri, 28 Apr 2023 10:37:02 GMT\nhttps:\/\/www.databricks.com\/blog\/applying-software-development-devops-best-practices-delta-live-table-pipelines\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Databricks Delta Live Tables (DLT) radically simplifies the development of the robust data processing pipelines by decreasing the amount of code that data...<\/div>\n      \nPlatform BlogSolutions\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">Databricks Delta Live Tables (DLT) radically simplifies the development of the robust data processing pipelines by decreasing the amount of code that data...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5919\n\n\nAnnouncing Public Preview of Databricks Marketplace\nThu, 27 Apr 2023 14:59:20 GMT\nhttps:\/\/www.databricks.com\/blog\/announcing-public-preview-databricks-marketplace\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce the public preview of Databricks Marketplace, an open marketplace for all your data, analytics, and AI, powered by...<\/div>\n      \nPlatform BlogAnnouncements\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">We are excited to announce the public preview of Databricks Marketplace, an open marketplace for all your data, analytics, and AI, powered by...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5923\n\n\nA data architecture pattern to maximize the value of the Lakehouse\nWed, 26 Apr 2023 17:13:25 GMT\nhttps:\/\/www.databricks.com\/blog\/data-architecture-pattern-maximize-value-lakehouse.html\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">One of Lakehouse's outstanding achievements is the ability to combine workloads for modern use cases, such as traditional BI, machine learning &amp; AI...<\/div>\n      \nPlatform BlogSolutions\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">One of Lakehouse's outstanding achievements is the ability to combine workloads for modern use cases, such as traditional BI, machine learning &amp; AI...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5889\n\n\nEnhancing Product Search with Large Language Models (LLMs)\nWed, 26 Apr 2023 11:33:33 GMT\nhttps:\/\/www.databricks.com\/blog\/enhancing-product-search-large-language-models-llms.html\n                \n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The text generation capabilities of ChatGPT, Dolly and the like are truly impressive and are rightfully recognized as major steps forward in the...<\/div>\n      \nIndustriesRetail\n\n            <div class=\"clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item\">The text generation capabilities of ChatGPT, Dolly and the like are truly impressive and are rightfully recognized as major steps forward in the...<\/div>\n      \nhttps:\/\/www.databricks.com\/node\/5905\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/discover\/getting-started-with-delta-lake-tech-talks","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jason-shiverick\/#","text":"Jason Shiverick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJason ShiverickData Platform Manager at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/company\/leadership-team","text":"\ub9ac\ub354\uc2ed \ud300 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 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\uc218\ub9bd\ud558\uace0 \uc218\uc2ed \ub144 \ub3d9\uc548 \ucd95\uc801\ud55c \uacbd\ud5d8\uc744 \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130\uc640 AI\uc5d0 \uc0c8\ub85c\uc6b4 \uae38\uc744 \ubc1d\ud799\ub2c8\ub2e4\uacbd\uc601\uc9c4 \uc18c\uac1c\uacbd\uc601\uc9c4\ucc3d\uc5c5\uc790\uc774\uc0ac\ud68cAli Ghodsi\uacf5\ub3d9 \uc124\ub9bd\uc790 \uacb8 CEOAndy Kofoid\uae00\ub85c\ubc8c \ud544\ub4dc \uc6b4\uc601 \ucc45\uc784\uc790David Conte\ucd5c\uace0 \uc7ac\ubb34 \ucc45\uc784\uc790Amy Reichanadter\ucd5c\uace0 \uc778\uc0ac \ucc45\uc784\uc790Tr\u00e2m Phi\uc804\ubb34 \uacb8 \ubc95\ubb34 \uc790\ubb38Ron Gabrisko\ucd5c\uace0 \ub9e4\ucd9c \ucc45\uc784\uc790Rick Schultz\ucd5c\uace0 \ub9c8\ucf00\ud305 \ucc45\uc784\uc790Hatim Shafique\ucd5c\uace0 \uc6b4\uc601 \ucc45\uc784\uc790Ferm\u00edn Serna\ucd5c\uace0 \ubcf4\uc548 \ucc45\uc784\uc790Naveen Zutshi\ucd5c\uace0 \uc815\ubcf4 \ucc45\uc784\uc790Vinod Marur\uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uc804\ubb34David Meyer\uc81c\ud488 \ubd80\ubb38 \uc804\ubb34Adam Conway\uc81c\ud488 \ubd80\ubb38 \uc804\ubb34Arsalan Tavakoli-Shiraji\uacf5\ub3d9 \uc124\ub9bd\uc790 \uacb8 \ud604\uc7a5 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 SVP\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \u0000\u0000\ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 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All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-roussel","text":"John Roussel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn RousselCIO at California Department of Public Health (CDPH)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/price-transparency-data","text":"Analyzing Transparency in Coverage data with the lakehouse | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorUnderstanding Price Transparency DataPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedUnderstand the costs of healthcare by unlocking price transparency data from health plansIn the United States, health plans are facing regulatory requirements around price transparency with a rule known as Transparency in Coverage. Health plans must post information for covered items and services. This is in the form of price transparency machine-readable file (MRF) data. These data sets are very large, often unzipping up to 150GB. Further, the JSON structure mandated by the Centers for Medicare & Medicaid Services allows for the creation of just one JSON object, challenging even the fastest parsers.With the Databricks Lakehouse for Healthcare and Life Sciences, data teams can:Ingest and read large price transparency machine-readable file (MRF) dataStream JSON objects and parse on the fly with Spark Structured StreamingEfficiently perform analysis using Databricks SQL (DBSQL)Download notebookResourcesUse Case GuideRead nowBlogWatch nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/columbia","text":"Customer Story: Columbia | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYMoving to the cloud ushers in a new era of data-driven retailing70%Reduction in data pipeline creation time48xFaster ETL workloads INDUSTRY: Retail and consumer goods SOLUTION: Advertising effectiveness,customer segmentation,product matching,recommendation engines PLATFORM USE CASE: Delta Lake,ETL CLOUD: Azure\u201cMore business units are using the platform in a self-service manner that was not possible before. I can\u2019t say enough about the positive impact that Databricks has had on Columbia.\u201d\n\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearColumbia is a data-driven enterprise, integrating data from all line-of-business systems to manage its wholesale and retail businesses across all its brands. However, their legacy ETL and analytics infrastructure was unable to support both batch and real-time use cases at scale, blocking their ability to meet the demands of the business and data teams. After migrating to Databricks, they are now able to process and prepare data more efficiently and reliably \u2014 driving valuable insights needed to make smarter business decisions.Legacy analytics systems that were costly and slowAs the retail industry continues to digitize across all channels, Columbia has been at the forefront of leveraging data across their business lines to impact sales, purchasing, supply chain, and product optimization. For example, they wanted to understand how to leverage insights related to geography, brand affinity, gross margins, and costs to improve operations and make smarter decisions. Or how to leverage customer engagement data from product reviews and comments to inform marketing campaigns and improve customer support.With troves of data at their disposal, the processing efficiency of both batch and real-time data for downstream analytics and reporting was not meeting internal service level agreements. Hampered by specialty ETL tooling and legacy data warehouses that were siloed and complex to scale, the enterprise information management (EIM) team struggled to efficiently build data pipelines that unlocked access to curated data for various data teams and business stakeholders. Furthermore, their infrastructure was rigid and costly to manage and scale which was problematic as the number of people needing access to data was on the rise.\u201cOur legacy systems could take weeks to ETL data for analytics and reporting,\u201d explained Lara Minor, a senior enterprise data manager at Columbia Sportswear. \u201cAs a result, we were unable to support a variety of use cases, impacting analyst and line-of-business satisfaction.\u201dWith various teams from the executives to data analysts and scientists all vying for company-wide data, they realized that they needed to re-platform their analytics system to the cloud to enable more agility and cost efficiency at scale. They also needed to streamline data preparation and ETL, while making it easier and safer for their stakeholders to access the data they need to make smarter decisions.Getting data to those who need it as quickly as possibleThe EIM team at Columbia decided to move to Microsoft Azure which opened the doors to use Azure Databricks and Delta Lake to upgrade their data processing and analytics capabilities. \u201cWe were looking for something that was scalable, elastic, and at a lower cost,\u201d said Minor. \u201cAzure and Databricks met those requirements.\u201dWith Databricks, they are now able to build high-performance ETL pipelines that support batch and real-time workloads. The pipelines feed into Delta Lake which provides secure access to curated data. \u201cDelta Lake provides ACID capabilities that simplify data pipeline operations to increase pipeline reliability and data consistency,\u201d explained Minor. \u201cAt the same time, features like caching and auto-indexing enable efficient and performant access to the data.\u201dOnce the data is ingested, it can be directed to various endpoints across the company depending on the end-user and use case. For example, business analysts could connect directly with PowerBI for sales reporting that requires near real-time information on-demand. They could make data accessible via Databricks interactive notebooks for data scientists to explore and train models. Or they could send data to their data warehousing tool for use cases with low latency and high concurrency requirements. Whichever data team needed access to the data, they were confident that the data was reliable and consistent.Faster data pipelines, shorter time-to-insightShortening data processing times is key to rapidly delivering data insights to the business. Databricks has helped Columbia\u2019s EIM team accelerate ETL and data preparation, achieving a 70% reduction in ETL pipeline creation time while reducing the amount of time to process ETL workloads from 4 hours to only 5 minutes, 48x improvement.With a scalable and performant platform that better supports batch and real-time workloads at their disposal, various data users are now empowered to make smarter decisions that impact business operations without having to be over-reliant on the EIM team.\u201cOne of the benefits of this platform is how fast people can come up to speed on it. All that data is coming in, and more business units are using it across the enterprise in a self-service manner that was not possible before,\u201d stated Minor. \u201cI can\u2019t say enough about the positive impact that Databricks has had on Columbia.\u201dWith curated data at their fingertips, use cases \u2014 from forecasting consumer demands to analyzing product reviews to increase customer satisfaction \u2014 are being driven by data. As Minor concurs, the sky\u2019s the limit in terms of how the team at Columbia can leverage data to make smarter business decisions and drive the business into the future.Related ContentSessionTechnical Talk at Spark + AI Summit 2020Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/noritaka-sekiyama","text":"Noritaka Sekiyama - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNoritaka SekiyamaPrincipal Big Data Architect at Amazon Web ServicesBack to speakersNoritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team at Amazon Web Services. He has more than 10 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks Named a Leader | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks Named a LeaderCloud Database Management SystemsDatabricks named a Leader in 2022 Gartner\u00ae Magic Quadrant\u2122 CDBMSDatabricks is proud to announce that Gartner has named us a Leader in the 2022 Magic Quadrant for Cloud Database Management Systems for the second consecutive year.We believe this recognition validates our vision for the lakehouse as a single, unified platform for data management and engineering \u2014 as well as, analytics and AI.Download the report to learn why Gartner named Databricks a Leader and gain additional insight into the benefits that a lakehouse platform can bring to your organization.Access the Report Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#2c5c5e455a4d4f556c484d584d4e5e454f475f024f4341","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c3685984c2427\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/capgemini-migrate-to-cloud-and-databricks","text":"Migrate to Cloud and Databricks by Capgemini and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionMigrate to Cloud and Databricks by CapgeminiMigration solution developed by Capgemini and powered by the Databricks Lakehouse Platform\nGet startedStreamline data migration to the Databricks Lakehouse PlatformCapgemini\u2019s industrialized and robust Data Migration Methodology (DMM) for migrating workloads to the cloud and Databricks delivers quicker time-to-value. We ensure that the cloud architecture and migration pattern are aligned to your cloud ambitions, while industrial methods, tooling and automation drive high-quality and cost-efficient migration. To increase the value of your data, Capgemini uses an industrialized data migration factory to help you streamline data migration to the Databricks Lakehouse Platform. Capgemini helps you offset the costs of the assessment so you can jump-start your journey through:Assessment: we design and implement a comprehensive cloud and data roadmap leveraging Capgemini\u2019s best-in-class eAPM assessment tool, which provides unparalleled insight into your IT portfolioMobilization: we address gaps in your readiness uncovered during assessment, and focus on building the baseline Lakehouse solution and reducing the costs of building cloud data environmentsMigration: we migrate your workloads and leverage cloud-based services to modernize your landscape, saving you up to 25% once in productionGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/macgregor-winegard\/#","text":"MacGregor Winegard - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMacGregor WinegardAssociate Data Engineer at KPMGBack to speakersMacGregor Winegard works alongside clients to develop cloud applications that extract, load and transform data for business use cases. He has experience utilizing Databricks in fields such as ESG reporting, IoT data collection, and energy data processing. MacGregor holds a Bachelor of Science from St. John Fisher University in Mathematics and Economics. As a student, MacGregor pursued research in several areas, including image processing, baseball statistics, and planar discrete dynamical systems. MacGregor currently is an associate Data Engineer at KPMG, and Databricks certified Data Engineer Associate.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/diversity-and-inclusion","text":"Diversity and Inclusion | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe future of data is open to allDiversity, Equity and Inclusion at DatabricksDriven by data. Powered by people.We\u2019re on a mission to diversify big data \u2014 starting with our team. We believe different backgrounds, experiences, perspectives, insights and skills fuel innovation and deepen our connection to one another and our customers. We strive to cultivate a culture of belonging where everyone is empowered to do the best work of their careers. From ensuring equal pay for equal work to building programming that celebrates, educates and uplifts our team, Diversity, Equity and Inclusion (DEI) is woven into everything we do.Fair Pay Workplace Certified\nWe\u2019re proud to be one of the first six organizations certified by\u00a0Fair Pay Workplace. As part of our efforts to achieve pay parity, Databricks underwent a rigorous evaluation of our pay data and practices and committed to staying accountable through ongoing pay equity analyses.\nGaingels and Flucas Ventures\nOur commitment to diversity, equity and inclusion encompasses our entire team \u2014\u00a0from the people who work with us to the people who invest in us. That\u2019s why we\u2019re proud to partner with an array of world-class investors, including\u00a0Gaingels\u00a0and\u00a0Flucas Ventures, which focus on funding companies that demonstrate a deep commitment to DEI.\n\u201cWe know that the more data we have, the better our insights. The same is true of diversity and inclusion \u2014 Databricks thrives by including the widest possible diversity of backgrounds, experiences and viewpoints.\u201d\u2014 Ali Ghodsi, Co-founder and CEO, DatabricksOur communitiesWe believe empowering our employees is the key to unlocking our full potential. Our vibrant Employee Resource Groups (ERGs) are employee-led collectives that play a critical role in creating an inclusive and supportive environment at Databricks. These diverse communities of employees and allies create space for connection and celebration and bring awareness to meaningful issues.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\nOur experiences\u201cAt Databricks, I build teams that I would want to belong to. That means having the safety to be my authentic self and providing that same comfort zone to everyone around me. The impact of that care we show for one another and our dedication to inclusion is huge for our entire community.\u201d\u2014 Stacy Kerkela, Director of EngineeringRead more\u201cHaving a LatinX Network at Databricks makes me feel a stronger sense of community \u2013 an open community \u2013 because at Databricks, our Employee Resource Groups welcome and educate all people, regardless of their background.\u201d\u2014 Miguel Peralvo, Senior Solutions ArchitectRead more\u201cMany companies are focused on increasing gender diversity, but it\u2019s great to be part of a company that is visibly taking action to help move the needle.\u201d\u2014 Allie Emrich, Program Management, ProductRead moreInclusion in actionReportPartnerships With ColorStack and Rewriting the CodeOur University Recruiting team partners with\u00a0ColorStack\u00a0and\u00a0Rewriting the Code\u00a0to help more women as well as Black and LatinX students pursue a career in technology.\nRead moreReportWomen in Tech Mentorship ProgramAt Databricks, we recognize the importance of offering professional growth and advancement opportunities for historically underrepresented communities.Read moreReport2021 InHerSight AwardWe\u2019re excited to be featured among the best computer software workplaces for women, according to women. Learn more by visiting our InHerSight profile.Read moreLet\u2019s build the future of data, togetherWe\u2019re on a mission to simplify and democratize data and AI \u2014 and we can\u2019t do it without you.Explore opportunitiesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/product\/unity-catalog","text":"Unity Catalog | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWUnity CatalogGouvernance unifi\u00e9e pour les donn\u00e9es, l'analytique et l'IA\n\u00a0D\u00e9marrerRegarder la d\u00e9mo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowUnity Catalog est une solution de gouvernance unifi\u00e9e pour tous les assets de donn\u00e9es et d'IA de votre lakehouse (fichiers, tables et mod\u00e8les de machine learning), quel que soit le cloud utilis\u00e9.Gouvernance centralis\u00e9e pour les donn\u00e9es et l'IAAvec un mod\u00e8le de gouvernance commun bas\u00e9 sur ANSI SQL, centralisez la gouvernance des fichiers, des tables, des tableaux de bord et des mod\u00e8les ML sur n\u2019importe quel cloud.Recherche et d\u00e9couverte des donn\u00e9es int\u00e9gr\u00e9esLocalisez, interpr\u00e9tez et r\u00e9f\u00e9rencez rapidement les donn\u00e9es de tout votre paysage pour une productivit\u00e9 maximale.Performance \u00e0 grande \u00e9chelleB\u00e9n\u00e9ficiez de meilleures performances pour vos requ\u00eates gr\u00e2ce au service de m\u00e9tadonn\u00e9es \u00e0 faible latence et \u00e0 l'optimisation automatique des tables.Tra\u00e7abilit\u00e9 automatis\u00e9e pour toutes les charges de travailCr\u00e9ez une vue unifi\u00e9e et transparente de l'ensemble de votre \u00e9cosyst\u00e8me de donn\u00e9es, enrichie par une tra\u00e7abilit\u00e9 fine et automatis\u00e9e de toutes les charges de travail SQL, R, Python, Scala, sur tous les types de ressources\u00a0: tables, notebooks, workflows et tableaux de bord.Int\u00e9gration \u00e0 vos outils existantsAppuyez-vous sur vos catalogues de donn\u00e9es et solutions de gouvernance existants pour p\u00e9renniser votre strat\u00e9gie de gouvernance des donn\u00e9es et de l'IA.Comment \u00e7a marcheCentralisez la gestion et la gouvernance de tous vos assets de donn\u00e9esGr\u00e2ce au mod\u00e8le de gouvernance commun reposant sur la norme ouverte ANSI SQL, simplifiez la gouvernance des fichiers, tables, tableaux de bord et mod\u00e8les ML, quel que soit le cloud. D\u00e9finissez une fois pour toutes des politiques d'acc\u00e8s au niveau des comptes, puis appliquez-les \u00e0 l'ensemble des charges et des espaces de travail. Unity Catalog conserve un journal des op\u00e9rations effectu\u00e9es sur les donn\u00e9es, permettant un audit centralis\u00e9 et pr\u00e9cis de vos donn\u00e9es. Vous pouvez remplir vos obligations de conformit\u00e9 en toute s\u00e9r\u00e9nit\u00e9.\u00a0G\u00e9rer des contr\u00f4les d'acc\u00e8s pr\u00e9cisUtilisez les fonctions SQL standard pour d\u00e9finir des filtres de lignes et des masques de colonne, et permettre des contr\u00f4les d'acc\u00e8s sp\u00e9cifiques. Comme Databricks continue \u00e0 d\u00e9velopper des capacit\u00e9s pour am\u00e9liorer l'\u00e9volutivit\u00e9 et l'int\u00e9gration, les prochains contr\u00f4les d'acc\u00e8s bas\u00e9s sur les attributs vous permettront de d\u00e9finir des politiques d'acc\u00e8s bas\u00e9es sur des balises personnalis\u00e9es (attributs).Une exp\u00e9rience de recherche unifi\u00e9e et s\u00e9curis\u00e9eLocalisez, interpr\u00e9tez et r\u00e9f\u00e9rencez rapidement les donn\u00e9es pertinentes de tout votre paysage gr\u00e2ce \u00e0 une exp\u00e9rience de recherche unifi\u00e9e, pens\u00e9e pour les data analysts, les data engineers et les data scientists. Dans Unity Catalog, la recherche est s\u00e9curis\u00e9e par d\u00e9faut\u00a0: l'acc\u00e8s aux r\u00e9sultats est limit\u00e9 en fonction des autorisations des utilisateurs. Vous b\u00e9n\u00e9ficiez donc d'une couche suppl\u00e9mentaire de s\u00e9curit\u00e9 pour la protection de la vie priv\u00e9e.Des performances de requ\u00eate sup\u00e9rieures \u00e0 toutes les \u00e9chellesUnity Catalog offre des performances de requ\u00eate sup\u00e9rieures gr\u00e2ce \u00e0 un service de m\u00e9tadonn\u00e9es \u00e0 faible latence et au r\u00e9glage automatique des tables. Les requ\u00eates sont ex\u00e9cut\u00e9es plus rapidement \u00e0 toutes les \u00e9chelles. Le compactage des donn\u00e9es automatiques et asynchrones optimise la taille des fichiers et r\u00e9duit automatiquement la latence d\u2019entr\u00e9e\/sortie (E\/S) en arri\u00e8re-plan.Data lineage automatis\u00e9 en temps r\u00e9elB\u00e9n\u00e9ficiez d'une visibilit\u00e9 de bout en bout sur la circulation des donn\u00e9es dans votre lakehouse gr\u00e2ce au data lineage en temps r\u00e9el sur toutes les charges de travail SQL, Python, Scala et R. Effectuez rapidement des contr\u00f4les de qualit\u00e9 des donn\u00e9es, analysez en profondeur l'impact des modifications et d\u00e9boguez la moindre erreur dans vos pipelines de donn\u00e9es. Profitez d'une v\u00e9ritable tra\u00e7abilit\u00e9 de vos tables, colonnes, notebooks, workflows et tableaux de bord. Les graphes de lineage de Unity Catalog tiennent compte des diff\u00e9rents niveaux d'acc\u00e8s\u00a0: leur disponibilit\u00e9 est donc limit\u00e9e en fonction des autorisations des utilisateurs. Une API REST permet \u00e9galement de r\u00e9cup\u00e9rer le lineage \u00e0 des fins d'int\u00e9gration \u00e0 d'autres catalogues.Partage s\u00e9curis\u00e9 des donn\u00e9es entre organisationsUnity Catalog prend en charge Delta Sharing en mode natif, le premier protocole ouvert au monde pour le partage s\u00e9curis\u00e9 de donn\u00e9es. Vous pouvez ainsi \u00e9changer facilement des donn\u00e9es existantes aux formats Delta Lake et Apache Parquet avec n'importe quelle plateforme informatique. Les utilisateurs n'ont pas besoin d'\u00eatre eux aussi sur la plateforme Databricks ou sur le m\u00eame cloud. D'ailleurs, ils ne sont m\u00eame pas oblig\u00e9s d'\u00eatre sur un cloud. Vous pouvez partager des donn\u00e9es en direct sans devoir les r\u00e9pliquer ni les copier sur un autre syst\u00e8me. Gr\u00e2ce aux int\u00e9grations natives avec Power BI, Tableau, Spark, Pandas et Java, les destinataires sont libres d'exploiter les donn\u00e9es partag\u00e9es dans l'outil de leur choix. Vous pouvez centraliser la gestion, la gouvernance, l'audit et le suivi de consommation des donn\u00e9es partag\u00e9es sur une m\u00eame plateforme.Int\u00e9grations transparentes avec vos outils existantsUnity Catalog fonctionne avec vos catalogues de donn\u00e9es, syst\u00e8mes de stockage de donn\u00e9es et solutions de gouvernance existants afin que vous puissiez tirer parti de vos investissements existants et cr\u00e9er un mod\u00e8le de gouvernance \u00e0 l\u2019\u00e9preuve du temps sans co\u00fbts de migration co\u00fbteux.Donn\u00e9es et stockage cloudGouvernance des donn\u00e9es et partenaires de catalogueClient\u00e8le\u00ab Unity Catalog nous a aid\u00e9s \u00e0 simplifier la gestion des donn\u00e9es et les contr\u00f4les d'acc\u00e8s dans toute l'entreprise. L'\u00e9quipe charg\u00e9e des donn\u00e9es de Compass a int\u00e9gr\u00e9 en toute s\u00e9curit\u00e9 plus de 100 sources de donn\u00e9es, migr\u00e9 tous les espaces de travail vers Unity Catalog et cr\u00e9\u00e9 une couche d'or dans laquelle les principales parties prenantes peuvent puiser pour obtenir des informations sur des domaines tels que les clients, les produits, l'utilisation, les revenus et bien plus encore - cr\u00e9ant ainsi une source unique de v\u00e9rit\u00e9, avec des contr\u00f4les d'acc\u00e8s complets dans toute l'entreprise.\"Rajesh Nagpal, directeur principal de l'ing\u00e9nierie des donn\u00e9es\u00ab\u00a0Unity Catalog a consid\u00e9rablement simplifi\u00e9 notre mise en place du contr\u00f4le d\u2019acc\u00e8s bas\u00e9 sur les r\u00f4les. Nous avons d\u00e9sormais la possibilit\u00e9 de s\u00e9curiser les donn\u00e9es au niveau du catalogue, de la base de donn\u00e9es, de la table et de la colonne. Nous provisionnons de mani\u00e8re transparente le niveau d\u2019acc\u00e8s appropri\u00e9 \u00e0 tous les utilisateurs. Nous avons la possibilit\u00e9 de conformer la gestion et la s\u00e9curisation de l'acc\u00e8s aux donn\u00e9es \u00e0 nos politiques strictes de conformit\u00e9 et de confidentialit\u00e9, en toute confiance.\u00a0\u00bb\u2014 Chris Locklin, Responsable de l'ing\u00e9nierie des plateformes de donn\u00e9es, Grammarly\u00ab\u00a0En adoptant Unity Catalog, Milliman a pu tisser un lien direct entre ses vastes assets de donn\u00e9es et ses utilisateurs, gr\u00e2ce \u00e0 une gestion simplifi\u00e9e des acc\u00e8s et une r\u00e9duction de la complexit\u00e9 du stockage. Unity Catalog permet \u00e0 Milliman de disposer d'une capacit\u00e9 d'exploration collaborative des donn\u00e9es et d'un stockage rationalis\u00e9, tout en respectant les normes strictes du secteur de la sant\u00e9. Avec Unity Catalog, nous pouvons \u00e9voluer rapidement en fonction des besoins de nos clients.\u00a0\u00bb\u2014 Dan McCurley, Architecte de solutions cloud, Milliman\" Unity Catalog nous permet de construire une plateforme de nouvelle g\u00e9n\u00e9ration qui lib\u00e8re tout le potentiel des v\u00e9hicules d\u00e9finis par logiciel qui \u00e9voluent et s'am\u00e9liorent au fur et \u00e0 mesure qu'ils accumulent des kilom\u00e8tres - am\u00e9liorant ainsi l'exp\u00e9rience de conduite des clients et maximisant les avantages environnementaux du transport \u00e9lectrifi\u00e9. Nous disposons d\u00e9sormais d'un catalogue de donn\u00e9es centralis\u00e9 et d'une gestion de l'acc\u00e8s \u00e0 travers diverses \u00e9quipes et espaces de travail, ce qui a ouvert des possibilit\u00e9s de collaboration et d'innovation sans pr\u00e9c\u00e9dent.\"CAS Venkat Sivasubramanian, directeur principal du Big Data\u00ab\u00a0Unity Catalog a vraiment chang\u00e9 la donne pour nous. Nos analystes peuvent acc\u00e9der aux tables externes AWS en temps r\u00e9el dans les espace de travail de Databricks et les joindre aux tables Delta Lake. Nous profitons ainsi des avantages de performance offerts par Databricks SQL sans faire migrer nos tables Glue. Avec Unity Catalog, diff\u00e9rentes \u00e9quipes peuvent collaborer sans devoir constamment changer les donn\u00e9es de place.\u00a0\u00bb\u2014 Rajat Gupta, Responsable de l'ing\u00e9nierie, Warner Bros. DiscoveryRessourcesKeynote et Webinar[Keynote]Gouvernance des donn\u00e9es et partage au bord du lac au Data + AI Summit 2022[Webinaire \u00e0 la demande]Comment simplifier la gouvernance des donn\u00e9es et de l'IAeBook et Blogs[eBook] Donn\u00e9es, analyse et gouvernance de l'IAAnnonce de la disponibilit\u00e9 g\u00e9n\u00e9rale de Data Lineage dans le catalogue UnityAnnonce de la disponibilit\u00e9 de la lign\u00e9e de donn\u00e9es avec Unity CatalogPr\u00e9sentation de Databricks Unity Catalog : une gouvernance granulaire pour les donn\u00e9es et l'IA sur le LakehouseDocumentationDocumentation AWSDocumentation AzurePr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/trust?itm_data=menu-item-securitytrustcenter","text":"Centre s\u00e9curit\u00e9 et confiance - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueNous savons \u00e0 quel point les donn\u00e9es font partie de vos assets les plus pr\u00e9cieux et doivent toujours \u00eatre prot\u00e9g\u00e9es. C'est pourquoi la s\u00e9curit\u00e9 est int\u00e9gr\u00e9e \u00e0 tous les niveaux de la plateforme Lakehouse de Databricks. Notre transparence vous permet de r\u00e9pondre \u00e0 vos besoins en r\u00e9glementation tout en profitant de notre plateforme.Nous savons \u00e0 quel point les donn\u00e9es font partie de vos assets les plus pr\u00e9cieux et doivent toujours \u00eatre prot\u00e9g\u00e9es. C'est pourquoi la s\u00e9curit\u00e9 est int\u00e9gr\u00e9e \u00e0 tous les niveaux de la plateforme Lakehouse de Databricks. Notre transparence vous permet de r\u00e9pondre \u00e0 vos besoins en r\u00e9glementation tout en profitant de notre plateforme.Une plateforme de confianceLa confiance passe par la transparence. D\u00e9couvrez comment nous s\u00e9curisons la plateforme gr\u00e2ce \u00e0 des pratiques \u00e0 la pointe du secteur\u00a0\u2013 tests d'intrusion, gestion des vuln\u00e9rabilit\u00e9s et d\u00e9veloppement de solutions s\u00e9curis\u00e9es \u2013 pour prot\u00e9ger la plateforme Lakehouse de Databricks.En savoir plusFonctionnalit\u00e9s de s\u00e9curit\u00e9Nous proposons des fonctionnalit\u00e9s de s\u00e9curit\u00e9 compl\u00e8tes pour prot\u00e9ger vos donn\u00e9es et charges de travail, telles que le chiffrement, les contr\u00f4les r\u00e9seau, les audits, l'int\u00e9gration des identit\u00e9s, les contr\u00f4les d'acc\u00e8s et la gouvernance des donn\u00e9es.En savoir plusConformit\u00e9Des clients du monde entier et de tous les secteurs d'activit\u00e9 utilisent la plateforme Lakehouse de Databricks. Nous disposons des certifications et des attestations n\u00e9cessaires pour r\u00e9pondre aux exigences particuli\u00e8res de conformit\u00e9 des secteurs d'activit\u00e9 fortement r\u00e9glement\u00e9s.En savoir plusConfidentialit\u00e9La confidentialit\u00e9 de vos donn\u00e9es est au c\u0153ur de notre projet, car nous savons combien elle est essentielle \u00e0 la fois pour votre organisation et pour vos clients. Databricks vous aide \u00e0 respecter les lois en mati\u00e8re de confidentialit\u00e9 ainsi que les exigences r\u00e9glementaires.En savoir plusEffectuez votre propre examen de s\u00e9curit\u00e9 en libre-service de Databricks \u00e0 l'aide de notre package de due diligence, qui comprend de la documentation et des supports de conformit\u00e9.Package de due diligenceProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/building-a-lakehouse-at-doordash-and-grammarly-aws","text":"Building a Data Lakehouse at DoorDash and Grammarly \u2013 DatabricksWebinarBuilding a Data Lakehouse at DoorDash and GrammarlyA single lakehouse for analysts and data scientistsOrganizations are looking to streamline their data management by melding their data warehouse and data lake into a single data lakehouse. A lakehouse provides a highly performant and reliable single source of data at a lower cost. See how DoorDash and Grammarly have used the Databricks Lakehouse Platform on AWS to:Address multiple data science use cases \u2014 including recommendation models, logistics and demand forecasting \u2014 as well as fraud detectionEnable their business analysts to access dashboards to view business performance and address issues immediatelyHave a single automated system to manage their data pipelines to support these use cases and moreIn this webinar, you\u2019ll learn how a lakehouse:Speeds GTM iteration and enables a more productive, efficient ML team, resulting in\u00a0increased revenue and profitabilityProvides a scalable, predictable framework,\u00a0minimizing risk and lowering TCO\u00a0by alleviating unnecessary DevOpsThis session will also include a demonstration of how you can get started and a live Q&A.SpeakersHien LuuHead of Machine Learning PlatformDoorDashMichael KebaData EngineerGrammarlyFranco PatanoSr. Solutions ArchitectDatabricksWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/samrat-ray\/#","text":"Samrat Ray - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSamrat RaySenior Staff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/technology-partner-program","text":"Programme de partenaires technologiques de Databricks - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWProgramme partenaires technologiquesInteragissez avec des milliers de clients Databricks pr\u00eats \u00e0 utiliser votre produitInscrivez-vous maintenantDatabricks s'int\u00e8gre aux meilleurs produits de donn\u00e9es et d'IA du march\u00e9 pour en faire la promotion. Nous fournissons \u00e0 nos partenaires l'assistance technique pour la mise sur le march\u00e9 dont vous avez besoin afin d'acqu\u00e9rir de nouveaux clients et d\u00e9velopper votre activit\u00e9.Avantages pour les partenaires technologiquesStimulation des ventesDes stimulations pour que les \u00e9quipes sur le terrain de Databricks contribuent \u00e0 vendre votre produitAcc\u00e8s clientsAcqu\u00e9rir directement de nouveaux clients via Databricks\u00a0Partner\u00a0ConnectEn savoir plusSupport marketingAcc\u00e9dez aux investissements marketing pour vous aider \u00e0 \u00e9tendre votre port\u00e9eAcc\u00e8s aux produits et \u00e0 l'\u00e9quipe de R&DAcc\u00e9der au personnel charg\u00e9 des produits, de l'ing\u00e9nierie et de l'assistance de DatabricksEnvironnement sandbox gratuitConstruire et tester dans un environnement sandbox gratuitProgrammes de marketing conjointsParticipez \u00e0 des programmes de marketing conjoints avec DatabricksPr\u00eat \u00e0 interagir avec des clients\u00a0?Inscrivez-vous maintenantTrouver un partenaireProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/spencer-cook\/#","text":"Spencer Cook - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpencer CookSenior Solutions Architect - Financial Services at DatabricksBack to speakersSpencer Cook, M.S., is a data professional with experience delivering end-to-end analytics solutions in the cloud to iconic brands. Since 2021, Spencer has been a financial services solutions architect at Databricks focused on revolutionizing the industry with lakehouse architecture.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/hash-buckets","text":"What are Hash Buckets?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHash BucketsAll>Hash BucketsTry Databricks for freeGet StartedIn computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found. Here are the main features of the key used:The key used can be your SSN, your telephone number, account number, etcMust have unique keysEach key is associated with\u2013mapped to\u2013a valueHash buckets are used to apportion data items for sorting or lookup purposes. The aim of this work is to weaken the linked lists so that searching for a specific item can be accessed within a shorter timeframe.  A hash table that uses buckets is actually a combination of an array and a linked list. Each element in the array [the hash table] is a header for a linked list. All elements that hash into the same location will be stored in the list. The hash function assigns each record to the first slot within one of the buckets. In case the slot is occupied, then the bucket slots will be searched sequentially until an open slot is found. In case a bucket is completely full, the record will get stored in an overflow bucket of infinite capacity at the end of the table. All buckets share the same overflow bucket. However, a good implementation will use a hash function that distributes the records evenly among the buckets so that as few records as possible go into the overflow bucket.Additional ResourcesDetecting Abuse at Scale: Locality Sensitive Hashing at Uber EngineeringBucketing Example NotebookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/09\/12\/simplifying-streaming-data-ingestion-delta-lake.html","text":"Simplifying Streaming Data Ingestion into Delta Lake - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorSimplifying Streaming Data Ingestion into Delta Lakeby Sachin PatilSeptember 12, 2022 in Engineering BlogShare this postMost business decisions are time sensitive and require harnessing data in real time from different types of sources. Sourcing the right data at the right time is the key to enabling the timely decisions. Time sensitive data sources are spread across different technologies from IoT sensors, social media, click streams, change data capture from databases etc. In order to derive key insights from these data, it has to be ingested first into the lakehouse. The key characteristic of these data is the continuous arrival in an unbounded fashion aka streaming. In this blog, we will focus on how streaming data is ingested into the lakehouse.High level data ingestion flowStreaming data from diverse data sources is staged into a message bus system or cloud object store before ingestion into the lakehouse. The data from the staging area is consumed by Apache Spark Structured Streaming (SS) pipelines that write the data into the lakehouse. There are two prominent staging environments - cloud object storage and message bus systems that are discussed below.Cloud object storage is a secure, reliable and scalable storage and persistence layer in the cloud. Amazon S3, Azure ADLS\/Blob storage or Google Cloud Storage (GCS) are examples of widely used object storage in the cloud. Usually, the events are captured into a batch and stored as a file in cloud object storage and these files need to be ingested in near real time as they arrive. Example use cases that require near real time data ingestion from cloud storage include telecom call data records, IoT event logs, etc.Message Bus Systems offer a loosely coupled data buffer that works on the publisher\/subscriber model. Apache Kafka, Apache Pulsar, Azure EventHub, AWS Kinesis and GCP Pub\/Sub are a few examples of message bus systems in open source and cloud. Message bus systems are suited for real time event capture because they ensure lower publish latency and larger fanout for supporting several consumers. Some example applications that use message buses for staging are click streams, credit card fraud detection, etc. For these applications, the data needs to be ingested in real time so that the downstream processing can deliver insights instantly.The high level architecture of streaming data ingestion into the lakehouse from these two key data staging environments is shown in Figure 1.Figure 1. High level view of streaming data ingestion into delta lakeAs shown in the figure, data from various source systems first land in one of the staging areas either in object stores or in message buses. This data is ingested into the lakehouse either by streaming connectors for message buses or auto loader for object stores. Delta Live Tables (DLT) is a simple declarative approach for creating reliable data pipelines and fully manages the underlying infrastructure at scale for batch and streaming data. It is also based on Spark Structured streaming and it is not covered in this blog. In the subsequent sections, we will describe in detail some of the challenges involved while ingesting streaming data from these sources.Data ingestion from object stores: Auto LoaderUsually, files are associated with batch data ingestion. However, continuous data ingestion from various sources into cloud based object stores in the form of files is often a common pattern. Typically, this pattern is preferred for use cases that need near real time processing wherein expected latency can be in a range of minutes. In addition, non-functional requirements, such as exactly once processing, reprocessing of failed ingestion jobs, time travel, and schema drift are needed as well.To illustrate the challenges of loading from cloud object stores into the lakehouse, let us consider a credit card payment processing system in real time which is needed for improving the customer experience and detecting payment fraud. Typically, the transactions from different payment channels are batched together into files in the object store. These files need to be ingested into the lakehouse for further downstream processing. As these are payment transactions, we need to ensure they are processed exactly once with a provision to reprocess the failed transactions with no duplicates. If this were to be processed in the AWS cloud, it will require a complex architecture that includes:Tracking the payment transaction files landing in Amazon S3 in a scalable way using Amazon SQS (Simple Queue Service) notificationsAmazon Lambda Functions to retrieve work from Amazon SQS and trigger the downstream processingAuditing the status of the payment transaction files using a control tableFigure 2. Event Based file processing in the AWS CloudThe key challenges are tracking large numbers of files landing in the object store, enabling exactly once processing of the data in those files and managing different schemas from various payment channels.Auto Loader simplifies streaming data ingestion by incrementally processing new data files as they arrive in cloud object storage and it doesn't need a user to write a custom application. It keeps track of the files processed so far by maintaining an internal state. In the case of failure, it uses the state to start from the last processed file. Furthermore, if there is a need to replay or reprocess data, it provides an option to process the existing files in the directory. The key benefits of Auto Loader are:The ability to handle billions of filesAsynchronous backfill using optimum utilization of the compute resourcesOptimized directory listing to improve the performanceSupport for schema inference and handling of schema driftCost efficient file notification by leveraging automatic file notification serviceHow does Auto Loader work?Auto Loader supports two modes for detecting new files: file notification and directory listing.File notification: Auto Loader can automatically set up a notification and queue service that subscribes to file events from the input directory. File notification mode is more performant and scalable for input directories with a high volume of files but requires additional cloud permissions. This option is better whenever files do not arrive in lexical order and obviates the need for explicit setting up of queues and notifications. To enable this mode, you need to set the option cloudFiles.useNotifications to true and provide the necessary permissions to create cloud resources. See more details about file notifications here.Directory listing: Another way to identify new files is by listing the input directory configured in the Auto Loader. Directory listing mode allows you to start Auto Loader streams without any additional permission configurations other than access to your data. From Databricks Runtime 9.1 onwards, Auto Loader can automatically detect whether files are arriving with lexical ordering to cloud storage and significantly reduce the amount of API calls it needs to make to detect new files. In the default mode, it triggers full directory listing after every seven consecutive incremental directory listings. However, the frequency of the full directory listing can be tweaked by setting the configuration cloudFiles.backfillInterval. One can explicitly enable or disable incremental listing by setting the configuration cloudFiles.useIncrementalListing. When this configuration is explicitly enabled, Auto Loader will not trigger full directory listings. See more details about directory listing here.As new files are discovered, their metadata is persisted in a scalable key-value store (RocksDB) in the checkpoint location of the Auto Loader pipeline. This serves as the state that keeps track of the files processed so far. The pipeline can both perform a backfill on a directory containing existing files and concurrently process new files that are being discovered through file notifications.Figure 3. Autoloader simplifies data ingestion from the Cloud Storage using RockDB based file metadata management and Structured StreamingData ingestion from a message busStreaming data is generally unbounded in nature. This data is staged in message buses that serve as a buffer and provide an asynchronous method of communication where multiple producers can write into and many consumers can read from. Message buses are widely used for low latency use cases such as fraud detection, financial asset trading, and gaming. Popular message bus services include Apache Kafka, Apache Pulsar, Azure EventHubs, Amazon Kinesis and Google Cloud Pub\/Sub. However, continuous data ingestion poses challenges such as scalability, resilience and fault tolerance.For ingestion from message buses into lakehouse, an explicit Spark Structured Streaming (SS) pipeline is instantiated with the appropriate source connector for the message bus and the sink connector for the Lakehouse. The key challenges in this case are throughput and fault tolerance.Let's discuss some common ingestion patterns from these sources. Although a message bus is a good choice for real time processing use cases, most applications need a design that balances between latency, throughput, fault tolerance requirements and cost. We will go through these design choices:Latency: Achieving lower latency is not always better. Rather you can lower the cost by choosing the right latency, accuracy and cost tradeoff. Spark Structured Streaming processes data incrementally controlled by Triggers which define the timing of streaming data processing. Lower latency of Spark Structured Streaming jobs is achieved with a lower trigger interval. It is advised to configure Structured Streaming trigger interval to balance the latency requirements and the rate that data arrives in the source. If you specify a very low trigger interval, the system may perform unnecessary checks to see if new data arrives.Spark Structured Streaming provides three trigger types:Default: By default, Spark Structured Streaming processes the next batch as soon as the previous batch is completed. In most use cases, the default would suit your requirements.Fixed Interval: Using fixed intervals, you can process the job at user specified intervals. Generally fixed intervals are used to wait for a specific time and run a larger microbatch.One time: At times, data arrives at a fixed interval and it would be a waste of resources to keep the cluster up and running throughout the day. One of the options is to run the job in a batch mode. However executing Spark Structured Streaming jobs in trigger Once or AvailableNow mode can be beneficial over the batch. With these execution settings, there is no need to keep the cluster running and you can significantly save the cost by periodically spinning a cluster, processing the data and shutting the cluster. Although it is similar to a batch job, it provides additional benefits such as bookkeeping management of data being processed, fault tolerance by maintaining table level atomicity and stateful operations across runs.Throughput: There are multiple parameters that can be tuned to achieve high throughput within Spark Structured Streaming. Apart from choosing the trigger types, one of the key parameters is the parallel processing of data ingestion jobs. To achieve the higher throughput, you can increase the number of partitions on the message bus. Normally Spark has one-to-one mapping between the message bus partitions to Spark Structured Streaming partitions for Apache Kafka. However in the case of AWS Kinesis, the messages are pre-fetched in the memory and there is no direct mapping between the number of Kinesis Shards and the number of Spark tasks.Let's consider a real world example where higher throughput was achieved by tuning the batch size and number of partitions. In one of the banking use cases, real time transactions were processed throughout the day using a streaming job. However, few of the events received in real time might be inaccurate. Hence a reconciliation batch was executed towards the end of the day to fix the issues. The reconciliation batch was processed using the same streaming code but different job instances. The number of partitions and batch size were increased to achieve high throughput compared to continuous flow data in another topic.Fault tolerance: As Spark Structured Streaming executes the jobs in microbatches, it gives two distinct advantages to achieve fault tolerance:Tasks can efficiently recover from failures by rescheduling the tasks on any of the other executorsThe deterministic tasks ensure that multiple executions of the same tasks provide same output that enables exactly once processingIn Spark Structured Streaming the recovery of failed jobs is achieved using the checkpoint location of each query. The offset within the checkpoint location enables you to restart the job from the exact failure point. The option to provide the checkpoint location in queries is:option(\"checkpointLocation\", \"dbfs:\/\/checkpointPath\")With replayable sources and idempotent sinks, Spark Structured Streaming jobs can achieve exactly-once semantics, which is often a requirement of production grade applications.ConclusionStreaming data ingestion is the first step in enabling time sensitive decisions in the lakehouse. In this blog, we categorized the streaming data sources as continuous flow of files or message bus services. Auto Loader simplifies the near real time ingestion from file sources using Spark Structured Streaming and provides advanced features such as automatic detection of file arrival, scalability to process a large volume of data, schema inference and cost effective data ingestion. Whereas for data ingestion from message bus services, Spark Structured Streaming enables the robust data ingestion framework that integrates with most of the message bus services across different cloud providers. The most production grade applications need a trade off between latency and throughput to minimize the cost and achieve higher accuracy.Try Databricks for freeGet StartedRelated postsIntroducing Databricks Ingest: Easy and Efficient Data Ingestion from Different Sources into Delta LakeFebruary 24, 2020 by Prakash Chockalingam in Engineering Blog\nGet an early preview of O'Reilly's new ebook for the step-by-step guidance you need to start using Delta Lake We are excited to...\nStructured Streaming: A Year in ReviewFebruary 7, 2022 by Steven Yu and Ray Zhu in Data Engineering\nAs we enter 2022, we want to take a moment to reflect on the great strides made on the streaming front in Databricks...\nLow-latency Streaming Data Pipelines with Delta Live Tables and Apache KafkaAugust 9, 2022 by Frank Munz in Product\nDelta Live Tables (DLT) is the first ETL framework that uses a simple declarative approach for creating reliable data pipelines and fully manages...\nUsing Spark Structured Streaming to Scale Your AnalyticsJuly 14, 2022 by Spencer Elkington and Ben Tallman in Customers\nThis is a guest post from the M Science Data Science & Engineering Team. Modern data doesn't stop growing \"Engineers are taught by...\nAnnouncing General Availability of Databricks\u2019 Delta Live Tables (DLT)April 5, 2022 by Michael Armbrust, Awez Syed, Paul Lappas, Erika Ehrli, Sam Steiny, Richard Tomlinson, Andreas Neumann and Mukul Murthy in Platform Blog\nToday, we are thrilled to announce that Delta Live Tables (DLT) is generally available (GA) on the Amazon AWS and Microsoft Azure clouds...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/product\/data-streaming","text":"Streaming de donn\u00e9es | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWStreaming de donn\u00e9esSimplifiez l'analytique en temps r\u00e9el, le ML et les applicationsD\u00e9marrerRegarder la d\u00e9moLa plateforme Lakehouse de Databricks simplifie consid\u00e9rablement le streaming de donn\u00e9es pour fournir de l'analytique, du machine learning et des applications en temps r\u00e9el sur une seule et m\u00eame plateforme.Donnez \u00e0 vos \u00e9quipes data les moyens de cr\u00e9er des charges de travail de streaming avec les langages et les outils qu'elles connaissent d\u00e9j\u00e0. Simplifiez le d\u00e9veloppement et les op\u00e9rations en automatisant les phases de production associ\u00e9es \u00e0 la cr\u00e9ation et \u00e0 la maintenance des charges de travail de donn\u00e9es en temps r\u00e9el. \u00c9liminez les silos en unifiant les donn\u00e9es en streaming et en batch sur une m\u00eame plateforme.Cr\u00e9ez plus rapidement des pipelines de streaming et des applicationsUtilisez les langages et les outils que vous ma\u00eetrisez d\u00e9j\u00e0 avec des API unifi\u00e9es de traitement batch et streaming dans SQL et Python. Mettez l'analytique, le ML et les applications en temps r\u00e9el au service de l'ensemble de votre organisation.Simplifiez les op\u00e9rations gr\u00e2ce \u00e0 l'automatisation des outilsD\u00e9ployez facilement vos pipelines et applications en temps r\u00e9el en production et b\u00e9n\u00e9ficiez d'une gestion simplifi\u00e9e. Les outils automatis\u00e9s simplifient l'orchestration des t\u00e2ches, la tol\u00e9rance aux pannes et le r\u00e9tablissement, l'optimisation des performances ainsi que l'automatisation des contr\u00f4les et de l'\u00e9volutivit\u00e9.Unifiez la gouvernance de toutes vos donn\u00e9es en temps r\u00e9el sur vos diff\u00e9rents clouds.Unity Catalog donne \u00e0 votre lakehouse un mod\u00e8le de gouvernance unifi\u00e9 pour l'ensemble de vos donn\u00e9es batch et streaming, afin de simplifier la d\u00e9couverte, la consultation et le partage des donn\u00e9es en temps r\u00e9el.Comment \u00e7a marche\u00a0?Ingestion et transformation de donn\u00e9es de streamingAnalytique, ML et applications en temps r\u00e9elOutils op\u00e9rationnels automatis\u00e9sMoteur de traitement en streaming de nouvelle g\u00e9n\u00e9rationUnification de la gouvernance et du stockageIngestion et transformation de donn\u00e9es de streamingSimplifiez l\u2019ingestion et l\u2019ETL des pipelines de donn\u00e9es en streaming avec Delta Live Tables. Exploitez une approche d\u00e9clarative simple du data engineering pour permettre \u00e0 vos \u00e9quipes d'utiliser les langages et les outils qu\u2019elles ma\u00eetrisent d\u00e9j\u00e0, comme SQL et Python. Cr\u00e9ez et ex\u00e9cutez des pipelines par batch et en streaming en un seul endroit avec des param\u00e8tres de rafra\u00eechissement contr\u00f4lables et automatis\u00e9s, ce qui permet de gagner du temps et de r\u00e9duire la complexit\u00e9 op\u00e9rationnelle. Quel que soit l\u2019endroit o\u00f9 vous pr\u00e9voyez d\u2019envoyer vos donn\u00e9es, gagnez du temps sur le nettoyage des donn\u00e9es brutes en cr\u00e9ant vos pipelines de streaming sur la plateforme Databricks Lakehouse.De plus en plus d'unit\u00e9s commerciales utilisent la plateforme en self-service, ce qui \u00e9tait impossible auparavant. \u00ab\u00a0Je suis extr\u00eamement impressionn\u00e9e par l'impact positif qu'a eu Databricks sur Columbia.\u00a0\u00bb- Lara Minor, Senior Enterprise Data Manager, Columbia SportswearEn savoir plusAnalytique, ML et applications en temps r\u00e9elAvec le streaming de donn\u00e9es, am\u00e9liorez imm\u00e9diatement la pr\u00e9cision de votre analytique et de votre IA pour en exploiter tout le potentiel. Pour votre entreprise, les insights en temps r\u00e9el d\u00e9coulent directement des pipelines de donn\u00e9es en streaming. Que ce soit pour effectuer de l'analytique SQL ou des rapports BI, pour entra\u00eener des mod\u00e8les de ML ou cr\u00e9er des applications op\u00e9rationnelles en temps r\u00e9el, exploitez les donn\u00e9es les plus r\u00e9centes pour un triple b\u00e9n\u00e9fice\u00a0: des informations en temps r\u00e9el, des pr\u00e9visions plus pr\u00e9cises et une prise de d\u00e9cision acc\u00e9l\u00e9r\u00e9e.\u00ab\u00a0Nous devons toujours fournir les donn\u00e9es les plus r\u00e9centes et les plus pr\u00e9cises \u00e0 nos partenaires commerciaux, sans quoi ils perdent confiance dans les insights... Le lakehouse Databricks a rendu extr\u00eamement simple ce qui \u00e9tait auparavant impossible.\u00a0\u00bb\u2013 Guillermo Rold\u00e1n, Responsable de l'architecture, LaLiga TechEn savoir plusOutils op\u00e9rationnels automatis\u00e9sLorsque vous cr\u00e9ez et d\u00e9ployez des pipelines de donn\u00e9es en streaming, Databricks automatise une grande part des t\u00e2ches op\u00e9rationnelles complexes requises pour le passage en production. La plateforme g\u00e8re notamment la mise \u00e0 l'\u00e9chelle automatique de l'infrastructure sous-jacente, l'orchestration des d\u00e9pendances du pipeline, la gestion et la correction des erreurs, l'optimisation des performances, etc.L'autoscaling am\u00e9lior\u00e9 optimise l\u2019utilisation du cluster en allouant automatiquement des ressources de calcul \u00e0 chaque charge de travail. Ces fonctionnalit\u00e9s, compl\u00e9t\u00e9es par des tests automatiques de qualit\u00e9 des donn\u00e9es et une gestion des exceptions, r\u00e9duisent le temps n\u00e9cessaire \u00e0 la cr\u00e9ation et \u00e0 la maintenance des outils op\u00e9rationnels pour vous permettre de vous concentrer sur la valeur de vos donn\u00e9es.En savoir plusMoteur de traitement en streaming de nouvelle g\u00e9n\u00e9rationLe Streaming structur\u00e9 Spark est la technologie fondamentale \u00e0 la base du streaming de donn\u00e9es sur la plateforme lakehouse de Databricks. Il fournit une API unifi\u00e9e pour le traitement en batch et en streaming. La plateforme lakehouse de Databricks est la meilleure fa\u00e7on d'ex\u00e9cuter vos charges de travail Apache Spark au sein d'un service g\u00e9r\u00e9 affichant un taux de disponibilit\u00e9 prouv\u00e9 de 99,95\u00a0%. Vos charges de travail Spark sont encore acc\u00e9l\u00e9r\u00e9es par Photon, le moteur lakehouse de nouvelle g\u00e9n\u00e9ration compatible avec les API Apache Spark. Il offre des performances records pour son co\u00fbt et peut \u00e9voluer automatiquement pour prendre en charge des milliers de n\u0153uds.En savoir plusUnification de la gouvernance et du stockageAvec le streaming de donn\u00e9es sur Databricks, vous b\u00e9n\u00e9ficiez des composants fondamentaux de la plateforme Lakehouse\u00a0: Unity Catalog et Delta Lake. Vos donn\u00e9es brutes sont optimis\u00e9es avec Delta Lake, le seul framework de stockage open source con\u00e7u de A \u00e0 Z pour les donn\u00e9es en streaming et en batch.Unity Catalog int\u00e8gre une gouvernance d\u00e9taill\u00e9e pour toutes vos donn\u00e9es et ressources d'IA. Il fournit un mod\u00e8le coh\u00e9rent pour la d\u00e9couverte, l'acc\u00e8s et le partage des donn\u00e9es sur tous les clouds. Unity Catalog fournit \u00e9galement une prise en charge native de Delta Sharing, le premier protocole ouvert du secteur pour un partage de donn\u00e9es simple et s\u00e9curis\u00e9 avec d\u2019autres organisations.Int\u00e9grationsOffrez un maximum de flexibilit\u00e9 \u00e0 vos \u00e9quipes de donn\u00e9es\u00a0: appuyez-vous sur Partner Connect et notre \u00e9cosyst\u00e8me de partenaires technologiques pour int\u00e9grer de mani\u00e8re transparente les outils les plus r\u00e9pandus de streaming.Streaming de donn\u00e9esT\u00e9moignages de clients\u00ab\u00a0Nous utilisons Databricks pour nos donn\u00e9es en mouvement \u00e0 haut d\u00e9bit. Gr\u00e2ce \u00e0 cette plateforme, nous avons consid\u00e9rablement augment\u00e9 la vitesse \u00e0 laquelle nous r\u00e9pondons aux besoins de nos patients, que ce soit en magasin ou en ligne. Nous g\u00e9rons actuellement une douzaine d'initiatives, qui reposent toutes sur les donn\u00e9es de Databricks.\u00a0\u00bb\u2014 Sashi Venkatesan, Directeur de l'ing\u00e9nierie produit, Walgreens\u00ab\u00a0D\u00e9sormais, nous d\u00e9tectons la fraude en temps r\u00e9el. Nous avons une longueur d'avance sur les fraudeurs qui tentent de d\u00e9jouer le syst\u00e8me, mais aussi sur les d\u00e9verrouillages ill\u00e9gaux, les robots d'appel et de SMS, et le vol d\u2019identit\u00e9.\u00a0\u00bbPEB Kate Hopkins, vice-pr\u00e9sident, AT&TEn savoir plusDelta\u00a0Live\u00a0tablesDatabricks WorkflowsUnity CatalogDelta LakeStreaming Spark structur\u00e9Contenu associ\u00e9E-books et d\u00e9monstrationsCr\u00e9er le Data Lakehouse par Bill Inmon, p\u00e8re du data warehouseDonn\u00e9es, analyses et gouvernance de l'IAGuide de l'\u00e9quipe de donn\u00e9es sur la plateforme Databricks LakehouseD\u00e9mos Delta Live Tables et streaming\u00c9v\u00e9nementsG\u00e9rez la transformation des donn\u00e9es avec Delta Live TablesS\u00e9rie de webinaires sur l'ingestion de donn\u00e9es sans tracasDATA+AI SUMMIT 2022Data + AI World Tour 2022BlogsPipeline de donn\u00e9es en streaming \u00e0 faible latence avec Delta Live Tables et Apache KafkaSimplifier l'ingestion de donn\u00e9es de streaming dans Delta\u00a0LakeDes informations en temps r\u00e9el : Les trois raisons principales pour lesquelles les clients aiment le streaming de donn\u00e9es avec DatabricksVos projets \u00e0 la vitesse de la lumi\u00e8re\u00a0: le traitement de flux plus rapide et plus simple avec Apache SparkUn aper\u00e7u de toutes les nouvelles fonctionnalit\u00e9s de streaming structur\u00e9 d\u00e9velopp\u00e9es en 2021 pour Databricks et Apache Spark \u2013 le blog DatabricksPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitRejoignez la communaut\u00e9ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/\/company\/careers","text":"Careers at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Careers at DatabricksWe\u2019re on a mission to help data teams solve the world\u2019s toughest problems. Will you join us?See open jobs OverviewCultureBenefitsDiversityStudents & new gradsUplevel your career. Level up the future.Databricks is leading the data and AI revolution. We created a category called the lakehouse. And now, thousands of companies are using it to solve problems like climate change, fraud, customer churn and so much more. If you\u2019re looking for an opportunity that could truly define your career, this is it.Why lakehouse is the futureWhy Databricks?We\u2019re growing fast and attracting the best talent in the world. Bricksters \u2014 as we call ourselves \u2014 are a special mix of smart, curious, quick thinkers. If you ask a Brickster what they love about working here, you\u2019ll likely hear about our culture.See our culture principlesFind your teamAdministrationBusiness DevelopmentCustomer SuccessEngineeringField EngineeringFinanceITLegalMarketingOperationsPeople & HRProductProfessional ServicesRecruitingSalesSecurityInternships & Early CareerBenefits, perks and hybrid workTo do your best work, your health and well-being are key. That\u2019s why we offer great benefits and perks \u2014 including flexible ways of working. It all depends on what works best for you and your team.Check out our benefitsDiversity, Equity and InclusionWe believe different backgrounds, perspectives and skills fuel our success. That\u2019s why we work hard at cultivating an inclusive and supportive environment. Find out how we\u2019re closing the pay gap, removing unconscious bias from recruitment and more.See inclusion in actionLocationsHeadquartered in San Francisco, California, we now have over 20 offices in 12 countries. With 4,500+ Bricksters worldwide and an ambitious growth strategy, we\u2019re one of the fastest growing enterprise software cloud companies.Check out our offices around the worldAmericas\n\u00a0San FranciscoSeattleWashington, D.C.New York CitySee moreEurope\n\u00a0LondonAmsterdamBerlinMunichSee moreAsia-Pacific\n\u00a0TokyoSingaporeSeoulHangzhouSee moreOpportunities for students and new graduatesWe\u2019re committed to developing our next generation of Databricks leaders. That\u2019s why we\u2019re intentional about having our interns and new college grads play an integral role in developing our platform.Our University Program is designed to help you make the most of your experience \u2014 from engineering hackathons and Intern Olympics to board game nights and happy hours.Explore internships and opportunities Health plan transparency in coverage (U.S. only)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pearl-ubaru\/#","text":"Pearl Ubaru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPearl UbaruSr. Technical Marketing Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kylie-taylor","text":"Kylie Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKylie TaylorData Scientist at Mars PetcareBack to speakersKylie Taylor is a Data Scientist at Mars Petcare. Her current work focuses on deploying machine learning models at scale and modeling the impacts of price inflation on shopper behavior. She holds a Masters in Economics with a focus in Statistics from the University of Texas at Austin. Previous to her role as a Data Scientist, she served as a Senior Statistician in the Global R&D division of Mars Petcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/11\/02\/databricks-sets-official-data-warehousing-performance-record.html","text":"Databricks Sets Official Data Warehousing Performance Record - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDatabricks Sets Official Data Warehousing Performance Recordby Reynold Xin and Mostafa MokhtarNovember 2, 2021 in Company BlogShare this postToday, we are proud to announce that Databricks SQL has set a new world record in 100TB TPC-DS, the gold standard performance benchmark for data warehousing. Databricks SQL outperformed the previous record by 2.2x. Unlike most other benchmark news, this result has been formally audited and reviewed by the TPC council.These results were corroborated by research from Barcelona Supercomputing Center, which frequently runs benchmarks that are derivative of TPC-DS on popular data warehouses. Their latest research benchmarked Databricks and Snowflake, and found that Databricks was 2.7x faster and 12x better in terms of price performance. This result validated the thesis that data warehouses such as Snowflake become prohibitively expensive as data size increases in production.Databricks has been rapidly developing full blown data warehousing capabilities directly on data lakes, bringing the best of both worlds in one data architecture dubbed the data lakehouse. We announced our full suite of data warehousing capabilities as Databricks SQL in November 2020. The open question since then has been whether an open architecture based on a lakehouse can provide the performance, speed, and cost of the classic data warehouses. This result proves beyond any doubt that this is possible and achievable by the lakehouse architecture.Rather than just sharing the results, we would like to take this opportunity to share with you the story of how we accomplished this level of performance and the effort that went into it. But we\u2019ll start with the results:TPC-DS World RecordDatabricks SQL delivered 32,941,245 QphDS @ 100TB. This beats the previous world record held by Alibaba\u2019s custom built system, which achieved 14,861,137 QphDS @ 100TB, by 2.2x. (Alibaba had an impressive system supporting the world\u2019s largest e-commerce platform). Not only did Databricks SQL significantly beat the previous record, it did so by lowering the total cost of the system by 10% (based on published listed pricing without any discounts).It\u2019s perfectly normal if you don\u2019t know what the unit QphDS means. (We don\u2019t either without looking at the formula.) QphDS is the primary metric for TPC-DS, which represents the performance of a combination of workloads, including (1) loading the data set, (2) processing a sequence of queries (power test), (3) processing several concurrent query streams (throughput test), and (4) running data maintenance functions that insert and delete data.The aforementioned conclusion is further supported by the research team at Barcelona Supercomputing Center (BSC) that recently ran a different benchmark derived from TPC-DS comparing Databricks SQL and Snowflake, and found that Databricks SQL was 2.7x faster than a similarly sized Snowflake setup.Chart 1: Elapsed time for test derived from TPC-DS 100TB Power Run, by Barcelona Supercomputing Center.\u00a0Chart 2: Price\/Performance for test derived from TPC-DS 100TB Power Run, by Barcelona Supercomputing Center.What is TPC-DS?TPC-DS is a data warehousing benchmark defined by the Transaction Processing Performance Council (TPC). TPC is a non-profit organization started by the database community in the late 80s, focusing on creating benchmarks that emulate real-world scenarios and, as a result, can be used objectively to measure database systems\u2019 performance. TPC has had a profound impact in the field of databases, with decade-long \u201cbenchmarking wars\u201d between established vendors like Oracle, Microsoft, and IBM that have pushed the field forward.The \u201cDS\u201d in TPC-DS stands for \u201cdecision support.\u201d It includes 99 queries of varying complexity, from very simple aggregations to complex pattern mining. It is a relatively new (work started in mid 2000s) benchmark to reflect the growing complexity of analytics. In the last decade or so, TPC-DS has become the de facto standard data warehousing benchmark, adopted by virtually all vendors.However, due to its complexity, many data warehouse systems, even the ones built by the most established vendors, have tweaked the official benchmark so their own systems would perform well. (Some common tweaks include removing certain SQL features such as rollups or changing data distribution to remove skew). This is one of the reasons why there have been very few submissions to the official TPC-DS benchmark, despite more than 4 million pages on the Internet about TPC-DS. The tweaks also ostensibly explain why most vendors seem to beat all other vendors according to their own benchmarks.How did we do it?As mentioned earlier, there have been open questions whether it\u2019s possible for Databricks SQL to outperform data warehouses in SQL performance. Most of the challenges can be distilled into the following four issues:Data warehouses leverage proprietary data formats and, as a result, can evolve them quickly, whereas Databricks (based on Lakehouse) relies on open formats (such as Apache Parquet and Delta Lake) that don\u2019t change as quickly. As a result, EDWs would have an inherent advantage.Great SQL performance requires the MPP (massively parallel processing) architecture, and Databricks and Apache Spark were not MPP.The classic tradeoff between throughput and latency implies that a system can be great for either large queries (throughput focused) or small queries (latency focused), but not both. Since Databricks focused on large queries, we had to perform poorly for small queries.Even if it is possible, the conventional wisdom is that it\u2019d take a decade or longer to build a data warehouse system. There\u2019s no way progress can be made so quickly.In the rest of the blog post, we will discuss them one by one.Proprietary vs open data formatsOne of the key tenets of the Lakehouse architecture is the open storage format. \u201cOpen\u201d not only avoids vendor lock-in but also enables an ecosystem of tools to be developed independent of the vendor. One of the major benefits of open formats is standardization. As a result of this standardization, most of the enterprise data is sitting in open data lakes and Apache Parquet has become the de facto standard for storing data. By bringing data warehouse-grade performance to open formats, we hope to minimize data movement and simplify the data architecture for BI and AI workloads.An obvious attack against \u201copen\u201d is that open formats are hard to change, and as a result hard to improve. Although in theory this argument makes sense, it is in practice not accurate.First, it is definitely possible for open formats to evolve. Parquet, the most popular open format for large data storage, has gone through multiple iterations of improvements. One of the main motivations for us introducing Delta Lake was to introduce additional capabilities that were difficult to do at the Parquet layer. Delta Lake brought additional indexing and statistics to Parquet.Second, the Databricks system automatically transcodes raw Delta Lake and Parquet data into a more efficient format when loading data from object stores to local NVMe SSDs (without user intervention). This enables further optimization opportunities.That said, for most data warehousing workloads, Delta Lake and Parquet already provide sufficient optimizations when compared with the proprietary formats used by data warehouses. For these workloads, optimization opportunities come primarily from the ability to process the queries faster, instead of scanning more data faster. As a matter of fact, for TPC-DS, querying data cached in a more optimized internal format is only 10% faster than querying cold data in S3 (we've found that to be true for both data warehouses we benchmarked and Databricks).MPP architectureA common misconception is that data warehouses employ the MPP architecture that is great for SQL performance, while Databricks does not. MPP architecture refers to the ability to leverage multiple nodes to process a single query. This is exactly how Databricks SQL is architected. It is not based on Apache Spark, but rather Photon, a complete rewrite of an engine, built from scratch in C++, for modern SIMD hardware and does heavy parallel query processing. Photon is thus an MPP engine.Throughput vs latency trade offThroughput vs latency is the classic tradeoff in computer systems, meaning that a system cannot get high throughput and low latency simultaneously. If a design favors throughput (e.g. by batching data), it would have to sacrifice latency. In the context of data systems, this means a system cannot process large queries and small queries efficiently at the same time.We won\u2019t deny that this tradeoff exists. In fact, we often discuss it in our technical design docs. However, current state of the art systems, including our own and all the popular warehouses are far away from the optimal frontier on both throughput and latency fronts.Consequently, it is entirely possible to come up with a new design and implementation that simultaneously improves both its throughput and latency. That is exactly how we\u2019ve built almost all our key enabling technologies in the last two years: Photon, Delta Lake, and many other cutting-edge technologies have improved the performance of both large and small queries, pushing the frontier to a new performance record.Time and focusFinally, conventional wisdom is that it would take at least a decade or so for a database system to mature. Given Databricks\u2019 recent focus on Lakehouse (to support SQL workloads), it would take additional effort for SQL to be performant. This is valid, but let us explain how we did it much faster than one might expect.First and foremost, this investment didn\u2019t start just a year or two ago. Since the inception of Databricks, we have been investing in various foundational technologies to support SQL workloads that would also benefit AI workloads on Databricks. This includes a full blown cost-based query optimizer, a native vectorized execution engine, and various capabilities like window functions. The vast majority of workloads on Databricks run through these thanks to Spark\u2019s DataFrame API, which maps into its SQL engine, so these components have had years of testing and optimization. What we haven\u2019t done as much was to emphasize SQL workloads. The positioning change towards Lakehouse is a recent one, driven by our customers\u2019 desire to simplify their data architectures.Second, the SaaS model has accelerated software development cycles. In the past, most vendors had yearly release cycles and then another multi-year cycle for customers to install and adopt the software. In SaaS, our engineering team can come up with a new design, implement it, and release it to a subset of customers in a matter of days. This shortened development cycle enabled teams to get feedback quickly and innovate faster.Third, Databricks could bring significantly more focus both in terms of leadership bandwidth and capital to this problem. Past attempts at building a new data warehouse system were done either by startups or a new team within a large company. There has never been a database startup as well funded as Databricks (over $3.5B raised) to attract the talent needed to build this. A new effort within a large company would be just yet another effort, and wouldn\u2019t have the leadership\u2019s full attention.We had a unique situation here: we focused initially on establishing our business not on data warehousing, but on related fields (data science and AI) that shared a lot of the common technological problems. This initial success then enabled us to fund the most aggressive SQL team build out in history; in a short period of time, we\u2019ve assembled a team with extensive data warehouse background, a feat that would take many other companies around a decade. Among them are lead engineers and designers of some of the most successful data systems, including Amazon Redshift; Google\u2019s BigQuery, F1 (Google\u2019s internal data warehouse system), and Procella (Youtube\u2019s internal data warehouse system); Oracle; IBM DB2; and Microsoft SQL Server.To summarize, it takes multiple years to build out great SQL performance. Not only did we accelerate this leveraging our unique circumstances, but we also started years ago even though we didn\u2019t use a megaphone to advertise the plan.Real-world customer workloadsWe are excited to see these benchmark results validated by our customers. Over 5,000 global organizations have been leveraging the Databricks Lakehouse Platform to solve some of the world\u2019s toughest problems. For example:Bread Finance is a technology-driven payments platform with big data use cases such as financial reporting, fraud detection, credit risk, loss estimation and a full-funnel recommendation engine. On the Databricks Lakehouse Platform, they are able to move from nightly batch jobs to near real time ingestion, and reduce data processing time by 90%. Moreover, the data platform can scale to 140x the volume of data at only 1.5x the cost.Shell is using our lakehouse platform to enable hundreds of data analysts execute rapid queries on petabyte scale datasets using standard BI tools, which they consider to be a \"game changer.\"Regeneron is accelerating drug target identification, providing faster insights to computational biologists by reducing the time it takes to run queries on their entire dataset from 30 minutes to down 3 seconds \u2013 a 600x improvement.SummaryDatabricks SQL, built on top of the Lakehouse architecture, is the fastest data warehouse in the market and provides the best price\/performance. Now you can get great performance on all your data at low latency as soon as new data is ingested without having to export to a different system.This is a testament to the Lakehouse vision, to bring world-class data warehousing performance to data lakes. Of course, we didn\u2019t build just a data warehouse. The Lakehouse architecture provides the ability to cover all data workloads, from warehousing to data science and machine learning.But we are not done yet. We have assembled the best team on the market, and they are working hard to deliver the next performance breakthrough. In addition to performance, we are also working on a myriad of improvements on ease-of-use and governance. Expect more news from us in the coming year.The TPC does not audit or validate results of benchmarks derived from the TPC-DS and does not consider results of derived benchmarks to be comparable to published TPC-DS results.Try Databricks for freeGet StartedRelated postsDatabricks Sets Official Data Warehousing Performance RecordNovember 2, 2021 by Reynold Xin and Mostafa Mokhtar in Company Blog\nToday, we are proud to announce that Databricks SQL has set a new world record in 100TB TPC-DS, the gold standard performance benchmark...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nick-king","text":"Nick King - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNick KingFounder & CEO at Data KineticBack to speakersNick has been working on enterprise technology platforms for the last 20 years. In his role at Data Kinetic he has focused driving the applied use of AI\/ML with enterprise companies. Previous to Data Kinetic, Nick has worked across multiple startups and open source projects from Snowplow, to DataRobot. He has also held roles at Microsoft, Google, VMware, and Cisco focusing on applied technologies and platforms.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/databricks-on-gcp-free-training-series?itm_data=gcppage-gcpstepbystep","text":"Databricks on GCP free training series - DatabricksFree TrainingDatabricks on Google Cloud step-by-step trainingStart these newly refreshed lessons todayOn-demand trainingWhy use Databricks Lakehouse with Google Cloud? Because you can maximize your analytics impact using the open Databricks platform with greater flexibility, unified infrastructure management and optimized performance. Learn how to get started in this free step-by-step training series.You\u2019ll find out how to:Deploy Databricks Lakehouse on \u2014 or migrate it to \u2014 Google CloudGet integrated data access to Google Cloud Services and cluster managementMeet your most stringent security requirementsTake advantage of the innovative features coming soon to Google CloudSponsor: Databricks (Databricks Privacy Policy)\nCo-sponsor: Google (Google Privacy Policy)SpeakersMina RaoAssociate Technical Curriculum DeveloperDatabricksDave LeBlancStaff Technical Curriculum DeveloperDatabricksDavid HarrisTechnical Curriculum DeveloperSpeaker-david-harrisMark RoepkeSenior Technical Curriculum DeveloperDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/parth-chandra","text":"Parth Chandra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingParth ChandraSoftware Engineer at AppleBack to speakersParth Chandra is a software engineer at Apple working on Spark performance and scalability. He is a PMC (emeritus) member of Apache Drill, and Apache Arrow. Prior to Apple he most recently worked at Mapr on Apache Drill.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/discover\/demos","text":"Centro de demonstra\u00e7\u00e3o de produtos e parcerias da Databricks \u2013 Demonstra\u00e7\u00e3o dos aceleradores de solu\u00e7\u00f5es | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWCentro de demonstra\u00e7\u00e3oCom estes v\u00eddeos sob demanda simples, voc\u00ea ter\u00e1 uma primeira vis\u00e3o da Databricks na perspectiva de um profissional. Cada demonstra\u00e7\u00e3o abaixo vem com materiais relacionados \u2014 incluindo notebooks, v\u00eddeos e e-books \u2014 para que voc\u00ea possa experimentar a Databricks por conta pr\u00f3pria.Comece gratuitamenteDemonstra\u00e7\u00f5es dos produtosPlataforma DatabricksNesta demonstra\u00e7\u00e3o, mostramos uma vis\u00e3o geral da Databricks Lakehouse Platform, incluindo uma discuss\u00e3o sobre a integra\u00e7\u00e3o de projetos de c\u00f3digo aberto, como Apache Spark\u2122, Delta Lake, MLflow e Koalas, no ecossistema da Databricks.Saiba maisDatabricks SQLFluxos de trabalho da DatabricksUnity CatalogData science e machine learningDelta SharingDelta LakeDelta Live TablesIntegra\u00e7\u00e3o de dados do Delta Lake (Auto Loader e COPY INTO)Demonstra\u00e7\u00f5es de parceriasIntegra\u00e7\u00e3o com a nuvem do Azure DatabricksA Azure Databricks Lakehouse Platform oferece o melhor dos data lakes e data warehouses em uma plataforma simples, aberta e colaborativa que se integra com seguran\u00e7a aos seus servi\u00e7os existentes do Azure. Nesta demonstra\u00e7\u00e3o, voc\u00ea ver\u00e1 as integra\u00e7\u00f5es mais comuns do Azure Databricks, como Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI e mais.Saiba maisIntegra\u00e7\u00e3o com a nuvem da Databricks na AWSImplanta\u00e7\u00e3o da Databricks no Google CloudConex\u00e3o de parceirosSolu\u00e7\u00f5es para cada setorSolu\u00e7\u00f5es para cada setorDa ideia \u00e0 prova de conceito (PoC) em apenas duas semanasOs aceleradores de solu\u00e7\u00f5es do Databricks s\u00e3o guias criados especificamente para acelerar os resultados usando notebooks totalmente funcionais e pr\u00e1ticas recomendadas. Os clientes do Databricks economizam tempo de descoberta, design, desenvolvimento e testes. Muitos v\u00e3o da ideia \u00e0 prova de conceito (PoC) em apenas duas semanas.Explorar aceleradoresCrie sua conta Databricks1\/2Primeiro NomeSegundo NomeEmailEmpresaT\u00edtuloTelefone (Opcional)SelecionarPa\u00edsCome\u00e7arProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/egor-gryaznov","text":"Egor Gryaznov - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEgor GryaznovCTO and Co-founder at BigeyeBack to speakersEgor Gryaznov is the co-founder and Chief Technology Officer at Bigeye, the enterprise data observability platform. Egor has spent his career empowering data teams by building powerful solutions for common problems that they face. Before starting Bigeye, Egor was a staff engineer at Uber, where he built and scaled the company\u2019s first data warehouse, from infrastructure to data modeling. In his free time, Egor enjoys cooking and playing with\/being bossed around by his infant son.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/consulting-and-si","text":"Parcerias de consultoria Databricks - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWParcerias de consultoria DatabricksConecte-se com parcerias Databricks em todo o mundo para ajudar voc\u00ea a criar, implantar ou migrar para a Plataforma Databricks LakehouseAs parcerias de consultoria Databricks contam com especialistas posicionados de maneira \u00fanica para ajudar voc\u00ea a implementar e dimensionar data engineering, data science colaborativa, machine learning de ciclo de vida completo e iniciativas de an\u00e1lise de neg\u00f3cios.\nEles trazem sua experi\u00eancia em tecnologia, ind\u00fastria e casos de uso para permitir que voc\u00ea aproveite ao m\u00e1ximo a Plataforma Databricks Lakehouse. Os servi\u00e7os incluem a cria\u00e7\u00e3o de uma estrat\u00e9gia de transforma\u00e7\u00e3o de dados exclusiva para sua empresa, moderniza\u00e7\u00e3o, migra\u00e7\u00e3o, gerenciamento e governan\u00e7a de dados e muito mais.Loading...ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-vo\/#","text":"Chris Vo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris VoLead Member of Tech Staff at AT&TBack to speakersChris Vo has 25+ years of software development experience. He has multiple Azure and Databricks certifications. He earned a Master's Degree in Computer Science at the University of Texas at Dallas (UTD) and a Bachelor's Degree in Computer Science at the University of Texas at Arlington (UTA).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks - Unify All Your Analytics and AI Workloads | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure DatabricksThe data and AI service from Databricks available through Microsoft Azure to store all your data on a simple open lakehouse and unify all your analytics and AI workloads.Get startedSchedule a demoAzure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI and other Azure services to store all your data on a simple, open lakehouse and unify all your analytics and AI workloads.Simple\nUnify your data, analytics and AI\non one common platform for all data use casesOpen\nUnify your data ecosystem\nwith open source, standards, and formatsCollaborative\nUnify your data teams\nto collaborate across the entire data and AI workflowWhy Azure Databricks?50x performance for Apache Spark\u2122 workloads\nDeploy auto-scaling compute clusters with highly optimized Spark that perform up to 50x faster.Learn moreMillions of server hours each day\nAzure Databricks is trusted by thousands of customers who run millions of server hours each day across more than 34\u00a0Azure regions.Learn moreEase of use\nStart with a single click in the Azure Portal, natively integrate with Azure security and data services, and boost productivity by up to 25% with collaborative data engineering and data science.Learn moreIndustry use casesFinancial servicesSwiss ReUnified\u00a0data analytics across data engineering, data science and analysts.HSBC\nBuilt a\u00a0digital payment platform\u00a0using Azure Databricks.ABN AMROImproved analytics workflows\u00a0by enabling collaboration, AI insights and advanced, automated machine learning capabilities.Learn moreRetailHealthcare and life sciencesJoin an Azure Databricks eventDatabricks, Microsoft and our partners are excited to host these events dedicated to Azure Databricks. Please join us at an event near you to learn more about the fastest-growing data and AI service on Azure! The agenda and format will vary, please see the specific event page for details.\u00a0Learn moreOptimized for AzureSeamlessly integrate to Azure data stores and services with specialized connectors for fast data access and\u00a0simplified management\u00a0across your environment. This makes it easy to set up\u00a0security controls,\u00a0manage environments, and\u00a0process\u00a0all your Azure data.Learn moreFeatured integrationsAzure Active DirectorySingle Sign-On\u00a0with Azure Active Directory is the best way to sign in to Azure Databricks. Azure Databricks also supports\u00a0automated user provisioning\u00a0with Azure AD to create new users, give them the proper level of access, and remove users to deprovision access.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultResourcesWhitepapersAzure Databricks for data engineeringAzure Databricks: The Best Platform to Run ML and AIThree Practical Use Cases with Azure DatabricksGetting Started With Apache Spark on Azure DatabricksVideosAli Ghodsi and Rohan Kumar (CVP, Microsoft) Fireside Chat at Keynote Data + AI Summit NA 2021Azure Databricks Cloud Integration DemoIngest data Into Delta Lake on Azure DatabricksExplore your data using Databricks SQLeBooks2021 Gartner Magic Quadrant for Data Science and Machine Learning PlatformsModern Cloud Data Platform for Dummies8 Steps for a Developer to Learn Apache Spark\u2122 With Delta LakeApache Spark\u2122 Under the Hood: Getting started with core architecture and basic conceptsReady to get started?Get startedSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/managed-spark","text":"What is Managed Spark?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWManaged SparkAll>Managed SparkTry Databricks for freeGet StartedWhat is Managed Spark?A managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, manage them with ease and turn them off when the task is complete. Users can also size clusters according to the workload, performance requirements or based on the existing resources. Furthermore, you will be granted access to fully managed Spark clusters that you can dynamically scale up and down in just a few seconds. \u00a0and this can be done even while jobs are processing. In addition, users will be able to turn off clusters when they no longer need them, hence saving money. Managed Spark providers create temporal clusters instead of making provisions and retaining a cluster for all your jobs. Typically they use a cluster of machines with a master node and workers.\u00a0Organizations can concentrate on extracting value out of their data instead of spending their valuable resources on operations. Advantages of Using a Managed Spark Service:Automated Cluster ManagementManaged deployment, logging, and monitoring according to the needs of your particular job let you focus on your data, instead of focusing on the cluster. Your clusters will be stable, scalable, and fast..Resizable ClustersBuilding and configuring Spark clusters is resource-intensive, however this is no longer of your concer as clusters can be created and scaled quickly. nodes are wind down when they're no longer needed. Everything is done on an as-needed basisDeveloper ToolsUsually there are provided multiple ways to manage a cluster.Automatic or Manual ConfigurationHardware and software on clusters is automatically configured for you while also allowing for manual control.Simplicity of ManagementYou will no longer have to stress out on managing the cluster or resource allocation and make any prioritisation through tools such as YARN resource manager.Cost EffectiveUsers only pay for the compute resources that are consumed during the process.Additional ResourcesAbout Apache SparkLearning Spark 2nd Edition eBook8 Steps for a Developer to Learn Apache Spark\u2122 with Delta Lake eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/databricks-named-leader-by-gartner","text":"Databricks Named a Leader | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks Named a LeaderCloud Database Management SystemsDatabricks named a Leader in 2022 Gartner\u00ae Magic Quadrant\u2122 CDBMSDatabricks is proud to announce that Gartner has named us a Leader in the 2022 Magic Quadrant for Cloud Database Management Systems for the second consecutive year.We believe this recognition validates our vision for the lakehouse as a single, unified platform for data management and engineering \u2014 as well as, analytics and AI.Download the report to learn why Gartner named Databricks a Leader and gain additional insight into the benefits that a lakehouse platform can bring to your organization.Access the Report Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/azure-databricks-free-training-series?itm_data=azurepage-azurestepbystep","text":"Azure Databricks free training series - DatabricksFree TrainingAzure Databricks step-by-step trainingCheck out our all-new contentOn-demand trainingGet the latest course content to help you unify your analytics and AI workloads on Azure Databricks. This data and AI service from Databricks is available through Microsoft Azure to help you store all your data on a simple, open lakehouse. In just three training sessions, you\u2019ll get the foundation you need to use Azure Databricks for data analytics, data engineering, data science and machine learning.You\u2019ll learn how to:Ingest event data, build your lakehouse and analyze customer product usageUse SQL to query your data lake with Delta LakeDesign and train an ML customer model in your lakehouseSpeakersMina RaoAssociate Technical Curriculum DeveloperDatabricksDave LeBlancStaff Technical Curriculum DeveloperDatabricksDavid HarrisTechnical Curriculum DeveloperDatabricksMark RoepkeSenior Technical Curriculum DeveloperDatabricksWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/why-attend?itm_data=hp-hamburger-whyattend-dais23","text":"Why Attend - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWhy AttendExplore everything Data + AI Summit has to offer \u2014 from the latest innovations and technologies to thought-provoking panel discussions to networking opportunities where you can connect with other data professionals in your industry.Register nowSession informationWith 10 amazing tracks and over 20 technologies to learn about, get the right experience for your level.\n\u00a0\nData Lakehouse ArchitectureThe decisions you make about your core data architecture will affect the reliability, performance and utility of your data analytics, data science and machine learning. Increasingly, many organizations are adopting the data lakehouse to improve their data platform. Has the ability to more easily combine structured, unstructured and real-time data workloads created new opportunities for data teams? Has ACID reliability on data lakes simplified how data is used? In this track, get answers to these questions and find out how to adopt a data lakehouse, migrate from data lakes and data warehouses, and integrate lakehouses with other data platforms.\nTechnologies\/topic ideas: lakehouse architecture, Delta Lake, Photon, platform security and privacy, serverless, cost management, data warehouse, data lake, Apache Iceberg, Data Mesh\nData GovernanceData governance, security and compliance are critical \u2014 they help guarantee that all data, BI and ML assets are maintained and managed securely across the enterprise and you\u2019re compliant with regulatory frameworks. In this track, learn best practices, frameworks, processes, roles, policies and standards for data governance of structured and unstructured data across clouds.\nTechnologies\/topic ideas: data governance, multicloud, Unity Catalog, security, compliance, privacy\nData SharingWhen enterprises can easily exchange data with their customers, partners, suppliers and internal lines of business, they can better collaborate, innovate and unlock value from that data. In this track, discover best practices for sharing data across data platforms and clouds, ways to avoid replication and lock-in, and how to distribute data products through marketplaces.\nTechnologies\/topic ideas: sharing and collaboration, Delta Sharing, data cleanliness, data cleanrooms, data marketplaces\nData Engineering If you want to optimize data processing and reduce costs, this session is for you. You\u2019ll learn how to use a combination of systems and processes to ingest, orchestrate and transform raw data for analytics and machine learning. Dive into best practices for data architectures, software engineering, ETL, data management, data quality, DataOps and orchestration.\nTechnologies\/topic ideas: data pipelines, orchestration, CDC, medallion architecture, Delta Live Tables, dbt, Databricks Workflows, ETL\/ELT, DataOps, Parquet, Apache Spark internals\nData Streaming Today\u2019s organization needs to respond in real time as events unfold. In this track, learn how data streaming can help you drive faster decision-making, make more accurate predictions and improve customer experiences. Explore best practices for implementing real-time data pipelines with your favorite tools and languages, find out how to reduce complexity for real-time data workflows and eliminate silos to support all your real-time use cases.\nTechnologies\/topic ideas: Apache Spark Structured Streaming, real-time ingestion, real-time ETL, real-time ML, real-time analytics, real-time applications, Delta Live Tables\nDSML: Production ML\/MLOpsOvercome the challenges of putting ML projects into production and operationalizing them at scale. In this track, you\u2019ll find out how to scale ML in production and apply MLOps best practices across the end-to-end machine learning lifecycle.\u00a0\nTechnologies\/topic areas: MLOps, Feature Stores, organizational ML, MLflow, Model Serving and more\nDSML: ML Use Cases\/TechnologiesMachine learning continues to disrupt industries and accelerate business outcomes across use cases and industries. In this track, discover how to apply ML to solve business challenges, explore technologies and best practices, and learn how to integrate data science with the rest of your organization.\u00a0\nTechnologies\/topic areas: PyTorch, TensorFlow, Keras, XGBoost, fast.ai, scikit-learn, Python and R ecosystems, deep learning, notebooks, LLMs and more\nData Warehouses, BI and Visualization Data analytics is a vital component of business decision-making. In this track, find out how to build analytics pipelines and integrations and learn about tooling and infrastructure for SQL analytics, BI and visualization. \u00a0\nTechnologies\/topic ideas: ANSI SQL, Redash, Databricks SQL, Tableau, Power BI, visualization techniques, Spark SQL and DataFrames, data integration, data warehouse and analytics\nResearchIn this track \u2014 dedicated to academic and advanced industrial research \u2014 explore large-scale data analytics and machine learning systems, the hardware that powers them (GPUs, I\/O storage devices, etc.) and how these systems are applied to use cases like genomics, astronomy, image scanning, disease detection, vaccine research and more.\nData StrategyChoosing a data lakehouse platform is only the first step in implementing your data strategy. Success requires a thoughtful approach to people and processes. In this track, you\u2019ll find out how to align goals, identify the right use cases, organize and enable teams, mitigate risk and operate at scale so you can be even more successful with data, analytics and AI.\nTechnologies\/topic ideas: data management, data governance, strategy, data teams, data mesh, data democratization\u00a0\nContent tailored to your roleData + AI Summit has something for everyone \u2014 explore, learn and connect with us and the data, analytics and AI community.\n\u00a0\n\u00a0\nData EngineerIncrease efficiency, control costs and reduce data risks \u2014 all in a day\u2019s work for today\u2019s data engineer. Broaden your knowledge and expand your skills by learning from industry experts and your peers how to deliver high-quality, reliable data for every use case from BI to AI.\nExplore sessionsData ScientistSuddenly, AI is everywhere and that\u2019s putting pressure on data scientists and ML engineers to quickly deliver results. Learn how lakehouse and tools like MLflow can accelerate productionization of models, increase productivity, reduce risk and increase ROI on new models.\nExplore sessionsData AnalystData analytics has moved beyond the warehouse. Join the global community of data analysts at Data + AI Summit and discover ways to support your stakeholders in making informed and timely decisions, achieve line of business KPIs and reduce rework risks.\nExplore sessionsIT Decision MakerData and AI are now mission critical for every business. Learn how the lakehouse architecture unifies data, analytics and AI on a single platform for better performance, lower TCO and faster innovation.\nExplore sessionsIndustry ExperiencesJoin and learn along with your industry peers in these specialized sessions focused on the unique challenges, use cases, and the data, analytics and AI requirements of your sector.\n\u00a0\nFinancial ServicesLearn how to minimize risk, deliver superior customer experience and accelerate innovation on lakehouse.\nDownload PDF\nGovernment and Public SectorLearn how lakehouse is helping to unlock the full potential of data to deliver mission objectives and better serve citizens.\nDownload PDF\nHealthcare and Life SciencesLearn ways to accelerate research and improve patient outcomes on lakehouse.\nDownload PDF\nManufacturingLearn how the lakehouse helps optimize supply chains, boost product innovation, increase operational efficiencies, predict fulfillment needs and reduce overall costs.\nDownload PDF\nCommunications, Media & EntertainmentLearn ways to accelerate audience and advertiser outcomes \u2014 360\u00b0 view of audience, lower churn, increased ARPU \u2014 with lakehouse.\nDownload PDF\nRetail and Consumer GoodsLearn how lakehouse is helping to harness the full power of data so retailers, suppliers and partners can collaborate across the value chain.\nDownload PDF\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/heiko-udluft\/#","text":"Heiko Udluft - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHeiko UdluftChief Technology Officer at Divirod, Inc.Back to speakersHeiko Udluft is proud to be part of the team that is building a data platform for the world\u2019s most valuable asset: WATER. As CTO of Divirod he is building our digital services with a team of developers in close collaboration with Market and Business Development team members. Previously he worked as Product Owner, Tech-Team Lead, and Data Scientist for Airbus Defense and Space GmbH in a business incubator. His background is in Aerospace Engineering with a specialization in Air Transport and Operations. He completed PhD-level research on decentralized control at Delft University of Technology. In this research, he applied Artificial Intelligence methods, specifically Agent-Based Modelling and Simulation, to increase the resiliency of critical infrastructure. Previously, he worked and studied at the Massachusetts Institute of Technology with a focus on improving the capacity and efficiency of a large-scale infrastructure system. His passion is in exploring technology and knowledge that can be implemented on a global scale to sustainably better human lives.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/build-your-own-large-language-model-dolly?itm_data=ml-promocard-dollywebinar","text":"Build Your Own Large Language Model Like Dolly | DatabricksOn DemandBuild Your Own Large Language Model Like DollyHow to fine-tune and deploy your custom LLMAvailable on demandCurious how your company can benefit from large language models (LLM) like ChatGPT? Imagine if you could train your own model \u2014 customized to your specific data to meet your specific needs.Now you can build your own LLM. And Dolly \u2014 our new research model \u2014 is proof that you can train yours to deliver high-quality results quickly and economically.Some of the most innovative companies are already training and fine-tuning LLM on their own data. And these models are already driving new and exciting customer experiences.Watch this webinar to discover how you can harness LLM for yourself. We\u2019ll walk you through examples on how to get started.You\u2019ll learn:How to use off-the-shelf pretrained models with tools like Hugging Face and GPU resourcesHow to fine-tune a model on your dataHow Dolly was builtSpeakerSean OwenPrincipal Product SpecialistDatabricksJoin usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christina-taylor\/#","text":"Christina Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristina TaylorSenior Staff Data Engineer at Catalyst SoftwareBack to speakersChristina is passionate about distributed computing, mutilcloud architecture, scalable data pipelines, the latest and greatest in the open source community. An intensely curious lifelong learner, she builds future-proof open data systems that support advanced analytics, data science, and customer facing use cases. She also has a keen interest in interdisciplinary areas such as Cloud FinOps, DevOps and MLOps. You can find her at Linux Foundation events and educational portals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2023\/03\/14\/real-time-insights-top-three-reasons-why-customers-love-data-streaming.html","text":"Real-Time Insights: The Top Three Reasons Why Customers Love Data Streaming with Databricks - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorReal-Time Insights: The Top Three Reasons Why Customers Love Data Streaming with Databricksby Erika Ehrli, Karthikeyan Ramasamy, Ray Zhu, Richard Tomlinson, Matt Jones and Frank MunzMarch 14, 2023 in Company BlogShare this postThe world operates in real-timeThe ability to make real-time decisions in today's fast paced world is more critical than ever before. Today's organizations need to react instantly to events and quickly access and analyze data in order to get real-time insights and make informed decisions. Simplifying the process of making real-time decisions across different use cases ultimately accelerates innovation, reduces costs, and greatly improves customer experiences.In the last few years we have seen an explosion of real time data constantly generated by every individual, machine and organization. Real time data is everywhere: business transactions in operational systems, customer and partner interactions, third- party data services in the cloud, and IoT data generated by sensors and devices.All this real time data creates new opportunities to build innovative applications such as fraud detection, personalized offers for customers, vaccine distribution, smart pricing, in-game analytics, predictive maintenance, content recommendations, connected cars and more.Data streaming is the keyData streaming is data that is continuously and\/or incrementally flowing from a variety of sources to a destination to be processed and analyzed in near real-time. This unlocks a new world of use cases around real-time ETL, real-time analytics, real-time ML, and real-time operational applications that in turn enable faster decision making. To harness the power of real-time data, organizations must broadly embrace data streaming across multiple use cases and simplify adoption of technology to boost differentiation within their markets.However many platforms do not provide a unified and simplified approach for streaming across all use cases. According to IDC, less than 25% of enterprises have adopted data streaming across the enterprise. Many organizations manage to successfully implement use cases leveraging data streaming pipelines for one off use cases, but struggle to make data streaming the norm vs the exception. So why is this?Challenges adopting data streamingIn reality, data streaming is really hard for most organizations. This is for several reasons:Specialized API's and language skills: Data practitioners encounter barriers to adopting streaming skillsets because there are new languages, APIs and tools to learn.Operational complexity: To implement data streaming at scale, data teams need to integrate and manage streaming-specific tools and cloud services. They also have to manually build complex operational tooling to help these systems recover from failure, restart workloads without reprocessing data, optimize performance, scale the underlying infrastructure and so on.Incompatible governance models: Different governance and security models across real-time and historical data platforms makes it difficult to provide the right access to the right users or see the end to end data lineage, and meet compliance requirements.How the Databricks Lakehouse Platform makes data streaming simpleThe Databricks Lakehouse Platform overcomes these challenges by making data streaming incredibly simple. Enabling every organization to deliver real time analytics, machine learning and applications on one platform. This is for 3 main reasons:It enables all your data teams. With Databricks, data engineers, data scientists, and analysts can easily build streaming data workloads with the languages and tools they already know and the API's they already use.It simplifies development and operations. Databricks give you out of the box capabilities that automate much of the production aspects associated with building and maintaining real-time data pipelines.It offers a unified platform for streaming and batch data. Databricks helps you eliminate data silos, centralize your security and governance models for all your use cases across clouds.Many of our customers, from enterprises to startups across the globe, love and trust Databricks. We have over 9,000 global customers across all industries building amazing solutions and delivering business impact with the lakehouse architecture. When it comes to data streaming, many of our customers such as AT&T, Walgreens, Columbia Sportswear, Edmunds, US Department of Transportation, Akamai, Kythera Labs and more\u00a0moved to the lakehouse and have seen fantastic success.The Databricks Lakehouse Platform is a preferred choice for many organizations. Here are the top three reasons why customers love data streaming on the Databricks Lakehouse Platform:1. The ability to build streaming pipelines and applications fasterThe Databricks Lakehouse Platform unlocks data streaming for the data teams you have in place today enabling you to build streaming data pipelines and real-time applications faster than ever before.Analysts, analytics engineers, data scientists and data engineers can easily build streaming pipelines using the tools and languages they are already familiar with like SQL and Python and avoid learning new languages and API's or specialized streaming technology.Delta Live Tables (DLT) turns SQL analysts into data engineers. Simple semantic extensions to SQL languages enable them to work with streaming data right away. For example using Delta Live Tables practitioners can add the word 'streaming' to a simple create table statement to create a streaming pipeline. Instead of low-level hand-coding of ETL logic, data engineers can build declarative pipelines \u2013 easily defining 'what' to do, not 'how' to do it. DLT automatically manages all the dependencies within the pipeline. This ensures all tables are populated correctly, continuously or on a set schedule.Both DLT and Spark Structured Streaming provide unified API's for streaming and batch workloads so data engineers and developers can build real-time applications with minimal changes to existing code and they can also continue to work in the same notebooks and SQL editors they already use and avoid learning new tools and IDE's.In technology and software, Statsig helps developers make better decisions by introducing end-to-end observability for each product update they launch. Using Databricks, Statsig can stream data faster, which means it ingests data faster, starts jobs earlier and lands jobs on time. Statsig's data pipelines ingest more than 10 billion events a day. Its systems are certified for the highest compliance standards in the industry to manage and secure data, and they serve those billions of user interactions at 99.9% availability with built-in redundancy.\"With the Databricks Lakehouse Platform, the actual streaming mechanics have been abstracted away \u2026 this has made ramping up on streaming so much simpler.\" \u2014 Pablo Beltran, Software Engineer, Statsig2. Simplified operations with automated toolingDeveloping code fast is a significant benefit but you then have to put that code into production. Customers frequently tell us they spend a huge amount of time writing and maintaining code to support the operational aspects of their streaming data pipelines. In fact this is often the lion's share of the overall effort. With Databricks the burden of building and maintaining operational tooling is significantly reduced through automated capabilities that come right out of the box.Products like Delta Live Tables automate the complex and time consuming aspects of building streaming data pipelines like the ability to automatically recover from failure, autoscaling the underlying compute infrastructure, optimizing performance and much more.You also get fully comprehensive monitoring to understand the health and performance of every aspect of your data pipelines and the ability to set up rules to automatically test and maintain data quality in real-time. You can define data quality and integrity controls, and address data quality errors with flexible policies such as being able to alert on, drop, or quarantine bad data or even fail pipelines.Developing and testing data pipelines to catch issues early without impacting production is really hard. Data engineering & analyst teams lack the tools to implement known CI\/CD software-best practices for developing and testing code.In manufacturing, Honeywell's Energy and Environmental Solutions division uses IoT sensors and other technologies to help businesses worldwide manage energy demand, reduce energy consumption and carbon emissions, optimize indoor air quality, and improve occupant well-being. Using Delta Live Tables on the Databricks Lakehouse Platform, Honeywell can now ingest billions of rows of sensor data into Delta Lake and automatically build SQL endpoints for real-time queries and multilayer insights into data at scale \u2014 helping Honeywell improve how it manages data and extract more value from it, both for itself and for its customers.\"Databricks helps us pull together many different data sources, do aggregations, and bring the significant amount of data we collect from our buildings under control so we can provide customers value.\" \u2014 Dr. Chris Inkpen, Global Solutions Architect, Honeywell Energy and Environmental Solutions3. Unified governance for real-time and historical dataReal-time data typically resides in message queues and pub\/sub systems like Apache Kafka and is separate from historical data found in data warehouse. This creates governance challenges for data engineers and data administrators trying to manage access to all data holistically across the enterprise.Unity Catalog solves this problem by providing a single data governance model for both real-time and historical data in one place. With Unity Catalog you can unify access and auditing for all your data across any cloud. It also offers the industry's first open data sharing protocol enabling you to securely share data and collaborate with all your lines of business and even external organizations across the world.And data in Unity Catalog becomes instantly discoverable for everyone in your organization providing complete visibility for faster insights and automatically provides comprehensive lineage that provides visibility into how data flows for impact analysis, including how it was transformed and used for every single real-time use case.In technology and software, Grammarly's trusted AI-powered communication assistance provides real-time suggestions to help individuals and teams write more confidently. By migrating to the Databricks Lakehouse Platform, Grammarly is now able to sustain a flexible, scalable and highly secure analytics platform that helps 30 million people and 50,000 teams worldwide write more effectively every day. Using the lakehouse architecture, data analysts within Grammarly now have a consolidated interface for analytics. To manage access control, enable end-to-end observability and monitor data quality, Grammarly relies on the data lineage capabilities within Unity Catalog. By consolidating data onto one unified platform, Grammarly has eliminated data silos.\"The ability to bring all these capabilities, data processing and analysis under the same platform using Databricks is extremely valuable. Doing everything from ETL and engineering to analytics and ML under the same umbrella removes barriers and makes it easy for everyone to work with the data and each other.\" \u2014 Sergey Blanket, Head of Business Intelligence at GrammarlyGet started with data streaming on the lakehouseThe Databricks Lakehouse Platform dramatically simplifies data streaming to deliver real time analytics, machine learning and applications on one platform. The top three reasons why Databricks customers love data streaming on the lakehouse are the ability to build streaming pipelines and applications faster, simplified operations from automated tooling and unified governance for real time and historical data.If you're looking to democratize data streaming across your organization and take your real-time decision-making to the next level for all your use cases, learn more about Data Streaming on the Lakehouse.Watch our Data Engineering and Data Streaming virtual event if you want to see sessions, demos, best practices and more success stories that showcase how to build and run modern data pipelines to support real-time analytics, ML, and applications on the lakehouse.Try Databricks for freeGet StartedRelated postsBuild Reliable and Cost Effective Streaming Data Pipelines With Delta Live Tables\u2019 Enhanced AutoscalingDecember 8, 2022 by Paul Lappas, Li Zhang, Alex Ott, Kiavash Kianfar, Yuhong Chen and Prashanth Babu Velanati Venkata in Platform Blog\nThis year we announced the general availability of Delta Live Tables (DLT), the first ETL framework to use a simple, declarative approach to...\nDelta Live Tables Announces New Capabilities and Performance OptimizationsJune 29, 2022 by Paul Lappas and Michael Armbrust in Product\nSince the availability of Delta Live Tables (DLT) on all clouds in April (announcement), we've introduced new features to make development easier, enhanced...\nLow-latency Streaming Data Pipelines with Delta Live Tables and Apache KafkaAugust 9, 2022 by Frank Munz in Product\nDelta Live Tables (DLT) is the first ETL framework that uses a simple declarative approach for creating reliable data pipelines and fully manages...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/francisco-rius","text":"Francisco Rius - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFrancisco RiusHead of Data Science and Data Engineering at Minecraft at MicrosoftBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nic-jansma\/#","text":"Nic Jansma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNic JansmaSenior Principal Lead Engineer at AkamaiBack to speakersNic is a software developer at Akamai building high-performance websites, apps and open-source tools, and co-chair of W3C Web Performance Working Group.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/datin-ts-habsah-binti-nordin","text":"Datin Ts. Habsah Binti Nordin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDatin Ts. Habsah Binti NordinChief Data Officer at PETRONASBack to speakersDatin Habsah Nordin is the Head of Enterprise Data at PETRONAS. She is responsible for orchestrating PETRONAS\u2019 data strategy with the aim to liberate data seamlessly, and institutionalize a center of excellence for Data in PETRONAS and oversees the efforts to build the Enterprise Data Hub (EDH) and scale advanced analytics across the organization.\nDatin Habsah is a PETRONAS scholar and holds a Bachelor of Science (Bsc) in Computer Science from the Case Western Reserve University, USA. She joined PETRONAS in 1995 and has since held various leadership roles in IT, Strategic Planning, Business Development, Marketing, Transformation, Internal Audit, Project Management, Data and Knowledge Management.\nPrior to her current role, Datin Habsah was involved in few successful transformation initiatives that focused on business and operating model design. She is now a Board Member of PTSSB DMCC, a company incorporated in the United Arab Emirates (UAE). Since 2021, she been appointed as the first female President of Kelab Sukan and Rekreasi PETRONAS (KSRP) been formed since 1976, and Chairman of the Board for Twin Towers Fitness Center.\nDatin Habsah has completed the INSEAD Leadership Programme (Duke Program) focusing on Strategic Excellence. She is a certified solution-focused coach accredited by the Canadian Council of Professional Certification (CCPC Global Inc) and Certified Data Management Professional accredited by DAMA. She is Adjunct Lecturer and Industry Advisory Panel for University Teknologi PETRONAS in the area of Computer & Information Science Department for undergraduate and postgraduate program.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/trust\/report","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueReport NowHelp investigate a security incident in your Databricks workspaceIf you suspect your workspace data may have been compromised or you have noticed inconsistencies or inaccuracies in your data, please report it to Databricks ASAP.\u00a0Report SPAM or suspicious communications originating from DatabricksIf you have received SPAM or any communications that you believe are fraudulent, or that have inappropriate, improper content or malware, please contact Databricks ASAP.\u00a0Understand an internal vulnerability scanner report against a Databricks productFor help analyzing a vulnerability scan report, please raise a support request through your Databricks support channel, submitting the product version, any specific configuration, the specific report output and how the scan was conducted.\u00a0Understand how a CVE impacts a Databricks workspace or runtimeIf you need information on the impact of a third-party CVE, or a Databricks CVE, please raise a support request through your Databricks support channel, and provide the CVE description, severity and references found on the\u00a0National Vulnerability Database\u00a0Report a bug in Databricks products or servicesIf you have found a reproducible vulnerability in any of our products, we want to know so that we can resolve it. Please join\u00a0our public bug bounty program\u00a0facilitated by HackerOne.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-tang\/#","text":"Mike Tang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike TangAssociate Director, Responsible AI at VerizonBack to speakersXuning (Mike) Tang has more than a decade of academic and industrial experience in machine learning, natural language processing, and big data technologies. He is enthusiastic about applied research and solving complex business problems with cutting-edge technologies. He has managed large teams to build advanced analytics solutions for major manufacturing, hospitality, and banking companies, as well as Am Law 100 law firms. Before joining Verizon, Mike was the leader of Berkeley Research Group (BRG)\u2019s Artificial Intelligence & Machine Learning practice, where he initiated BRG\u2019s ethical AI market offering. Prior to that, he worked for Deloitte and Fannie Mae.\nMike earned his Ph.D. from Drexel University in the College of Computing and Informatics. He has filed multiple patents and inventions and published more than 40 peer-reviewed research papers in top computer science journals and international conferences. He also serves as an associate editor and reviewer for multiple flagship journals in Artificial Intelligence and Machine Learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pedro-boareto","text":"Pedro Boareto - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPedro BoaretoChapter Leader of Analytics Engineering at BradescoBack to speakersExpert in Big Data and Analytics, currently leading Analytics Engineering in Bradesco's Open Banking Project and phD student. He has a background in industrial engineering, with a master's in industrial and system engineering focused on healthcare process improvements. Has extensive experience in automation, data warehousing, cost optimization, and architecture solutions. He's also a voluntary data analyst at a public hospital. In his free time, he enjoys movies, exercise, and cooking.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/via","text":"Via | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYBuilding an operationally efficient omnichannel businessR$3.9 millionin savings due to improved productivity25%reduction in compute costs INDUSTRY: Retail and consumer goods SOLUTION: Customer lifetime value,demand forecasting,safety stock analysis,threat detection,subscriber churn prediction PLATFORM USE CASE: Lakehouse,Delta Lake,machine learning,Databricks SQL,ETL CLOUD: AzureThe Databricks Lakehouse has allowed us to unlock the power of analytics and machine learning. Now we can harness all our data to deliver industry-leading shopping experiences while upping operational efficiency.\u201d\n\u2013 Cezar Steinz, Manager of MLOps at ViaBrazilian customers rely on Via (formerly Via Varejo) for a wide selection of goods and services \u2014 from consumer electronics and home appliances to furniture and credit cards. But with decades of siloed data influencing different business decisions and a Hadoop data warehouse that was complex and didn\u2019t foster ML innovation, Via struggled to accurately forecast demand, which impacted their entire supply chain. By unifying data and analytics on the Databricks Lakehouse Platform, Via was able to develop a scalable architecture that enables data access throughout the organization. This enabled faster time-to-market to operationalize machine learning and provided insights that surface critical consumer trends to optimize business operations, prevent fraudulent activities and create a more targeted retail experience across touch points.Bringing together decades of disconnected dataConsumers have been shopping with Via, a major Brazilian retailer with nearly 100 million customers, for over 60 years. But with decades of misaligned data and siloed channels impacting how decisions had been \u2014 and were still being \u2014 made across the organization, Via\u2019s data team struggled to piece together a complete picture of consumer demand to shape business operations and supply chain considerations.Due to the longevity and nature of the business, Via had many traditional transaction environments, including a mainframe built on Hadoop. Over the years, they had consolidated this with a Teradata data warehouse that was complex to manage and unable to support the needs of their data scientists, forcing them to build and train models on individual laptops. Without the ability to collaborate and scale training against their entire data set, data scientists could not wholly assess insights in context with related information.\u201cCollaboration was a big pain point, and so was scalability,\u201d said Cezar Steinz, Manager of MLOps at Via. \u201cWe needed to train our models with complete data. That can be more than 24 billion rows of information. It\u2019s impossible to train those kinds of models on a laptop.\u201dThis led to decreased accuracy in analysis, which destabilized everything from the customer journey to fraud prevention \u2014 eventually undercutting revenue and slowing growth. Via realized that in order to fully empower their data scientists and analysts, they needed not only a common data layer, but also the ability to efficiently and collaboratively operationalize their data to help with supply chain optimization, demand forecasting and more. To build a unified data structure and streamline analytics and ML, Via turned to Databricks.Data governance, fraud prevention and consumer demandThe Databricks Lakehouse Platform on Azure has enabled Via to access insights that lead to better business decisions \u2014 including calculating churn, determining the next best offer or action (NBO\/NBA), detecting and mitigating fraud, and developing pricing models that drive conversions and finance services (credit personalization and other payment methods).With the lakehouse approach, Via now has a common view of their data for analytics and ML. Delta Lake is used to provide data consistency and reliability as the company builds ETL pipelines to feed BI dashboards via integrations with Power BI as well as support the training of ML models. More importantly, they are able to deliver with high performance and confidence, which is paramount to meeting their daily decision-making needs.\u201cDatabricks gives us better data governance,\u201d said Steinz. \u201cWith Delta Lake, an analyst can access the exact data needed to address the specific use case at hand \u2014 if we\u2019re talking about a logistics carrier, for example, we access just the relevant logistics data tables. It\u2019s ideal that we can share specific data with the right people.\u201d Delta Lake also offers Via better traceability so that they can have a better understanding of how their data is being used and whether they can reuse some of their data in different ML models.Feature Store, a centralized repository of features, has provided Via\u2019s data scientists and analysts with the ability to easily share and discover features. This has allowed them to truly unify not only their data, but also the teams that are accessing and using the data to make better and smarter decisions for the business. \u201cDatabricks Feature Store enables us to create a robust and stable environment for creating and reusing features consumed by models,\u201d said Steinz. \u201cThis has enabled our data scientists and analysts to be more productive, as they no longer have to waste time converting data into features from scratch each time.\u201dWith their data centralized in the lakehouse, their analysts use Databricks SQL to quickly analyze data and share insights with the rest of the business through Power BI dashboards and reports. And with MLflow, Via\u2019s data scientists are able to easily manage the entire ML lifecycle \u2014 from tracking model versions to running experiments and reviewing results. \u201cCreating a project with MLflow is of paramount importance, as it makes it feasible to package a model for us to run on any platform,\u201d explained Steinz. \u201cThis means we are no longer limited to how we deploy ML to influence our business.\u201dData democratization and streamlined ML modelsWith data performance humming and data science working with all their data, Via has been able to rapidly develop and deploy ML models that help with churn prediction, product recommendations, fraud and credit analysis, and customer behavioral analysis. These various use cases have allowed Via to deliver a shopping experience that is secure and highly targeted to meet the needs of their fickle customers \u2014 resulting in increased conversion and customer lifetime value. On the analytics front, a unified view into their data gives them the ability to extract insights that help guide strategies from streamlining supply chain operations to opportunities for new product innovations that delight their customers.From an operational perspective, Databricks has helped reduce compute costs and boost cross-team collaboration. Across the entire data organization, Via has realized a 30% increase in productivity, resulting in an estimated total savings of R$ 3.9 million. With the help of Feature Store and automated cluster management, they have also seen a drop in data processing costs of 25%.\u201cOur data department has grown exponentially as we meet business expectations with fast, consistent and high-value deliveries,\u201d expressed Steinz. \u201cThis is only possible because of the Databricks Lakehouse Platform and the experts behind it.\u201dLooking ahead, with the democratization of data deeply ingrained in their culture, Via is well prepared to achieve their mission to make their customers\u2019 dreams come true by leveraging data and AI to deliver the best possible buying experience.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speakers","text":"Speakers - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpeakersBrowse the roster to find new and familiar faces alike. The Data + AI Summit draws experts from all over the globe across a wide array of fields.\nFeatured speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAll speakersAayush PatelData & Platform EngineerSkywatchAbhishek PatelHead of Databricks COELTIMindtreeAdam WilsonCo-Founder, Chief of ProductDivirod, Inc.Adi PolakData & AI TechnologistTechnologistAdriana IspasStaff Product ManagerDatabricksAikaterini KalouPrincipal Data ScientistCitrixAjali SenSenior ManagerAccentureAjmal AzizSolutions ArchitectDatabricksAkira AjisakaSenior Software Development EngineerAmazon Web ServicesAlain BrianconVP Data Science Profiles by KantarKantar GroupAlbert HuSenior Analytics EngineerRec RoomAlessandro GaravagliaLead ML EngineerGucciAlexander BoothAssistant Director of Research & DevelopmentTexas Rangers Baseball Club, LLCAlexander VanadioPrincipal ConsultantOptivAli GhodsiCo-founder and CEODatabricksAlon GubkinCo-Founder & CTOAporiaAman KapoorHead of Data PlatformPetronasAmanda MilbergSenior Partner Sales EngineerDataikuAmine BenhamzaLead Solutions ArchitectDatabricksAmir SkovronikDistinguished Software EngineerAkamaiAmrinder Singh OberaiEMR Migrations LeadDatabricksAnanya GhoshBusiness Application Owner for DatabricksNationwide InsuranceAndrew BlanceInnovation ConsultantWaterstonsAndria FuquenTechnical Program ManagerImmutaAndy HanksSenior Data Architect, Analytics PlatformCRISP Shared ServicesAnfisa KaydakVP, Data Product & EngineeringHealthverityAngela ChuSenior Solution ArchitectDatabricksAnil PuliyerilSenior ArchitectHabuAnindita MahapatraLead Solutions ArchitectDatabricksAnindya SahaML Platform Software EngineerAnkit MathurTech Lead, Model Serving GPUsDatabricksAnna RussoGlobal Director of Data ScienceGucciAnton OkolnychyiSoftware EngineerAppleAntoni BaumSoftware EngineerAnyscaleAntonio CasteloCollibraAnup SeguCo-Head of Data EngineeringYipitDataArtem MeshcheryakovConsultantORAYLIS GmbHArthur LiSenior Software EngineerInstacartArujit PradhanSoftware EngineerCoinbaseArun PamulapatiSr. Staff Security Field EngineerDatabricksAshwin GangadharSenior Solutions ArchitectMongoDBAtiyah CurmallyPrincipal Environmental SpecialistInternational Finance CorporationAustin FordStaff Product ManagerDatabricksAvinash SooriyarachchiSenior Solutions ArchitectDatabricksBalaji RamanujamAVP - Senior Principal Technology ArchitectInfosysBasak EskiliML EngineerAhold DelhaizeBehzad BordbarLead Data ScientistMarks & SpencerBeinan WangSenior Staff Software EngineerAlluxioBen CoppersmithSr. Manager, Data PlatformDisney StreamingBen WilsonPrincipal Specialist Solutions ArchitectDatabricksBeth MattsonSenior Data EngineerOur Family WizardBin MuVice President and Head of Data & AnalyticsAdobeBinwei Yangsoftware engineerintelBlaise SandwidiLead Data Scientist, As. ESG Officer, PhDInternational Finance Corporation (IFC)\u2013World Bank GroupBob ZhangSenior Technical Program ManagerMicrosoftBrad CorwinChief Data ScientistBooz Allen HamiltonBradley AxenMachine Learning EngineerBlockBrendan BarsnessData and Analytics ArchitectDeloitteBrooke WenigDirector, Machine Learning PracticeDatabricksCan ElfeogluStaff Product ManagerDatabricksCelia KungEngineering ManagerDatabricksChang SheCEOLanceDBChao SunSoftware EngineerAppleChen GuoStaff Software EngineerCoinbaseChris StevensSenior Staff Software EngineerDatabricksChris VoLead Member of Tech StaffAT&TChris InkpenSolutions architectHoneywellChris HechtDatabricksChris MantzData ArchitectSlalomChristian Acu\u00f1aSenior Data EngineerGrammarlyChristian HamiltonDirector, Data Science Technology84.51Christina TaylorData EngineerToptalChristina TaylorSenior Staff Data EngineerCatalyst SoftwareChristopher LocklinEngineer Manager, Data PlatformGrammarlyChunxu TangResearch ScientistAlluxioCody FergusonData & AI Management Branch ChiefChief Digital and Artificial Intelligence Office - AdvanaCorey ZumarSoftware EngineerDatabricksCorey ZwartChief Technology OfficerPumpJack DataworksCort LunkeData & Analytics Lead - TruterraLand O'LakesCraig WileySr. Director of Product, Lakehouse AIDatabricksCyrielle SimeonePrincipal Product Marketing ManagerDatabricksDael WilliamsonField CTODatabricksDan HoustonManager, Data Science and Exploration Advanced AnalyticsUSPSDan SmithHead of Technology Data & AnalyticsPerenti GroupDanica FineSenior Developer AdvocateConfluentDaniel TenedorioSr. Staff Software EngineerDatabricksDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL)MITDarshana SivakumarStaff Product ManagerDatabricksDarth VaderSith LordThe Galactic EmpireDatin Ts. Habsah Binti NordinChief Data OfficerPETRONASDavid SkinnerChief Strategy OfficerAcxiomDavid TempelmanResident Solutions ArchitectDatabricksDawn SongProfessor, Department of Electrical Engineering and Computer ScienceUC BerkeleyDeepa ParanjpeDirector of EngineeringDiscoveryDeepak SekarSr. Solution ArchitectDatabricksDenny LeeSr. Staff Developer AdvocateDatabricksDerek SlagerCTOAmperityDerek SugdenAd Measurement Lead \u2013 Measurement & AttributionEffectvDevlina DasSenior Software EngineerInstacartDeylo WooData Engineer ArchitectProvidence Health ServicesDilip BiswalSenior ArchitectAdobeDillon BostwickSolutions ArchitectDatabricksDipankar MazumdarDeveloper AdvocateDremioDon ScottVP, New Product DevelopmentHitachi Solutions AmericaDon Bosco DuraiCofounder and CTOPrivaceraDonghwa KimSr. Director of IT ArchitectureOntada, a McKesson CompanyDouglas MooreLead Specialist Solutions ArchitectDatabricksDurga KalaSr. DirectorVisa Inc.Egor GryaznovCTO and Co-founderBigeyeEllen SulcsDirector, Data Products & EngineeringT-MobileEllie HajarianSnr IT ManagerTD BankElliot ShmuklerCo-Founder & CEOAnomaloEmad MostaqueCEOstability.aiEric PeterSr Staff Product ManagerDatabricksEric SchmidtFormer CEO and Chairman, Google; Co-FounderSchmidt FuturesErika EhrliSenior Director of Product MarketingDatabricksErin BoelkensVP of ProductLiveRampErni DurdevicSpecialist Solutions Architect (Geospatial)DatabricksFabian JakobsSr Staff Software EngineerDatabricksFabien CochetIT Expert on Data and AnalyticsMichelinFabio Luis Correia da SilvaArchitecture SpecialistBradescoFaraz YasrobiSoftware EngineerGrammarlyFrancisco RiusHead of Data Science and Data EngineeringMinecraft at MicrosoftFranco PatanoProduct SpecialistDatabricksFrank MunzPrincipal Technical Marketing EngineerDatabricksGanesh DeivarayanSr ManagerAmerican AirlinesGaurav SarafProduct ManagerDatabricksGavita RegunathPrincipal Data ScientistAdvancing AnalyticsGeoffrey FreemanSolutions ArchitectT-MobileGidon GershinskyLead Systems ArchitectAppleGilad AsulinBig Data Engineer Team LeaderAkamai Technologies, IncGreg NelsonVP of Data OperationsHighmark HealthGreg KroleskiProduct ManagementDatabricksGregory LittleDCDAO for Enterprise Platforms and Business OptimizationDoD CFO Transformation OfficeHannes M\u00fchleisenCo-Founder and CEODuckDB LabsHao ZhuSenior ManagerNVIDIAHari ShankarSenior Director, R&DVizioHari RajaramSr Director \/ Principal Data ArchitectProcoreHarrison ChaseCEOLangChainHarsh MishraLead Enterprise ArchitectAustralian Rail Track CorporationHeiko UdluftChief Technology OfficerDivirod, Inc.Himanshu AroraResident Solutions ArchitectDatabricksHimanshu RajaDatabricksHitesh SahniHead of Cloud Data Platforms and Data Engineering SolutionsDeutsche Post DHLHolly SmithSenior Resident Solutions ArchitectDatabricksHuaxin GaoSoftware EngineerAppleHyukjin KwonStaff Software EngineerDatabricksIan SotnekDirector of ProductAI Squared, IncIan GallowaySenior Director, ApplicationsCollins AerospaceIfigeneia DerekliField Engineering Manager & Unity Catalog SpecialistDatabricksIoannis PapadopoulosCloud TechnologistDatabricksItai YaffeSenior Big Data ArchitectAkamaiIvan PengSoftware EngineerDoorDashJacek LaskowskiIT Freelancerjapila.plJackie BrosamerDirector of Software EngineeringBlockJacob RennChief TechnologistAI Squared, IncJacolon WalkerCo-founder & CTOMonadJaison DominicSenior Manager Information SystemsAmgenJames DemmelDr. Richard Carl Dehmel Distinguished ProfessorUniversity of California, BerkeleyJames NormanPrincipal Software EngineerNikeJamie BakerDirector of ProductMatillionJason ShiverickData Platform ManagerRivianJay BhankhariaSenior Director, Data PartnershipsDatabricksJay YangPrincipal Data EngineerProcoreJeff Breeding-AllisonSenior Data ScientistMars PetcareJeff MrozTechnical SME for Cloud and Big DataWoolpert \/ US Army Corps of EngineersJeffrey HessLead TechnologistBooz Allen HamiltonJeffrey ParkinsonVP, Core Data EngineeringNorthwestern MutualJeffrey ChouCo-Founder, CEOSync ComputingJegadeesan PugazhenthiLead Big Data EngineerAT&TJeremy LewallenProduct ManagerDatabricksJiajun YaoSoftware EngineerAnyscaleJim HibbardSenior Developer AdvocateDatabricksJim ThorstadSolutions ArchitectDatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchUniversity of California at BerkeleyJoanna GurryExecutive, Data DeliveryNational Australia Bank (NAB)Joe WalshDirector of Measurement & AttributionEffectvJohn RousselCIOCalifornia Department of Public Health (CDPH)John ThompsonGlobal Head, Artificial IntelligenceEYJohn KutayDirector of Product ManagementStriimJon OsbornField CTOAscend.ioJonathan KellerSr. Director, Product ManagementDatabricksJonathan HollanderVP, Enterprise Data Technology PlatformsTD BankJonathan NeoData EngineerCanvaJordan PeckPrincipal Technical Account ManagerSnowplowJordan DonmoyerManager, Customer Data SolutionsThe Hershey CompanyJoseph SarsfieldMachine Learning EngineerMarks & SpencerJoseph BradleyLead Product SpecialistDatabricksJules DamjiLead Developer AdvocateAnyscaleJulie FerrisVice President, Commercial OptimizationDefinitive HealthcareJulien Le DemChief ArchitectAstronomerJun Rong LauData Engineer\/AnalystGrabTaxi Holding Pte LtdJunta NakaiRVP, Industry Solutions, Financial Services and SustainabilityDatabricksJustin BreeseSr. Product ManagerDatabricksJustin DeBrabantSVP of ProductActionIQJustin LaiDistinguished Data ArchitectBlackBerryJustin ThompsonDirector, IT Data and AnalyticsJetBlueKarthik RamasamyHead of StreamingDatabricksKasey UhlenhuthStaff Product ManagerDatabricksKeith AndersonSolution PrincipalHitachi SolutionsKeshav SanthanamPhD StudentStanford UniversityKetan GanatraSolution ArchitectDatabricksKieran TaylorSenior Software Engineer IIInstacartKrishti BikalSenior Executive - Director BI & AnalyticsEmeraldKyle HaleProduct SpecialistDatabricksKylie TaylorData ScientistMars PetcareLakhan PrajapatiDirector of Architecture and EngineeringZS associatesLarry FeinsmithHead of Global Tech Strategy, Innovation and PartnershipsJP Morgan Chase & Co.Lee YangSr. Principal SW EngineerNVIDIALeena DalviAssistant Vice President, Enterprise Data & AnalyticsNavy Federal Credit UnionLeo DuncanSr. Solutions ArchitectKyvos Insights Inc.Leon EllerSolutions ArchitectDatabricksLewis MbaeHead of Customer EngineeringRudderStackLin QiaoCo-creator of PyTorch, Co-founder and CEOFireworksLindsay MicoHead of Data ScienceProvidence HealthLindsey WoodlandExecutive Vice President, Client Data Science605Lior GavishCTO and Co-founderMonte Carlo DataLiping HuangSenior Solutions ArchitectDatabricksLorenzo De TomasiData Architect, Data Platforms Lead at BarillaBarilla G. e R. Fratelli S.p.A.Lucas dos Santos CelestinoPlatform Product ManagerAB InbevLuk VerhelstData ArchitectVolvo Group (consultant)Luyang WangLead Distinguished ScientistVerizonMacGregor WinegardAssociate Data EngineerKPMGMaciej SzpakowskiCo-founderProphecyMadalina TanasieChief Technology OfficerCollibraMaggie DavisPrincipal, Data EngineeringSlalomMahesh PrakriyaDirector in Intelligence PlatformMicrosoftMalav ShahSenior Data ScientistDIRECTVManbir PaulVP of Engineering, Data Insights and MarTechSephoraMani KandasamyTech FellowDeloitte Consulting LLPManu SharmaCEOLabelboxMarcel KramerHead of Data EngineeringABN AMRO Bank N.VMaria VechtomovaML EngineerAhold DelhaizeMaria DaibertData Platform Product ManagerAB InbevMarianna CervinoGlobal Data ScientistGucciMarius PangaSolutions ArchitectDatabricksMark LeeSenior Specialist Solutions ArchitectDatabricksMark D'AndreaGlobal Chief Revenue OfficerAccuweatherMartin GrundSenior Staff Software EngineerDatabricksMat KeepSenior Director, MongoDB Products TeamMongoDBMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflowDatabricksMatt McKenzieGM, TechnologyTabcorpMatteo QuattrocchiDirector, Policy-EMEABSAMatthew HayesVice President of SAP BusinessQlikMatthew PowersDeveloper AdvocateDatabricksMatthew HayesSoftware EngineerDatabricksMatthew DoxeySenior EpidemiologistWashington State Department of HealthMatthew KarasickChief Product OfficerHabuMaxime AgostiniCEOSarus Technologies IncMeena RamSr Director, Enterprise Data and Records Management OfficeCIBCMegan FogalSolutions ArchitectDatabricksMenglei SunSenior Software EngineerDatabricksMiao WangSenior Engineering ManagerAdobeMichael ShtelmaLead Specialist Solutions ArchitectDatabricksMichael ArmbrustDistinguished EngineerDatabricksMichael GreenSenior Data ScientistHitachi Solutions AmericaMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious DiseasesCalifornia Department of Public Health (CDPH)Michael SankyRVP, Industry Solutions, Healthcare and Life SciencesDatabricksMike ConoverSoftware EngineerDatabricksMike TangAssociate Director, Responsible AIVerizonMike Del BalsoCo-founder + CEOTectonMilos ColicTech Lead EMEA Public Sector - Sr. Solutions ArchitectDatabricksMiranda LunaProduct ManagementDatabricksMitch ErtlePartner Solutions EngineerSigma ComputingMohan KolliIT DirectorLabCorpMorgan HsuDirector, Data and ML EngineeringFanDuelMostafa MokhtarPrincipal Software EngineerDatabricksMurali MadireddiArchitectAccentureNabil RaadSVP of Data and AnalyticsGM FinancialNadine FarahHead of Dev RelOnehouseNaresh YegireddiStaff Data EngineerIndigo AGNat FriedmanCreator of Copilot; Former CEOGithubNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North AmericaHitachi Solutions America Ltd.Naveen ZutshiChief Information OfficerDatabricksNeil PatelLead Specialist Solutions ArchitectDatabricksNic JansmaSenior Principal Lead EngineerAkamaiNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, TechnologyGlaxoSmithKlineNick KingFounder & CEOData KineticNicolas PelaezTechnical MarketingDatabricksNihar ShethSenior Product ManagerAWS - AmazonNitu NiveditaManaging DirectorAccentureNoam BresslerML Team LeadDeepchecksNoritaka SekiyamaPrincipal Big Data ArchitectAmazon Web ServicesOliver DykstraData EngineerTexas RangersOnik KurktchianHead of S&P Global Marketplace WorkbenchS&P GLOBALOri ZoharPrincipal Product Marketing ManagerDatabricksOz KatzCTO @ Treeverse, co-creator of lakeFSTreeverse LTDPakshal Kumar H DhelariaSenior Software Engineer 1CitrixPamela PettitSolutions ArchitectDatabricksParth ChandraSoftware EngineerApplePascal van BellenSenior ConsultantORAYLIS GmbHPatrick HallPrincipal Scientist | Visiting FacultyBNH.AI | GWUPaul RoomeStaff Product ManagerDatabricksPaul MracekSenior Solutions ArchitectDatabricksPaul WellmanVP, Executive Product Owner, Data-as-a-ServiceTD BankPaul MarshSenior Director Application DevelopmentNew York JetsPaula MartinezCEO & CofounderMarvikPearl UbaruSr. Technical Marketing EngineerDatabricksPedro BoaretoChapter Leader of Analytics EngineeringBradescoPercy LiangProfessor of Computer ScienceStanfordPhilippe LeonhartDigital Transformer, Corporate Business ServicesMichelinPieter NoordhuisSr. Staff Software EngineerDatabricksPouya Barrach-YousefiData Pro and Director Strategic AccountsProphecyPrashanth BabuLead Product SpecialistDatabricksPrateek ChawlaFounding EngineerMonte CarloPraveen VemulapalliDirector- TechnologyAT&TPravin DarbareVice President of Data AnalyticsWorkdayPritesh PatelPublic Sector Leader, UK&IDatabricksPulkit ChadhaSr. Solutions ArchitectDatabricksRafael BarcelosSoftware ArchitectMicrosoft CorporationRafi KurlansikLead Solutions ArchitectDatabricksRaghu JayachandranSenior Manager Enterprise DataRaceTrac Inc.Rahil BhatnagarDevelopment Lead, LOLAAnheuser BuschRahul PandeySolution ArchitectadidasRajesh IyerVice President Financial Services Insights & DataCapgeminiRakesh KumarStaff Software EngineerLyft IncRakesh SinghLead ArchitectABN AMRO Bank N.VRashmi KansakarDirector, Data & Cloud Architect84.51Rekha BachwaniEngineering Director, ML EngineeringThe Walt Disney CompanyReynold XinCo-founder and Chief ArchitectDatabricksRicardo PortillaPrincipal Solution ArchitectDatabricksRisha RavindranathSr Manager, Data GovernanceComcast AdvertisingRob SakerGlobal VP, Retail and ManufacturingDatabricksRobin SutaraField CTODatabricksRobinson CreightonPrincipal Analyst, Enterprise Data OpsComcast AdvertisingRodrigo BeceiroCTO & CofounderMarvikRoger DunnCo-founder, CTOExponamRoie Schwaber-CohenStaff Developer AdvocatePineconeRomit JadhwaniSr. Director, Data Analytics, Engineering and IntegrationsDatabricksRong MaSoftware EngineerintelRuifeng ZhengSenior Software EngineerDatabricksRyan BoydCo-founderMotherDuckRyan HarrisPrincipal Cybersecurity EngineerHSBCRyan JohnsonSenior Staff EngineerDatabricksSaad AnsariSenior Staff Product ManagerDatabricksSachin Balgonda PatilSolutions ArchitectDatabricksSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSamrat RaySenior Staff Product ManagerDatabricksSanjeev KumarVice President, Data Analytics and AIGainwell TechnologiesSanket AminSenior Manager of CAS Data Science and AnalyticsCollins AerospaceSarah PollittGroup Product ManagerMatillionSatish GarlaSr Solutions ArchitectDatabricksSatya NadellaChairman and CEOMicrosoft, Live Virtual GuestScott MeierDirector, Data Analytics Service, Financial Services CenterU.S. Department of Veterans AffairsScott StarbirdGeneral Counsel, Public Affairs and Strategic PartnershipsDatabricksScott BellPrincipal Consultant and Databricks SMERapidDataScott CastleChief Strategy OfficerSisenseSean KnappFounder & CEOAscend.ioSean OwenPrincipal Product SpecialistDatabricksSeth BabcockHead of Connected Aviation Tech Ops Solutions and AnalyticsCollins AerospaceShasidhar ErantiSpecialist Solutions ArchitectDatabricksShawn GilleranPrincipal Cloud Solutions LeadLiveRampShawn BenjaminData and Business Intelligence ChiefU.S. Department of Homeland Security - USCISShir ChorevCTODeepchecksShiv TrisalGTM Director, Manufacturing & EnergyDatabricksSiddharth BhaiSr. Manager, Product ManagementDatabricksSidharth KunnathPrincipal ArchitectAmerican Airlines, IncSimon WhiteleyCTOAdvancing AnalyticsSirui SunDatabricksSlava FridCTOWorldQuant PredictiveSneh KakiletiVice President, Product ManagementZoomInfoSpencer CookSenior Solutions Architect - Financial ServicesDatabricksSreekanth RatakondaPrincipal Solutions ArchitectLabcorpSridhar DevarapalliSenior Director, Product ManagementDatabricksSrinivasa KanamathaSenior ManagerBlackBerryStan LinSenior Software EngineerMicrosoft CorporationStefania LeoneSr. Manager Product ManagementDatabricksStephen SheltonVice President, Business IntelligencePluto TVSteve MahoneySr Manager, Product ManagementDatabricksSteve SobelGlobal Lead - Communications, Media & EntertainmentDatabricksSteven YuPrincipal Solutions ArchitectDatabricksSumesh NairDirector of Engineering, Data and Cloud StrategyOptum, United HealthGroupSuneel KonidalaSr. ManagerAccentureSunil RanganathanDirector, MLOPsTredenceSuresh MatlapudiLead Solutions Architect and Specialist SME, MigrationsDatabricksSurya TuragaSr. Solutions ArchitectDatabricksSuze HowseHead of Enterprise DataMarks and SpencerTanmay KumarSenior ManagerDeloitte Consulting LLPTathagata DasDatabricksTaylor HosbachData ScientistDIRECTVTeja TangedaPrincipal Data EngineerAmerican AirlinesTEST BecknerTESTTESTTest1 TestCFP1102testThet KoPrincipal Data EngineerSEEKThomas La PianaSenior Software EngineerEthycaThomas RoachSr. Solutions ArchitectDatabricksThorsten JacobsSr. Solutions ArchitectDatabricksTianyu LiuLead Data Scientist (Analytics)GrabTimothy AhrensMessaging Design Division ChiefDepartment of StateTodd GreensteinProduct ManagerDatabricksTomer PatelSoftware Engineering ManagerAkamai TechnologiesTony WangPhD studentStanfordUri MayHuntersVadivel SelvarajStaff Software EngineerRivianVarun SharmaPrincipal Data EngineerVisa Inc.Vicky AndonovaManager, Applied Machine LearningAnomaloVika SmilanskyDirector of Product MarketingThoughtSpotVikas Reddy AravabhumiStaff Backline EngineerDatabricksVincent ChenDirect of Product \/ Founding EngineerSnorkel AIVinit DoshiSenior ManagerTredenceVinod MarurSVP of EngineeringDatabricksVolker TjadenManager Solution ArchitectsDatabricksVuong NguyenSenior Solutions ArchitectDatabricksWassym BensaidSr. Vice President, Software DevelopmentRivianWeston HutchinsProduct ManagerDatabricksWill GirtenSr. Specialist Solutions ArchitectDatabricksWilliam ZanineHead of Data Management, Channel and Specialty North AmericaIQVIAWilly LulciucSr. Software EngineerAstronomerXiao LiSenior Engineering ManagerDatabricksXuefu WangSr. Data ScientistThe Trade DeskYali SassoonCPOSnowplowYang YouPresidential Young ProfessorNational University of SingaporeYaniv KundaSenior Software ArchitectAkamaiYaron SingerCEO & Co-FounderRobust IntelligenceYeshwanth VijayakumarSr Engineering Manager\/ArchitectAdobeYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and TechnologyU.S. ArmyYuki SaitoTechnical EvangelistNTT DATA CorporationZachary BannorData Engineering ManagerCond\u00e9 NastZachary HuangPhDColumbia UniversityZaheera ValaniSenior Director of EngineeringDatabricksZeashan PappaSenior Product Specialist - Data GovernanceDatabricksZoe DurandSenior Product ManagerDatabricksSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/code-of-conduct\/?_gl=1*1i2gjhq*_ga*NjJmNzBjYzgtOGFhYi00MTYwLTg3MjktMTcxYzIyZTAzYjM0*_ga_PQSEQ3RZQC*MTY4MTcwNTkyNC4xMDcuMC4xNjgxNzA1OTI0LjYwLjAuMA..&_ga=2.68071377.1988636371.1681687893-62f70cc8-8aab-4160-8729-171c22e03b34&_gac=1.83762532.1680277031.Cj0KCQjwiZqhBhCJARIsACHHEH-M4XCl4tuJ05NvqDEChz-8-RE-4XIPYaVm_HzJBijsf9XqoKC5dmwaAjv9EALw_wcB","text":"Code of Conduct - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCode of ConductData + AI Summit Event , Organized by DatabricksSummit Organizers are committed to creating a safe and inclusive experience for our conference attendees, regardless of gender, sexual orientation, disability, physical appearance, body size, race, or religion. We do not tolerate harassment in any form. All communication \u2014 including at the event and various associated venues, as well as online \u2014 should be appropriate for a professional audience, including people of many different backgrounds and experiences. Be kind to others. Do not insult or put down other attendees. Act professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate at any time at any event organized by Databricks.\nInteraction Guidelines for AttendeesFor all interactions during the Data + AI Summit Event, we expect participants to abide by the event\u2019s Code of Conduct to ensure the environment remains productive and respectful. The following guidelines will further help ensure we maintain an inclusive experience throughout our event:\n\nBe respectful of others.\nAvoid conflicts and arguments.\nUse common sense, kindness, and consideration together with the guidelines outlined above.\nIf you intend to participate in the event, please make sure to dress appropriately.\n\nEnforcementIf a participant engages in behavior that doesn\u2019t comply with these expectations, Summit Organizers may take any action that we deem appropriate, including warning the participant, excluding the participant from certain activities, prohibiting the participant from attending future events organized by Databricks, expelling the participant from the event without a refund, banning the participant from online forums, and other similar type experiences. Participants asked to stop any harassing or other unacceptable behaviors are expected to comply immediately. Anyone violating these rules may be asked to leave the experience without a refund at the sole discretion of Summit Organizers.\n\nPlease note, while we take all concerns raised seriously, we will use our discretion to determine when and how to follow up on reported incidents, and may decline to take any further action and\/or may direct the participant to other resources to address the concern.\nReporting an IssueIf you are being harassed, notice that someone else is, or have any concerns, please contact Summit Organizers at [email\u00a0protected] and provide your name, phone number, email, and a description of the situation. Summit Organizers can only address complaints about behavior at the Event.\nThe reporting mechanisms under this Code of Conduct are not intended to address criminal activity or emergency situations. If you have been the victim of a crime or there is an emergency, please contact the appropriate municipal authorities, such as the police, fire, medical, or other emergency responders.\nThank you for helping make Databricks Data + AI Summit a welcoming, friendly place for all to share new ideas, learn, and connect.\n\nInformation for Presenters: Presenters who are unsure whether their presentations or other materials and communications are consistent with these expectations, please contact Toby Malina at\u00a0 [email\u00a0protected] in advance of the experience.\n\u00a0\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/blog\/2020\/12\/18\/personalizing-the-customer-experience-with-recommendations.html","text":"How to Personalize the Customer Experience With Recommendations - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorPersonalizing the Customer Experience with Recommendationsby Rob Saker, Bryan Smith, Bilaji Raman, Ye Wang, Yiyan Zhang and Terry TangDecember 18, 2020 in Engineering BlogShare this post Go directly to the Recommendation notebooks referenced throughout this post.Retail made a giant leap forward in the adoption of e-commerce in 2020, E-commerce as a percentage of total retail saw multiple years of progress in one year. Meanwhile, COVID, lockdowns and economic uncertainty have completely disrupted how we engage and retain customers. Companies need to rethink personalization to effectively compete in this period of rapid change.In 2020, we saw a rapid shift in consumer behavior, not just in the adoption of e-commerce. Store brands saw increased consumer adoption. Staple goods saw a resurgence in demand. Customers not only rethought their relationships with specific products but retailers as well, spreading their spend across multiple retail partners. The relevance of in-store displays, features and promotions was challenged by leading retailers capable of driving 35% of their revenue through personalized recommendations.\nProviding an experience that makes customers feel understood helps retailers stand out from the crowd of mass merchants and build loyalty. This was true before COVID but shifting consumer preferences make this more critical for retail organizations. With research showing the cost of customer acquisition being as much as five times as retaining existing ones, organizations looking to succeed in the new normal must continue to build deeper connections with the existing customers in order to retain a solid consumer base. There is no shortage of options and incentives for today\u2019s consumers to rethink long-established patterns of spending.\nPersonalization is a must to competePresented with overwhelming choice, consumers expect the brands they buy and the organizations they buy them from to deliver an experience aligned with their needs and preferences. Personalization, once presented as an exotic vision for what could be, is increasingly becoming the baseline expectation for consumers continuously connected, short on time and seeking value through an increasingly more complex set of considerations.\nBrands that deliver personalized experiences can compete with these retail giants. In a pre-COVID analysis of consumer attitudes and spending patterns, 80% of participants indicated they were more likely to do business with a company offering personalized experiences. Those individuals were found to be 10-times more likely to make 15 or more purchases per year with organizations they believe understood and responded to their personal needs and preferences. In a separate survey, 50% of participants reported seeing the brands they buy as extensions of themselves, driving deeper, more sustained customer loyalty for the brands that get it right.\nAs COVID forced a shift in consumer focus towards value, availability, quality, safety and community, brands most attuned to changing needs and sentiments saw customers switch from rivals. While some segments gained business and many lost, organizations that had already begun the journey towards improved customer experience saw better outcomes, closely mirroring patterns observed in the 2007-2008 recession (Figure 1).\n)As we look towards what will be the new normal, it is clear that the personalization of customer experiences will remain a key focus for many B2C and even B2B organizations. Increasingly, market analysts are recognizing customer experience as a disruptive force enabling upstart organizations to upend long-established players. Organizations focused on competing through product, placement, pricing and promotion alone will find themselves under pressure from competitors capable of delivering more value to consumers for each dollar received.\nFocus on the customer journeyPersonalization starts with a careful exploration of the customer journey. This starts as customers come to recognize a need and move to identify a product to fulfill it. It then shifts towards the selection of a channel for its purchase and concludes with consumption, disposal and the possible repeat purchase. The path is varied and not simply linear, but with every stage, there is an opportunity for value to be created for the customer.\nThe digitization of each stage provides the customer with flexibility in terms of how they will engage and provides the organization with the ability to assess the health of their model. While part and parcel of the online and mobile experience, digitization can be extended to the in-store, in-transit and even the in-home stages of the customer journey with appropriate considerations of transparency, privacy and value-add for the customer.\n Figure 2. Bringing the digital experience into the store can be used to facilitate a personalized engagementThis customer-generated data as well as third-party inputs provide the organization with the information they need to refine their understanding of the customer and their unique journeys. Individual motivations, goals and preferences can now be better understood and more personalized experiences delivered to the customer.\nThe examination of the customer journey, its digitization and the analysis of the data generated by it are used to create a feedback loop through which the customer experience improves. To get this loop in motion and sustain it over time, a clear vision for competing on customer experience must be expressed. This vision must bring together the entire organization, not just marketing and their IT-enablers, around shared goals. These goals must then be translated into incentive structures that encourage cross-departmental collaboration and innovation. The organization\u2019s journey towards delivering differentiating customer experiences is fundamentally a journey towards becoming a learning organization, one which puts insights into motion, celebrates the learnings that come with failure, and rapidly scales its successes to drive customer value.\nLeverage customer preferencesPersonalization is multifaceted, but at various points in the customer journey, organizations will have the opportunity to select content, products, promotions to be presented to the customer. In these moments, we can take into consideration past feedback from customers to select the right items to present. Customer feedback doesn\u2019t always come to us in the form of 1-to-5 star ratings or written reviews. Feedback may be expressed through interactions, dwell times, product searches, and purchase events. Careful consideration of how customers interact with various assets and how these interactions may be interpreted as expressions of preference can unlock a wide range of data with which you can enable personalization.\nWith feedback in hand, we now consider which items to present. Consider a customer browsing an assortment of recommended products, clicking on one, exploring alternatives to this item, putting it into their cart and then exploring items frequently bought in combination with this item. At each stage of this very narrow slice of the customer\u2019s journey, the customer is interacting with our content with very different goals in mind. The customer\u2019s preferences are unchanged throughout this journey but their intent leads us to use that information to make very different choices with regards to what we might present.\nUnderstand it\u2019s as much art as scienceThe engines we use to serve content based on customer preferences are known as recommenders. To describe their construction as much Art as Science would be an understatement. With some recommenders, we focus heavily on the shared preferences of similar customers to expand the range of content we might expose to customers. With others, we focus on the properties of the content itself (e.g., product descriptions) and leverage user-specific interactions with related content to quantify the likelihood an item is likely to resonate with the customer. Each class of recommendation engine orients around a general goal, but within each, there are myriad decisions the business must make that orient its recommendations towards specific goals.\nThe complexity of these engines and the nature of why we build them are such that any upfront evaluation of their supposed accuracy is suspect. While offline evaluation methods have been proposed and should be employed to ensure that the recommenders we build are not flying off the rails, the reality is that we can only effectively evaluate their ability to assist us in achieving a particular goal by releasing them in limited pilots and assessing customer response. And in those assessments, it\u2019s important to keep in mind that there is no expectation of perfection, only incremental improvement over the prior solution.\nConsider tradeoffs between performance & completenessThe primary challenge we must overcome in the assembly of any recommender is scalability. Consider a recommender leveraging user similarities. A small pool of 100,000 users requires the evaluation of approximately 5,000,000,000 user pairs and each of those evaluations may involve a comparison of preferences for each item we might recommend. From a purely technical standpoint, performing this number of calculations is not a problem, but the cost of doing it on a regular basis and within the time-constraints imposed on these systems makes a brute-force evaluation untenable.\nIt\u2019s for this reason that the technical literature surrounding the development of recommender systems puts a heavy emphasis on approximate similarity techniques. These techniques offer shortcuts that allow us to home in on those users or items most likely to be similar to the objects we are comparing. With these techniques, there is a tradeoff between performance gains and recommendation completeness. So while these techniques are quite technically oriented, there is an important conversation to be had between solution architects and the business stakeholders about the right balance between these two considerations.\nJumpstart your efforts with solution acceleratorsIt goes without saying that careful management of resources can go a long way to keeping the cost of on-going recommender development, training and deployment. Databricks is purpose-built for scalable development on cloud infrastructures that allow organizations to rapidly provision and then deprovision resources for exactly this reason.\nTo help our customers understand how they might use Databricks to develop various recommenders, we\u2019ve made available a series of detailed notebooks as part of our Solution Accelerators program. Each notebook leverages a real-world dataset to show how raw data may be transformed into one or more recommender solutions.\nThe focus of these notebooks is on education. No one should take the techniques demonstrated here as the only way or even the preferred way to solve a specific recommendation challenge. Still, in wrestling with the issues described above, we hope that some portions of the presented code will assist our customers in tackling their own recommender needs. Collaborative Filter RecommendersCF 01: Data PreparationCF 02: Identify Similar UsersCF 03: Build User-Based Recommendations CF 04: Build Item-Based RecommendationsCF 05: Deploy Collaborative FiltersContent-Based RecommendersCN 01: Data PreparationCN 02a: Determine Title SimilaritiesCN 02b: Determine Description SimilaritiesCN 02c: Determine Category SimilaritiesCN 03: Construct User-Profile RecommendersCN 04 Deploy Content-based RecommendersYou can also view our on-demand webinar around personalization and recommendations.\nTry Databricks for freeGet StartedRelated postsPersonalizing the Customer Experience with RecommendationsDecember 18, 2020 by Rob Saker, Bryan Smith, Bilaji Raman, Ye Wang, Yiyan Zhang and Terry Tang in Engineering Blog\nGo directly to the Recommendation notebooks referenced throughout this post. Retail made a giant leap forward in the adoption of e-commerce in 2020...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks, \ub9ac\ub354\ub85c \uc120\uc815 | Databricks2022\ub144 Gartner\u00ae Magic Quadrant\u2122Databricks, \ub9ac\ub354\ub85c \uc120\uc815\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uad00\ub9ac \uc2dc\uc2a4\ud15cDatabricks, 2022\ub144 Gartner\u00ae Magic Quadrant\u2122 CDBMS \ubd80\ubb38\uc5d0\uc11c \ub9ac\ub354\ub85c \uc120\uc815Databricks\uac00 \uc791\ub144\uc5d0 \uc774\uc5b4 2022\ub144\uc5d0\ub3c4 Gartner \ub9e4\uc9c1 \ucffc\ub4dc\ub7f0\ud2b8 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130\ubca0\uc774\uc2a4 \uad00\ub9ac \uc2dc\uc2a4\ud15c \ubd80\ubb38\uc758 \ub9ac\ub354\ub85c \uc120\uc815\ub410\ub2e4\ub294 \uc790\ub791\uc2a4\ub7ec\uc6b4 \uc18c\uc2dd\uc744 \uc54c\ub824\ub4dc\ub9bd\ub2c8\ub2e4.\uc774\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \ubd84\uc11d \ubc0f AI\uc640 \ub354\ubd88\uc5b4, \ub370\uc774\ud130 \uad00\ub9ac \ubc0f \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \uc704\ud55c \ub2e8\uc77c \ud1b5\ud569 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ub9cc\ub4e4\uace0\uc790 \ud558\ub294 Databricks\uc758 \ube44\uc804\uc774 \uc778\uc815\uc744 \ubc1b\uc740 \uc99d\uac70\ub77c\uace0 \uc0dd\uac01\ud569\ub2c8\ub2e4.Databricks\uac00 Gartner \ub9ac\ub354\ub85c \uc120\uc815\ub41c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uace0 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc774 \uae30\uc5c5\uc5d0 \uc81c\uacf5\ud558\ub294 \ud61c\ud0dd\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \uc778\uc0ac\uc774\ud2b8\ub97c \ud655\uc778\ud558\ub824\uba74 \ubcf4\uace0\uc11c\ub97c \ub2e4\uc6b4\ub85c\ub4dc\ud558\uc138\uc694.\ubcf4\uace0\uc11c \uc561\uc138\uc2a4\ud558\uae30 Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sean-knapp","text":"Sean Knapp - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSean KnappFounder & CEO at Ascend.ioBack to speakersSean Knapp is the founder and CEO of Ascend.io. Prior to Ascend.io, Sean was a co-founder, CTO, and Chief Product Officer at Ooyala.\nAt Ooyala Sean oversaw Product, Engineering and Solutions, and played key roles in scaling the company. Before founding Ooyala, Sean worked at Google where he was the tech lead for Google's Web Search Frontend Engineering team. \nSean holds a B.S. and M.S. in Computer Science from Stanford University where he competed as a member of the Track & Field team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/romit-jadhwani","text":"Romit Jadhwani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRomit JadhwaniSr. Director, Data Analytics, Engineering and Integrations at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/fraud-detection","text":"Solution Accelerator - How to build: Rule-based AI models to combat financial fraud | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: Rule-based AI models to combat financial fraudPrevent fraud in real time to reduce operational costs and increase customer trust\nPreempt fraud with rule-based patterns and select ML algorithms for reliable fraud detection. Use anomaly detection and fraud prediction to respond to bad actors rapidly.\nRead the full write-up\nNOTEBOOKCreate a fraud orchestration engineDownload NotebookBenefits and business valueWin customer trustEnsure security for customers to build trust and loyalty\nMove fast and prevent lossesMove from rules to machine learning to respond in time and reduce operational costs associated with fraudScale flexiblyCut through all the data complexities and implement fraud prevention at scale with the LakehouseReference ArchitectureData usedResourcesCase studiesStorebrand delivers analytics and ML innovation at speed and scaleFinancial technology company catches more fraud with Microsoft Azure AICompany blogDetecting Financial Fraud at Scale with Decision Trees and MLflow on DatabricksEngineering blogNew Methods for Improving Supply Chain Demand ForecastingDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tanmay-kumar\/#","text":"Tanmay Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTanmay KumarSenior Manager at Deloitte Consulting LLPBack to speakersImpact-driven leader with experience in engaging and maintaining C-level relationships and delivering large business transformation programs with focus on enterprise data\/cloud strategy, data management and modernization for Banking, Technology and Media clients.\nSenior program executive with extensive experience in leading cross-discipline functional and data engineering\/science teams for project scoping, requirements and delivery, defining technology roadmap, developing success strategy, fostering vendor partnerships, driving process improvement, executive communication, agile\/scrum techniques, implementing project governance and staff recruitment.\nTechnical expertise in designing cloud-based data architectures, implementing data warehouses, data lakes, integration pipelines, business intelligence, visualization & data science platforms across functions like Sales, Marketing, Risk and Finance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/adagrad","text":"What is AdaGrad?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAdaGradAll>AdaGradTry Databricks for freeGet StartedGradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.Types of Gradient Descent There are three primary types of gradient descent used in modern machine learning and deep learning algorithms.Batch Gradient DescentBatch Gradient Descent is the most straightforward type. It calculates the error for each example in the training dataset, however, it only updates the model after all training examples have been evaluated.Stochastic Gradient DescentStochastic Gradient Descent calculates the error and updates the model for each example in the training dataset.Mini Batch Gradient DescentMini Batch Gradient Descent instead of going over all examples, it sums up over lower number of examples based on the batch size and performs an update for each of these batches. Stochastic Gradient Descent is a common method for optimization. It is conceptually simple and can often be efficiently implemented. However, it features a parameter (the step size) that needs to be manually tuned. There have been proposed different options to automate this tuning. One of the successful scheme is AdaGrad. While standard stochastic subgradient methods mainly follow a predetermined procedural scheme that disregards the characteristics of the data being observed. In contrast, AdaGrad\u2019s algorithms dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradient-based learning. AdaGrad has been released in two versions. Diagonal AdaGrad (this version is the one used in practice), its main characteristic is to maintain and adapts one learning rate per dimension; the second version known as Full AdaGrad maintains one learning rate per direction (e.g.. a full PSD matrix). Adaptive Gradient Algorithm (Adagrad) is an algorithm for gradient-based optimization. The learning rate is adapted component-wise to the parameters by incorporating knowledge of past observations. \u00a0It performs larger updates (e.g. high learning rates) for those parameters that are related to infrequent features and smaller updates (i.e. low learning rates) for frequent one. It performs smaller updates As a result, it is well-suited when dealing with sparse data (NLP or image recognition) Each parameter has its own learning rate that improves performance on problems with sparse gradients.Advantages of Using AdaGradIt eliminates the need to manually tune the learning rateConvergence is faster and more reliable \u2013 than simple SGD when the scaling of the weights is unequalIt is not very sensitive to the size of the master stepAdditional ResourcesSeparating Hype from Reality in Deep Learning WebinarLearning Tensorflow - Training and ConvergenceBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suresh-matlapudi","text":"Suresh Matlapudi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuresh MatlapudiLead Solutions Architect and Specialist SME, Migrations at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bob-zhang\/#","text":"Bob Zhang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBob ZhangSenior Technical Program Manager at MicrosoftBack to speakersBob Zhang is a Senior Technical Program Manager in Azure Data focused on Microsoft Data Integration connectivity. Bob has extensive experience working on enterprise software products and data integration and currently owns connectivity scenarios for Power Query, the data transformation and preparation technology used in Power BI, Excel, and many more Microsoft products.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/trust\/architecture","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssuePlatform ArchitectureExpand AllDescriptionThe Databricks Lakehouse architecture is split into two separate planes to simplify your permissions, avoid data duplication and reduce risk. The control plane is the management plane where Databricks runs the workspace application and manages notebooks, configuration and clusters. The data plane handles your data processing. With serverless deployments, the data plane exists in your Databricks account rather than your cloud service provider account. You can enforce your data exfiltration protection requirements with Databricks with security controls like customer-managed VPCs\/VNets and admin console options that disable export.Our security features page covers architectural security controls, such as encryption, access control, and governance.Step-by-Step ExampleSuppose you have a data engineer that signs in to Databricks and writes a notebook that transforms raw data in Kafka to a normalized data set sent to storage such as Amazon S3 or Azure Data Lake Storage or Google Cloud Storage. The following steps make that happen:The data engineer seamlessly authenticates, via your single sign-on if desired, to the Databricks web UI in the control plane.As the data engineer writes code, their web browser sends it to the control plane. JDBC\/ODBC requests also follow the same path.When ready, the control plane creates a Databricks cluster in the data plane, and sends the data engineer\u2019s code.The cluster pulls from Kafka, transforms the data and writes it to your storage.The cluster reports status and any outputs back to the control plane.The data engineer doesn\u2019t need to worry about many of the details \u2014 they simply write the code and Databricks runs it.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/machine-learning","text":"Databricks Machine Learning | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMachine LearningAccelerate your AI projects with a data-centric approach to machine learningTry for freeSchedule a demo\nBuild Your Own Large Language Model Like Dolly\nOn-demand webinar\nWatch nowDive deeper into Machine Learning on DatabricksManaged MLflowModel RegistryML RuntimeCollaborative NotebooksFeature StoreAutoMLExplainable AIReposModel MonitoringModel ServingBuilt on an open\u00a0lakehouse\u00a0architecture, Databricks Machine Learning empowers ML teams to prepare and process data, streamlines cross-team collaboration and standardizes the full ML lifecycle from experimentation to production.$6M+ in savingsCONA Services uses Databricks for full ML lifecycle to optimize supply chain for hundreds of thousands of stores.Learn moreR$3.9M in savingsVia leverages machine learning to accurately forecast demand, reducing compute costs by 25%.Learn more$50M+ in cost reductionAmgen improves data science collaboration to accelerate drug discovery and save operational costs.Learn moreSimplify all aspects of data for MLBecause Databricks ML is built on an open\u00a0lakehouse\u00a0foundation with\u00a0Delta Lake, you can empower your machine learning teams to access, explore and prepare any type of data at any scale. Turn features into production pipelines in a self-service manner without depending on data engineering support.Automate experiment tracking and governanceManaged MLflow automatically tracks your experiments and logs parameters, metrics, versioning of data and code, as well as model artifacts with each training run. You can quickly see previous runs, compare results and reproduce a past result, as needed. Once you have identified the best version of a model for production, register it to the Model Registry to simplify handoffs along the deployment lifecycle.Manage the full model lifecycle from data to production \u2014 and backOnce trained models are registered, you can collaboratively manage them through their lifecycle with the Model Registry. Models can be versioned and moved through various stages, like experimentation, staging, production and archived. The lifecycle management integrates with approval and governance workflows according to role-based access controls. Comments and email notifications provide a rich collaborative environment for data teams.Deploy ML models at scale and low latencyDeploy models with a single click without having to worry about server management or scale constraints. With Databricks, you can deploy your models as REST API endpoints anywhere with enterprise-grade availability.Product componentsCollaborative NotebooksDatabricks notebooks natively support Python, R, SQL and Scala so practitioners can work together with the languages and libraries of their choice to discover, visualize and share insights.Learn moreMachine Learning RuntimeOne-click access to preconfigured ML-optimized clusters, powered by a scalable and reliable distribution of the most popular ML frameworks (such as PyTorch, TensorFlow and scikit-learn), with built-in optimizations for unmatched performance at scale.Learn moreFeature StoreFacilitate the reuse of features with a data lineage\u2013based feature search that leverages automatically logged data sources. Make features available for training and serving with simplified model deployment that doesn\u2019t require changes to the client application.Learn moreAutoMLEmpower everyone from ML experts to citizen data scientists with a \u201cglass box\u201d approach to AutoML that delivers not only the highest performing model, but also generates code for further refinement by experts.Learn moreManaged MLflowBuilt on top of MLflow \u2014 the world\u2019s leading open source platform for the ML lifecycle \u2014 Managed MLflow helps ML models quickly move from experimentation to production, with enterprise security, reliability and scale.Learn moreProduction-Grade Model ServingServe models at any scale with one-click simplicity, with the option to leverage serverless compute.Learn moreModel MonitoringMonitor model performance and how it affects business metrics in real time. Databricks delivers end-to-end visibility and lineage from models in production back to source data systems, helping analyze model and data quality across the full ML lifecycle and pinpoint issues before they have damaging impact.Learn moreReposRepos allows engineers to follow Git workflows in Databricks, enabling data teams to leverage automated CI\/CD workflows and code portability.Learn moreMigrate to DatabricksTired of the data silos, slow performance and high costs associated with legacy systems like Hadoop and enterprise data warehouses? Migrate to the Databricks Lakehouse: the modern platform for all your data, analytics and AI use cases.Migrate to DatabricksResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on data science and machine learning topics.\nExplore resourceseBooksThe Big Book of MLOpsExplore the new Delta Sharing solutionMigration Guide: Hadoop to DatabricksDemos and blogsDive deeper into Databricks Machine Learning solutions5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse ArchitectureVirtual eventsAutoML: Rapid, Simplified machine learning for everyoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningMLOps Virtual Event \u201cOperationalizing Machine Learning at Scale\u201dBuilding Machine Learning PlatformsDelta Lake: The Foundation to Your LakehouseStep-by-step Guide to Hadoop MigrationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-structured-streaming","text":"What is Structured Streaming?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWStructured StreamingAll>Structured StreamingTry Databricks for freeGet StartedStructured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a streaming fashion. This can reduce latency and allow for incremental processing. The best thing about Structured Streaming is that it allows you to rapidly and quickly get value out of streaming systems with virtually no code changes. It also makes it easy to reason about because you can write your batch job as a way to prototype it and then you can convert it to a streaming job. The way all of this works is by incrementally processing that data.Additional ResourcesStructured Streaming DocumentationParallelization of Structured Streaming Jobs Using Delta LakeBuilding a Streaming Microservice Architecture: with Apache Spark Structured Streaming and FriendsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jiajun-yao","text":"Jiajun Yao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJiajun YaoSoftware Engineer at AnyscaleBack to speakersJiajun works on the Engineering team for Ray core at Anyscale. Prior to working at AnyScale, he was at LinkedIn where he worked on Liquid, an in-memory graph database.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nihar-sheth","text":"Nihar Sheth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNihar ShethSenior Product Manager at AWS - AmazonBack to speakersNihar Sheth is a Senior Product Manager on the Amazon Kinesis Data Streams team at Amazon Web Services. He is passionate about developing intuitive product experiences that solve complex customer problems and enables customers to achieve their business goals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adriana-ispas","text":"Adriana Ispas - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdriana IspasStaff Product Manager at DatabricksBack to speakersAdriana Ispas is a staff product manager at Databricks working on the Databricks Runtime and Databricks SQL. She holds a Ph.D. in Computer Science from ETH Zurich.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/automl-rapid-simplified-machine-learning-for-everyone?itm_data=productml-link-automlwebinar","text":"AutoML: Rapid, simplified machine learning for everyone \u2013 DatabricksWebinarAutoMLRapid, simplified machine learning for everyoneAvailable on-demandWatch now to learn how to build, test and deploy ML models at scaleDon\u2019t let the wrong technology hinder the efforts of your data scientists. Databricks has simple, powerful AutoML capabilities that can help both citizen and professional data scientists rapidly build, test and deploy ML models at scale.Join us to learn how to:Self-serve the full ML lifecycle without writing codeAuto-generate models and editable notebooks to make customizations in preproductionEnhance experiment trackingFacilitate automated hyperparameter tuning and explainability for audit and complianceFeaturing SpeakersDr. Stephen S. KelleyStaff Data ScientistFableticsKasey UhlenhuthStaff Product ManagerDatabricksWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ketan-ganatra","text":"Ketan Ganatra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKetan GanatraSolution Architect at DatabricksBack to speakersAs a Solution Architect working with Databrick's SI partners, Ketan helps them build competencies and products around the Lakehouse platform. Ketan acts as a SME on ML topics. Prior to joining Databricks, he led development and production roll-out of the first ever Enterprise ML use case in the Department of Defense. Ketan Has 20+ years of IT experience and degrees in Electronics Engg and MBA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). 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In using the Sites, you agree that you will not, and will not allow or authorize any third party to:\n\u00a0Use the Sites or any Content for any purpose that is illegal, fraudulent, deceptive or unauthorized by these Terms, or would give rise to civil liability, or to solicit the performance of any illegal activity or other activity which infringes the rights of Databricks or others, or to encourage or promote any such activity.Engage in or promote any conduct that is offensive, harassing, predatory, stalking, violent, threatening, discriminatory, racist, hateful, or otherwise harmful, against any individual or group.Harvest or collect information about any third parties, including their email addresses or other personally identifiable information.Send, by email or other means, any unsolicited or unauthorized advertising, promotional materials, junk mail, spam, chain letter, pyramid scheme, political campaign message, offering of an investment opportunity, or any other form of solicitation, or conceal or forge headers of emails or other messages, or otherwise misrepresent the identity of senders, for the purpose of sending spam or other unsolicited messages.Impersonate or post on behalf of, or express or imply the endorsement of, any individual or entity, including Databricks or any of its representatives, or otherwise misrepresent your affiliation with a person or entity.Use the Sites in any manner, whether deliberate or otherwise, including without limitation a denial of service attack, that could in any way (a) interfere with, damage, disable, overburden or impair the functioning of the Sites, or Databricks\u2019 systems or networks, or any systems or networks connected to the Sites, or (b) violate any requirements, procedures, policies or regulations of such systems or networks.Operate non-permissioned network services, including open proxies, mail relays or recursive domain name servers, or use any means to bypass user limitations relating to the Sites.Use any robot, spider, crawler, scraper, deep-link, page-scrape, site search\/retrieval application or other manual or automated device, program, algorithm or methodology or interface not provided by us to access, acquire, copy, retrieve, index, scrape, data mine, in any way reproduce or circumvent the navigational structure or presentation of the Sites or monitor any portion of the Sites or to extract data, or to sell, resell, frame, mirror or otherwise exploit for any commercial purpose, any portion of, use of, or access to the Sites (including any Content, Software and other materials available through the Sites), or attempt to circumvent any content filtering techniques we may employ.Remove any copyright, trademark or other proprietary rights notice from the Sites or from Content or other materials contained on or originating from the Sites.Create a database of any type by systematically downloading and storing any Content unless expressly permitted by Databricks to do so.Attempt to gain unauthorized access to any portion or feature of the Sites, or any other systems or networks connected to the Sites or to any Databricks server, or to any of the services offered on or through the Sites, by hacking, password mining or any other illegitimate means.Use or attempt to use any account you are not authorized to use.Probe, scan, monitor or test the vulnerability of the Sites or any network connected to the Sites, or breach the security or authentication measures on the Sites or any network connected to the Sites.Modify, adapt, create derivative works of, translate, reverse engineer, decompile or disassemble any portion of the Sites (including any Content or other materials available through the Sites), or do anything that might discover source code or bypass or circumvent measures employed to prevent or limit access to any area, Content or code within the Sites except as, and solely to the extent, expressly authorized under applicable law overriding any of these restrictions.Develop any third-party applications that interact with the Sites or Content without our prior written consent.Use or apply the Sites in any manner directly or indirectly competitive with any business of Databricks.\u00a0LINKS\nWe may from time-to-time at our discretion host or provide links to services, products, web pages, websites or other content of third parties (\u201cThird-Party Content\u201d). 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You represent and warrant that you will not export or re-export such Software in violation of these regulations.You acknowledge that your breach of any of the provisions of these Terms may cause immediate and irreparable harm to Databricks for which we may not have an adequate remedy in money damages. We will therefore be entitled to obtain an injunction against such breach from any court of competent jurisdiction immediately upon request and will be entitled to recover from you the costs incurred in seeking such an injunction. The availability or exercise of our right to obtain injunctive relief will not limit our right to seek or obtain any other remedy.You agree that we will not be liable for delays, failures, or inadequate performance of the Sites resulting from conditions outside of our reasonable control, including but not limited to natural disasters or other acts of God, failure of telecommunications networks or any other network or utility, threatened or actual acts of terrorism or war, riots, labor strikes, or governmental acts or orders.Last Updated May 25, 2018ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=london%2C%20united%20kingdom","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/delta-lake-on-databricks","text":"Delta Lake on Databricks - Schedule a Demo Now!Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta LakeReliability, security and performance for your data lakeTry for freeWatch a demoWhat is Delta Lake?Delta Lake is an open format storage layer that delivers reliability, security and performance on your data lake \u2014 for both\u00a0streaming\u00a0and batch operations. By replacing data silos with a single home for structured, semi-structured and unstructured data, Delta Lake is the foundation of a cost-effective, highly scalable lakehouse.High-quality, reliable dataDeliver a reliable single source of truth for all of your data, including\u00a0real-time\u00a0streams, so your data teams are always working with the most current data. With support for ACID transactions and schema enforcement, Delta Lake provides the reliability that traditional data lakes lack. This enables you to scale reliable data insights throughout the organization and run analytics and other data projects directly on your data lake \u2014 for up to\u00a050x faster time-to-insight.Open and secure data sharingDelta Sharing\u00a0is the industry\u2019s first open protocol for secure data sharing, making it simple to share data with other organizations regardless of where the data lives. Native integration with the\u00a0Unity Catalog\u00a0allows you to centrally manage and audit shared data across organizations. This allows you to confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs. Integrations with leading tools and platforms allow you to visualize, query, enrich, and govern shared data from your tools of choice.Lightning-fast performanceWith Apache Spark\u2122 under the hood, Delta Lake delivers massive scale and speed. And because it\u2019s optimized with performance features like indexing, Delta Lake customers have seen\u00a0ETL workloads execute up to 48x faster.Open and agileAll data in Delta Lake is stored in open Apache Parquet format, allowing data to be read by any compatible reader. APIs are open and compatible with Apache Spark. With Delta Lake on Databricks, you have access to a vast open source ecosystem and avoid data lock-in from proprietary formats.Automated and trusted data engineeringSimplify data engineering with\u00a0Delta Live Tables\u00a0\u2013 an easy way to build and manage data pipelines for fresh, high-quality data on Delta Lake. It helps data engineering teams by simplifying\u00a0ETL\u00a0development and management with declarative pipeline development, improved data reliability and cloud-scale production operations to help build the lakehouse foundation.Security and governance at scaleDelta Lake reduces risk by enabling fine-grained access controls for data governance, functionality typically not possible with data lakes. You can quickly and accurately update data in your data lake to comply with regulations like GDPR and maintain better data governance through audit logging. These capabilities are natively integrated and enhanced on Databricks as part of the\u00a0Unity Catalog, the first multi-cloud data catalog for the Lakehouse.Use CasesBI on your dataMake new, real-time data instantly available for querying by data analysts for immediate insights on your business by running business intelligence workloads directly on your data lake. Delta Lake allows you to operate a multicloud lakehouse architecture that provides data warehousing performance at data lake economics for up to 6x better price\/performance for SQL workloads than traditional cloud data warehouses.Learn moreUnify batch and streamingRun both batch and streaming operations on one simplified architecture that avoids complex, redundant systems and operational challenges. In Delta Lake, a table is both a batch table and a streaming source and sink. Streaming data ingest, batch historic backfill and interactive queries all work out of the box and directly integrate with Spark Structured Streaming.Meet regulatory needsDelta Lake removes the malformed data ingestion challenges, difficulty deleting data for compliance, and issues modifying data for change data capture. With support for ACID transactions on your data lake, Delta Lake ensures that every operation either fully succeeds or fully aborts for later retries \u2014 without requiring new data pipelines to be created. Additionally, Delta Lake records all past transactions on your data lake, so it\u2019s easy to access and use previous versions of your data to meet compliance standards like GDPR and CCPA reliably.Data Ingestion NetworkNative connectors easily ingest data into Delta Lake quickly and reliably from all your applications, databases and file storage.Customers\u201cDatabricks delivered the time to market as well as the analytics and operational uplift that we needed in order to be able to meet the new demands of the healthcare sector.\u201d\n\u2013 Peter James, Chief Architect, Healthdirect AustraliaLearn more\u201cBy leveraging Databricks and Delta Lake, we have already been able to democratize data at scale, while lowering the cost of running production workloads by 60%, saving us millions of dollars.\u201d\n\u2014 Steve Pulec, Chief Technology Officer, YipitDataLearn more\u201cDelta Lake provides ACID capabilities that simplify data pipeline operations to increase pipeline reliability and data consistency. At the same time, features like caching and auto-indexing enable efficient and performant access to the data.\u201d\n\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearLearn more\u201cDelta Lake has created a streamlined approach to the management of data pipelines. This has led to a decrease in operational costs while speeding up time-to-insight for downstream analytics and data science.\u201d\n\u2014 Parijat Dey, Assistant Vice President of Digital Transformation and Technology, Viacom18Learn moreResources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.\nExplore ResourceseBooksBig Book Of Data Engineering Use CasesData, Analytics and AI governanceExplore Data Management 101Rise of the Data Lakehouse by Bill Inmon, father of the data warehouseTech talks and trainingGetting Started with Delta Lake \u2013 Tech Talk SeriesWebinarsThe Good The Bad The UglyDeep Dive into Lakehouse with Delta LakeReady to get started?Try Databricks for freeDelta Lake documentationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/machine-learning-nurture\/dsml-demo","text":"\n\n\n\n\n\n\n\nData Science and Machine Learning | Databricks Demo\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/derek-sugden\/#","text":"Derek Sugden - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDerek SugdenAd Measurement Lead \u2013 Measurement & Attribution at EffectvBack to speakersDerek Sugden is an accomplished professional who serves as the Ad Measurement Lead on the Measurement and Attribution Team at Effectv. With a background in Ichthyology, Derek made a transition to the media and entertainment industry over 5 years ago. He brings a unique perspective and a wealth of knowledge to his role, utilizing his expertise to advance attribution capabilities and measure the effectiveness of cross-screen advertising campaigns.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shasidhar-eranti","text":"Shasidhar Eranti - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShasidhar ErantiSpecialist Solutions Architect at DatabricksBack to speakersShasidhar is part of Specialist Solutions Architects team at Databricks. He is an expert in designing and building batch and streaming applications at scale using Apache Spark. At Databricks he works directly with customers to build. deploy and manage end-to-end spark pipelines in production, also help guide towards Spark best practices. \nShashidhar started his Spark journey back in 2014 in Bangalore, later he worked as an independent consultant for couple of years and joined Databricks in 2018.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pulkit-chadha\/#","text":"Pulkit Chadha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPulkit ChadhaSr. Solutions Architect at DatabricksBack to speakersPulkit Chadha is a Sr. Solutions Architect at Databricks. He has over 12 years of experience working in Data Engineering with expertise in building and optimizing data pipelines using various tools and technologies. Pulkit has worked with enterprises in various industries like Healthcare, Media and Entertainment, Hi-Tech, and Manufacturing providing data engineering solutions to meet enterprises' unique business needs. His work history includes the likes of Dell Services, Adobe, and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/gdpr-faqs","text":"Privacy FAQs | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy FAQsDatabricks has put together the guidance on this page to assist our customers in understanding their obligations and our obligations under privacy laws and regulations.DisclaimerThis information does not, and is not intended to, constitute legal advice. All information, content, and materials available below are for general informational purposes only.[NEW] Will Databricks process my data deletion request if it is through a third party?Databricks will process valid data deletion (and other rights) requests. You can exercise your data rights by emailing\u00a0[email\u00a0protected]. There are several third party services that claim they\u2019ll automate data rights requests and help you exercise your rights. However, these services frequently require companies like Databricks to join a network, accept their terms, and provide additional personal data about you back to the services. Because we value your privacy and the security of your information, we treat these requests as spam and will not send these companies additional information about you, and accordingly will not be able to process any data subject requests received through such services.How does Databricks perform onward data transfers?\u00a0\u2014 New Standard Contractual Clauses (SCCs) were published on June 4, 2021. what do I need to do now to lawfully transfer data from the EEA to Databricks?Databricks\u2019\u00a0Platform Services Data Processing Addendum\u00a0(DPA) now uses the\u00a02021 Standard Contractual Clauses\u00a0to transfer personal data to countries outside of the EEA where necessary to provide the Databricks Services. Databricks is a global company and onward data transfers may be used in accordance with our DPA to provide the Platform Services, to provide support, and for our\u00a0Subprocessors.If I am an existing Customer, does this mean I need to update my Agreements with Databricks?The European Data Protection Board\u2019s (EDPB) guidance on the 2021 Standard Contractual Clauses indicates that there is an 18-month grace period for existing data transfers until December 27, 2022. We believe that this means there is no action needed for existing Customers at this time provided that your current data processing agreement with Databricks contains a fall-back to the prior SCCs in the event Privacy Shield was invalidated (note that this was standard in our data processing agreements from 15 July 2019) or otherwise includes the prior SCCs. However, you should consult with your legal team to review the EDPB\u2019s guidance. If you decide you would like to update your Agreement with Databricks, please execute our new\u00a0Platform Services Data Processing Addendum\u00a0and send it to\u00a0[email\u00a0protected]. Note that executing a new DPA will supersede your existing DPA as of the date we acknowledge receipt of the newly executed version.If you have any questions, please reach out to the Databricks privacy team at\u00a0[email\u00a0protected].Privacy Shield was invalidated on July 16, 2020 \u2014 how can I lawfully transfer personal data from the EEA to Databricks?The Court of Justice of the European Union (CJEU)\u00a0ruled\u00a0on 16 July 2020 in the Schrems II case that the\u00a0EU-US Privacy Shield Framework\u00a0is no longer a valid mechanism for companies to transfer personal data from the European Union to the United States. Practically, this means that companies that were relying on the Privacy Shield certification of a vendor to permit the transfer of personal data from the EU to the US must now rely on an alternate mechanism for transfer. Databricks relies on the\u00a02021 Standard Contractual Clauses\u00a0for onward data transfers, as of the data processing addendum released on September 25, 2021. Please see above for any questions on continued use of a prior data processing addendum.General Privacy InformationWhat are Data Rights Requests?Certain privacy laws and regulations provide a right for certain individuals (known as \u2018data subjects\u2019 under the GDPR or \u2018consumers\u2019 under the CCPA) to be able to receive or request action be taken with respect to certain personal data (also known as \u2018personally identifiable information\u2019 or \u2018personal information\u2019). We refer to these requests below generally as \u2018data subject requests\u2019.Databricks has created many self-service features within our product to assist our Customers in complying with their legal obligations relating to the data they process within Databricks. The Databricks Platform can help you satisfy a data subject request with respect to data that you\u2019re holding about a data subject by, for example, permitting you to delete notebooks and cells (including the command history) that may contain personal data.Additionally, you (through the admin on your account) may request that we export or delete personal data on behalf of your users that we may hold. If we determine that a data subject request we receive directly relates to data about your users or the individual has let us know that they believe you hold data about them, we will attempt to notify you prior to responding to such request. Please contact us at\u00a0[email\u00a0protected]\u00a0with any questions.Does Databricks have a data processing agreement?Databricks offers a standalone data processing agreement to comply with certain data protection laws that contains our contractual commitments with respect to applicable data protection and privacy law. If your company determines that you require terms with us relating to an applicable data protection or privacy regulation and you do not yet have in place a data processing addendum (DPA) with us, please review and complete the instructions on our\u00a0DPA.Please note that if you have previously executed a DPA with Databricks, it is likely that the DPA already contains sufficient provisions to meet the requirements of the California Consumer Privacy Act\u2019s provisions relating to agreements between a business and a service provider in order to avoid our processing of any personal data contained within your customer data being deemed a \u2018sale\u2019 under the CCPA. If you are concerned that it does not, please either execute a new DPA with Databricks (available at\u00a0https:\/\/www.databricks.com\/legal\/dpa) or reach out to us at\u00a0[email\u00a0protected]\u00a0with any questions you may have.Can using Databricks help me comply with applicable data protection laws, like the GDPR or CCPA?While there\u2019s no product out there that can make you GDPR- or CCPA- compliant by itself, Databricks offers some truly unique functionality that may help you with your privacy compliance, particularly if you\u2019re using data lakes to store personal data that might be subject to a data subject request (DSR). Please see the\u00a0blog\u00a0we posted on this for GDPR (and\u00a0here, for CCPA) and a\u00a0webinar\u00a0where we discuss how using Databricks Delta Lake can help you process DSRs in a data lake scenario that might otherwise be nearly impossible.Additionally, one of the most important steps Databricks takes to help you be GDPR and CCPA compliant is that we minimize the amount of data that we actually receive from you in the first place. Databricks is architected to ensure that the vast majority of customer data, including personal data, does not leave the environments specified by the customer (e.g. their cloud storage). Unlike many vendors that require customers to copy customer data into the vendor\u2019s environment, requiring a customer to worry that the supplier won\u2019t properly respond to a deletion request in a sufficient time to allow the customer to meet prescribed GDPR or CCPA requirements, the Databricks platform is designed to allow customers to keep their data within their own cloud environment under their control. While some customer data (and therefore some personal data) may end up in notebooks, we provide self-service functionality to enable a customer to delete this information (e.g., in response to a data subject request). So when the customer is required to delete data under a data subject request, or wants to make sure that it knows where its data is, the customer can rest easy knowing that the processes and controls they have already set up for their data remain applicable when using the Databricks platform.What are Databricks\u2019 privacy features?In particular, Databricks:offers functionality within our product for our customers to be able to permanently delete notebooks and cells, along with the corresponding revision history, that may contain personal data, and making sure that, once marked for deletion, those contents are permanently purged within 30 days after being marked for deletion without any need for customers to take additional action;implemented pseudonymization techniques (in short \u2013 splitting user-specific records into a piece that cannot, by itself, identify the particular individual and a separately stored piece that can be used to return the data to an identifiable form only when needed) and redaction techniques to add an additional layer of protection on personal data (like a user email address) that might be recorded in Databricks\u2019 usage logs;offers Databricks Delta Lake, a unified data management system built into the Databricks platform, that dramatically simplifies the task of being able to perform data subject requests against data stored in data lakes; andhas put in place systems to be able to process data subject requests in a timely manner; andself-certified to Privacy Shield, certified to\u00a0ISO27001, and attested to ISO27018, the internationally recognized industry standard approach for protecting personal data in the cloud. Additionally, on an annual basis, Databricks obtains an independently audited SOC 2 Type II report, which can be made available to you under NDA.California Consumer Privacy Act (CCPA) Specific InformationWhat is the CCPA?The California Consumer Privacy Act (\u201cCCPA\u201d) is a California privacy law intended to protect California consumers from businesses that improperly collect, use, or share their personal information, and is changing the way businesses have to manage and protect the consumer data they collect and store.Is my company subject to the CCPA?The CCPA is broadly applicable to businesses that operate in California. The CCPA covers businesses that:Have annual gross revenues in excess of twenty-five million dollars ($25,000,000), as adjusted pursuant to paragraph (5) of subdivision (a) of Section 1798.185Alone or in combination, annually buy, receive for the business\u2019s commercial purposes, sell, or share for commercial purposes, alone or in combination, the personal information of 50,000 or more consumers, households, or devices.Derive 50 percent or more of its annual revenues from selling consumers\u2019 personal information.The CCPA may also cover \u2018service providers\u2019 that work with businesses subject to the CCPA.Does complying with the GDPR mean I am already compliant with the CCPA?Many companies wrongfully think that the data privacy processes and controls put in place for GDPR compliance will guarantee compliance with the CCPA\u2013and while the things you may have done to prepare for the GDPR are helpful and a great start\u2013they are unlikely to be sufficient. Companies need to focus on understanding their need for compliance and must determine which processes and controls can effectively prevent the misuse and unauthorized sale of consumer data.What does the CCPA require me to do?Similar to the GDPR, the CCPA empowers individuals to request:what personal information is being captured,how personal information is being used, andto have that personal information deleted.Additionally, the CCPA (unlike the GDPR) encompasses information about \u2018households\u2019. While the CCPA does not define what is meant by a \u2018household\u2019, this has potential to significantly expand the scope of personal information subject to these requests. Failure to comply in a timely manner can result in statutory fines and statutory damages (where a consumer need not even prove damages) that can rise quickly. The challenge for companies doing business in California or otherwise subject to the CCPA, then, is to ensure they can quickly find, secure, and delete that personal informationEU General Data Protection Regulation (GDPR) Specific InformationWhat is the GDPR?GDPR stands for the EU General Data Protection Regulation, and it codifies certain rights related to personal data originating from the European Economic Area (EEA). The GDPR replaces the EU Data Protection Directive (aka Directive 95\/46\/EC), an EU directive that had been in place regarding data protection since 1995. The GDPR is a regulation, rather than a directive, meaning that instead of prescribing results that must be obtained and allowing each member state of the EU to put in place its own laws, the GDPR mostly harmonizes the approach for data protection and privacy throughout the entire EEA by imposing specific requirements that must be met. It comes into force on May 25, 2018.Is my company subject to the GDPR?The short answer is almost certainly yes. You should confirm with your privacy legal counsel, but with few exceptions, the GDPR applies to any company that collects or processes personal data of individuals located in the EEA.What does the GDPR require me to do?The GDPR is extraordinarily complex (the regulation spans 99 articles across 88 pages of dense legal text). However, the obligations imposed by the GDPR boil down to seven core principles:Lawfulness, fairness and transparency. Personal data shall be processed lawfully, fairly and in a transparent manner in relation to the data subjectPurpose limitation. Personal data shall be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposesData minimisation. Personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processedAccuracy. Personal data shall be accurate and, where necessary, kept up to dateStorage limitation. Personal data shall be kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processedIntegrity and confidentiality. Personal data shall be processed in a manner that ensures appropriate security of the personal data, including protection against unauthorised or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organisational measuresAccountability. The controller shall be responsible for, and be able to demonstrate compliance with the GDPR.How can I contact Databricks\u2019 EU representative?Databricks has appointed a representative in the EU in accordance with Article 27 of the GDPR. You may contact our representative at\u00a0[email\u00a0protected]Additional ResourcesMake your Data Lake CCPA CompliantHow to avoid drowning in DSRs in a data lakeGDPR WebinarGDPR Compliance PrimerDatabricks DocumentationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/kr\/product\/pricing","text":"Databricks \uac00\uaca9 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\uc7a5\uae30 SQL \uc694\uae08 \ud504\ub85c\ubaa8\uc158 - 40% \uc774\uc0c1 \uc808\uac10 Serverless SQL \ubc0f \uc0c8\ub85c\uc6b4 SQL Pro\ub97c \ub300\uc0c1\uc73c\ub85c \ud55c 15\uac1c\uc6d4 \ud504\ub85c\ubaa8\uc158\uc744 \ud65c\uc6a9\ud574 \ubcf4\uc138\uc694\uc790\uc138\ud788Databricks \uac00\uaca9\ub2e8\uc21c\ud55c \ub2e8\uc77c \ud50c\ub7ab\ud3fc\uc73c\ub85c \uc120\ud638\ud558\ub294 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d, AI, \uc6cc\ud06c\ub85c\ub4dc\ub97c \ud1b5\ud569\ubb34\ub8cc \uccb4\ud5d8 \uc2dc\uc791Databricks \uac00\uaca9\uc740 \uc5b4\ub5bb\uac8c \ucc45\uc815\ub418\ub098\uc694?\uc0ac\uc6a9\ud558\ub294 \ub9cc\ud07c \uc9c0\ubd88Databricks\ub294 \uc120\ubd88 \ube44\uc6a9 \uc5c6\uc774 \uc0ac\uc6a9\ud558\ub294 \ub9cc\ud07c \ube44\uc6a9\uc744 \uc9c0\ubd88\ud569\ub2c8\ub2e4. \uc0ac\uc6a9 \uc81c\ud488\uc5d0 \ub300\ud574 \ucd08 \ub2e8\uc704\ub85c \uc9c0\ubd88\ud569\ub2c8\ub2e4.\ud655\uc815 \uc0ac\uc6a9 \ub514\uc2a4\uce74\uc6b4\ud2b8\ub85c \ub354 \ud06c\uac8c \uc808\uc57dDatabricks\ub294 \uc0ac\uc6a9\uc790\uac00 \ud2b9\uc815 \uc0ac\uc6a9\ub7c9\uc744 \ud655\uc815\ud560 \ub54c \ub354 \ud070 \ud560\uc778 \ud61c\ud0dd\uc744 \ub4dc\ub9bd\ub2c8\ub2e4. \ud655\uc815 \uc0ac\uc6a9\ub7c9\uc774 \ub9ce\uc744\uc218\ub85d \uc0ac\uc6a9\ud55c \ub9cc\ud07c \uc9c0\ubd88\ud560 \ub54c\ubcf4\ub2e4 \ub354 \ud070 \ud560\uc778\uc774 \uc81c\u0000\u0000\uacf5\ub418\uace0 \uc5ec\ub7ec \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ud655\uc815 \uc694\uae08\uc744 \uc720\uc5f0\ud558\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740  \ubb38\uc758\ub97c \ud1b5\ud574 \ud655\uc778\ud558\uc138\uc694.\uc81c\ud488 \ub458\ub7ec\ubcf4\uae30\uc6cc\ud06c\ud50c\ub85c \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d\uc791\uc5c5Starting at $0.07 \/ DBU\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc2e4\ud589\ud558\uc5ec \ub370\uc774\ud130 \ub808\uc774\ud06c\ub97c \uad6c\ucd95\ud558\uace0 \uaddc\ubaa8\uc5d0 \ub9de\uac8c \ub370\uc774\ud130\ub97c \uad00\ub9ac\ud558\uc138\uc694.\uc790\uc138\ud788\uc6cc\ud06c\ud50c\ub85c \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d Delta Live \ud14c\uc774\ube14Starting at $0.20 \/ DBU\uc790\uc2e0\uc758 \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \uac00\uc7a5 \uc801\ud569\ud55c DLT \uc5d0\ub514\uc158\uc5d0\uc11c Python\uc774\ub098 SQL\uc744 \uc0ac\uc6a9\ud558\uc5ec \uace0\ud488\uc9c8\uc758 \uc2a4\ud2b8\ub9ac\ubc0d \ub610\ub294 \ubc30\uce58 ETL \ud30c\uc774\ud504\ub77c\uc778\uc744 \uac04\ud3b8\ud558\uac8c \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5Databricks SQLStarting at $0.22 \/ DBUBI \ubcf4\uace0, \ubd84\uc11d \ubc0f \uc2dc\uac01\ud654\uc5d0 SQL \ucffc\ub9ac\ub97c \uc2e4\ud589\ud558\uc5ec \ub370\uc774\ud130 \ub808\uc774\ud06c\ub85c\ubd80\ud130 \uc2dc\uae30 \uc801\uc808\ud55c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc2b5\ub2c8\ub2e4. Classic \ubc0f Serverless (\uad00\ub9ac\ud615) \ucef4\ud4e8\ud305\uc5d0 \ubaa8\ub450 \uc81c\uacf5\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2dd\ubaa8\ub4e0 \uc6a9\ub3c4Starting at $0.40 \/ DBU\uc778\ud130\ub799\ud2f0\ube0c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2dd \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc2e4\ud589\ud574\ubcf4\uc138\uc694. \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, BI, \ub370\uc774\ud130 \ubd84\uc11d\uc5d0\ub3c4 \uc720\uc6a9\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2ddServerless \uc2e4\uc2dc\uac04 \uc720\ucd94Starting at $0.07 \/ DBU\uc571\uacfc \uc6f9\uc0ac\uc774\ud2b8\uc5d0\uc11c \uc2e4\uc2dc\uac04 \uc608\uce21\uc744 \uc218\ud589\ud558\uc138\uc694.\n\uc790\uc138\ud788Databricks \ud50c\ub7ab\ud3fc \ubc0f \uc560\ub4dc\uc628Databricks \ud50c\ub7ab\ud3fc \ubc0f \uc560\ub4dc\uc628\ud50c\ub7ab\ud3fc \uacc4\uce35: \uae30\ubcf8 \uc6cc\ud06c\ub85c\ub4dc\uc5d0\uc11c \uc5d4\ud130\ud504\ub77c\uc774\uc988\uc5d0 \uc911\uc694\ud55c \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0 \ubaa8\ub4e0 \uac83\uc744 \uc2e4\ud589\ud560 \uc218 \uc788\ub3c4\ub85d \uc801\uc808\ud55c \uc218\uc900\uc758 \uad00\ub9ac, \uac70\ubc84\ub10c\uc2a4 \ubc0f \ubcf4\uc548\uc744 \uc81c\uacf5\ud558\ub294 \ud50c\ub7ab\ud3fc \uac04 \uae30\ub2a5\n\ud50c\ub7ab\ud3fc \uc560\ub4dc\uc628: \ud5a5\uc0c1\ub41c \uad00\ub9ac, \uac70\ubc84\ub10c\uc2a4 \ubc0f \ubcf4\uc548 \uae30\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 Databricks \ud50c\ub7ab\ud3fc\uc5d0 \ub300\ud55c \uc81c\ud488 \uac04 \ud5a5\uc0c1 \uae30\ub2a5\uc790\uc138\ud788Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\ub370\ubaa8 \uc608\uc57dFAQ\ubb34\ub8cc \uccb4\ud5d8\uc5d0\ub294 \ubb34\uc5c7\uc774 \ud3ec\ud568\ub418\ub098\uc694?14\uc77c \ubb34\ub8cc \ud3c9\uac00\ud310 \uc0ac\uc6a9\uc758 \uc774\uc810:\uc5ec\ub7ec \ub370\uc774\ud130 \ud300\uc774 \ud568\uaed8 \uc194\ub8e8\uc158\uc744 \uac1c\ubc1c\ud558\uae30 \uc88b\uc740 \ud611\uc5c5\ud615 \ud658\uacbd\ub300\ud654\ud615 \ub178\ud2b8\ubd81\uc5d0\uc11c Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn \ub4f1\uc744 \uc0ac\uc6a9\ubb34\ub8cc \ud3c9\uac00\ud310 \uae30\uac04 \ub3d9\uc548 \uadc0\ud558\uc758 \uacc4\uc815\uc5d0\uc11c \uc0ac\uc6a9\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4 \uc81c\uacf5\uc790\uc758 \ub9ac\uc18c\uc2a4(\uc608: \ucef4\ud4e8\ud305 \uc778\uc2a4\ud134\uc2a4)\uc5d0 \ub530\ub77c \ube44\uc6a9\uc774 \ubd80\uacfc\ub429\ub2c8\ub2e4.\ubb34\ub8cc \uccb4\ud5d8\uc774 \ub05d\ub098\uba74 \uc5b4\ub5bb\uac8c \ub418\ub098\uc694?\ud3c9\uac00\ud310 \uc0ac\uc6a9 \uae30\uac04\uc774 \uc885\ub8cc\ub418\uba74 \ubb34\ub8cc \ud3c9\uac00\ud310\uc744 \uc0ac\uc6a9\ud558\ub294 \ub3d9\uc548 \uc774\uc6a9\ud588\ub358 \uc694\uae08\uc81c\ub97c \uc790\ub3d9\uc73c\ub85c \uad6c\ub3c5\ud558\uac8c \ub429\ub2c8\ub2e4. \uad6c\ub3c5\uc740 \uc5b8\uc81c\ub4e0 \ucde8\uc18c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uac00\uaca9\uc740 \uc0ac\uc6a9\ub7c9\uc774\ub098 \uc2a4\ud1a0\ub9ac\uc9c0 \uc6a9\ub7c9\uc744 \uae30\ubc18\uc73c\ub85c \ud558\ub098\uc694?Databricks \uac00\uaca9\uc740 \ucef4\ud4e8\ud305 \uc0ac\uc6a9\ub7c9\uc5d0 \uae30\ubc18\ud569\ub2c8\ub2e4. \uc2a4\ud1a0\ub9ac\uc9c0\uc640 \ub124\ud2b8\uc6cc\ud06c \ube44\uc6a9 \ubc0f \uae30\ud0c0 \uad00\ub828 \ube44\uc6a9\uc740 \uc120\ud0dd\ud558\ub294 \uc11c\ube44\uc2a4\uc640 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4 \uc81c\uacf5\uc0ac\uc5d0 \ub530\ub77c \ub2ec\ub77c\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.DBU\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?Databricks Unit(DBU)\uc740 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc0ac\uc6a9\ub418\ub294 \ucc98\ub9ac \ub2a5\ub825\uc758 \uc815\uaddc \ub2e8\uc704\ub85c, \uad00\ub9ac \ubc0f \uac00\uaca9 \ucc45\uc815 \ubaa9\uc801\uc73c\ub85c \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \uc0ac\uc6a9\ub418\ub294 DBU \uac1c\uc218\ub294 \ud504\ub85c\uc138\uc2f1 \uba54\ud2b8\ub9ad\uc2a4\uc5d0 \uae30\ubc18\ud558\uba70, \uc0ac\uc6a9 \ucef4\ud4e8\ud305 \ub9ac\uc18c\uc2a4\uc640 \ucc98\ub9ac \ub370\uc774\ud130 \uc6a9\ub7c9\uc774 \ud3ec\ud568\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uac00\uaca9\uc774 \ubaa8\ub4e0 \ub9ac\uc804\uc5d0\uc11c \ub3d9\uc77c\ud55c\uac00\uc694?Databricks \uc694\uae08\uacfc \ud074\ub77c\uc6b0\ub4dc \uc778\ud504\ub77c \uc694\uae08\uc740 \uc9c0\ub9ac\uc801 \ub9ac\uc804 \ubc0f \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4 \uc81c\uacf5\uc0ac\uc5d0 \ub530\ub77c \ub2ec\ub77c\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uac01 \uc81c\ud488\uc758 Databricks \uc694\uae08 \ud398\uc774\uc9c0\ub97c \ucc38\uc870\ud558\uc138\uc694.Databricks\uac00 \ub2e4\ub978 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4\ub098 \uc624\ud508 \uc18c\uc2a4 \uc194\ub8e8\uc158\ub9cc\ud07c \ube44\uc6a9 \ud6a8\uc728\uc801\uc778\uac00\uc694?Databricks \uc81c\ud488\uc740 \uace0\uac1d\uc758 \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \ud6a8\uacfc\uc801\uc778 \ucd1d\uc18c\uc720\ube44\uc6a9(TCO)\uc744 \uc81c\uacf5\ud558\ub3c4\ub85d \uac00\uaca9\uc774 \ucc45\uc815\ub429\ub2c8\ub2e4. Databricks\uc758 \ube44\uc6a9 \uc808\uac10 \ud6a8\uacfc\ub97c \ucd94\uc0b0\ud560 \ub54c\ub294\uc791\uc5c5 \uc644\uc131\ub960, \uae30\uac04, \ud544\uc694\ud55c \uc218\ub3d9 \uc791\uc5c5 \ubc0f \ub9ac\uc18c\uc2a4 \ub4f1\uc744 \ud3ec\ud568\ud55c \ub300\uccb4 \uc194\ub8e8\uc158\uc758 \uc8fc\uc694 \uce21\uba74\uc744 \uace0\ub824\ud574\uc57c \ud569\ub2c8\ub2e4. \uc815\ud655\ud55c \uc808\uac10\uc561 \ucd94\uc0b0\uc5d0 \ub3c4\uc6c0\uc744 \ubc1b\uc73c\ub824\uba74 \uac1c\ub150 \uc99d\uba85 \ubc30\ud3ec\uc758 \uc77c\ud658\uc73c\ub85c \uc5ec\ub7ec \uacb0\uacfc\ub97c \ub098\ub780\ud788 \ube44\uad50\ud558\ub294 \ud3b8\uc774 \uc88b\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \uc774 \uace0\uac1d\uc758 \ub2a5\ub960 \ud5a5\uc0c1 \uc815\ub3c4\uc640\uc640 \uace0\uac1d \ubca4\uce58\ub9c8\ud06c\uc758 \uacb0\uacfc\ub97c\ud655\uc778\ud574 \ubcf4\uc138\uc694. \uc2dc\uc791\ud558\ub824\uba74. \ubb38\uc758\ud574 \uc8fc\uc138\uc694.Databricks Community Edition\uc774\ub780 \ubb34\uc5c7\uc778\uac00\uc694?Databricks Community Edition\uc740 Spark\ub97c \ubc30\uc6b0\uace0\uc790 \ud558\ub294 \ubaa8\ub4e0 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uc81c\ud55c\uc801\uc73c\ub85c \uae30\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 \ubb34\ub8cc \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. \uc5ec\uae30\uc5d0\uc11c \ub4f1\ub85d\ud558\uc138\uc694.\uc694\uae08\uc740 \uc5b4\ub5bb\uac8c \uccad\uad6c\ub418\ub098\uc694?\uae30\ubcf8\uc801\uc73c\ub85c \ucd08\ub2f9 \uc0ac\uc6a9\ub7c9\uc744 \uae30\uc900\uc73c\ub85c \ud55c \uc6d4 \uc694\uae08\uc774 \uc2e0\uc6a9\uce74\ub4dc\ub85c \uccad\uad6c\ub429\ub2c8\ub2e4. \uc790\uc138\ud55c \uccad\uad6c \uc635\uc158(\uc608: \uccad\uad6c\uc11c\ub97c \ud1b5\ud55c \uccad\uad6c, \uc5f0\uac04 \ud50c\ub79c)\uc740 \uc0c1\ub2f4\uc744 \ud1b5\ud574 \ubb38\uc758\ud558\uc138\uc694.\uae30\uc220 \uc9c0\uc6d0\uc744 \uc81c\uacf5\ud558\ub098\uc694?Databricks\uc5d0\uc11c\ub294 \uae30\uc220 \uc9c0\uc6d0\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \ub610\ud55c \uae30\uc220 \ubb38\uc11c\ub97c \ud655\uc778\ud558\uc2e4 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \ubb38\uc758\ud558\uc138\uc694.\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\u0000\u0000\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
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{"source":"https:\/\/www.databricks.com\/product\/collaborative-notebooks","text":"Databricks Notebooks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks NotebooksCollaborative data science with familiar languages and toolsTry for freeSchedule a demoWork across engineering, data science and machine learning teams in one workspace. Use multiple languages, built-in data visualizations and automatic versioning, all within Notebooks.BenefitsWork togetherShare Notebooks and work with peers across teams in multiple languages (R, Python, SQL and Scala) and libraries of your choice. Real-time coauthoring, commenting and automated versioning simplify collaboration while providing control.Share insightsQuickly discover new insights with built-in interactive visualizations, or leverage libraries such as Matplotlib and ggplot. Export results and Notebooks in HTML or IPYNB format, or build and share dashboards that always stay up to date.Production at scaleSchedule Notebooks to automatically run machine learning and data pipelines at scale. Create multistage pipelines using Databricks Workflows. Set up alerts and quickly access audit logs for easy monitoring and troubleshooting.FeaturesData AccessQuickly access available data sets or connect to any data source, on-premises or in the cloud.DashboardsShare insights with your colleagues and customers, or let them run interactive queries with Spark-powered dashboards.Multi-language supportExplore data using interactive notebooks with support for multiple programming languages within the same notebook, including R, Python, Scala and SQL.Run Notebooks as JobsTurn notebooks or JARs into resilient production jobs with a click or an API call.Interactive VisualizationsVisualize insights through a wide assortment of point-and-click visualizations. Or use powerful scriptable options like Matplotlib, ggplot and D3.Jobs SchedulerExecute jobs for production pipelines on a specific schedule.Real-Time CoauthoringWork on the same notebook in real time while tracking changes with detailed revision history.Notebook WorkflowsCreate multistage pipelines with the control structures of the source programming language.CommentsLeave a comment and notify colleagues from within shared Notebooks.Notifications and LogsSet up alerts and quickly access audit logs for easy monitoring and troubleshooting.Automatic VersioningAutomatic change-tracking and versioning to help you pick up where you left off.Permissions ManagementQuickly manage access to each individual notebook, or a collection of Notebooks, and experiments, with one common security model.Git-based ReposSimplified Git-based collaboration, reproducibility and CI\/CD workflows.ClustersQuickly attach Notebooks to auto-managed clusters to efficiently and cost-effectively scale up compute.Runs SidebarAutomatically log experiments, parameters and results from Notebooks directly to MLflow as runs, and quickly see and load previous runs and code versions from the sidebar.IntegrationsConnect to Tableau, Looker, Power BI, RStudio, Snowflake and also through your favorite IDEs such as VS Code \u2014 allowing data scientists and engineers to use their tools of choice.How it worksShared and interactive Notebooks, experiments and extended files support allow data scientist teams to organize, share and manage complex data science projects more effectively throughout the lifecycle. APIs and Job Scheduler allow data engineering teams to quickly automate complex pipelines, while business analysts can directly access results via interactive dashboards.Overview of collaborative featuresVisualize your dataManage, schedule, and scale nodesCustomersResourcesDocumentationNotebooksJobseBooks and WebinarsThe Big Book of Data Science Use CasesThe Big Book of Machine Learning Use CasesAutoML Rapid, simplified machine learning for everyoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningThe Data Scientist\u2019s Guide to Apache Spark\u2122The Apache Spark\u2122 CollectionMLOps Virtual EventManaging the Complete Machine Learning LifecycleProduct DemoCollaboration in DatabricksVisualizations in DatabricksCase StudyHPNielsenReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/data-engineering","text":"Data Engineering | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWData EngineeringMillionen Produktions-Workloads werden t\u00e4glich auf Databricks ausgef\u00fchrtErste SchritteDemo ansehen\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowNehmen Sie Batch- und Streaming-Daten auf einfache Weise in die\u00a0Databricks Lakehouse-Plattform auf und transformieren Sie sie. Orchestrieren Sie zuverl\u00e4ssige Produktionsabl\u00e4ufe, w\u00e4hrend Databricks Ihre Infrastruktur automatisch in gro\u00dfem Ma\u00dfstab verwaltet. Steigern Sie die Produktivit\u00e4t Ihrer Teams mit integrierten Datenqualit\u00e4tstests und Support f\u00fcr Best Practices f\u00fcr die Softwareentwicklung.Batch und Streaming zusammenf\u00fchrenBeseitigen Sie die Trennung von Datenbest\u00e4nden und f\u00fchren Sie sie auf einer Plattform mit einer einzigen und einheitlichen API zusammen, um Batch- und Streaming-Daten in gro\u00dfem Ma\u00dfstab zu erfassen, zu transformieren und schrittweise zu verarbeiten.Auf die Wertsch\u00f6pfung aus Daten konzentrierenDatabricks verwaltet automatisch Ihre Infrastruktur und die operativen Komponenten Ihrer Produktionsabl\u00e4ufe, sodass Sie sich auf die Wertsch\u00f6pfung und nicht auf die Tools konzentrieren k\u00f6nnen.Die Tools Ihrer Wahl verbindenEine offene Lakehouse-Plattform zum Verbinden und Verwenden Ihrer bevorzugten Data Engineering-Tools f\u00fcr Datenaufnahme, ETL\/ELT und Orchestrierung.Auf der Lakehouse-Plattform entwickeltDie Lakehouse-Plattform bietet die beste Grundlage f\u00fcr die Entwicklung und die gemeinsame Nutzung vertrauensw\u00fcrdiger Datenbest\u00e4nde, die zentral verwaltet werden, zuverl\u00e4ssig und blitzschnell sind.\u201eF\u00fcr uns wird Databricks zum Allzweck-Tool f\u00fcr unsere gesamte ETL-Arbeit. Je mehr wir mit der Lakehouse-Plattform arbeiten, desto einfacher ist sie sowohl f\u00fcr Benutzer als auch f\u00fcr Plattformadministratoren.\u201c\u2013 Hillevi Crognale, Engineering Manager, YipitDataWie funktioniert es?Vereinfachte DatenaufnahmeAutomatisierte ETL-VerarbeitungZuverl\u00e4ssige Workflow-OrchestrierungDurchg\u00e4ngige Beobachtbarkeit und \u00dcberwachungDatenverarbeitungs-Engine der n\u00e4chsten GenerationGrundlage von Governance, Zuverl\u00e4ssigkeit und LeistungVereinfachte DatenaufnahmeNehmen Sie Daten in Ihre Lakehouse-Plattform auf und betreiben Sie Ihre Analytics-, KI- und Streaming-Anwendungen von einem Ort aus.\u00a0Auto Loader\u00a0verarbeitet Dateien, die im Cloud-Speicher landen, inkrementell und automatisch in geplanten oder kontinuierlichen Jobs, ohne dass Statusinformationen verwaltet werden m\u00fcssten. Neue Dateien werden effizient \u00fcberwacht, ohne sie in einem Verzeichnis auflisten zu m\u00fcssen, wobei das System bis in den Milliardenbereich skaliert. Au\u00dferdem kann Auto Loader das Schema automatisch aus den Quelldaten ableiten und im Laufe der Zeit an aufkommende \u00c4nderungen anpassen. Der Befehl\u00a0COPY INTO\u00a0erleichtert Analysten die Batch-Dateiaufnahme in\u00a0Delta Lake\u00a0\u00fcber SQL.\u201eWir konnten eine Produktivit\u00e4tssteigerung von 40\u00a0% beim Data Engineering verzeichnen \u2013 die Zeit, die f\u00fcr die Entwicklung neuer Ideen ben\u00f6tigt wird, wurde von Tagen auf Minuten reduziert und die Verf\u00fcgbarkeit und Genauigkeit unserer Daten erh\u00f6ht.\u201c\u2013 Shaun Pearce, Chief Technology Officer,\u00a0GoustoMehr InformationenAutomatisierte ETL-VerarbeitungNach der Erfassung m\u00fcssen Rohdaten transformiert werden, um sie f\u00fcr Analytics und KI aufzubereiten. Databricks bietet mit\u00a0Delta-Live-Tables\u00a0(DLT) leistungsstarke ETL-Funktionen f\u00fcr Data Engineers, Data Scientists und Analysten. DLT ist das erste Framework, das in der Lage ist, mithilfe eines einfachen deklarativen Ansatzes ETL- und ML-Pipelines f\u00fcr Batch- oder\u00a0Streaming-Daten zu erstellen und gleichzeitig betriebliche Komplexit\u00e4ten wie Infrastrukturmanagement, Aufgabenorchestrierung, Fehlerbehandlung und Wiederherstellung sowie Leistungsoptimierung zu automatisieren. Mit DLT k\u00f6nnen Engineers ihre Daten auch als Code behandeln und Best Practices f\u00fcr die Softwareentwicklung wie Tests, \u00dcberwachung und Dokumentation anwenden, um zuverl\u00e4ssige Pipelines auch in gro\u00dfer Zahl bereitzustellen.Mehr InformationenZuverl\u00e4ssige Workflow-OrchestrierungDatabricks\u00a0Workflows\u00a0ist der vollst\u00e4ndig verwaltete Orchestrierungsservice f\u00fcr alle Ihre Daten, Analytics und KI und nativ in Ihrer\u00a0Lakehouse-Plattform vorhanden. Orchestrieren Sie verschiedene Workloads f\u00fcr den gesamten Lebenszyklus, einschlie\u00dflich\u00a0Delta-Live-Tables\u00a0und\u00a0Jobs f\u00fcr SQL,\u00a0Spark, Notebooks, dbt, ML-Modelle und mehr. Die tiefgreifende Integration in die zugrunde liegende Lakehouse-Plattform stellt sicher, dass Sie zuverl\u00e4ssige Produktions-Workloads in jeder Cloud erstellen und ausf\u00fchren und gleichzeitig eine umfassende und zentralisierte, f\u00fcr Endbenutzer jedoch niederschwellige \u00dcberwachung bieten.\u201eUnsere Mission ist es, die Art und Weise zu ver\u00e4ndern, wie wir den Planeten mit Energie versorgen. Unsere Kunden im Energiesektor ben\u00f6tigen Daten, Beratungsdienste und Forschung, um diese Transformation zu erreichen. Databricks Workflows gibt uns die Geschwindigkeit und Flexibilit\u00e4t, um die Erkenntnisse zu liefern, die unsere Kunden ben\u00f6tigen.\u201c\u2014 Yanyan Wu, Vice President of Data,\u00a0Wood MackenzieMehr InformationenDurchg\u00e4ngige Beobachtbarkeit und \u00dcberwachungDie Lakehouse-Plattform bietet Ihnen Transparenz \u00fcber den gesamten Daten- und KI-Lebenszyklus, sodass Data Engineers und Betriebsteams den Zustand ihrer Produktionsabl\u00e4ufe in Echtzeit sehen, die Datenqualit\u00e4t verwalten und historische Trends verstehen k\u00f6nnen. In Databricks\u00a0Workflows\u00a0k\u00f6nnen Sie auf Datenflussdiagramme und Dashboards zugreifen, die den Zustand und die Leistung Ihrer Produktionsauftr\u00e4ge und\u00a0Delta Live Tables-Pipelines\u00a0verfolgen. Ereignisprotokolle werden auch als\u00a0Delta Lake Tables\u00a0angezeigt, sodass Sie Leistungs-, Datenqualit\u00e4ts- und Zuverl\u00e4ssigkeits-Metrics aus jedem Blickwinkel \u00fcberwachen und visualisieren k\u00f6nnen.Datenverarbeitungs-Engine der n\u00e4chsten GenerationDatabricks Data Engineering basiert auf\u00a0Photon. Photon ist die mit Apache Spark-APIs kompatible Next-Generation-Engine, die ein\u00a0rekordverd\u00e4chtiges\u00a0Preis-Leistungs-Verh\u00e4ltnis bietet und gleichzeitig automatisch auf Tausende von Knoten skalierbar ist.\u00a0Spark Structured Streaming\u00a0implementiert eine zentrale und einheitliche API f\u00fcr die Batch- und Stream-Verarbeitung, sodass\u00a0Streaming im Lakehouse\u00a0ganz einfach eingef\u00fchrt werden kann, ohne Code \u00e4ndern oder neue Kompetenzen erwerben zu m\u00fcssen.Mehr InformationenModernste Data-Governance, Zuverl\u00e4ssigkeit und LeistungData Engineering auf Databricks bedeutet, dass Sie von den grundlegenden Komponenten der\u00a0Lakehouse-Plattform\u00a0\u2013 Unity Catalog und Delta Lake \u2013 profitieren. Ihre Rohdaten sind f\u00fcr\u00a0Delta Lake optimiert, ein Open-Source-Speicherformat, das durch ACID-Transaktionen zuverl\u00e4ssig ist und skalierbare Metadatenbearbeitung mit blitzschneller Leistung bietet. In Kombination mit\u00a0Unity Catalog\u00a0erhalten Sie eine detaillierte Governance f\u00fcr alle Ihre Daten- und KI-Assets. So wird die Art und Weise, wie Sie Governance durchsetzen, mit einem einheitlichen Modell vereinfacht, um Daten \u00fcber Clouds hinweg zu entdecken, darauf zuzugreifen und sie zu teilen. Unity Catalog bietet auch native Unterst\u00fctzung f\u00fcr\u00a0Delta Sharing, das branchenweit erste offene Protokoll f\u00fcr den einfachen und sicheren Datenaustausch mit anderen Unternehmen.Zu Databricks migrierenSind die Datensilos, die langsame Leistung und die hohen Kosten f\u00fcr Altsysteme wie Hadoop und Enterprise Data Warehouses m\u00fcde? Holen Sie sich eine einzige moderne Plattform f\u00fcr alle Ihre Daten-, Analytics- und KI-Anwendungsf\u00e4lle.Zu Databricks migrierenIntegrationenBieten Sie Ihren Datenteams maximale Flexibilit\u00e4t \u2013 nutzen Sie\u00a0Partner Connect\u00a0und ein \u00d6kosystem aus\u00a0Technologiepartnern,\u00a0um nahtlos beliebte Data Engineering-Tools zu integrieren. Sie k\u00f6nnen beispielsweise gesch\u00e4ftskritische Daten mit Fivetran aufnehmen, sie mit dbt transformieren und Ihre Pipelines mit Apache Airflow orchestrieren.Datenaufnahme und ETL+ jeder sonstige Apache Spark\u2122-kompatible ClientKundenberichteMehr entdeckenDelta LakeWorkflowsDelta Live TablesDelta-Freigabe\u00c4hnliche Inhalte\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu den Vorteilen von Data Engineering in Databricks.\nRessourcen erkundenE-Books\u201eErrichten eines Data Lakehouse\u201c von Bill Inmon, dem Vater des Data WarehouseDaten, Analysen und KI-GovernanceGrundlagen des DatenmanagementsDas gro\u00dfe Buch des Data EngineeringDie neue Delta-Sharing-L\u00f6sung erkundenMigrieren von einem Data Warehouse zu einem Data Lakehouse f\u00fcr DummiesVeranstaltungenDatentransformation \u2013 mit Delta Live Tables kein ProblemProblemlose Datenerfassung Webinar-ReiheDATA+AI SUMMIT 2022Ihr Data Warehouse modernisierenBlogsBekanntgabe der allgemeinen Verf\u00fcgbarkeit von Databricks Delta Live Tables (DLT)Einf\u00fchrung in die Databricks-Abl\u00e4ufeEin \u00dcberblick \u00fcber alle neuen strukturierten Streaming-Funktionen, die 2021 f\u00fcr Databricks und Apache Spark entwickelt wurden10 leistungsstarke Funktionen zur Vereinfachung des halbstrukturierten Datenmanagements im Databricks LakehouseM\u00f6chten Sie loslegen?Kostenlos testenMitglied der Community werdenAWSAzureGCPProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/azure-databricks-cloud-integration","text":"Azure Databricks Demo: Seamless Cloud Integration | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAzure Databricks Cloud Integration DemoDownload NotebooksTry DatabricksThe Azure Databricks Lakehouse Platform gives you the best of data lakes and data warehouses, on a simple, open and collaborative platform that securely integrates with your existing Azure services. In this demo, we cover several of the most common Azure Databricks integrations, including Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI and more.See full list of demosDive deeper into Azure DatabricksTo play this video, click here and accept cookiesVideo transcriptIntro to Lakehouse on Azure Databricks\nAzure Databricks is the jointly developed Data + AI service from Databricks and Microsoft for data engineering, data science, analytics and machine learning. The Azure Databricks Lakehouse Platform gives you the best of data lakes and data warehouses, on a simple, open and collaborative platform that securely integrates with your existing Azure services.\nBatch ETL pipelines with Azure Data Factory and Azure Databricks\nOrchestrating data pipelines for extract, transform and load (ETL) operations is easier than ever thanks to the integration between Azure Databricks and Azure Data Factory. In this demo, we\u2019ll be working with power output and maintenance system records from a fleet management system used to maintain wind turbines across the United States. We\u2019ve created an Azure Data Factory pipeline that uses COPY commands to incrementally ingest data from the fleet management system in SQL server to our landing zone in Azure Data Lake Storage Gen2. Data Factory then executes a Databricks notebook to process the data using Databricks Auto Loader, and saves it into Delta Lake tables.Collapse full transcriptExpand full transcriptCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-meier","text":"Scott Meier - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott MeierDirector, Data Analytics Service, Financial Services Center at U.S. Department of Veterans AffairsBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ben-coppersmith","text":"Ben Coppersmith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBen CoppersmithSr. Manager, Data Platform at Disney StreamingBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/star-schema","text":"What is Star Schema?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWStar SchemaAll>Star SchemaTry Databricks for freeGet StartedWhat is a star schema?A star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The star schema design is optimized for querying large data sets.Introduced by Ralph Kimball in the 1990s, star schemas are efficient at storing data, maintaining history, and updating data by reducing the duplication of repetitive business definitions, making it fast to aggregate and filter data in the data warehouse.\u00a0Fact tables and dimension tablesA star schema is used to denormalize business data into dimensions (like time and product) and facts (like transactions in amounts and quantities).A star schema has a single fact table in the center, containing business \"facts\" (like transaction amounts and quantities). The fact table connects to multiple other dimension tables along \"dimensions\" like time, or product. Star schemas enable users to slice and dice the data however they see fit, typically by joining two or more fact tables and dimension tables together.Denormalized dataStar schemas denormalize the data, which means adding redundant columns to some dimension tables to make querying and working with the data faster and easier. The purpose is to trade some redundancy (duplication of data) in the data model for increased query speed, by avoiding computationally expensive join operations.In this model, the fact table is normalized but the dimensions tables are not. That is, data from the fact table exists only on the fact table, but dimensional tables may hold redundant data.Benefits of star schemasFact\/dimensional models like star schemas are simple to understand and implement, and make it easy for end users to find the data they need. They can be applied to data marts and other data resources.Great for simple queries because of their reduced dependency on joins when accessing the data, as compared to normalized models like snowflake schemas.Adapt well to fit OLAP models.Improved query performance as compared to normalized data, because star schemas attempt to avoid computationally expensive joins.How does a star schema differ from 3NF (Third Normal Form)?3NF, or Third Normal Form, is a method of reducing data-redundancy through normalization. It is a common standard for databases that are considered fully normalized. It typically has more tables than a star schema due to data normalization. On the flip-side, queries tend to be more complex due to the increased number of joins between large tables.ResourcesDatabricks Blog: Five Simple Steps for Implementing a Star Schema in Databricks with Delta LakeDatabricks SQL product pageDatabricks glossary - Snowflake schema\u00a0Back to GlossaryLearn what\u2019s driving the Lakehouse pattern.REGISTER NOWProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/mapreduce","text":"What is MapReduce?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMapReduceAll>MapReduceTry Databricks for freeGet StartedWhat is MapReduce?MapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.\u00a0 It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and 2) Reduce.\u00a0In the Mapping step, data is split between parallel processing tasks.\u00a0Transformation logic can be applied to each chunk of data.\u00a0Once completed, the Reduce phase takes over to handle aggregating data from the Map set.. In general, MapReduce uses Hadoop Distributed File System (HDFS) for both input and output.\u00a0However, some technologies built on top of it, such as Sqoop, allow access to relational systems.History of MapReduceMapReduce was developed in the walls of Google back in 2004 by Jeffery Dean and Sanjay Ghemawat of Google (Dean & Ghemawat, 2004). In their paper, \u201cMAPREDUCE: SIMPLIFIED DATA PROCESSING ON LARGE CLUSTERS,\u201d and was inspired by the map and reduce functions commonly used in functional programming. At that time, Google\u2019s proprietary MapReduce system ran on the Google File System (GFS). By 2014, Google was no longer using MapReduce as their primary big data processing model. MapReduce was once the only method through which the data stored in the HDFS could be retrieved, but that is no longer the case. Today, there are other query-based systems such as Hive and Pig that are used to retrieve data from the HDFS using SQL-like statements that run along with jobs written using the MapReduce model.How does MapReduce work?A MapReduce system is usually composed of three steps (even though it's generalized as the combination of Map and Reduce operations\/functions). The MapReduce operations are:Map: The input data is first split into smaller blocks. The Hadoop framework then decides how many mappers to use, based on the size of the data to be processed and the memory block available on each mapper server. Each block is then assigned to a mapper for processing. Each \u2018worker\u2019 node applies the map function to the local data, and writes the output to temporary storage. The primary (master) node ensures that only a single copy of the redundant input data is processed.Shuffle, combine and partition: worker nodes redistribute data based on the output keys (produced by the map function), such that all data belonging to one key is located on the same worker node. As an optional process the combiner (a reducer) can run individually on each mapper server to reduce the data on each mapper even further making reducing the data footprint and shuffling and sorting easier.\u00a0Partition (not optional) is the process that\u00a0decides how the data has to be presented to the reducer and also assigns it to a particular reducer.Reduce: A reducer cannot start while a mapper is still in progress. Worker nodes process each group of <key,value> pairs output data, in parallel to produce <key,value> pairs as output. All the map output values that have the same key are assigned to a single reducer, which then aggregates the values for that key. Unlike the map function which is mandatory to filter and sort the initial data, the reduce function is optional.What are some considerations with MapReduce?Rigid Map Reduce programming paradigmWhile exposing Map and Reduce interfaces to programmers has simplified the creation of distributed applications in Hadoop,\u00a0 it is difficult to express a broad range of logic in a Map Reduce programming paradigm. Iterative process is an example of logic that does not work well in Map Reduce.\u00a0In general, data is not kept in memory, and iterative logic is handled by chaining MapReduce applications together resulting in increased complexity.Read\/Write IntensiveMapReduce jobs store little data in memory as it has no concept of a distributed memory structure for user data. Data must be read and written to HDFS. More complex MapReduce applications involve chaining smaller MapReduce jobs together. Since data cannot be passed between these jobs, it will require data sharing via HDFS. This introduces a processing bottleneck.Java FocusedMapReduce is Java-based, and hence the most efficient way to write applications for it will be using java. Its code must be compiled in a separate development environment, then deployed into the Hadoop cluster. This style of development is not widely adopted by Data Analysts nor Data Scientists who are used to other technologies like SQL or interpreted languages like Python. MapReduce does have the capability to invoke Map\/Reduce logic written in other languages like C, Python, or Shell Scripting. However, it does so by spinning up a system process to handle the execution of these programs. This operation introduces overhead which will affect the performance of the job.Phased out from Big Data offeringsMapReduce is slowly being phased out of Big Data offerings. While some vendors still include it in their Hadoop distribution, it is done so to support legacy applications. Customers have moved away from creating MapReduce applications, instead adopting simpler and faster frameworks like Apache Spark.What is MapReduce used for?Legacy applications and Hadoop native tools like Sqoop and Pig leverage MapReduce today. There is very limited MapReduce application development nor any significant contributions being made to it as an open source technology.Common misconceptions about MapReduce and SparkAbout MapReduceAbout SparkAdvantages of MapReduceScalabilityFlexibilitySecurity and authenticationFaster processing of dataVery simple programming modelAvailability and resilient natureSimple tips on how to improve MapReduce performanceEnabling uber modeUse native libraryIncrease the block sizeMonitor time taken by map tasksIdentify if data compression is splittable or notSet number of reduced tasksAnalyze the partition of dataShuffle phase performance movementsOptimize MapReduce codeMapReduce vs. Databricks Delta EngineThe Databricks Delta Engine is based on Apache Spark and a C++ engine called Photon. This allows the flexibility of DAG processing that MapReduce lacks, the speed from in-memory processing and a specialized, natively compiled engine that provides blazingly fast query response times. Users can interact with the Databricks Delta Engine using Python, Scala, R, or SQL. Existing Spark applications can be modified to use the Delta Engine with a simple line change i.e. specifying \u201cdelta\u201d as the data format. MapReduce and HDFS, does not natively support transactional consistency of data, nor the ability to update\/delete existing data within datasets.\u00a0The Delta Engine allows concurrent access to data by data producers and consumers, also providing full CRUD capabilities. Finally, MapReduce does not possess built-in capabilities to address small files, a common problem in any big data environment. Databricks Delta Engine has auto-compaction that will optimize the size of data written to storage. It also has an OPTIMIZE command that can compact files on demand. With Delta\u2019s transactional consistency feature, this operation can be issued while data is being accessed by end users or applications.Five best alternatives to MapReduceApache SparkApache StormCephHydraGoogle BigQueryAdditional ResourcesHadoop to Lakehouse migration guideMigration hubCloud Modernization Ebook: A business guide into the hidden value of migration from HadoopOn-demand quick demo's of the Databricks Lakehouse PlatformBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thomas-roach","text":"Thomas Roach - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThomas RoachSr. Solutions Architect at DatabricksBack to speakersI am a Sr Solutions Architect at Databricks where I help our customers leverage our technology to solve strategic problems and maximize the value of their data assets. I have been working with Data for over two decades. The first 15 working with RDBMS technologies and the last eight working with Big Data technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/media-mix-modeling","text":"Media Mix Modeling | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorMedia Mix Modeling (MMM)Pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nOptimize marketing campaigns across multiple channelsDetermining the most effective combination of advertising and marketing channels to reach a target audience and achieve business goals is critical in today\u2019s dynamic media landscape. Using the Databricks Lakehouse for Media & Entertainment, organizations can:Unify data from various channels such as TV, social media, email marketing and moreIdentify and measure marketing channel effectiveness in driving engagement and revenueSimulate marketing channel scenarios to improve campaign performance through fine-tuning marketing inputOptimize media spend allocation around specific scenarios by analyzing historical dataRead eBookResourcesSolution AcceleratorRead nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/build-your-own-large-language-model-dolly?itm_data=datalakehouse-relatedcontent-dollywebinar","text":"Build Your Own Large Language Model Like Dolly | DatabricksOn DemandBuild Your Own Large Language Model Like DollyHow to fine-tune and deploy your custom LLMAvailable on demandCurious how your company can benefit from large language models (LLM) like ChatGPT? Imagine if you could train your own model \u2014 customized to your specific data to meet your specific needs.Now you can build your own LLM. And Dolly \u2014 our new research model \u2014 is proof that you can train yours to deliver high-quality results quickly and economically.Some of the most innovative companies are already training and fine-tuning LLM on their own data. And these models are already driving new and exciting customer experiences.Watch this webinar to discover how you can harness LLM for yourself. We\u2019ll walk you through examples on how to get started.You\u2019ll learn:How to use off-the-shelf pretrained models with tools like Hugging Face and GPU resourcesHow to fine-tune a model on your dataHow Dolly was builtSpeakerSean OwenPrincipal Product SpecialistDatabricksJoin usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/convolutional-layer","text":"What is a Convolutional Layer?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWConvolutional LayerAll>Convolutional LayerTry Databricks for freeGet StartedIn deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language processing, signal processing, and various other purposes The architecture of a Convolutional Network resembles the connectivity pattern of neurons in the Human Brain and was inspired by the organization of the Visual Cortex. This specific type of Artificial Neural Network gets its name from one of the most important operations in the network: convolution.What Is a Convolution?Convolution is an orderly procedure where two sources of information are intertwined; it\u2019s an operation that changes a function into something else. Convolutions have been used for a long time typically in image processing to blur and sharpen images, but also to perform other operations. (e.g. enhance edges and emboss) CNNs enforce a local connectivity pattern between neurons of adjacent layers.  CNNs make use of filters (also known as kernels), to detect what features, such as edges, are present throughout an image. There are four main operations in a CNN: \u00a0ConvolutionNon Linearity (ReLU)Pooling or Sub SamplingClassification (Fully Connected Layer)The first layer of a Convolutional Neural Network is always a Convolutional Layer. Convolutional layers apply a convolution operation to the input, passing the result to the next layer. A convolution converts all the pixels in its receptive field into a single value. For example, if you would apply a convolution to an image, you will be decreasing the image size as well as bringing all the information in the field together into a single pixel. The final output of the convolutional layer is a vector. Based on the type of problem we need to solve and on the kind of features we are looking to learn, we can use different kinds of convolutions.The 2D Convolution LayerThe most common type of convolution that is used is the 2D convolution layer and is usually abbreviated as conv2D. A filter or a kernel in a conv2D layer \u201cslides\u201d over the 2D input data, performing an elementwise multiplication. As a result, it will be summing up the results into a single output pixel. The kernel will perform the same operation for every location it slides over, transforming a 2D matrix of features into a different 2D matrix of features.The Dilated or Atrous ConvolutionThis operation expands window size without increasing the number of weights by inserting zero-values into convolution kernels. Dilated or Atrous Convolutions can be used in real time applications and in applications where the processing power is less as the RAM requirements are less intensive.Separable ConvolutionsThere are two main types of separable convolutions: spatial separable convolutions, and depthwise separable convolutions. The spatial separable convolution deals primarily with the spatial dimensions of an image and kernel: the width and the height. Compared to spatial separable convolutions, depthwise separable convolutions work with kernels that cannot be \u201cfactored\u201d into two smaller kernels. As a result, it is more frequently used.Transposed ConvolutionsThese types of comvolutions are also known as deconvolutions or fractionally strided convolutions. A transposed convolutional layer carries out a regular convolution but reverts its spatial transformation. \u00a0Additional ResourcesApplying your Convolutional Neural Network WebinarA Convolutional Neural Network Implementation For Car ClassificationBenchmark Tests and How-tos of Convolutional Neural Network on HorovodRunner Enabled Apache Spark ClustersBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dan-smith\/#","text":"Dan Smith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDan SmithHead of Technology Data & Analytics at Perenti GroupBack to speakersDan Smith is currently the Head of Technology Data & Analytics at Perenti Group, a global leading mining services company. He leads the data team providing information to 9000+ people in the business. Dan lead Perenti's digital transformation change of an on-prem migration to a Cloud based Lakehouse architecture, and expanding on all the capabilities that it brings. He previously had roles with Systems Integrators, Consultancies and Product development companies. Recently Dan has worked closely with key cloud providers to implement fit for purpose, future proofed data architectures for Perenti. His goal is to uncover insights and drive business value in the short term, while setting up success and flexibility for future capabilities in the medium and long term.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/modernize-your-data-warehouse","text":"Modernize Your Data Warehouse | DatabricksOn-demand WebinarModernize Your Data WarehouseA migration journey to the Databricks Lakehouse PlatformAvailable on-demandModern business requires agile decision-making with real-time data analytics. Innovation hinges on predictive insights generated from machine learning and AI. ETL and data warehouse infrastructures are simply not able to keep up with the growing volume, variety and velocity of data, or the need of business to gain advanced insights across enterprise data silos of disparate data marts and data warehouses. Innovation remains a pipedream.Hundreds of companies have already moved their traditional ETL and data warehouse workloads to the Databricks Lakehouse Platform in the cloud. Join us to learn more about why the lakehouse is your next data warehouse \u2014 and to better understand the architecture, customers\u2019 modernization journeys, and how to plan and execute your data warehouse migration to Databricks.In this webinar, we will feature:Why the Lakehouse is your next Data WarehouseHow Databricks experts can help you plan a comprehensive EDW and ETL migration processHow to implement your migration and highlight some key migration partnersLive Q&As throughout the presentationSpeakersSoham BhattMigration Lead SADatabricksAmit KaraTechnical Marketing DirectorDatabricksWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=demos-try-azure-trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/jobs","text":"Databricks Jobs Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWorkflows & Streaming: Jobs PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorJobs Easily ingest and transform batch and streaming data on the Databricks Lakehouse PlatformSelect planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudLoading...Compare featuresJobs Light ComputeJobs ComputeJobs Compute PhotonManaged Apache SparkPhoton Engine Performance (Massively parallel processing)Job Scheduling With LibrariesJob Scheduling With NotebooksAutopilot ClustersDatabricks Runtime for MLManaged MLflowDelta Lake With Delta EngineBroad Support of Different VM Instance TypesSee the Pricing calculator for hourly DBU emission by instance typeSee the Pricing calculator for hourly DBU emission by instance typeDBU emission rate 2.9x vs. non-Photon. See the Pricing calculator.Governance and ManageabilitySee Platform Capabilities and Add-Ons for detailsEnterprise SecuritySee Platform Capabilities and Add-Ons for detailsPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements\nCalculate priceStart free trialContact usFAQThere are two cluster options for jobs \u2013 Jobs cluster and Jobs Light cluster. How do I decide which one to use?Jobs Light cluster is Databricks\u2019 equivalent of open source Apache Spark. It targets simple, non-critical workloads that don\u2019t need the performance, reliability or autoscaling benefits provided by Databricks\u2019 proprietary technologies. In comparison, the Jobs cluster provides you with all the aforementioned benefits to boost your team productivity and reduce your total cost of ownership.What is Photon?Photon is the next-generation engine on the Databricks Lakehouse Platform that provides massively parallel, extremely fast query performance at lower total cost.What are the differences between Jobs workloads and All-Purpose workloads?Jobs workloads are workloads running on Jobs clusters. Jobs clusters are clusters that are both started and terminated by the same job. Only one job can be run on a Jobs cluster for isolation purposes. All-Purpose workloads are workloads running on All-Purpose clusters. All-Purpose clusters are clusters that are not classified as Jobs clusters. They can be used for various purposes such as running commands within Databricks notebooks, connecting via JDBC\/ODBC for BI workloads, running MLflow experiments on Databricks. Multiple users can share an All-Purpose cluster for doing interactive analysis in a collaborative way.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/propensity-scoring","text":"Propensity Scoring | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorPropensity ScoringPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedDeliver personalized customer experiencesConsumers increasingly expect to be engaged in a personalized manner, but most retailers struggle to deliver. One of the first steps in the personalization journey is often the examination of sales data for insights into individual customer preferences. With this process, called propensity scoring, companies can estimate customers' potential receptiveness to an offer or to content related to a subset of products. Using these scores, marketers can determine which of the many messages at their disposal should be presented to a specific customer.Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that:Enable the persistence, discovery and sharing of features across various model training exercisesQuickly generate models by leveraging industry best practicesTrack and analyze the various model iterations generatedDownload notebookEstimate Propensity with Real-Time Clickstream DataIn ecommerce platforms, the path to a purchase is not always as straightforward as we might expect. A customer may click on a product, put it in their cart, and immediately make a purchase, but more typically, especially with more expensive or complex items, the customer will browse, compare, leave the site for a while, return to give the product more consideration, and do all this multiple times before completing the purchase. Quite often, customers will engage in this process and never complete the pruchase, instead, abandoning the cart altogether, having either made a purchase through another channel or becoming disinterested in the product.Get started with our Solution Accelerator for Real-Time Clickstream Propensity to better predict whether users will complete the purchase of a product with which they are interacting byEnabling the operationalization of real-time insightsLeveraging live event data generated by an ecommerce website to predict whether users will complete the purchase of a product with which they are interactingDownload notebookDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsResourcesBlogLearn moreSolution AcceleratorLearn moreWebinarWatch nowReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/legal\/privacynotice#dbadditionalinformation","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/automation-bias","text":"What is Automation Bias?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAutomation BiasAll>Automation BiasTry Databricks for freeGet StartedWhat is Automation Bias?Automation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, or aircraft cockpits are becoming more common. It is a human tendency to take the road of least cognitive effort while leaning towards \"automation bias\". The same concept can be translated to the fundamental way that AI and automation work, which is mainly based on learning from large sets of data. This type of computation assumes that things won\u2019t be radically different in the future. Another aspect that should be considered is the risk of using a flawed training data then the learning will be flawed.What is Machine Bias?Machine Bias relates to the ways in which algorithms exhibit the bias of the algorithm used or their input data. Today, artificial intelligence (AI) is helping us uncover new insight from data and enhance human decision-making one such example is the face recognition feature used to sign into our smartphones. Unintended bias can come from many causes (Wikipedia lists 184), but the three main drivers are:incomplete data samplesincorrect datasets.skewed learning that happens through interactions over time, also known as interaction bias We can prevent data bias by using a comprehensive and broad dataset, reflective of all possible edge use cases, the more comprehensive the dataset, the more accurate the AI predictions are going to be. Let\u2019s take a look at several points you should take into consideration when working on your AI. Choose the right learning model for the problem. There\u2019s probably no single model that you can follow in order to completely avoid bias, but there are parameters that can inform your team as it\u2019s building. You will have to identify the best model for a given situation as well as troubleshoot ideas before committing to them Choose a representative training data set. Making sure to use training data that is diverse and includes different groups. Monitor performance using real data. You should be simulating real-world applications as much as possible when building algorithms. \u00a0Additional ResourcesUnderstanding the limitations of AI: When Algorithms FailBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sean-knapp\/#","text":"Sean Knapp - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSean KnappFounder & CEO at Ascend.ioBack to speakersSean Knapp is the founder and CEO of Ascend.io. Prior to Ascend.io, Sean was a co-founder, CTO, and Chief Product Officer at Ooyala.\nAt Ooyala Sean oversaw Product, Engineering and Solutions, and played key roles in scaling the company. Before founding Ooyala, Sean worked at Google where he was the tech lead for Google's Web Search Frontend Engineering team. \nSean holds a B.S. and M.S. in Computer Science from Stanford University where he competed as a member of the Track & Field team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jordan-peck","text":"Jordan Peck - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJordan PeckPrincipal Technical Account Manager at SnowplowBack to speakersJordan Peck is Principal Technical Account Manager at Snowplow in Leeds, UK. He helps Snowplow's strategic customers unlock the full potential of the platform, with expertise in data modelling, behavioral tracking design and activating new use cases with behavioural data. With these expertise, Jordan helps Snowplow's most complex and strategic customers create tailored solutions to meet their unique challenges and build valuable data applications using Snowplow's cutting-edge technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks MarketplaceMercato aperto per dati, analisi e AICominciaTo play this video, click here and accept cookiesChe cos'\u00e8 Databricks\nMarketplace?\nDatabricks Marketplace \u00e8 un mercato aperto per dati, analisi e AI, basato sullo standard open-source Delta Sharing. Databricks Marketplace offre alle aziende maggiori opportunit\u00e0 di fare innovazione e portare avanti i progetti di analisi e AI.\u00a0\nIl marketplace mette a disposizione set di dati e risorse per AI e analisi (come modelli di ML, notebook, applicazioni e dashboard), senza dipendere da piattaforme proprietarie, processi ETL complicati o repliche costose. Questo approccio aperto consente di \"mettere a frutto\" i dati pi\u00f9 velocemente in qualsiasi cloud con gli strumenti preferiti.Scopri molto pi\u00f9 dei datiSblocca l'innovazione e fai progredire le attivit\u00e0 di AI, ML e analisi della tua organizzazione. Accedi ad altre risorse oltre ai set di dati, come modelli di ML, notebook, applicazioni e soluzioni.Valuta i prodotti di dati pi\u00f9 velocementeNotebook preconfigurati e dati campione aiutano a valutare i prodotti di dati pi\u00f9 velocemente e ad avere la certezza che un prodotto sia adatto alle attivit\u00e0 di AI, ML e analisi dell'azienda.Evita di essere vincolato a un unico fornitoreRiduci drasticamente i tempi necessari per fornire informazioni approfondite e dettagliate ed evita i vincoli grazie a una soluzione di condivisione e collaborazione aperta e trasparente, trasversale a molteplici cloud, regioni o piattaforme. Integra la soluzione direttamente con i tuoi strumenti preferiti ed esattamente dove lavori.Fornitori di dati su Databricks MarketplaceDiventa un fornitore di dati sul marketplace\nRisorseeventoIscriviti ora al Data + AI Summit 2023RegistratieBookUn nuovo approccio alla condivisione di datiLeggieBookGovernance di dati, analisi e intelligenza artificialeLeggiPresentazioniGovernance e condivisione dei dati sul lakehouse al Data + AI Summit 2022 BlogAnnuncio della presentazione pubblica in anteprima di Databricks MarketplacePresentazione di Databricks Marketplace al Data + AI Summit 2022DocumentazioneawsazureGCPProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/de\/learn","text":"Lernen | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLernenTauchen Sie ein in die Databricks-Ressourcen und entdecken Sie eine neue Welt \u2013 ganz einfach per Mausklick. Sie finden hier Schulungen und Zertifizierungen, anstehende Events, n\u00fctzliche Dokumentation und vieles mehr.Erste Schritte mit DatabricksGrundlagen erlernenDie Databricks Lakehouse Platform erleichtert die Erstellung und Ausf\u00fchrung von Datenpipelines, die Zusammenarbeit bei Data-Science- und Analytics-Projekten und die Erstellung und Bereitstellung von Machine-Learning-Modellen. Lesen Sie unsere Handb\u00fccher f\u00fcr den Einstieg.Neu bei Databricks? Beginnen Sie Ihren Weg mit Databricks, angeleitet von einem erfahrenen Customer Success Engineer.Eingliederung bei Databricks\nLakehouse Fundamentals Training\nWatch 4 short videos, take the quiz and get your badge\nto share on LinkedIn or your r\u00e9sum\u00e9\nGet startedData Science und Data EngineeringDatabricks-AdministratorenSQL-AnalysenMachine LearningWeiterbildungLassen Sie sich von der Databricks Akademie weiterbilden und zertifizieren. Sie erfahren direkt von den Experten, die seinerzeit das Apache Spark\u2122-Forschungsprojekt an der UC Berkeley ins Leben gerufen haben, wie man Datenanalysen meistert.Databricks AkademieZertifizierungBei den Zertifizierungspr\u00fcfungen wird getestet, wie gut Sie die Databricks Lakehouse Platform und die zugrundeliegenden Methoden kennen, die f\u00fcr die erfolgreiche Umsetzung von Projekten notwendig sind. Sie verhelfen Ihnen zu mehr Anerkennung in der Branche, zur Differenzierung gg\u00fc. Ihren Mitbewerbern, zu h\u00f6herer Produktivit\u00e4t und besseren Ergebnissen sowie zu einem greifbaren Ma\u00dfstab f\u00fcr Ihre Bildungsinvestitionen.Databricks-ZertifizierungAntworten auf Ihre Fragen erhaltenW\u00e4hlen Sie eine der folgenden M\u00f6glichkeiten, um Klarheit \u00fcber Fragen zu erhalten, die m\u00f6glicherweise zu Beginn auftauchen:Einem technischen Experten von Databricks live Fragen stellenOnline-CommunityErkunden Sie beliebte Themen in der Databricks-Community.Mit der Community vernetzenBeliebte ForenthemenDatabricksDelta LakeSparkSQLpysparkAzureAWSGCPBrauchen Sie praktische Hilfe?Wenn Sie einen Supportvertrag haben oder an einem interessiert sind, sehen Sie sich unten unsere Optionen an. Wenn Sie Informationen zur strategischen Unternehmensberatung (mit einem Customer Success Engineer oder einem Professional Services-Vertrag) haben, wenden Sie sich bitte an den Administrator Ihres Arbeitsbereichs, damit dieser Ihren Databricks-Kundenbetreuer anspricht.Sehen Sie sich unsere Support-Optionen anNotebook-GalerieDiese Galerie pr\u00e4sentiert einige der M\u00f6glichkeiten des Einsatzes von Notebooks. Der Schwerpunkt liegt hierbei auf Technologien und Anwendungsf\u00e4llen, die sich leicht in Ihre eigene Databricks-Umgebung oder die kostenlose Community Edition importieren lassen.Databricks Notebook-GalerieDokumentationDie Databricks-Website mit der technischen Dokumentation enth\u00e4lt Praxisanleitungen und Referenzinformationen f\u00fcr die Persona-basierten Umgebungen Databricks Data Science und Engineering, Databricks Machine Learning und Databricks SQL.AWS-DokumentationAzure-DokumentationGoogle-DokumentationDatabricks-Events und die CommunityData + AI SummitFreuen Sie sich auf Keynotes, Produktank\u00fcndigungen und \u00fcber 200\u00a0Fach-Sessions, an denen Experten aus Industrie, Forschung und Wissenschaft teilnehmen.Mehr InformationenGlobale VeranstaltungenSichern Sie sich Ihren Platz bei einer unserer globalen oder regionalen Konferenzen, bei Live-Produktdemos, Webinaren, von Partnern gesponserten Veranstaltungen oder Meetups.Mehr InformationenOnline-Meetups zu Daten + KIHalten Sie sich auf dem Laufenden dar\u00fcber, was in Databricks-Meetup-Gruppen weltweit passiert, und schlie\u00dfen Sie sich einer Gruppe in Ihrer N\u00e4he (oder \u2013 virtuell \u2013 in der Ferne) an.Mehr InformationenBakenHier lernen Sie Databricks Beacons kennen, eine Gruppe von Community-Mitgliedern, die alles geben, um der Daten- und KI-Community Auftrieb zu geben.Mehr InformationenUniversity AllianceTreten Sie der Databricks University Alliance bei, und erhalten Sie Zugang zu kostenlosen Ressourcen f\u00fcr Lehrende, die Databricks im Unterricht einsetzen m\u00f6chten.Mehr InformationenVidcast \u201eData Brew\u201cDaten + KI mit Experten erforschenBrooke Wenig und Denny LeeVideoreiheOnline-Tech-Talks und MeetupsBrooke Wenig und Denny LeeTech-Gespr\u00e4cheDen gesamten Machine-Learning-Lebenszyklus mit MLflow verwaltenJules DamjiTech-Gespr\u00e4cheErste Schritte mit Delta LakeDenny LeeTech-Gespr\u00e4cheEintauchen in Delta Lake (f\u00fcr Fortgeschrittene)Denny LeeDatabricks-Democenter (Produktdemos)Forschung zu Daten + KIMatei ZahariaMitbegr\u00fcnder und Chief TechnologistDatabricksReynold XinMitbegr\u00fcnder und Chief ArchitectDatabricksSue Ann HongSoftware EngineerDatabricksLesen Sie aktuelle Beitr\u00e4ge von Databricks-Gr\u00fcndern, -Mitarbeitern und -Forschern zu verteilten Systemen, KI und Datenanalyse \u2013 in Zusammenarbeit mit f\u00fchrenden Universit\u00e4ten wie der UC Berkeley und Stanford.Greifen Sie auf die Forschung zuProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/company\/newsroom\/press-releases\/databricks-launches-simplified-real-time-machine-learning-lakehouse","text":"Databricks Launches Simplified Real-Time Machine Learning for the Lakehouse - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Launches Simplified Real-Time Machine Learning for the LakehouseMarch 7, 2023Share this postDatabricks Model Serving offers fully managed, production ML capabilities built natively within the Databricks Lakehouse Platform\u00a0\nSAN FRANCISCO \u2013 March 7, 2023 \u2013 Databricks, the lakehouse company, today announced the launch of Databricks Model Serving to provide simplified production machine learning (ML) natively within the Databricks Lakehouse Platform. Model Serving removes the complexity of building and maintaining complicated infrastructure for intelligent applications. Now, organizations can leverage the Databricks Lakehouse Platform to integrate real-time machine learning systems across their business, from personalized recommendations to customer service chatbots, without the need to configure and manage the underlying infrastructure. Deep integration within the Lakehouse Platform offers data and model lineage, governance and monitoring throughout the ML lifecycle, from experimentation to training to production. Databricks Model Serving is now generally available on AWS and Azure.\u00a0\nWith the opportunities surrounding generative artificial intelligence (AI) taking center stage, businesses feel the urgency to prioritize AI investments across the board. Leveraging AI\/ML enables organizations to uncover insights from their data, make accurate, instant predictions that deliver business value, and drive new AI-led experiences for their customers. For example, AI can enable a bank to quickly identify and combat fraudulent charges on a customer\u2019s account or give a retailer the ability to instantly suggest complementary accessories based on a customer\u2019s clothing purchases. Most of these experiences are integrated in real-time applications. However, implementing these real-time ML systems has remained a challenge for many organizations because of the burden placed on ML experts to design and maintain infrastructure that can dynamically scale to meet demand.\u00a0\n\u201cDatabricks Model Serving accelerates data science teams\u2019 path to production by simplifying deployments, reducing overhead and delivering a fully integrated experience directly within the Databricks Lakehouse,\u201d said Patrick Wendell, Co-Founder and VP of Engineering at Databricks. \u201cThis offering will let customers deploy far more models, with lower time to production, while also lowering the total cost of ownership and the burden of managing complex infrastructure.\u201d\u00a0\nDatabricks Model Serving removes the complexity of building and operating these systems and offers native integrations across the lakehouse, including Databricks\u2019 Unity Catalog, Feature Store and MLflow. It delivers a highly available, low latency service for model serving, giving businesses the ability to easily integrate ML predictions into their production workloads. Fully managed by Databricks, Model Serving quickly scales up from zero and back down as demand changes, reducing operational costs and ensuring customers pay only for the compute they use.\u00a0\n\u201cAs a leading global appliance company, Electrolux is committed to delivering the best experiences for our consumers at scale \u2014 we sell approximately 60 million household products in around 120 markets every year. Moving to Databricks Model Serving has supported our ambitions and enabled us to move quickly: we reduced our inference latency by 10x, helping us deliver relevant, accurate predictions even faster,\u201d said Daniel Edsg\u00e4rd, Head of Data Science at Electrolux. \u201cBy doing model serving on the same platform where our data lives and where we train models, we have been able to accelerate deployments and reduce maintenance, ultimately helping us deliver for our customers and drive more enjoyable and sustainable living around the world.\u201d\nDatabricks\u2019 unified, data-centric approach to machine learning from the lakehouse enables businesses to embed AI at scale and allows models to be served by the data and ML training platform. Lakehouse provides a consistent view of data throughout the entire ML lifecycle, which accelerates deployments and reduces errors, without having to stitch together disparate services. With Databricks, organizations can manage the entire ML process \u2013 from data preparation and experimentation to model training, deployment and monitoring \u2013 all in one place. Databricks Model Serving integrates with Lakehouse Platform capabilities, including:\u00a0\u00a0\n\nFeature Store: Provides automated online lookups to prevent online\/offline skew. Define features once during model training, and Databricks will automatically retrieve and join the relevant features in the future.\nMLflow Integration: Natively connects to MLflow Model Registry, enabling fast and easy deployment of models. After providing the underlying model, Databricks will automatically prepare a production-ready container for model deployment.\u00a0\nUnified Data Governance: Manage and govern all data and ML assets with Unity Catalog, including those consumed and produced by model serving.\n\nDatabricks is committed to driving innovation with its Lakehouse Platform and delivering more capabilities that make powerful, real-time machine learning accessible to any organization. This includes new quality and diagnostic features coming soon for Databricks Model Serving which will automatically capture requests and responses in a Delta table to monitor and debug models and generate training data sets. Databricks is also enabling GPU-based inference support, which is available in preview.\u00a0\nTo learn more about how Databricks enables production ML at scale with the Lakehouse, read the Databricks blog or sign up to join the ML Virtual Event on March 14, 2023, to hear from Databricks product leaders and customers\nAbout Databricks\nDatabricks is the lakehouse company. More than 9,000 organizations worldwide \u2014 including Comcast, Cond\u00e9 Nast, and over 50% of the Fortune 500 \u2014 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark\u2122, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world\u2019s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\nContact: [email\u00a0protected]\u00a0\n\u00a0\nRecent Press ReleasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowView AllResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Databricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30 | DatabricksDatabricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30AWS, Microsoft Azure \ub610\ub294 Google Cloud \uc911 \uc6d0\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4\uc5d0\uc11c 14\uc77c \ub3d9\uc548 Databricks \ud50c\ub7ab\ud3fc \uc804\uccb4\ub97c \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud574 \ubcf4\uc138\uc694.\ub370\uc774\ud130 \uc218\uc9d1 \ub2e8\uc21c\ud654 \ubc0f ETL \uc790\ub3d9\ud654\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uc218\ubc31 \uac1c\uc758 \uc18c\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574 \ubcf4\uc138\uc694. \uac04\ub2e8\ud55c \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \uc5b8\uc5b4\ub85c \ud611\uc5c5\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uacf5\ub3d9 \uc800\uc791, \uc790\ub3d9 \ubc84\uc804 \uad00\ub9ac, Git \ud1b5\ud569, RBAC\ub97c \ud65c\uc6a9\ud558\uc5ec Python, R, Scala \ubc0f SQL\ub85c \ucf54\ub529\ud558\uc138\uc694.\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 12\ubc30 \ub354 \uc6b0\uc218\ud55c \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc804 \uc138\uacc4 7,000\uac1c \uace0\uac1d\uc0ac\uac00 BI\ubd80\ud130 AI\uc5d0 \uc774\ub974\ub294 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc704\ud574\uc11c Databricks \ub97c \uc120\ud0dd\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.Databricks \uacc4\uc815 \uc0dd\uc131\ud558\uae301\/2\uc774\ub984\uc131\ud68c\uc0ac \uc774\uba54\uc77c\ud68c\uc0ac\uc9c1\ud568\uc804\ud654\ubc88\ud638(\uc120\ud0dd\uc0ac\ud56d)\ubcf4\uae30 \uc911\uc5d0\uc11c \uc120\ud0dd\ud558\uc138\uc694\uad6d\uac00\uacc4\uc18d\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0(\uc5c5\ub370\uc774\ud2b8\ub428)\uc774\uc6a9\uc57d\uad00\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ellen-sulcs\/#","text":"Ellen Sulcs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEllen SulcsDirector, Data Products & Engineering at T-MobileBack to speakersEllen Sulcs started her career at T-Mobile in 2017 building algorithms to predict the network experience of mobile devices as they were activated on T-Mobile\u2019s network. The algorithms turned into a mobile app and API and led her down a path to Product Management. In 2018, she was given the opportunity to establish a Data Product Management practice at T-Mobile which slowly evolved into leading a full-scale software and data engineering organization.\nPrior to her career at T-Mobile, Ellen dropped out of her PhD program to pursue a career as a Data Scientist in the healthcare industry. In her free time, Ellen has a child, so she doesn\u2019t have free time. But she was once an avid rower, cook and hiking enthusiast.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/product\/pricing","text":"Pre\u00e7os do Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPromo\u00e7\u00e3o de pre\u00e7o do SQL por tempo estendido - Economize mais de 40% Aproveite nossa promo\u00e7\u00e3o de 15 meses para o SQL serverless e o novo SQL ProSaiba maisPre\u00e7os do DatabricksUma plataforma simples para unificar todos os seus dados, an\u00e1lises e cargas de trabalho de IA, em todas as suas nuvens preferidasInicie o teste gratuitoComo funcionam os pre\u00e7os da Databricks?Pague conforme o usoA Databricks oferece uma abordagem de pagamento conforme o uso, sem custos iniciais. Pague apenas pelos produtos que usar por segundo.Economize mais com descontos por uso comprometidoA Databricks permite reduzir seus custos por meio de descontos quando voc\u00ea se compromete com determinados n\u00edveis de uso. Quanto maior for seu compromisso de uso, maior ser\u00e1 o desconto em compara\u00e7\u00e3o com o pagamento conforme o uso. Voc\u00ea pode usar compromissos de forma flex\u00edvel em v\u00e1rias nuvens. Entre em contato conosco para obter detalhes.Explorar produtosFluxos de trabalho e streamingJobsStarting at $0.07 \/ DBUExecute pipelines de engenharia de dados para criar data lakes e gerenciar dados em escalaSaiba maisFluxos de trabalho e streaming Delta Live TablesStarting at $0.20 \/ DBUCrie facilmente pipelines de streaming ou ETL em batch de alta qualidade usando Python ou SQL com a edi\u00e7\u00e3o DLT que melhor se adapta \u00e0 sua carga de trabalhoSaiba maisData WarehousingDatabricks SQLStarting at $0.22 \/ DBUExecute queries SQL para relat\u00f3rios, an\u00e1lises e visualiza\u00e7\u00e3o de BI para obter insights oportunos de data lakes. Dispon\u00edvel no compute Classic e serverless (gerenciado).Saiba maisData Science e Machine LearningAll-PurposeStarting at $0.40 \/ DBUExecute cargas de trabalho interativas de data science e machine learning. Tamb\u00e9m \u00e9 adequado para engenharia de dados, BI e an\u00e1lisesSaiba maisData Science e Machine LearningInfer\u00eancia serverless em tempo realStarting at $0.07 \/ DBUFa\u00e7a previs\u00f5es em tempo real em seus aplicativos e sites.\nSaiba maisComplementos e plataforma do DatabricksComplementos e plataforma do DatabricksN\u00edveis da plataforma: recursos de v\u00e1rias plataformas que fornecem o n\u00edvel certo de gerenciamento, governan\u00e7a e seguran\u00e7a para executar tudo, desde cargas de trabalho b\u00e1sicas at\u00e9 cargas de trabalho cr\u00edticas para a empresa\nComplementos da plataforma: aprimoramentos de v\u00e1rios produtos \u00e0 plataforma Databricks que trazem maior capacidade de gerenciamento, governan\u00e7a e seguran\u00e7aSaiba maisExperimente o Databricks gratuitamenteComece gratuitamenteAgendar uma demonstra\u00e7\u00e3oPerguntas frequentesO que a avalia\u00e7\u00e3o gratuita inclui?A avalia\u00e7\u00e3o gratuita de 14 dias oferece:Um ambiente colaborativo para as equipes de dados criarem solu\u00e7\u00f5es juntasNotebooks interativos para usar o Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn e muito maisObserve que voc\u00ea ainda receber\u00e1 cobran\u00e7a do seu provedor de nuvens por recursos, como inst\u00e2ncias de compute, usados dentro de sua conta durante o per\u00edodo de avalia\u00e7\u00e3o gratuitaO que acontece ap\u00f3s a avalia\u00e7\u00e3o gratuita?Ao final do per\u00edodo, voc\u00ea \u00e9 automaticamente inscrito no plano em que esteve durante a avalia\u00e7\u00e3o gratuita. Voc\u00ea pode cancelar sua assinatura a qualquer momento.Os pre\u00e7os s\u00e3o baseados no volume de uso ou armazenamento?Os pre\u00e7os do Databricks s\u00e3o baseados no uso do compute. Os custos de armazenamento, rede e relacionados variam de acordo com os servi\u00e7os que voc\u00ea escolher e do seu provedor de servi\u00e7os em nuvem.O que \u00e9 DBU?Uma Unidade do Databricks (DBU) \u00e9 uma unidade normalizada de poder de processamento na Databricks Lakehouse Platform usada para fins de precifica\u00e7\u00e3o. O n\u00famero de DBUs que uma carga de trabalho consome \u00e9 determinado pela m\u00e9trica de processamento, que pode incluir os recursos de compute usados e a quantidade de dados processados. O pre\u00e7o \u00e9 o mesmo em todas as regi\u00f5es?Os pre\u00e7os do Databricks e do Cloud Infrastructure podem variar de acordo com a regi\u00e3o e o provedor de servi\u00e7os de nuvem. Para obter detalhes, consulte as p\u00e1ginas de pre\u00e7os do Databricks para produtos individuaisO Databricks \u00e9 t\u00e3o econ\u00f4mico quanto outros servi\u00e7os de nuvem ou solu\u00e7\u00f5es de c\u00f3digo aberto?Os pre\u00e7os dos produtos Databricks incluem fornecimento de um custo total de propriedade (TCO) atraente aos clientes por suas cargas de trabalho. Ao estimar suas economias com o Databricks,, \u00e9 importante considerar os principais aspectos das solu\u00e7\u00f5es alternativas, incluindo a taxa de conclus\u00e3o do job, a dura\u00e7\u00e3o e o esfor\u00e7o manual e os recursos necess\u00e1rios para dar suporte a um job. Para ajudar voc\u00ea a estimar com precis\u00e3o suas economias, recomendamos comparar os resultados lado a lado como parte de uma implanta\u00e7\u00e3o de prova de conceito. Por exemplo, veja a acelera\u00e7\u00e3o alcan\u00e7ada por este cliente e os resultados de seu benchmark. Entre em contato conosco para come\u00e7ar.O que \u00e9 o Databricks Community Edition?O Databricks Community Edition \u00e9 uma plataforma de funcionalidade limitada e gratuita desenvolvida para quem quer aprender Spark. Inscreva-se aqui.Como receberei a cobran\u00e7a?Por padr\u00e3o, voc\u00ea receber\u00e1 a cobran\u00e7a mensalmente com base no uso por segundo em seu cart\u00e3o de cr\u00e9dito. Entre em contato conosco para obter mais op\u00e7\u00f5es de faturamento, como fatura ou plano anual.Voc\u00eas fornecem suporte t\u00e9cnico?Oferecemos suporte t\u00e9cnico. Voc\u00ea tamb\u00e9m pode verificar a documenta\u00e7\u00e3o t\u00e9cnica. Entre em contato conosco para saber mais.ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/jp\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Databricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb | DatabricksDatabricks \u306e\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebDatabricks \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u5168\u6a5f\u80fd\u3092 14 \u65e5\u9593\u7121\u6599\u3067\u304a\u8a66\u3057\u3044\u305f\u3060\u3051\u307e\u3059\u3002AWS\u3001Microsoft Azure\u3001Google Cloud \u306e\u3044\u305a\u308c\u304b\u3092\u304a\u9078\u3073\u304f\u3060\u3055\u3044\u3002\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3001ETL \u3092\u81ea\u52d5\u5316\u6570\u767e\u306b\u304a\u3088\u3076\u30bd\u30fc\u30b9\u304b\u3089\u306e\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3068\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u306b\u3088\u308b\u30c7\u30fc\u30bf\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u69cb\u7bc9\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u4efb\u610f\u306e\u8a00\u8a9e\u3067\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032Python\u3001R\u3001Scala\u3001SQL \u306b\u3088\u308b\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u304c\u53ef\u80fd\u3067\u3059\u3002\u5171\u540c\u7de8\u96c6\u3001\u81ea\u52d5\u30d0\u30fc\u30b8\u30e7\u30f3\u7ba1\u7406\u3001Git \u7d71\u5408\u3001RBAC \u3082\u5229\u7528\u3067\u304d\u307e\u3059\u3002\u30af\u30e9\u30a6\u30c9\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e 12 \u500d\u306e\u4fa1\u683c\u6027\u80fdDatabricks \u306f\u3001\u4e16\u754c 7000 \u793e\u4ee5\u4e0a\u306e\u304a\u5ba2\u69d8\u306b\u63a1\u7528\u3055\u308c\u3001BI \u3084 AI \u306e\u3042\u3089\u3086\u308b\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002Databricks \u30a2\u30ab\u30a6\u30f3\u30c8\u3092\u4f5c\u6210\u3059\u308b1\/2\u304a\u540d\u524d\uff08\u59d3)\u304a\u540d\u524d\uff08\u540d)\u696d\u52d9\u7528\u30e1\u30fc\u30eb\u30a2\u30c9\u30ec\u30b9\u4f01\u696d\uff0f\u56e3\u4f53\u540d\u5f79\u8077\u540d\u96fb\u8a71\u756a\u53f7\uff08\u4efb\u610f)\u9078\u629e\u3057\u3066\u304f\u3060\u3055\u3044\u56fd\u540d\u9001\u4fe1\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5 (\u66f4\u65b0)\u5229\u7528\u898f\u7d04\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jitendra-malik\/#","text":"Jitendra Malik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI Research at University of California at BerkeleyBack to speakersJitendra Malik was born in Mathura, India in 1960. He received the B.Tech degree in Electrical Engineering from Indian Institute of Technology, Kanpur in 1980 and the PhD degree in Computer Science from Stanford University in 1985. In January 1986, he joined the university of California at Berkeley, where he is currently the Arthur J. Chick Professor in the Department of Electrical Engineering and Computer Sciences. He is also on the faculty of the department of Bioengineering, and the Cognitive Science and Vision Science groups. During 2002-2004 he served as the Chair of the Computer Science Division, and as the Department Chair of EECS during 2004-2006 as well as 2016-2017. In 2018 and 2019, he served as Research Director and Site Lead of Facebook AI Research in Menlo Park.\nProf. Malik's research group has worked on many different topics in computer vision, computational modeling of human vision, computer graphics and the analysis of biological images. Several well-known concepts and algorithms arose in this research, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. He has mentored more than 70 PhD students and postdoctoral fellows.\nHe received the gold medal for the best graduating student in Electrical Engineering from IIT Kanpur in 1980 and a Presidential Young Investigator Award in 1989. At UC Berkeley, he was selected for the Diane S. McEntyre Award for Excellence in Teaching in 2000 and a Miller Research Professorship in 2001. He received the Distinguished Alumnus Award from IIT Kanpur in 2008. His publications have received numerous best paper awards, including five test of time awards - the Longuet-Higgins Prize for papers published at CVPR (twice) and the Helmholtz Prize for papers published at ICCV (three times). He received the 2013 IEEE PAMI-TC Distinguished Researcher in Computer Vision Award, the 2014 K.S. Fu Prize from the International Association of Pattern Recognition, the 2016 ACM-AAAI Allen Newell Award, the 2018 IJCAI Award for Research Excellence in AI, and the 2019 IEEE Computer Society Computer Pioneer Award. He is a fellow of the IEEE and the ACM. He is a member of the National Academy of Engineering and the National Academy of Sciences, and a fellow of the American Academy of Arts and Sciences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/patrick-hall\/#","text":"Patrick Hall - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPatrick HallPrincipal Scientist | Visiting Faculty at BNH.AI | GWUBack to speakersPatrick is principal scientist at BNH.AI, where he advises clients on AI risk management and supports NIST's AI Risk Management Framework. He also serves as visiting faculty in the Department of Decision Sciences at The George Washington School of Business, teaching classes on data ethics and business analytics. Patrick's technical work has been profiled in Fortune, Wired, InfoWorld, and TechCrunch, and he is the lead author of the book Machine Learning for High Risk Applications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/angela-chu","text":"Angela Chu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAngela ChuSenior Solution Architect at DatabricksBack to speakersAngela Chu has turned data into information for more than 25 years, the last three have been spent as a Solutions Architect and Streaming Subject Matter Expert at Databricks. She enjoys learning about different technologies and solving complex problems with it, and then sharing her learnings with my customers and peers. When she is not having fun with technology, she is spending time with my family and traveling to different countries so her kids can experience the amazing cultures from around the world.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/qos","text":"How to build: A Quality of Service (QoS) analytics solution for streaming video services | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorBuild a QoS analytics solution for streaming video servicesIncrease viewer retention through data-driven engagement strategies\nAnalyze both streaming and batch data sets to ensure a performant streaming content experience that drives engagement and loyalty.\nRead the full write-up\nACCELERATORDatabricks streaming video QoS solutionDownload notebookBenefits and business valueOptimize user experiencesProcess massive volumes of data to improve streaming performance\nGrow viewershipExtract audience insights from session data to drive audience growthTarget new viewersIncrease audience engagement with personalized ads based on viewer behavior and Comscore ratingsReference ArchitecturePlayer\/client telemetry data (streaming): video starts, time to first frame, start failure, playback failure, rebuffering ratio, bit rate, session length CDN delivery logs (batch)ResourcesCase studyLearn moreBlogLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/holly-smith\/#","text":"Holly Smith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHolly SmithSenior Resident Solutions Architect at DatabricksBack to speakersHolly Smith is a renowned speaker and multi award winning Data & AI expert who has over a decade of experience working with Data & AI teams in a variety of capacities from individual contributors all the way up to leadership. She has spent the last four years at Databricks working with multi national companies as they embark on their journey to the cutting edge of data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected]om and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/data-science\/ide-integrations","text":"Databricks IDE Integrations | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks IDE IntegrationsBuild on the Lakehouse in your favorite IDETry Databricks for freeGet ExtensionIntroductionDatabricks is building a complete development experience for developers and teams who prefer IDEs, and have existing software engineering workflows. Our official IDE integrations bring all of the core capabilities of Databricks into your IDE, including securely connecting to workspaces, clusters and data. They are uniquely designed for IDE workflows, with support for your favorite editor features, full access to Git tools, local unit testing, and debugging of code running in your cluster.The full power of Databricks, in your IDEGet the capabilities of the Databricks Lakehouse in your IDE. You can build your data and AI apps with the performance of Databricks. Connect to your workspaces to collaborate with your team. Run on clusters to get access to scale for large data applications. And access all your data in the lakehouse from the comfort of your IDE.Use unique IDE capabilitiesThe Databricks integrations are built to take advantage of the capabilities of IDEs such as source control, unit testing and debugging. You can do all your familiar work in your IDE like refactoring, code navigation, code assistants and more while iterating rapidly with local unit testing.A fully supported IDE experienceDatabricks will continue to invest to improve and update these integrations. You get the full support of Databricks for these official integrations so you can ensure your investment is safe and secure. Set up quickly and get started with Databricks in your IDE.Get StartedWant to start developing in VS Code yourself? You can download the extension directly from the VS Code Marketplace.Follow our setup documentation [AWS, Azure, and GCP] for step-by-step instructions to fulfill workspace requirements, install the extension and configure your profile. We walk you through how to connect to your Databricks workspace and provide some test code to run a file on a cluster from your IDE. Then you are all set to start developing from VS Code.ResourcesBlogAnnouncing a Native Visual Studio Code Experience for DatabricksDocumentationAWSAzureGCPReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/data-engineering","text":"\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29REGISTER NOW\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u6570\u5343\u4e07\u306e\u672c\u756a\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u304c\u65e5\u3005 Databricks \u4e0a\u3067\u5b9f\u884c\u3055\u308c\u3066\u3044\u307e\u3059\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306f\u3001\u30d0\u30c3\u30c1\uff0f\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3001\u5909\u63db\u3092\u5bb9\u6613\u306b\u3057\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u30a4\u30f3\u30d5\u30e9\u306e\u7ba1\u7406\u3092\u81ea\u52d5\u5316\u3059\u308b\u3053\u3068\u3067\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u672c\u756a\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u307e\u305f\u3001Databricks \u306f\u3001\u30c7\u30fc\u30bf\u54c1\u8cea\u306e\u691c\u8a3c\u6a5f\u80fd\u3068\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u958b\u767a\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u304a\u308a\u3001\u30c1\u30fc\u30e0\u306e\u751f\u7523\u6027\u304c\u5411\u4e0a\u3057\u307e\u3059\u3002\u30d0\u30c3\u30c1\uff0f\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u306e\u4e21\u65b9\u306b\u5bfe\u5fdc\u7d71\u5408\u3055\u308c\u305f API \u3092\u5099\u3048\u305f\u5358\u4e00\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u30b5\u30a4\u30ed\u3092\u6392\u9664\u3057\u3001\u30d0\u30c3\u30c1\uff0f\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u306e\u5927\u898f\u6a21\u306a\u53d6\u308a\u8fbc\u307f\u3001\u5909\u63db\u3001\u5897\u5206\u51e6\u7406\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u904b\u7528\u8ca0\u8377\u306e\u8efd\u6e1bDatabricks \u306f\u3001\u30a4\u30f3\u30d5\u30e9\u3068\u672c\u756a\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u904b\u7528\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u3092\u81ea\u52d5\u7684\u306b\u5272\u308a\u5f53\u3066\u308b\u3053\u3068\u3067\u3001\u30c4\u30fc\u30eb\u306e\u904b\u7528\u7ba1\u7406\u306e\u624b\u9593\u3092\u306a\u304f\u3057\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u30c7\u30fc\u30bf\u306b\u96c6\u4e2d\u3067\u304d\u307e\u3059\u3002\u4efb\u610f\u306e\u30c4\u30fc\u30eb\u3092\u63a5\u7d9a\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u30aa\u30fc\u30d7\u30f3\u6027\u306b\u3088\u308a\u3001\u4efb\u610f\u306e\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u305f\u30c7\u30fc\u30bf\u306e\u53d6\u308a\u8fbc\u307f\u3001ETL\/ELT\u3001\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u304c\u53ef\u80fd\u3067\u3059\u3002\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u304c\u57fa\u76e4\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306f\u3001\u30c7\u30fc\u30bf\u8cc7\u7523\u306e\u69cb\u7bc9\u3068\u5171\u6709\u3001\u4e00\u5143\u7ba1\u7406\u3092\u53ef\u80fd\u306b\u3057\u3001\u9ad8\u901f\u3067\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30c7\u30fc\u30bf\u30bd\u30fc\u30b9\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u300c\u79c1\u305f\u3061\u306b\u3068\u3063\u3066 Databricks \u306f\u3001\u3042\u3089\u3086\u308b ETL \u696d\u52d9\u306e\u30ef\u30f3\u30b9\u30c8\u30c3\u30d7\u30b7\u30e7\u30c3\u30d7\u306b\u306a\u308a\u3064\u3064\u3042\u308a\u307e\u3059\u3002\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u6d3b\u7528\u3059\u308c\u3070\u3059\u308b\u307b\u3069\u3001\u30e6\u30fc\u30b6\u30fc\u3001\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u7ba1\u7406\u8005\u306e\u4e21\u65b9\u306e\u8ca0\u62c5\u3092\u524a\u6e1b\u3067\u304d\u307e\u3059\u3002\u300dYipitData \u793e \u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30de\u30cd\u30fc\u30b8\u30e3\u30fc Hillevi Crognale \u6c0f\u4ed5\u7d44\u307f\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u306e\u7c21\u7d20\u5316ETL \u51e6\u7406\u306e\u81ea\u52d5\u5316\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u30a8\u30f3\u30c9\u30c4\u30fc\u30a8\u30f3\u30c9\u306e\u89b3\u5bdf\u30fb\u76e3\u8996\u6b21\u4e16\u4ee3\u306e\u30c7\u30fc\u30bf\u51e6\u7406\u30a8\u30f3\u30b8\u30f3\u30ac\u30d0\u30ca\u30f3\u30b9\u3001\u4fe1\u983c\u6027\u3001\u6027\u80fd\u3092\u652f\u3048\u308b\u57fa\u76e4\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u306e\u7c21\u7d20\u5316\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u30c7\u30fc\u30bf\u3092\u53d6\u308a\u8fbc\u307f\u3001\u5206\u6790\u3001AI\u3001\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u3092\u4e00\u5143\u7ba1\u7406\u3067\u304d\u307e\u3059\u3002\u30aa\u30fc\u30c8\u30ed\u30fc\u30c0\u306f\u3001\u30b9\u30b1\u30b8\u30e5\u30fc\u30eb\u3055\u308c\u305f\u30b8\u30e7\u30d6\u3084\u9023\u7d9a\u3057\u305f\u30b8\u30e7\u30d6\u306b\u304a\u3044\u3066\u3001\u30af\u30e9\u30a6\u30c9\u30b9\u30c8\u30ec\u30fc\u30b8\u306b\u30ed\u30fc\u30c9\u3055\u308c\u305f\u30d5\u30a1\u30a4\u30eb\u306b\u5bfe\u3057\u3066\u5897\u5206\u51e6\u7406\u3092\u81ea\u52d5\u3067\u884c\u3044\u307e\u3059\u3002\u30c7\u30fc\u30bf\u306e\u72b6\u614b\u306b\u3064\u3044\u3066\u306e\u8a73\u7d30\u3092\u624b\u52d5\u3067\u7ba1\u7406\u3059\u308b\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u6570\u5341\u5104\u898f\u6a21\u306e\u65b0\u3057\u3044\u30d5\u30a1\u30a4\u30eb\u3067\u3082\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u30ea\u30b9\u30c8\u3059\u308b\u3053\u3068\u306a\u304f\u52b9\u7387\u7684\u306b\u8ffd\u8de1\u3057\u3001\u30bd\u30fc\u30b9\u30c7\u30fc\u30bf\u304b\u3089\u30b9\u30ad\u30fc\u30de\u3092\u81ea\u52d5\u7684\u306b\u63a8\u6e2c\u3057\u3001\u6642\u9593\u306e\u7d4c\u904e\u3068\u3068\u3082\u306b\u30b9\u30ad\u30fc\u30de\u3092\u9032\u5316\u3055\u305b\u308b\u3053\u3068\u3082\u53ef\u80fd\u3067\u3059\u3002\u30a2\u30ca\u30ea\u30b9\u30c8\u306f COPY INTO \u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001SQL \u3092\u4ecb\u3057\u3066 Delta Lake \u3078\u306e\u30d0\u30c3\u30c1\u30d5\u30a1\u30a4\u30eb\u306e\u53d6\u308a\u8fbc\u307f\u3092\u5bb9\u6613\u306b\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002\u300c\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u751f\u7523\u6027\u304c 40% \u5411\u4e0a\u3057\u307e\u3057\u305f\u3002\u65b0\u3057\u3044\u0000\u0000\u30a2\u30a4\u30c7\u30a2\u306e\u958b\u767a\u306b\u304b\u304b\u308b\u6642\u9593\u3092\u6570\u65e5\u304b\u3089\u6570\u5206\u306b\u77ed\u7e2e\u3057\u3001\u30c7\u30fc\u30bf\u306e\u53ef\u7528\u6027\u3068\u7cbe\u5ea6\u304c\u9ad8\u307e\u3063\u3066\u3044\u307e\u3059\u3002\u300dGousto \u793e\u00a0\u6700\u9ad8\u6280\u8853\u8cac\u4efb\u8005 Shaun Pearce \u6c0f\u8a73\u3057\u304f\u898b\u308bETL \u51e6\u7406\u306e\u81ea\u52d5\u5316\u53d6\u308a\u8fbc\u3093\u3060\u672a\u52a0\u5de5\u30c7\u30fc\u30bf\u306f\u3001\u5206\u6790\u3084 AI \u306b\u5229\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002Databricks \u306f\u3001Delta Live Tables\uff08DLT\uff09\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30c6\u30a3\u30b9\u30c8\u3001\u30a2\u30ca\u30ea\u30b9\u30c8\u306b\u5f37\u529b\u306a ETL \u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002DLT \u306f\u3001\u30d0\u30c3\u30c1\u30c7\u30fc\u30bf\u3084\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u306b ETL \u304a\u3088\u3073 ML \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u69cb\u7bc9\u3059\u308b\u3001\u30b7\u30f3\u30d7\u30eb\u306a\u5ba3\u8a00\u578b\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u4f7f\u7528\u3057\u305f\u521d\u306e ETL \u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u3059\u3002\u30a4\u30f3\u30d5\u30e9\u7ba1\u7406\u3001\u30bf\u30b9\u30af\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u3001\u30a8\u30e9\u30fc\u51e6\u7406\u3084\u30ea\u30ab\u30d0\u30ea\u3001\u6027\u80fd\u306e\u6700\u9069\u5316\u3068\u3044\u3063\u305f\u8907\u96d1\u306a\u904b\u7528\u30bf\u30b9\u30af\u3092\u81ea\u52d5\u5316\u3057\u307e\u3059\u3002\u30a8\u30f3\u30b8\u30cb\u30a2\u306f DLT \u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u3092\u30b3\u30fc\u30c9\u3068\u3057\u3066\u6271\u3046\u3053\u3068\u304c\u3067\u304d\u3001\u30c6\u30b9\u30c8\u3001\u76e3\u8996\u3001\u6587\u66f8\u5316\u306a\u3069\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u9069\u7528\u3057\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u5927\u898f\u6a21\u306b\u5c55\u958b\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u306e\u30aa\u30fc\u30b1\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3Databricks Workflows \u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u30cd\u30a4\u30c6\u30a3\u30d6\u3067\u3001\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI 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\u3092\u6d3b\u7528\u3057\u305f\u30c7\u30fc\u30bf\u5909\u63db\u30c7\u30fc\u30bf\u53d6\u308a\u8fbc\u307f\u3092\u7c21\u5358\u306b\u3059\u308b\u65b9\u6cd5DATA + AI SUMMIT 2022\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3092\u30e2\u30c0\u30ca\u30a4\u30ba\u30d6\u30ed\u30b0Delta Live Tables \u306e\u4e00\u822c\u63d0\u4f9b\u958b\u59cb\u3092\u767a\u8868Databricks Workflows \u306e\u3054\u7d39\u4ecbDatabricks \u3068 Apache Spark \u5411\u3051 2021 \u5e74\u306b\u958b\u767a\u3055\u308c\u305f\u69cb\u9020\u5316\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u65b0\u6a5f\u80fd\u306e\u6982\u8981Databricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u304a\u3051\u308b\u534a\u69cb\u9020\u5316\u30c7\u30fc\u30bf\u306e\u7ba1\u7406\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3059\u308b 10 \u306e\u5f37\u529b\u306a\u6a5f\u80fd\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u306b\u53c2\u52a0\u3059\u308bAWSAzureGCP\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jim-thorstad\/#","text":"Jim Thorstad - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJim ThorstadSolutions Architect at DatabricksBack to speakersTBDLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Prova Databricks gratis | DatabricksProva Databricks gratisProva la piattaforma Databricks completa per 14 giorni su AWS, Microsoft Azure o Google Cloud.Semplifica l\u2019acquisizione dei dati e automatizza i processi ETLAcquisisci i dati da centinaia di sorgenti. Usa un semplice approccio dichiarativo per costruire le pipeline di dati.Collabora nella lingua che preferisciScrivi codice in Python, R, Scala e SQL con co-creazione, gestione automatica delle versioni, integrazioni Git e controllo degli accessi per ruoli (RBAC).Rapporto prezzo\/prestazioni 12 volte migliore rispetto ai data warehouse in cloudScopri perch\u00e9 oltre 7.000 clienti in tutto il mondo si affidano a Databricks per tutti i loro carichi di lavoro, dalla BI all\u2019AI.Crea il tuo account Databricks1\/2NomeCognomeE-mail aziendaleAziendaTitolo professionaleTelefono (Optional)Si prega di selezionareNazioneContinuaInformativa sulla privacy (aggiornata)Condizioni d'usoLe vostre scelte sulla privacyI vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/br\/product\/data-streaming","text":"Streaming de dados | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWStreaming de dadosSimplifique an\u00e1lises em tempo real, ML e aplica\u00e7\u00f5esComece agoraAssista \u00e0 demonstra\u00e7\u00e3oA\u00a0Plataforma Databricks Lakehouse\u00a0simplifica drasticamente o streaming de dados para fornecer an\u00e1lises em tempo real, machine learning e aplica\u00e7\u00f5es em uma \u00fanica plataforma.Permita que suas equipes de dados criem cargas de trabalho de streaming com as linguagens e ferramentas que j\u00e1 conhecem. Simplifique o desenvolvimento e as opera\u00e7\u00f5es, automatizando os aspectos de produ\u00e7\u00e3o associados \u00e0 cria\u00e7\u00e3o e manuten\u00e7\u00e3o de cargas de trabalho de dados em tempo real. Elimine silos unificando streaming e dados em batch em uma \u00fanica plataforma.Crie pipelines e aplica\u00e7\u00f5es de streaming mais rapidamenteUse as linguagens e ferramentas que voc\u00ea j\u00e1 conhece com APIs unificadas para batch e streaming em SQL e Python. Coloque\u00a0an\u00e1lises,\u00a0ML\u00a0e\u00a0aplica\u00e7\u00f5es\u00a0em tempo real para trabalhar em toda a sua organiza\u00e7\u00e3o.Simplifique as opera\u00e7\u00f5es com automa\u00e7\u00e3o de ferramentasImplante facilmente seus\u00a0pipelines em tempo real\u00a0e aplica\u00e7\u00f5es para produ\u00e7\u00e3o e beneficie-se do gerenciamento simplificado. Ferramentas automatizadas simplificam a orquestra\u00e7\u00e3o de tarefas, toler\u00e2ncia e recupera\u00e7\u00e3o de falhas, verifica\u00e7\u00e3o autom\u00e1tica, otimiza\u00e7\u00e3o de desempenho e redimensionamento autom\u00e1tico.Unifique a governan\u00e7a de todos os seus dados em tempo real em suas diferentes nuvensO Unity Catalog\u00a0oferece ao seu lakehouse um modelo de governan\u00e7a unificado para todos os seus dados em batch e streaming, facilitando a descoberta, visualiza\u00e7\u00e3o e\u00a0compartilhamento\u00a0de dados em tempo real.Como funciona?Ingest\u00e3o e transforma\u00e7\u00e3o de dados de streamingAn\u00e1lises em tempo real, ML e aplica\u00e7\u00f5esFerramentas operacionais automatizadasMecanismo de processamento de stream de \u00faltima gera\u00e7\u00e3oGovernan\u00e7a e armazenamento unificadosIngest\u00e3o e transforma\u00e7\u00e3o de dados de streamingSimplifique a ingest\u00e3o de dados e o ETL para pipelines de dados de streaming com as\u00a0Delta Live Tables. Aproveite uma abordagem declarativa simples para a\u00a0engenharia de dados\u00a0para permitir que suas equipes usem as linguagens e ferramentas que j\u00e1 conhecem, como SQL e Python. Crie e execute pipelines de dados em batch e streaming em um s\u00f3 lugar com configura\u00e7\u00f5es de atualiza\u00e7\u00e3o control\u00e1veis e automatizadas, economizando tempo e reduzindo a complexidade operacional. N\u00e3o importa onde voc\u00ea planeja enviar seus dados, construir pipelines de dados de streaming na Plataforma Databricks Lakehouse garante que voc\u00ea n\u00e3o perca tempo entre dados brutos e limpos.\u201cCada vez mais unidades de neg\u00f3cios est\u00e3o usando a plataforma de maneira self-service, o que antes era imposs\u00edvel. Estou extremamente impressionada com o impacto positivo que a Databricks teve na Columbia.\u201d\u2014 Lara Minor, gerente s\u00eanior de dados empresariais, Columbia SportswearSaiba maisAn\u00e1lises em tempo real, ML e aplica\u00e7\u00f5esCom o streaming de dados, melhore imediatamente a precis\u00e3o e capacidade de a\u00e7\u00e3o a partir de suas an\u00e1lises e IA para aproveitar todo o seu potencial. Sua empresa se beneficiar\u00e1 de insights em tempo real, derivados diretamente de pipelines de dados de streaming. Seja realizando\u00a0An\u00e1lises SQL\u00a0ou\u00a0Relat\u00f3rios de BI,\u00a0treinando modelos de ML\u00a0ou criando aplica\u00e7\u00f5es operacionais em tempo real, aproveite os dados mais recentes para obter vantagens para ficar \u00e0 frente da concorr\u00eancia: insights em tempo real, previs\u00f5es mais precisas e tomadas de decis\u00e3o mais r\u00e1pidas.\u201cDevemos sempre fornecer os dados mais recentes e precisos aos nossos parceiros de neg\u00f3cios ou eles perder\u00e3o confian\u00e7a nos insights... A Plataforma Databricks Lakehouse tornou extremamente f\u00e1cil o que antes era imposs\u00edvel.\u201d\u2014 Guillermo Rold\u00e1n, diretor de arquitetura, LaLiga TechSaiba maisFerramentas operacionais automatizadasQuando voc\u00ea cria e implanta pipelines de dados de streaming, a Databricks automatiza muitas das tarefas operacionais complexas necess\u00e1rias para passar para a produ\u00e7\u00e3o. A plataforma lida com processos como redimensionamento autom\u00e1tico da infraestrutura, orquestra\u00e7\u00e3o de depend\u00eancias de pipeline, tratamento e recupera\u00e7\u00e3o de erros, otimiza\u00e7\u00e3o de desempenho e muito mais.\u00a0O redimensionamento autom\u00e1tico aprimorado\u00a0otimiza a utiliza\u00e7\u00e3o do cluster alocando automaticamente recursos de computa\u00e7\u00e3o para cada carga de trabalho. Esses recursos, complementados por testes autom\u00e1ticos de qualidade de dados e tratamento de exce\u00e7\u00f5es, reduzem o tempo necess\u00e1rio para criar e manter ferramentas operacionais para que voc\u00ea possa se concentrar em obter valor dos seus dados.Saiba maisMecanismo de processamento de stream de \u00faltima gera\u00e7\u00e3oO Spark Structured Streaming\u00a0\u00e9 a tecnologia fundamental por tr\u00e1s do streaming de dados na Databricks Lakehouse Platform. Ele fornece uma API unificada para processamento em batch e streaming. A Databricks Lakehouse Platform \u00e9 a\u00a0melhor maneira de executar suas cargas de trabalho do Apache Spark\u00a0em um servi\u00e7o gerenciado com uma disponibilidade comprovada de 99,95%. Suas cargas de trabalho do Spark s\u00e3o ainda mais aceleradas pelo\u00a0Photon, o mecanismo lakehouse de \u00faltima gera\u00e7\u00e3o compat\u00edvel com as APIs do Apache Spark. Ele oferece desempenho\u00a0recorde\u00a0por seu custo e pode ser redimensionado automaticamente para suportar milhares de n\u00f3s.Saiba maisGovernan\u00e7a e armazenamento unificadosCom o streaming de dados no Databricks, voc\u00ea se beneficia dos componentes fundamentais da\u00a0Plataforma Lakehouse\u00a0\u2014 Unity Catalog e Delta Lake. Seus dados brutos s\u00e3o otimizados com a\u00a0Delta Lake, a \u00fanica estrutura de armazenamento de c\u00f3digo aberto criada desde o in\u00edcio para dados em batch e streaming.\u00a0O Unity Catalog\u00a0inclui governan\u00e7a detalhada para todos os seus dados e ativos de IA com um modelo consistente para descobrir, acessar e compartilhar dados nas nuvens. O Unity Catalog tamb\u00e9m fornece suporte nativo para\u00a0Delta Sharing, o primeiro protocolo aberto do setor para compartilhamento de dados f\u00e1cil e seguro com outras organiza\u00e7\u00f5es.Integra\u00e7\u00f5esD\u00ea flexibilidade \u00e0s suas equipes de dados: aproveite o\u00a0Partner Connect\u00a0e nosso ecossistema de\u00a0parceiros de tecnologia\u00a0para integrar perfeitamente ferramentas de streaming populares.Streaming de dadosHist\u00f3ria de cliente\u201cUsamos a Databricks para movimentar nossos dados em alta velocidade. Com esta plataforma, aumentamos drasticamente a velocidade com que respondemos \u00e0s necessidades dos nossos pacientes, seja na loja ou online. Atualmente, gerenciamos cerca de uma d\u00fazia de iniciativas, todas baseadas em dados na Databricks.\u201d\u2014 Sashi Venkatesan, diretor de engenharia de produto, Walgreens\u201cAgora, detectamos fraudes em tempo real. Estamos um passo \u00e0 frente dos fraudadores que tentam enganar o sistema, fazer desbloqueios ilegais, bots de chamada e texto e roubo de identidade.\u201d\u2014 Kate Hopkins, vice-presidente, AT&TDescubra maisDelta Live TablesFluxos de trabalho da DatabricksUnity CatalogDelta LakeSpark Structured StreamingConte\u00fado relacionadoe-books e demonstra\u00e7\u00f5esBuilding the Data Lakehouse, de Bill Inmon, pai do data warehouseData, Analytics and AI governanceGuia da equipe de dados para a Databricks Lakehouse PlatformDemos de streaming de Delta Live TablesEventosGerencie a transforma\u00e7\u00e3o de dados com Delta Live TablesS\u00e9rie de webinars sobre ingest\u00e3o de dados sem complica\u00e7\u00f5esData + AI Summit 2022Data +AI World Tour 2022BlogsPipelines de dados de streaming de baixa lat\u00eancia com Delta Live Tables e Apache KafkaSimplifique a ingest\u00e3o de dados de streaming na Delta LakeInsights em tempo real: as tr\u00eas principais raz\u00f5es pelas quais os clientes adoram o streaming de dados com o DatabricksSeus projetos na velocidade da luz: processamento de stream mais r\u00e1pido e f\u00e1cil com o Apache SparkUma vis\u00e3o geral de todos os novos recursos de streaming estruturado desenvolvidos em 2021 para Databricks e Apache Spark \u2014 Blog da DatabricksTudo pronto para come\u00e7ar?Experimente gratuitamenteJunte-se \u00e0 comunidadeProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cort-lunke\/#","text":"Cort Lunke - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCort LunkeData & Analytics Lead - Truterra at Land O'LakesBack to speakersSpeaker Bio\nA software architect at Land O\u2019Lakes and adjunct instructor at the University of St. Thomas Graduate Programs in Software, Cort has over 10 years of experience spanning data, analytics, server engineering, and cloud platforms. He currently leads the data and analytics team for Truterra, a Land O\u2019Lakes business and leading provider of sustainability programs in agriculture and food.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/martin-grund","text":"Martin Grund - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMartin GrundSenior Staff Software Engineer at DatabricksBack to speakersMartin Grund is a Senior Staff Software Engineer and Tech Lead at Databricks working at the intersection between query processing, data governance and security. Martin has previously led the engineering for Amazon Redshift Spectrum and worked on Cloudera Impala. He holds a PhD in computer science from the Hasso-Plattner-Institute in Germany.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/unity-catalog","text":"Unity Catalog - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnity CatalogUnified governance for data, analytics and AIGet StartedWatch Demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowUnity Catalog is a unified governance solution for all data and AI assets including files, tables, machine learning models and dashboards in your lakehouse on any cloud.Centralized governance for data and AIWith a common governance model based on ANSI SQL, centrally govern files, tables, dashboards and ML models on any cloud.Built-in data search and discoveryQuickly find, understand and reference data from across your data estate, boosting productivity.Performance and scaleBenefit from enhanced query performance with low-latency metadata serving and auto-tuning of the tables.Automated lineage for all workloadsCreate a unified, transparent view of your entire data ecosystem with automated and granular lineage for all workloads in SQL, R, Python, Scala and across all asset types \u2014 tables, notebooks, workflows and dashboards.Integrated with your existing toolsFuture-proof your data and AI governance with the flexibility to leverage your existing data catalogs and governance solutions.How it worksCentrally manage and govern all data assetsWith a common governance model based on open standard ANSI SQL, simplify governance for files, tables, dashboards and ML models on any cloud. Define access policies once at the account level and enforce across all workloads and workspaces. Unity Catalog also provides centralized fine-grained auditing by capturing an audit log of actions performed against the data and helps you meet your compliance and audit requirements.Manage fine-grained access controlsUse standard SQL functions to define row filters and column masks, allowing fine-grained access controls on rows and columns. As Databricks continues to build out capabilities to improve scalability and integration, upcoming attribute-based access controls will enable you to define access policies based on custom tags (attributes).Unified and secure data search experienceQuickly find, understand and reference relevant data from across your data estate with a unified data search experience for data analysts, data engineers and data scientists. Data search in Unity Catalog is secure by default, limiting search results based on the access privileges of users, and adding an additional layer of security for privacy considerations.Enhanced query performance at any scaleUnity Catalog provides enhanced query performance with low-latency metadata serving and table auto-tuning, resulting in faster executions of queries at any scale. Asynchronous automatic data compaction optimizes file sizes and reduces input\/output (I\/O) latency automatically in the background.Automated and real-time data lineageGain end-to-end visibility into how data flows in your lakehouse with automated and real-time data lineage across all workloads in SQL, Python, Scala and R. Quickly perform data quality checks, complete impact analysis of data changes, and debug any errors in your data pipelines. Benefit from lineage across tables, columns, notebooks, workflows and dashboards. Lineage graphs in Unity Catalog are privilege-aware, restricting access to lineage graphs based on the access privileges of users. Lineage can also be retrieved via REST API to support integrations with other catalogs.Secure data sharing across organizationsUnity Catalog natively supports\u00a0Delta Sharing, the world\u2019s first open protocol for secure data sharing, enabling you to easily share existing data in Delta Lake and Apache Parquet formats to any computing platform. Consumers don\u2019t have to be on the Databricks platform, same cloud or any cloud at all. You can share live data, without replicating or copying it to another system. Native integrations with Power BI, Tableau, Spark, pandas and Java allow recipients to consume shared data directly from the tools of their choice. You can centrally manage, govern, audit and track usage of the shared data on one platform.Seamless integrations with your existing toolsUnity Catalog works with your existing data catalogs, data storage systems and governance solutions so you can leverage your existing investments and build a future-proof governance model without expensive migration costs.Data and cloud storageData governance and catalog partnersCustomers\u201cUnity Catalog helped us simplify data management and access controls across the company. The Compass data team has securely onboarded 100+ data sources, migrated all workspaces to Unity Catalog, and created a gold layer for key stakeholders to tap into, to gain insights into areas like customer, product, usage, revenue, and more \u2014 creating a single source of truth, with complete access controls across the company.\u201d\u2014 Rajesh Nagpal, Senior Director of Data Engineering\u201cUnity Catalog significantly simplified our implementation of role-based access control, allowing us to secure data at a catalog, database, table and column level. We seamlessly provision the appropriate level of access to all users and can confidently manage and secure data access to meet our strict compliance and privacy policies.\u201d\u2014 Chris Locklin, Engineering Manager of Data Platforms, Grammarly\u201cUnity Catalog has allowed Milliman to tie its expansive data assets directly to its users, simplifying access management and reducing storage complexity. Unity Catalog allows Milliman to meet stringent health care standards, provide collaborative data exploration and reduce storage complexity. With Unity Catalog, we can quickly scale to meet our clients\u2019 needs.\u201d\u2014 Dan McCurley, Cloud Solutions Architect, Milliman\u201cUnity Catalog is enabling us to build a next-generation platform that unlocks the full potential of software-defined vehicles that evolve and improve as they rack up miles \u2013 enhancing the driving experience for customers and maximizing the environmental benefits of electrified transportation. We now have a centralized data catalog and access management across various teams and workspaces, which has opened up unprecedented opportunities for collaboration and innovation.\u201d\u2014 Venkat Sivasubramanian, Senior Director, Big Data\u201cUnity Catalog has been a game changer for us. Our analysts can access AWS external tables in real time in Databricks workspaces and can join them with Delta Lake tables. It gives us the performance benefits of Databricks SQL without migrating Glue tables. With Unity Catalog, various teams can collaborate with each other without moving the data from one place to another.\u201d\u2014 Rajat Gupta, Engineering Manager, Warner Bros. DiscoveryResourcesKeynote and Webinar[Keynote]Data Governance and sharing on the lakehouse at Data + AI Summit 2022[On-demand Webinar]How to simplify data and AI governanceeBook and Blogs[eBook] Data, Analytics and AI governanceAnnouncing General Availability of Data Lineage in Unity CatalogAnnouncing the Availability of Data Lineage With Unity CatalogIntroducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the LakehouseDocumentationAWS documentationAzure documentationGCP documentationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zeashan-pappa\/#","text":"Zeashan Pappa - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZeashan PappaSenior Product Specialist - Data Governance at DatabricksBack to speakersZeashan is a technology executive and architect who has 20+ years of enterprise software architecture, engineering, consulting, and project management expertise. \nZeashan has advised and successfully managed complex technical projects for some of the world's largest companies and across many industry verticals, including brand names such as Humana, Kaiser, Starbucks, Credit Suisse, MetLife, Microsoft, Bank of America, Astrazeneca, Kodak, Prudential, Dell, American Express, Disney, Walmart, Target, Pfizer, JP Morgan Chase, Bristol Myers Squibb, Wells Fargo, Pfizer, and Office Depot.\nZeashan is currently a field product leader at Databricks, helping to lead GTM strategy and NPI for Unity Catalog, Delta Sharing, Cleanrooms and Marketplace.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-definitive-guide-to-delta-lake-series?itm_data=lakehouse-link-deltalakeseries","text":"The Definitive Guide to Delta Lake Series | DatabricksSeriesBring fast analytics to your data lakeImprove quality, security and performance in your data lake.In \u201cThe Delta Lake Series\u201d, we will explore how Delta Lake brings quality, reliability, security and performance to your data lake to enable a lakehouse architecture. Download this eBook series to understand the unique capabilities of Delta Lake, explore common use cases like streaming and learn how Delta Lake delivers substantial performance improvements for our customers.The eBook series breaks out into the following chapters:Chapter 01 \u2014 Fundamentals and PerformanceChapter 02 \u2014 FeaturesChapter 03 \u2014 LakehouseChapter 04 \u2014 StreamingChapter 05 \u2014 Customer Use CasesGet the SeriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/technology-partner-program","text":"Databricks Technology Partner Program | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTechnology Partner ProgramConnect with thousands of Databricks customers ready to use your productApply nowDatabricks integrates with and promotes the best data and AI products in the market. We provide our partners with the technical and go-to-market support you need to acquire new customers and grow your business.Technology Partner BenefitsSales incentivesIncentives for Databricks\u2019 field organization to help sell your productCustomer accessDirectly acquire new customers via Databricks Partner ConnectLearn moreMarketing supportAccess marketing investments to help scale your reachProduct and R&D team accessGet access to Databricks product, engineering and support staffFree sandbox environmentBuild and test in a free sandbox environmentJoint marketing programsParticipate in joint marketing programs with DatabricksReady to connect?Apply nowFind a partnerProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/12\/10\/azure-databricks-now-generally-available-in-the-azure-china-region.html","text":"Azure Databricks Now Generally Available in the Azure China Region - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAzure Databricks Now Generally Available in the Azure China Regionby Sid Dhulipalla and Clinton FordDecember 10, 2020 in Company BlogShare this postWe are excited to announce that Azure Databricks is now generally available in Microsoft\u2019s Azure China region, enabling new data and AI use cases with fast, reliable and scalable data processing, analytics, data science and machine learning on the cloud. With availability across more than 30 Azure regions, global organizations appreciate the consistency, ease of use and collaboration enabled by Azure Databricks.\nHelping customers and partners scale with global availabilityOrganizations need a consistent set of cloud services across their global operations and customers looking to migrate on-premises big data workloads from a data center to the cloud frequently need a local Microsoft Azure region to meet data residency and data sovereignty requirements. Azure China is a sovereign cloud in mainland China that meets a high bar of security and compliance requirements. Azure Databricks helps customers deploy and scale batch and streaming data processing, simplify analytics and data science and implement machine learning in a way that is consistent and collaborative.\nNow, with Azure Databricks general availability in Azure China, organizations that operate in China can leverage the same enterprise-grade service and collaborative notebooks in the region as well. From retail recommendations and financial services risk analysis to improved diagnostics in healthcare and life sciences, Azure Databricks enables data teams of all sizes and across industries to innovate more quickly and more collaboratively on the cloud.\n\u201cAzure Databricks enables our data engineering and data science teams to deliver results even faster than ever. Scalable data processing and machine learning enable our teams to quickly adapt to shifts in consumer demand and buying behavior,\u201d says Kevin Zeng, Greater China IT CTO at Procter & Gamble. \u201cThe availability of Azure Databricks in China enables our global teams to provide a consistent experience for our customers in the region.\u201dYou can learn more about Azure Databricks general availability in the Azure China region by visiting the Azure Products by Region page. Learn more about what you need to consider before moving your workloads to the Azure China region with Microsoft\u2019s Azure China checklist and for questions please reach out to the team through Azure Support.\nGet started with Azure Databricks by attending a live event and this free, 3-part training series.\nTry Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks\u00a0\u2013 Vereinheitlichen aller Analyse- und KI-Workloads | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWAzure DatabricksDer Daten- und KI-Service von Databricks, der auf Microsoft Azure verf\u00fcgbar ist, speichert alle Ihre Daten in einem einfachen offenen Lakehouse und f\u00fchrt alle Analytics- und KI-Workloads zusammen.Erste SchrittePlanen Sie eine DemoAzure Databricks ist f\u00fcr Azure optimiert und eng in Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI und weitere Azure-Services integriert. Dies erm\u00f6glicht das Speichern aller Ihrer Daten in einem einfachen, offenen Lakehouse und das Zusammenf\u00fchren aller Ihrer Analytics- und KI-Workloads.Einfach\nIhre Daten, Analysen und KI\nauf einer gemeinsamen Plattform f\u00fcr alle Datenanwendungsf\u00e4lle vereinenOffen\nIhr Daten\u00f6kosystem\nmit Open Source, Standards und Formaten vereinheitlichenKollaborativ\nIhre Datenteams vereinen,\ndamit sie \u00fcber den gesamten Daten- und KI-Workflow hinweg zusammenarbeiten k\u00f6nnenWarum Azure Databricks?50-fach bessere Leistung bei Apache Spark\u2122-Workloads\nStellen Sie automatisch skalierende Computing-Cluster mit hochoptimiertem Spark bereit, die bis zu 50-mal schneller arbeiten.Mehr InformationenJeden Tag Millionen von Serverstunden\nTausende von Kunden vertrauen auf Azure Databricks, die t\u00e4glich Millionen von Serverstunden in mehr als 34\u00a0Azure-Regionen ausf\u00fchren.Mehr InformationenAnwenderfreundlichkeit\nBeginnen Sie mit einem einzigen Klick im Azure-Portal, profitieren Sie von der nativen Integration in die Azure-Sicherheits- und Datenservices und steigern Sie die Produktivit\u00e4t um bis zu 25\u00a0% mit kollaborativem Data Engineering und Data Science.Mehr InformationenAnwendungsf\u00e4lle in der IndustrieFinanzdienstleistungenSwiss ReEinheitliche\u00a0Datenanalysen f\u00fcr Data Engineering, Data Science und Analysten.HSBC\nAufbau einer\u00a0digitalen Zahlungsplattform\u00a0mit Azure Databricks.ABN AMROVerbesserte Analyse-Workflows\u00a0durch Zusammenarbeit, KI-gest\u00fctzte Erkenntnisse und fortschrittliche, automatisierte Machine-Learning-Funktionen.Mehr InformationenEinzelhandelGesundheitswesen und BiowissenschaftenAn einer Azure Databricks-Veranstaltung teilnehmenDatabricks, Microsoft und unsere Partner freuen sich, diese Veranstaltungen rund um Azure Databricks auszurichten. Besuchen Sie eine Veranstaltung in Ihrer N\u00e4he und erfahren Sie mehr \u00fcber den am schnellsten wachsenden Daten- und KI-Service auf Azure. Veranstaltungsablauf und -format k\u00f6nnen variieren. Einzelheiten entnehmen Sie bitte der jeweiligen Veranstaltungsseite.\u00a0Mehr InformationenOptimiert f\u00fcr AzureNahtlose Integration in Azure-Datenspeicher und -dienste mit speziellen Konnektoren f\u00fcr schnellen Datenzugriff und\u00a0vereinfachte Verwaltung\u00a0in Ihrer gesamten Umgebung. Das macht es einfach,\u00a0Sicherheitskontrollen einzurichten,\u00a0Umgebungen zu verwalten und alle Ihre\u00a0Azure-Daten zu verarbeiten.Mehr InformationenAusgew\u00e4hlte IntegrationenAzure Active DirectorySingle Sign-On\u00a0mit Azure Active Directory ist die beste M\u00f6glichkeit, um sich bei Azure Databricks anzumelden. Azure Databricks unterst\u00fctzt auch eine\u00a0automatisierte Benutzerbereitstellung\u00a0mit Azure AD. So k\u00f6nnen Sie neue Benutzer erstellen, ihnen die angemessene Zugriffsebene gew\u00e4hren und Benutzer entfernen, um den Zugriff zu entziehen.Azure Data Lake StoreAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultRessourcenWhitepaperAzure Databricks f\u00fcr Data EngineeringAzure Databricks: Die beste Plattform zur Ausf\u00fchrung von ML und KIDrei praktische Anwendungsf\u00e4lle mit Azure DatabricksErste Schritte mit Apache Spark auf Azure DatabricksVIDEOSGespr\u00e4ch am Kamin zwischen Ali Ghodsi und Rohan Kumar (CVP, Microsoft) beim Keynote Data + AI Summit NA 2021Azure Databricks Cloud Integration-DemoDaten in Delta Lake von Azure Databricks aufnehmenIhre Daten mit Databricks SQL erkundenE-BooksGartner\u00ae Magic Quadrant\u2122 for Data Science and Machine Learning Platforms 2021Moderne Cloud-Datenplattformen einfach erkl\u00e4rt8 Schritte f\u00fcr einen Entwickler zum Erlernen von Apache Spark\u2122 mit Delta LakeApache Spark\u2122\u00a0\u2013 eine \u00dcbersicht: Erste Schritte mit der Kernarchitektur und grundlegenden KonzeptenM\u00f6chten Sie loslegen?Erste SchrittePlanen Sie eine DemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/cohort-building","text":"Building Patient Cohorts With Knowledge Graphs - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorCohort Building With Knowledge GraphsPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedInterpreting Clinical Relationships With John Snow Labs & DatabricksCohort building in healthcare and life sciences requires criteria extracted from unstructured and semi-structured clinical documentation for cohort analysis. With the Databricks Lakehouse for Healthcare and Life Sciences and John Snow Labs, healthcare data teams can:Explore real-world and patient data at scaleIdentify related entities across various data setsBuild patient cohorts by identifying commonalities between entitiesDownload Cohort Building NotebookResourcesOn-Demand DemoWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/events","text":"Databricks Events | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks EventsExplore upcoming Databricks meetups, webinars, conferences and more.Join Generation AIJune 26\u201329Learn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowLoading...Browse All Upcoming EventsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/genome-wide-association-studies","text":"Genome-Wide Association Studies | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorGenome-Wide Association StudiesPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAnalyze genetic associations at massive scaleGenome-wide association studies identify genetic variations associated with a target disease or trait. Researchers and clinicians can use this information to better detect, treat and prevent chronic health conditions. This Solution Accelerator notebook builds on top of Glow, an open source project for genomic analysis, to provide a fast, scalable and easy-to-implement method for whole genome regression tests.Easily process VCF and phenotypic data at scale with pre-built pipelinesUse notebooks and SQL dashboards to visualize genetic associationsAnalyze genomic data 10x faster compared to other industry toolsDownload notebookResourcesBlogRead nowCase studyLearn moreWebinarWatch nowDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-roussel\/#","text":"John Roussel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn RousselCIO at California Department of Public Health (CDPH)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nabil-raad\/#","text":"Nabil Raad - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNabil RaadSVP of Data and Analytics at GM FinancialBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anindita-mahapatra","text":"Anindita Mahapatra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnindita MahapatraLead Solutions Architect at DatabricksBack to speakersAnindita joined Databricks in 2019 and is a lead solutions architect in financial services helping customers gleam value from their data initiatives. She co-created Security Analysis Tool (SAT), specializes in Big Data & Analytics with 20+ years of experience in designing scalable multi-tenant solutions. She teaches a Data Engineering course at the Harvard Extension & has written a book \u2018Simplifying Data Engineering and Analytics with Delta\u2019.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/data-mart","text":"What is a Data Mart?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData MartAll>Data MartTry Databricks for freeGet StartedWhat is a data mart?A data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smaller and more focused than a data warehouse, and generally exists as a subset of an organization's larger enterprise data warehouse. Data marts are commonly used for analytics, business intelligence, and reporting. Data marts were the first evolutionary step in the physical reality of central data warehouses and data lakes. ACNielsen offered their clients the first data mart in the early 1970s to provide a way for them to store information digitally and boost their sales efforts.Characteristics of data martsTypically built and managed by the enterprise data team, although they can be built and maintained by business unit SMEs organically as well.Business group data stewards maintain the data mart, and end users have read-only access \u2014 they can query and view tables, but cannot modify them, in order to prevent less technically-savvy users from accidentally deleting or modifying critical business data.Typically uses a dimensional model and star schema.Contains a curated subset of data from the larger data warehouse. The data is highly structured, having been cleansed and conformed by the enterprise data team to make it easy to understand and query.Designed around the unique needs of a particular line of business or use case.Users typically query the data using SQL commands.Types of data marts: independent data marts, dependent data marts, and hybrid data martsToday, there are three basic types of data marts:Independent data marts are not part of a data warehouse, and are very similar to the original data mart offered by ACNielsen. They are typically focused on one area of business or subject area. Data sources can include both external and internal sources. It is then translated, processed, and loaded into the data mart, where it is stored until needed.Dependent data marts are built into an existing data warehouse. A top-down approach is used, supporting the storage of all data in a centralized location. A clearly defined section of data is then selected for purposes of research.Hybrid data marts combine the data taken from a data warehouse and \"other\" data sources. This can be useful in a variety of situations, including providing the ad hoc integration with a new group, or product, which has been added to an organization. Hybrid data marts are well-suited for multiple database environments and provide fast implementation turnaround. These systems make data cleansing easy, and work well with smaller data-centric applications.Benefits of data martsSingle source of truth \u2014 the data mart can serve as a single source of truth for a particular line of business, so everyone is working off of the same facts and data.Simplicity \u2014 business users looking for data can visit the curated data mart for easy access to the data they care about, instead of having to wade through the entire data warehouse and join tables together to get the data they need.Challenges with data martsEnterprise data warehouses are created with good intentions to serve all of an enterprise's data management needs. But invariably, you can't keep everyone happy, as different business units have different data needs and objectives. So departments copy and create their own data marts (sometimes with Enterprise IT help) with the aim of augmenting a particular data warehouse's subject area, to meet their self-service analytics and departmental reporting needs. As a result, over time, data marts can become data silos and shadow copies of data \u2014 from an enterprise perspective \u2014 but they do serve the department's needs well. When many departments do this - there is no single version of truth.How Lakehouse solves the challenges with data martsLakehouse solves the challenges mentioned above by putting all of the enterprise data warehouses and data marts on one platform, with unified security and governance \u2014 while still offering different teams the flexibility to have their own sandboxes. Since any data mart or \"augmented copy\" is made on the same Lakehouse platform as all the others \u2014 the Lakehouse's data catalog discovers that, and given the Data Governance rules like tagging and using a data dictionary etc., it ensures that the augmented copy is made discoverable by all \u2014 preventing similar duplicate copies.Build your next data mart on Databricks SQLTry Databricks SQL for freeResourcesDatabricks SQLDelta Lake on DatabricksGlossary \u2014 Data warehouseBack to GlossaryLearn what\u2019s driving the Lakehouse pattern.REGISTER NOWProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/01\/28\/burning-through-electronic-health-records-in-real-time-with-smolder.html","text":"EHR Analytics in Real Time Using Smolder, Apache Spark\u2122, and Delta Lake - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorBurning Through Electronic Health Records in Real Time With Smolderby Ryan DeCosmo and Frank Austin NothaftJanuary 28, 2021 in Engineering BlogShare this postCheck out the\u00a0solution accelerator\u00a0to download the notebook referred throughout this blog.\u00a0In previous blogs, we looked at two separate workflows for working with patient data coming out of an electronic health record (EHR). In those workflows, we focused on a historical batch extract of EHR data. However, in the real world, data is continuously inputted into an EHR. For many of the important predictive healthcare analytics use cases, like sepsis prediction or ER overcrowding, we need to work with the clinical data as it flows through the EHR.How does data actually flow through an EHR? Typically, there are several passes of refinement. In some EHR implementations, data first lands in a near-real-time fashion into a NoSQL style operational store. After a day, the new data in this NoSQL store moves from the operational store into normalized and dimensional SQL stores. Other EHR implementations have different database implementations, but still, there is typically a delay before a final \u201chistorical\u201d record of EHR data is available for batch analysis. To analyze clinical data in real time, we need to access either push-based HL7 message feeds or pull-based FHIR API endpoints. These feeds and endpoints contain a variety of health information data. For instance, the Admission\/Discharge\/Transfer (ADT) messages can be used to track when a patient comes in or moves between units, while Order Entry (ORM) messages place\/modify\/cancel orders, such as giving oxygen to a patient or running a specific laboratory test. By combining feeds and resources together, we can get a comprehensive view of our patients and our hospital.Healthcare teams and clinicians face a number of questions when building a real-time analytics system on top of EHR data: should I consume FHIR or HL7? How should I parse the records? How should I store and merge data? In this blog, we introduce Smolder, an open-source library for manipulating EHR data using Apache Spark\u2122. Smolder provides Spark-native data loaders and APIs that transforms HL7 messages into Apache Spark\u2122 SQL DataFrames. To simplify manipulating, validating, and remapping the content in messages, Smolder adds SQL functions for accessing message fields. Ultimately, this makes it possible to build streaming pipelines to ingest and analyze HL7 data in minutes while providing an easy-to-use declarative syntax that eliminates the need to learn low-level libraries like HAPI. These pipelines can achieve near-real-time latencies while achieving data unification across healthcare data sources by leveraging open source standards like Delta LakeIn the rest of this blog, we will use the Smolder library to analyze EHR data in near-real-time to identify patients with high care utilization. First, we will do a deep dive on the HL7v2 standard, how it works, and what it means. Then, we will discuss the design principles that guided our development of Smolder. Finally, we will show how to load the data into Delta Lake in real-time by using Apache Spark\u2019s Structured Streaming APIs, and the Smolder library. We will use this data to drive a dashboard that helps us identify in real time where we have high-utilization patients across our hospital system.Working with HL7 messagesHL7v2\nHL7 stands for Health Level 7, an international standards body that defines interoperability standards for healthcare. They maintain multiple prominent standards, such as the emerging FHIR healthcare data exchange standard that defines REST APIs and JSON schemas for exchanging healthcare data, the XML-based (consolidated) Clinical Document Architecture (CDA and C-CDA) standard, and the original HL7v2 standard. These standards have different purposes: FHIR defines API endpoints that are useful for application development, C-CDA defines standards that are best used for exchanging historical information about a patient, and HL7v2 is a messaging dialect that captures real-time updates to the state and data that is present in an EHR. While there has been a lot of recent interest in FHIR for application development, HL7v2 is generally the most appropriate standard to use for analytics due to its widespread adoption. Most institutions have legacy systems currently leveraging HL7 feeds. As a result, it is easier to tap into a larger amount of data and create a richer base for analytics, without having to wait for every system to support FHIR. Also, HL7 feeds themselves are typically streams of data based on TCP\/IP, which meshes very cleanly to event-based streaming architectures.\u00a0\nMSH|^~\\&|||||20201020150800.739+0000||ADT^A03^ADT_A03|11374301|P|2.4\nEVN|A03|20170820074419-0500\nPID|||d40726da-9b7a-49eb-9eeb-e406708bbb60||Heller^Keneth||||||140 Pacocha Way Suite 52^^Northampton^Massachusetts^^USA\nPV1||a|^^^COOLEY DICKINSON HOSPITAL INC THE|ambulatory||||49318f80-bd8b-3fc7-a096-ac43088b0c12^THE^COOLEY||||||||||||||||||||||||||||||||||||20170820074419-05\\\n00\nCode: This is an example HL7 message. This message is an ADT_A03 message, which provides information about a patient being discharged. We generated this message using the open-source Synthea medical record simulator.Since we have settled on HL7v2, let\u2019s start by looking at the contents of an HL7v2 message. The image above shows a single HL7v2 message, which is multiline, pipe delimited. There is also an XML version of the spec. FHIR is a JSON-based spec.\u00a0 The schema for each message type and segment type is specified by the HL7v2 spec. Each line of the message is a segment, and the first column is the \u201csegment descriptor,\u201d which tells us what the schema is for in that segment. When we parse the ADT_A03 message above, we have two segments; the \u201cPID\u201d segment identifier contains information about the patient\u2019s identity and the \u201cPV1\u201d segment contains information about the patient\u2019s visit that they are discharged from. In a patient identity segment, the second field is the ID for the patient, the fourth field is the name, and so on.So, how can you work with this data? We have helped multiple customers ingest HL7 data into Databricks using Apache Spark\u2019s streaming capabilities. Historically, we have seen customers build a conduit between their EHR and a streaming service like Apache Kafka\u2122\ufe0f, Kinesis or EventHubs. Then they connect one of these streaming busses up to Apache Spark, which yields a DataFrame of message text. Finally, they parse this text using either a handwritten parser or a low-level library like HAPI.While this approach has worked for some customers, having to hand-code parsing libraries--or rely on libraries like HAPI that have overhead--can cause challenges. One of the key benefits of data lakes is to be able to delay validation in a pipeline. We typically talk about this being the bronze layer, which is the data that is ingested and stored in its raw form. This gives you the flexibility to maintain the observed historical data without having to make any choices about the size and shape of your data yet.This is particularly useful when you need to do historical validation and analysis before embarking on a business-facing use case. For example, consider the case of validating the primary care provider (PCP) field. If you discover a healthcare system was swapping the PCP with a different physician on the care team, you would want to be able to retroactively correct the error in all those records. Smolder by design, subscribes to this paradigm.Unlike HAPI, Smolder breaks messages down into structs that make no attempt at validation beyond it being a valid HL7 message. This allows us to capture the observed data, while still making it accessible to query and populate our silver layer.Designing Smolder, an open-source library for working with HL7 in Apache SparkWe started developing Smolder to provide an easy-to-use system that can achieve near-real-time latencies for processing HL7v2 messages and make this data accessible to a large ecosystem of tools for data science and visualization. To do this, we took the following approach:Turn HL7 messages into DataFrames with a single line of code: DataFrames are widely used across data science\u2014whether through Pandas, R, or Spark\u2014and can be used through widely-accessible declarative programming frameworks like SQL. If we can load HL7 messages into a DataFrame with a single line of code, we have dramatically increased the number of downstream places we can work with HL7 messages.Use simple, declarative APIs to extract data from messages: While libraries like HAPI provide APIs for working with HL7v2 messages, these APIs are complex, deeply object-oriented, and require a lot of knowledge about the HL7v2 messaging format. If we can instead give people one-line SQL-like functions, they can make sense of the data in HL7 messages without needing to learn a new and complex API.Have a consistent schema and semantics for HL7 messages, no matter the source: Smolder supports both the direct ingestion of HL7v2 messages, as well as the ingestion of HL7v2 message text that has come from another streaming source, whether an open-source tool like Apache Kafka or cloud-specific services like AWS\u2019 Kinesis or Azure\u2019s EventHubs. No matter the source, the messages always are parsed into the same schema. When coupled with Apache Spark\u2019s Structured Streaming semantics, we\u00a0 achieve portable, platform-neutral code that can easily be validated and runs equivalently during batch or streaming data processing.Ultimately, this approach makes Smolder a lightweight library that is easy to learn and use, which can support demanding SLAs on large volumes of HL7 messages. Now we will dive into Smolder\u2019s APIs and how to build a dashboard that analyzes hospital admission patterns.Parsing HL7 messages using SmolderApache Spark\u2122\u2019s Structured Streaming API allows a user to process streaming data by using an extension of the Spark SQL APIs. When coupled with the Smolder library, you can load HL7v2 messages into a DataFrame, either using Smolder to read batches of raw HL7v2 messages, or by using Smolder to parse out HL7v2 message text that comes in from another streaming source. For instance, if you have a batch of messages to load, you simply invoke the hl7 reader:\nscala> val df = spark.read.format(\"hl7\").load(\"path\/to\/hl7\/messages\")\ndf: org.apache.spark.sql.DataFrame = [message: string, segments: array<struct>>]\n<\/struct>The schema returned contains the message header in the message column. The message segments are nested in the segments column, which is an array that contains two nested fields: the string id for the segment (e.g., PID for a patient identification segment) and an array of segment fields.Smolder can also be used to parse raw message text. This might happen if you had an HL7 message feed land in an intermediate source first (e.g., a Kafka stream). To do this, we can use Smolder's parse_hl7_message helper function. First, we start with a DataFrame containing HL7 message text:\nscala> val textMessageDf = ...\ntextMessageDf: org.apache.spark.sql.DataFrame = [value: string]\n\nscala> textMessageDf.show()\n+--------------------+                                                          \n|               value|\n+--------------------+\n|MSH|^~\\&|||||2020...|\n+--------------------+\nThen, we can import the parse_hl7_message message from the com.databricks.labs.smolder.functions object and apply that to the column we want to parse:\nscala> import com.databricks.labs.smolder.functions.parse_hl7_message\nimport com.databricks.labs.smolder.functions.parse_hl7_message\n\nscala> val parsedDf = textMessageDf.select(parse_hl7_message($\"value\").as(\"message\"))\nparsedDf: org.apache.spark.sql.DataFrame = [message: struct>>>]\nThis yields the same schema as our hl7 data source.Extracting data from HL7v2 message segments using SmolderWhile Smolder provides an easy-to-use schema for HL7 messages, we also provide helper functions in com.databricks.labs.smolder.functions to extract subfields of a message segment. For instance, let's say we want to get the patient's name, which is the 5th field in the patient ID (PID) segment. We can extract this with the segment_field function:\nscala> import com.databricks.labs.smolder.functions.segment_field\nimport com.databricks.labs.smolder.functions.segment_field\n\nscala> val nameDf = df.select(segment_field(\"PID\", 4).alias(\"name\"))\nnameDf: org.apache.spark.sql.DataFrame = [name: string]\n\nscala> nameDf.show()\n+-------------+\n|         name|\n+-------------+\n|Heller^Keneth|\n+-------------+\nIf we then wanted to get the patient's first name, we can use the subfield function:\nscala> import com.databricks.labs.smolder.functions.subfield\nimport com.databricks.labs.smolder.functions.subfield\n\nscala> val firstNameDf = nameDf.select(subfield($\"name\", 1).alias(\"firstname\"))\nfirstNameDf: org.apache.spark.sql.DataFrame = [firstname: string]\n\nscala> firstNameDf.show()\n+---------+\n|firstname|\n+---------+\n|   Keneth|\n+---------+The bronze layer contains raw message feeds (e.g., a table per feed of ADT, ORM, ORU, etc)The silver layer aggregates this information into tables that are useful for downstream applications (e.g., a longitudinal patient record, aggregates about hospital resources)The gold layer contains application-level data (e.g., for a hospital overcrowding alerting system, occupancy per ward per hospital)Why build on top of Delta Lake? First of all, Delta is an open format that ensures that data is easily accessible from many analytical systems, whether its a data science ecosystem through Apache Spark or through data warehouse systems like Synapse. Additionally, Delta Lake is designed to support cascading streams, meaning that data can stream through the bronze layer, into the silver, and finally gold layers. Additionally, Delta Lake provides numerous ways to optimize our tables to improve query performance. For instance, we probably want to query rapidly across both patient ID and date of an encounter, since those are common fields to query over: as we discussed in our previous blog, we can use Z-ordering. Delta Lake supports Z-ordering to do multi-dimensional data clustering and provide good performance on both of these query patterns.Get started building a health Delta Lake with SmolderIn this blog, we introduced Smolder, an Apache 2 licensed library for loading patient data from an EHR. You can get started by reading our project docs, or create a fork of the repository to start contributing code today. To learn more about using Delta Lake to store and process clinical datasets, download our free eBook on working with real-world clinical datasets. You can also start a free trial today using the notebooks from this solution accelerator.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/solutions\/industries\/federal-government","text":"Federal Government Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData analytics and AI for federal agenciesUnlock innovation to deliver better public services with data and machine learningFrom the Federal Data Strategy to the AI Executive Order, it\u2019s clear that the U.S. federal government is focused on modernizing its data analytics and warehousing capabilities.The Databricks Lakehouse Platform empowers federal agencies to unlock the full potential of their data to deliver on their mission objectives and better serve citizens.Empowering Federal agencies to leverage data\u00a0and AI to deliver on mission objectivesTrusted by leading public sector agencies+ Any other Apache Spark\u2122\ufe0f compatible clientSee how industry leaders are using Databricks to improve the experience for citizens across all public servicesLatest blog posts, webinars, and case studiesWhy Databricks for the federal governmentModernize your data analytics130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Deliver mission outcomes effectively and efficiently130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Create better experiences for citizens130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Learn moreExtensive compliance for quick and easy approval to operate (ATO)Databricks has achieved ATOs on the regions, networks and compliance controls that support your mission objectivesCloudsC2S\nSC2S\nGovCloud\nPublic Cloud\nNetworksPublic\nNIPR\nSIPR\nJWICS\nCompliance controlsFedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICS-503\nHow Databricks fuels innovation for the federal governmentHealthcareImprove the delivery and quality of healthcare services for citizens with powerful analytics and a 360\u00b0 view of patients.\nPatient 360\u00a0\nSupply chain optimization\u00a0\nInsurance management\u00a0Genomics\u00a0\nDrug discovery and deliveryDefenseApply the power of predictive analytics to geospatial, IoT and surveillance data to improve operations and protect the nation.\u00a0\nLogistics\nPredictive maintenance\u00a0\nSurveillance and reconnaissance\u00a0\nLaw enforcement and readinessHomeland SecurityDetect and prevent criminal activities and national threats with real-time analytics and data-driven decision-making.\u00a0\nCustoms and border protection\u00a0\nImmigration and citizenship\u00a0\nCounter-terrorism\u00a0\nFederal emergency aid managementPublic Authority\/CommerceProactively detect anomalies with machine learning to mitigate risk and prevent fraudulent activity.\u00a0\nTax fraud and collection\u00a0\nProcess and operations management\u00a0\nGrants management\u00a0\nCustomer 360EnergyImprove energy management with data insights that ensure energy resiliency and sustainability.\u00a0\nSecurity of energy infrastructure\u00a0\nSmarter energy management\u00a0\nEnergy exploration\u00a0\nElectrical grid reliabilityIntelligence CommunityLeverage real-time insights to make informed decisions that can impact the safety of our citizens and the world.\u00a0\nThreat detection\u00a0\nNeutralize cyberattacks\u00a0\nIntelligence surveillance and reconnaissance\u00a0\nSocial media analyticsResourcesCustomer StoriesDriving Digital Transformation to Put Patients First at CMSData Governance Best Practices \u2014 Lessons Learned From the Centers for Medicare and Medicaid ServicesLessons Learned From Modernizing the USCIS Data Analytics PlatformModernizing the Air Force With Big Data and AIWebinarsRapid Response to Hospital Operations Using Data and AI During COVID-19Geospatial Analytics and AI in the Public SectorModern Data Analytics Architecture for the GovernmentImproving Threat Detection With Big Data and AINewsAzure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)Government-Grade Security in the AWS CloudBringing Unified Analytics to Government ClientsEmpowering the U.S. Intelligence Community With Mission-Critical Analytics and AISummit talksAutomating the Federal Aviation Administration\u2019s (FAA) System-Wide Information Management (SWIM) Data Ingestion and AnalysisGeospatial Analytics at Scale: Analyzing Human Movement Patterns During a PandemicReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.\u00a0Try for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Experimente o Databricks | DatabricksExperimente o Databricks gratuitamente Experimente a plataforma Databricks completa gratuitamente por 14 dias em sua nuvem AWS, Microsoft Azure ou Google Cloud.Simplique a ingest\u00e3o de dados e automatize processos de ETLImporte dados de centenas de fontes. Utilize uma abordagem asseverativa e simples para construir pipelines de dados.Colabore em sua linguagem preferidaCode em Python, R, Scala e SQL com colabora\u00e7\u00e3o, versionamento autom\u00e1tico, integra\u00e7\u00f5es com Git e controles de acesso (RBAC) Pre\u00e7o\/Performance at\u00e9 12x superior a data warehouses em nuvemDescubra porque mais de 7000 clientes de todo mundo confiam na Databricks para todos os seus workloads de Dados, de BI a AI.Crie sua conta Databricks1\/2Primeiro NomeSegundo NomeEmailEmpresaT\u00edtuloTelefone (Opcional)SelecionarPa\u00edsContinuarAviso de privacidade (atualizado)Termos de UsoSuas op\u00e7\u00f5es de privacidadeSeus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/br\/customers","text":"Clientes da\u2028 Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWClientes da DatabricksDescubra como empresas inovadoras em todos os setores usam a Databricks Lakehouse PlatformHist\u00f3rias em destaque\n\n\nHist\u00f3ria de cliente\n\nCria\u00e7\u00e3o de um neg\u00f3cio omnicanal eficiente do ponto de vista operacional\nOs clientes brasileiros contam com a Via (antiga Via Varejo) para uma ampla sele\u00e7\u00e3o de produtos e servi\u00e7os, como eletr\u00f4nicos de consumo, eletrodom\u00e9sticos, m\u00f3veis e cart\u00f5es de cr\u00e9dito.\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nTransformando pagamentos m\u00f3veis em um superaplicativo financeiro\nO PicPay tem a miss\u00e3o de se tornar o primeiro superaplicativo de tecnologia financeira do Brasil, oferecendo uma variedade de servi\u00e7os, como cart\u00f5es de cr\u00e9dito, carteira digital, pagamentos P2P, com\u00e9rcio eletr\u00f4nico e rede social.\n\nLeia mais\n\n\nHist\u00f3ria de cliente\n\nShell inova com solu\u00e7\u00f5es de energia para um mundo mais limpo\nA Databricks Lakehouse ajuda a democratizar os dados e modernizar as opera\u00e7\u00f5es globalmente\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nReinventando o mobile banking com ML\nComo um dos maiores bancos internacionais, o HSBC apresenta uma nova forma de gerenciar pagamentos digitais em dispositivos m\u00f3veis.\n\nLeia mais\n\n\nHist\u00f3ria de cliente\n\nABN AMRO transforma o setor banc\u00e1rio em escala global\nABN AMRO coloca os dados e Al em a\u00e7\u00e3o com a Databricks Lakehouse\n\nLeia mais\n\n\nHist\u00f3ria do cliente\n\nExperi\u00eancias de jogo avan\u00e7adas que chamam a aten\u00e7\u00e3o dos jogadores\nA SEGA Europe encanta gamers no mundo todo h\u00e1 d\u00e9cadas com jogos ic\u00f4nicos, como Sonic the Hedgehog, e novos favoritos, como Warhammer.\u00a0\n\nLeia maisExplorar todos os clientesO efeito da equipe de dadosAs equipes de dados s\u00e3o as for\u00e7as unidas que resolvem os problemas mais dif\u00edceis do mundo.Veja como \u2192A pr\u00f3xima hist\u00f3ria de sucesso pode ser suaEntre em contatoRecursosHist\u00f3ria de clienteDescubra como a Databricks permite que a Cond\u00e9 Nast ofere\u00e7a conte\u00fado personalizado aos seus clientes.Saiba maisHist\u00f3ria de clienteSaiba como a Apple e o Disney+ obtiveram sucesso unindo an\u00e1lises e IASaiba maisHist\u00f3ria de clienteSlawek Kierner, vice-presidente s\u00eanior e diretor de dados e an\u00e1lises da Humana, fala sobre o papel dos dados e da IA na equidade da sa\u00fadeAssistirTudo pronto para come\u00e7ar?Experimente gratuitamenteEntre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
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5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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DatabricksDatabricks \u306e\u30c7\u30fc\u30bf\u30fbAI \u30b5\u30fc\u30d3\u30b9\u3068\u3001Microsoft Azure \u3068\u306e\u7dca\u5bc6\u306a\u7d71\u5408\u304c\u3001\u30b7\u30f3\u30d7\u30eb\u3067\u30aa\u30fc\u30d7\u30f3\u306a\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3067\u306e\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u306e\u4fdd\u5b58\u3068\u3001\u5206\u6790\u30fbAI \u306e\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306e\u96c6\u7d04\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u30ea\u30af\u30a8\u30b9\u30c8Azure \u74b0\u5883\u5411\u3051\u306b\u6700\u9069\u5316\u3055\u308c\u305f\u300cAzure Databricks\u300d\u306f\u3001Azure Data Lake Storage\u3001Azure Data Factory\u3001Azure Synapse Analytics\u3001Power BI\u3001\u305d\u306e\u4ed6\u306e Azure 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\u3092\u96c6\u7d04\u30aa\u30fc\u30d7\u30f3\n\u30c7\u30fc\u30bf\u306e\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3092\u69cb\u7bc9\uff1a\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u3001\u30aa\u30fc\u30d7\u30f3\u30b9\u30bf\u30f3\u30c0\u30fc\u30c9\u3001\u30aa\u30fc\u30d7\u30f3\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3067\u3001\u30c7\u30fc\u30bf\u306e\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u3092\u69cb\u7bc9\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\n\u30c7\u30fc\u30bf\u3068 AI \u306e\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u5168\u822c\u3067\u306e\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u4fc3\u9032Azure Databricks \u304c\u9078\u3070\u308c\u308b\u7406\u7531Apache Spark\u2122\n\u9ad8\u5ea6\u306b\u6700\u9069\u5316\u3055\u308c\u305f Spark \u3092\u5099\u3048\u3001\u6700\u5927 50 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{"source":"https:\/\/www.databricks.com\/p\/webinar\/operationalizing-machine-learning-at-scale","text":"MLOps Virtual Event | DatabricksMLOps Virtual EventOperationalizing machine learning at scaleAvailable on demandAs organizations continue to develop their machine learning (ML) practice, there\u2019s a growing need for robust and reliable platforms capable of handling the entire ML lifecycle. The emergence of MLOps is promising but many challenges remain.Register now to watch the latest developments from Databricks geared towards automating MLOps \u2014 including new Git and CI\/CD integrations, auto logging of experiments, model explainability and model serving.We\u2019ll also cover:Best practices from domain experts to operationalize ML at scale, from experimentation to productionA checklist of the capabilities you\u2019ll need, common pitfalls, as well as technological and organizational challenges (and how to overcome them)Details and speakersPresentations will be enhanced with demos, as well as success stories and learnings from experts who have deployed real-world examples of such pipelines for predictive analytics. Live Q&A and discussion will keep this event engaging for data science practitioners and leaders alike.\u00a0Featured Customers\u00a0AgendaOpening Keynote\nMLOps and ML Platforms State of the Industry \u2014 Matei Zaharia, CTO and Co-founder, Databricks and Clemens Mewald, Director of Product Management, DatabricksProduct DemoEnd-to-end MLOps for PyTorch on Databricks using MLflow \u2014 Sean Owen, Principal Architect, Databricks.Customer StoriesApplying MLOps at Scale \u2014 Keven Wang, Competence Lead, ML Engineer, H&M \u2013\u00a0an overview of H&M reference architecture and demo of the production workflow. This talk will cover the entire MLOps stack addressing a few common challenges in AI and Machine learning products, like development efficiency, end to end traceability, speed to production, etc.CI\/CD in MLOps \u2013 Implementing a Framework for Self-Service Experimentation and Deployment at Enterprise Scale \u2014Wesly Clark, Chief Architect, Enterprise Analytics and AI, J.B. Hunt Transport and Cara Phillips, Data Science, MLOps Consultant, Artis Consulting \u2013\u00a0this talk will cover the core values, concepts, and conventions of the framework followed by a technical demo of how to implement the self-service automation of Databricks resources, code, and jobs deployment into Azure DevOps CI\/CD pipelines.Live Q&AsFeatured SpeakersMatei ZahariaCTO and Co-founderDatabricksKeven WangCompetence Lead, ML EngineerH&MWesly ClarkChief Architect, Enterprise Analytics and AIJ.B. Hunt TransportCara PhillipsData Science, MLOps ConsultantArtis ConsultingTranscriptSpeaker 1:\nData is big, but it\u2019s potential is even bigger. When combined with AI data holds the promise of curing diseases, saving lives, reversing climate change, and changing the way we live. We believe the future depends on data and unlocking its limitless potential. We\u2019re here to make that happen.Speaker 1:\nDatabricks is the data and AI company. We help data teams, engineers, analysts, and scientists work together to find value inside data and solve the world\u2019s toughest problems. Because the challenges we face as businesses, as people, and as a planet, aren\u2019t easy. They can\u2019t be solved in silos. It can\u2019t be solved by one person. We need all the data, all the science, all the brain power. We need all hands on deck, in one place. On the only open unified platform for data management, business analytics and machine learning, and that changes everything. It expands our sense of what\u2019s possible. It makes things simple. It turns weeks into minutes. So data teams can innovate faster, because that\u2019s how innovation should happen. Collaborative and fast.Speaker 1:\nSo let\u2019s defy assumptions. Break the mold. Map every genome. Cure every cancer. Binge watch the cosmos. Spelunk black holes. Make every voice heard. Hack the hackers. [inaudible 00:01:33]. Take more moonshots and land them.Speaker 2:\nThe heavens have become a part of man\u2019s world.Speaker 1:\nFrom now on nothing stands between you and your data, you and the answers because the power of data is the power of knowing. Now you know.Sylvia Simion:\nWelcome everyone. And thank you for joining our MLOps Virtual Event. My name is Sylvia Simon. I do product marketing at Databricks, and I\u2019m very excited to be here with you as your host today, as well as with our speakers, because we have a very exciting lineup and they have prepared for you some awesome presentations and demos to discuss and show you best practices and techniques on how to better operationalize and automate machine learning at scale. So I really hope you\u2019ll enjoy hearing from them and learn more about machine learning practices in a diverse set of settings.Sylvia Simion:\nWe will kick things off shortly with our opening keynote and demo, which will be followed by speakers from H&M, JB Hunt and Artis Consulting. And then we will wrap things up with a live Q&A\u2019s at the end of the event, but first some housekeeping and logistics.Sylvia Simion:\nYour audio connections will be muted for the entire webinar, we can\u2019t hear you. A recording of this event will be available. Make sure to visit the Databricks blog for details. And to deliver the best possible experience the talks have been pre-recorded. With that said, we designed this to be a highly interactive event. Our speakers and a few engineers from Databricks are on hand to field questions. If you have a question at any point during this event use the chat box, which is part of the platform. We will also have a live Q&A session at the end of the event. If you have a question for a specific presenter, please indicate it in your question and we will direct it to the appropriate person.Sylvia Simion:\nFor those of you who are not familiar with who Databricks is, our company was founded by the original creators of Apache Spark seven years ago. Our mission is to help data teams solve the world\u2019s toughest problems. And our business is focused on helping companies accelerate innovation by bringing together data engineers, data scientists and analysts across the organization. Lots of people recognize us as the creators and founders of some of the best of breed open source technologies, starting with Spark, but also Delta Lake, MLflow And recently we also acquired Redash.Sylvia Simion:\nSo let\u2019s get started. Let\u2019s jump in. We have a packed agenda for the day. Our opening keynote on MLOps and ML Platforms state of the industry will be delivered by Matei Zaharia and Clemens Mewald from Databricks. Matei and Clemens will be followed by Sean Owen, who will give us a demo for end to end MLOps for Pytorch using MLflow on Databricks.Matei Zaharia:\nHi, everyone and welcome to our MLOps Virtual Event on automating machine learning at scale. So I think as everyone on this webinar is aware machine learning is transforming all major industries in many as from healthcare to logistics, to industrial internet of things. The travel companies already deploying thousands and in some cases millions of models to manage day-to-day operations. But at the same time, machine learning is very different from traditional software and developing and operating machine learning applications is complex. So let\u2019s look at a few of the ways that it\u2019s different. First of all, in terms of goals. The goal of the traditional software is usually just to meet some kind of functional specification. For example, when you press this button and you create an account for someone. And basically it\u2019s a boolean goal, either you\u2019ve met the goal or you haven\u2019t. Once you\u2019ve done it, you\u2019ve got software that works and that\u2019s it. It\u2019s going to keep working.Matei Zaharia:\nOn the other hand in machine learning, the goal is usually to optimize a metrics such as prediction accuracy. And so it\u2019s something where you\u2019re never completely done. There\u2019s always ways to make them better. And it might also change over time as the world you changes. Our second important difference is what affects the quality. In traditional software, the quality of your software depends only on the code that you\u2019ve written. So you can review that code, you can debug it and at some point you can say, okay, it\u2019s done and then the application will keep working really well.Matei Zaharia:\nIn contrast, in machine learning, by definition machine learning is programs that generalize from data sets you can give them to train them. So the quality depends heavily on the training data and this data has to change over time as the world around you changes and so the quality of your application is also going to change. In addition, as you change the data, now you might also have the change tuning parameters for your algorithms and this is an additional complexity. So it\u2019s a lot harder to say that, okay, once I\u2019ve written the code I\u2019m done with application, you have to keep training it with new data and keep tuning optimizing it in order to get the best performance.Matei Zaharia:\nAnd finally, let\u2019s look at what kind of software you use to build the applications and how you manage that. So in traditional software, usually just pick one software stack. For example, you pick a database, you pick a web server framework, you pick a UI framework and so on, and then you just build your application with those and that\u2019s it.Matei Zaharia:\nIn contrast, in machine learning, because your goal is to optimize some kind of metrics you always want to be able to experiment with new libraries, new algorithms, to do various parts of your pipeline, and maybe combine them in a new way to do the same test, because if you can improve the prediction accuracy by half a percent, quarter of a percent that makes potentially a very large impact on your business. So you need infrastructure for machine learning that makes it very easy to switch and experiment with different libraries and algorithms, unlike traditional software. So as a result of these differences operating machine learning applications is very complex and that\u2019s why it has given rise to the whole field of MLOps.Matei Zaharia:\nFirst of all there are many teams and systems involved because the application involves not just some code written by an ML engineer, but also a data pipeline that\u2019s feeding episodes, and also some work to integrate the models in an application that then monitor how it\u2019s behaving and provide feedback into improving it. So it involves at least these three different teams, sometimes maybe more that need to cooperate.Matei Zaharia:\nSecondly the application needs to constantly update its data and you need to constantly compute and recompute metrics to see how it\u2019s doing. So you need not just an application that\u2019s running by the whole set of data pipelines behind it that keep feeding it and keep retraining it and make sure that it\u2019s working at peak efficiency.Matei Zaharia:\nAnd finally, with machine learning, it\u2019s pretty hard to move from development to production environments because in development, you\u2019re experimenting with so many different libraries and approaches and you need to somehow capture it in a reproducible way and run it in production or run it in an application and make sure it\u2019s producing the same results.Matei Zaharia:\nBecause of one of these complexities what we found talking to a lot of machine learning teams in the industry that they often have to spend half of their time just maintaining the existing models that they\u2019ve put into production. And they don\u2019t have a lot of time to spend on developing new models. So it\u2019s really important to come up with an MLOps process that automates as much of this as possible so that these teams can actually innovate as well, not just spend time babysitting these models and making sure that they work at least as well today as they did yesterday.Matei Zaharia:\nSo their response to these challenges is a whole new class of software called machine learning platforms, which has software to manage the ML development and operations process all the way from data at the experimentation and into production. And quite a few companies have built internal ML platforms to date. Some examples include the largest web companies such as Google, Facebook and Uber, but many other enterprises are building as well. And there is also a lot of work in the open source community to design them, in particular Databricks, we started MLflow which is one of the most widely used open source projects in this space. And these ML platforms usually provide a range of functionality. They could include data management, experiment management, detract metrics overtime, model management, to let you share models, and also functions to make it very easy to deploy the models for inference or to reproduce one or test monitoring and application. And they do all this through a consistent interface so that your teams can adopt them and work with different models in the same way, and keep finding and keep improving the best model for a particular test.Matei Zaharia:\nThere are a lot of different components in ML platforms, but one thing I want to talk about is what are the top features that can make an ML platform succeed or fail and that really make them a lot more successful. So based on our experience working with thousands of organizations that are using ML, we found three really important features that you should think of. The first one is ease of adoption of the ML platforms by data scientists, engineers, and the users of the model. Basically everyone will be involved in that process. So you need to ask how much work does it take for them to use the platform, especially if they have existing code or existing data pipelines or existing apps that you want to adopt this platform. And also you need to ask what machine learning libraries, what deployment environments and so on are supported by it.Matei Zaharia:\nAnd most of these things will make a huge difference. If the platform is easy to adopt, then data scientists, data engineers, and so on will begin using it and you\u2019ll start getting all these benefits of the principal way to manage and operate data applications. And if it\u2019s hard to adopt that it will be an uphill battle and people might view it as too much hassle to actually begin using this. So that\u2019s one of the main things that we\u2019ve tried to optimize for, for example in MLflow.Matei Zaharia:\nThe second important factor is integration with your data infrastructure. As I said, machine learning applications all feed on data and it\u2019s very common for the machine learning team to want to go back and change a data pipeline, collect a new type of data and so on or to manage the data sets themselves, for example, to create versions so that they can have a reproducible model training and experiments.Matei Zaharia:\nSo it\u2019s really important for your MLOps infrastructure to integrate with the data infrastructure, new features, such as data motioning, monitoring, governance and API set and user interfaces that make it easy for data people and machine learning engineers to collaborate. And that\u2019s something that we spend a lot of effort on as well of course.Matei Zaharia:\nAnd the final thing that we\u2019ve found very useful is to have collaboration functions that allow teams to share code, data, features, experiments and models in a central place inside a company. And of course, to do this securely so that you can actually govern who has access to what. And this is because a lot of machine learning projects can benefit from building on previous projects. And also because there are so many different types of keys and users involved, that it\u2019s really important for people to be able to find the latest version of a model, or the latest version of data set and so on and build out on it reliably as opposed to just emailing the exact files and so on around between themselves.Matei Zaharia:\nThese lessons motivate the way that we support MLOps and the database and then also in the open source projects that our teams develop. So basically our philosophy around MLOps is twofold. First of all, we think that every organization\u2019s requirements will be slightly different because of the internals of their business, the data they have, or the expertise they have and so on and it will change over time, and as a result of that, we might have provide a very general platforms that are easy to integrate with diverse tools you might have in your company. And that allow you to change details of how you\u2019re doing machine learning over time and still have a principal way to manage it, and a principal way for teams to consume and operate the applications that you\u2019ve built using ML. And we can do this through using three pillars.Matei Zaharia:\nThe first one is the Databricks\u2019 Workspace, which is basically a unified development environment where data scientists, ML engineers, data engineers, analysts can all collaborate to work the same data and the same code so that helps me keep together. And then two open source projects, Delta Lake is a data management layer doc of cloud storage, which is Amazon S3 that provides transactions versioning, and a whole bunch of rich management features to let you easily work with these large data sets on the team. And the MLflow is an open source machine learning platform that you can integrate with many popular programming languages, libraries, deployment tools and so on to do a lot of the functions I talked about such as experiment management, monitoring, sharing model centrally and so on.Matei Zaharia:\nSo in this webinar, we\u2019re going to talk about the requirements for MLOps and some of these technologies in more detail. We\u2019re going to talk about how we and other organizations are performing MLOps at scale. We\u2019ll have some demos to show this as well as experience from two of our large ML customers, about what they\u2019ve learned in the process. And finally we\u2019ll have a live Q&A with the presenters at the end. I hope you enjoy the webinar.Clemens Mewald:\nAll right. Thank you, Matei for that overview. And I\u2019ll walk you through how we at Databricks address some of these problems. So Databricks provides a lot of different capabilities, but in this talk, I\u2019d like to take a view on Databricks from the perspective of an ML platform. So during this talk, I\u2019m going to go through each one of these boxes and describe how Databricks addresses a lot of these challenges. And we\u2019ll start with the data science workspace. The data science workspace is really the environment where data engineers, data scientists, ML engineers and data analysts can come together and collaborate on the world\u2019s toughest problems. The core user surface within the data science workspace using notebooks. And Databricks has quite a unique notebook offering.Clemens Mewald:\nFirst and foremost, it actually has multi language support. What that means is that each notebook has a default language. You can see this is a Python notebook. That means every quarter in that notebook, It will be by default interpreted as Python, but then each individual cell can actually declare its own language. So you can read Scala, SQL, Python or R all within the same notebook. And that doesn\u2019t only give you a lot of flexibility, but it also facilitates collaboration. So a data engineer could use Scala in the same notebook and the data scientists could use Python. And then these notebooks also have cloud native collaborative features that you\u2019re used from other products, such as commenting within a notebook. And also when you share a notebook, we have a feature called Co-Presence where you have a Co-Presence indicator which shows you that someone else\u2019s in the same notebook. And then if the person has edit rights, you can see their cursor and their edits in real time. So you can really in real time collaborate on the same notebook and on the same code.Clemens Mewald:\nNow, notebooks are great for exploration, and experimentation but we also want to make sure that we facilitate putting them into production. So we\u2019ve introduced a new feature called Git-based projects that allow you to [inaudible 00:17:58] data into Databricks and then check in your notebooks, into your favorite Git provider of choice, go through the code review process, run some tests, run any CSV automation that you can think of, and then bring them back into Databricks to run production jobs. So this really combines the flexibility of notebooks with the rigor of a CSV and software deployment systems.Clemens Mewald:\nNow, once you have two data science workspace in place, the next thing you really care about is making sure that you have access to all of your data. So Databricks provides a very unique product called Delta Lake, which is also an open source product, but also integrated into the platform. Delta Lake provides a transaction layer on top of your Delta Lake so your data stays within your data Lake of choice and Delta Lake provides you additional benefits on top of them.Clemens Mewald:\nFirst and foremost, you can ingest any format of data at any scale from any source. So it doesn\u2019t matter if it\u2019s a CSV file or like pre-K files or a CSV file, you can ingest all of them and use the Delta Lake format. And Delta Lake provides asset transactions to actually guarantee data validity. So any ingestion and any change that you do on your Delta tables, actually creates a new transaction and that also facilitates a feature would be called time travel. So every time a transaction happens, we increment the version, number into write head log. And then you can always go back in time, hence the name, and look at your data at a specific version, because we just disregard the transaction that happened after that version, which is a very unique feature and actually facilitates reproducibility. And to integrate this with MLflow we actually created an automated logging of what data you used and the version information. And I\u2019ll show you that in more detail on a later slide.Clemens Mewald:\nSo at Databricks we really want to focus on training the machine learning models. So the machine learning runtime provides a DevOps-free that environment that\u2019s pre-configured and optimized for machine running. And we provide it in a few different flavors on the screenshot. You see, I pick the GPU runtime, which has all of the drivers and configuration set for you, so you can just get going. And when you choose that, you just have to pick a [inaudible 00:20:24] type on the cloud of your choice. And then you can go ahead and train your GPU models.Clemens Mewald:\nNow, what do we package up in these runtimes? Well, we package up the most popular ML libraries. That is anything from TensorFlow, the Keras, Pytorch, Scikit-learn and of course MLflow. It is pre-configured and pre-installed in the machine learning during runtime. We release machine learning runtime regularly to make sure that all of these are up to date. And we test rigorously to make sure that all of this actually work well together. And you don\u2019t have to worry about setting up these environments yourself. We also include libraries to more easily distribute your machine learning, deep learning libraries. And I have a slide on this right after this one. And then of course, we also built in libraries for hyper parameter tuning and autoML that I\u2019ll get back to in a slide or two as well.Clemens Mewald:\nSo for our distributed training, we actually built in support into the machine learning during runtime to distribute Keras, TensorFlow and PyTorch models. Of course, you can always train them and evaluate model that\u2019s distributed on Spark, but Horovod run a specific user library that helps you distribute Keras, TensorFlow and PyTorch models. And then we also introduced support for the TensorFlow native distribution strategy, which was introduced in TensorFlow 2.0.Clemens Mewald:\nAnd then for hyper parameter tuning, we integrate a library called Hyperopt that has a pretty simple interface. We just configured a search space, and then you call this function admin, and then we\u2019ve also extended it with this API called SparkTrials. So if you use Hyperopt just the open source library, it will run all these trials in sequence. But with SparkTrials, we actually use a cluster to parallelize the trials and here you can see around six trials in parallel for a total of 96 trials. And again, this doesn\u2019t need to be a Spark model, so you can train a Scikit-learn model in instruction that you pass it. And then we basically just take the Scikit-learn model and train six different versions of the model with different hyper parameters at the same time. And you\u2019ll see in a later slide as well, but this integrates with MLflow automatically. So you get all of the tracking of your hyper parameters training run in MLflow for free.Clemens Mewald:\nSo now that your model is trained what are the deployment options? And MLflow really provides a really flexible and rich set of deployment options out of the box. So on this slide, what you can see here is just a schematic of some of the supported ML frameworks, how it is being logged as a MLflow model, in the MLflow tracking server, and then the deployment being managed by the MLflow registry. And then really you have a lot of different options of deploying these models, whether it be a docker container, a Spark UDF as a rest end point or using some of the open source libraries. And let me double click on one of these options to highlight an important part about model deployment with MLflow.Clemens Mewald:\nSo this is the core method you would use to deploy a ML model that is logged as a MLflow model as a spark UDF. So as you can see here, you just load it and here you\u2019d be referencing the model that\u2019s in the model registry by name and production stage, and then you just apply it to a data frame. This works for a Spark MLLib model. Now let\u2019s see what this looks like for Scikit-learn. This is the line of code that you would use for a Scikit-learn model and this is the line of code that you would use for a TensorFlow model. So just for dramatic effects, let me go back, Spark MLLib, Scikit-learn, TensorFlow. So I think you\u2019re noticed, yes, they\u2019re all the same. And that\u2019s one of the benefits of the MLflow format is that it has this abstraction called Pyfunc, which exposes any ML model as pyfunc function.Clemens Mewald:\nSo all of the deployment options look the same. So it doesn\u2019t matter whether the model was trained in Spark MLLib, Scikit-learn, TensorFlow, it works the same. And the same statement is true for all of the deployment option. So building a Docker container for an MLflow model, same thing, no matter what a MLflow framework that we used. So this is really convenient, especially because I haven\u2019t seen a single enterprise that use only one type of framework.Clemens Mewald:\nSo now that we discussed the full entire flow, let\u2019s actually look at the foundation of all of this that\u2019s provided by MLflow and to give you end to end MLOps and governance capabilities. So in MLflow we\u2019ve introduced this capability that we call auto logging. So we automatically track as much information as we can about your work and that stacked with something I\u2019ve alluded to earlier, which is tracking of the data source and the versioning. So if you use a data table-Clemens Mewald:\nBacking of the data source and the versioning. So if you use a data table, we keep track of the table itself that you used and the version number as described earlier. So with this, you can actually go back after the fact and say, I want to take a look at the data that I used for training at the exact version that I was using to back then. And this information is logged in automatically. By the way, we do hook into the Spark data source API. So this works for any Spark data source if you read a CSV file, it works as well. However, of course, if you read a CSV file, we don\u2019t have to versioning and it\u2019s time travel feature. Now we also started capturing the schema for these models.Clemens Mewald:\nSo you can see an example of where we have to input schema and then the type of the prediction column for the model and that helps us in a lot of different ways. One of them is in model deployment. We can actually check if a schema is compatible with the deployment time of the model. This just shows the basic like auto tracking for all of the Mlflow frameworks. So for all of these Mlflow frameworks, if you trained a model and use auto logging in MLflow, you get all of the parameters, the metrics on a percent basis, and all of the artifacts that we can track automatically logged for you. And as you can see, this works for all of the popular Mlflow frameworks.Clemens Mewald:\nThis is again what I showed earlier, the automatic logging for hyperparameter tuning search, and then we can visualize it in what\u2019s called a parallel coordinates plot. And the way to read this is each one of these lines monitors trials. And they are color coded by the optimization metric, which is the loss. So you can see all of the blue lines have a loss, and then you can visually see which values of each parameter actually leads to a high quality model. And again, this is automatically logged if you do have parameter tuning on Databricks using the machine learning one time.Clemens Mewald:\nWe\u2019ve also started implementing automated tracking of model interpretability. So using a very popular library called SHAP on the hood, we calculate feature importance for the model on the way you trained it. And then if you do something like train an image model, we can actually visualize the future importance based on which areas in the image contribute to prediction. So this is really powerful and it gives you an insight into how your models behave at training time.Clemens Mewald:\nAnd then of course, in addition to all of the male specific features, we also keep track of the code itself. In the snap version of the code when you train it, the classic configuration of the computer that you used when you ran the model and also the environment configuration terms of what libraries that you use.Clemens Mewald:\nOnce a model is ready for deployment, I mentioned earlier, you can use the model registry in Databricks. So this is a screenshot of the model, of the managed model of registered in Databricks, where you can find models, their versions, and which of these versions in which deployment stages. And we actually have excess controls implemented on a per stage level that actually facilitate the handoff between different stages, which we\u2019ll see in the next slide.Clemens Mewald:\nSo you can see we have governance in terms of requesting conditions to specific stages for models. And if someone doesn\u2019t have access controls to actually make the transitions, they only see the options for the request. And then we of course keep an audit log of everything that has happened to model. And we just recently implemented comments here as well, where you can basically comment and collaborate with your colleagues on managing the deployment process of these models.Clemens Mewald:\nThis screenshot is from the certain product and Databricks. This is the simplest way you can deploy a Mlflow model as a rest end point. You click a button that says enable serving, and we bring up a cluster and expose the model as a rest end point and it also automatically knows all of their versions and deployment stages. So if you call the model name slash production end point you will always get that your request will always be routed to the version that\u2019s going to be marked production. And this is just a screenshot of an output that\u2019s actually using Spark streaming for real-time model monitoring. So this is actually computing a streaming AMSE to tell you the quality of the model as new predictions and labels come in.Clemens Mewald:\nSo as you may be able to guess, as we walked through all of this information that we\u2019re keeping track of, we\u2019re basically checking off all of their comments in this reproducibility checklist. So we have the code that you used the data that you used, the cluster configuration, environment specification that you used. So if you actually implemented a reproducibility feature that allows you for around after the fact we produce the code that you used, if you used the data table and we know the data version that you used, we can recreate the cluster for you or with the exact configuration. And we can also recreate the exact environment and library configuration that you have in your end which is quite unique, and which is enabled by the fact that they actually track all of this information end to end from data to model deployment. And that\u2019s a quick overview of Databricks as an ML platform. And with this, I\u2019m going to hand it off to Sean and we\u2019ll give you a demo of the actual product.Sean Owen:\nWell, hello everyone. This is Sean Owen. I\u2019m a principal solutions architect here at Databricks, and I\u2019m here today to show you a few new features of MLflow in Databricks. These are things like Webhooks and serving from the registry and new auto logging features for Pytorch and SHAP. But along the way, I also want to show you how to use some interesting ways I think in which you can apply these tools like Pytorch and SHAP and even Delta Lake to solve this problem. And the problem here to be specific is classifying images, chest x-rays. And these are provided by the national Institute of health and this data set actually became part of the competition on Kaggle. So along with the images, we have labels, they\u2019re one or more of 14 different diagnoses that indicate what is maybe shown in the x-ray, what might be wrong with the chest in those cases. And the task here will be to learn, to label these images and maybe explain why they\u2019re labeled that way. And of course, along the way, we\u2019ll use MLflow to help us.Sean Owen:\nSo word of caution, I\u2019m not a doctor, you\u2019re probably not a doctor either and the model we\u2019re going to build here is a simple one. It\u2019s probably not good enough for clinical use. It\u2019s not necessarily accurate enough. So please don\u2019t diagnose from this. Don\u2019t try this at home, but I hope that it shows that this kind of learning and explanation is quite possible. So as in all things, we begin with the data, and I\u2019m not going to spend too much time on the data here, but I do want to show you how a technology like Delta Lake can help process so-called unstructured data like images here. So Delta as you may know, underpins the Lakehouse architecture and Databricks, which means that you can do a data warehouse like operations at scale, but you can also analyze non tip tabular data like images in the same place and Delta can help with both.Sean Owen:\nSo we\u2019re going to start by reading the images with Spark and Spark can easily read a directory full of images, and we get nice thumbnails here in line when we load these here in Databricks. However, we might not want to just read the images with Spark, but go ahead and ETL then into a Delta table. So why? Well, a Delta is transactional for one. So that means we don\u2019t have to worry about who\u2019s writing to the table of images as we\u2019re reading it. It also offers time travel. This lets us maybe go back and query the state of this image data set at a previous point in time. Maybe when we built that model three weeks ago, we can go query that table as of that time.Sean Owen:\nBut maybe more than that, deep learning often involves some degree of pre processing. We have to normalize images, size, and depth and channels, and maybe we want to do that just once, rather than over and over as we make passes through the data to build a model. And also in the cloud, it can be kind of slow to read a bunch of small files over and over keep listing those storage buckets. So maybe there\u2019s a speed advantage to ETLing once into a table and reading those blobs from a nice compressed efficient data store like Delta, if we have to read them over and over.Sean Owen:\nSo to that end, we\u2019re going to start with a little bit of that. We\u2019ll agree the images, but also quickly ETL them into blobs and we\u2019ll need to also load the metadata associated with these images, the labels, and parse them a little bit to get the various labels for each of the images, and then simply join them. Having joined the image data and the labels, we can simply write this out as a Delta table and register it in the Meta store. And we should be able to see that example here if we want. Okay, we\u2019re good. We\u2019ve got images, columns, and about 14 different possible diagnoses. Back to the notebook.Sean Owen:\nSo now let\u2019s look a little bit at the modeling issue. And in this example, we are going to eventually use MLflow because I want to show you how MLflow integrates with Pytorch. Actually MLflow integrates with something called Pytorch Lightning. So for the Pytorch users out there you\u2019ll know that using Pytorch often means writing a fair bit of boilerplate code to describe the training loop and run it manually. Pytorch Lightning abstracts some of that away. So you don\u2019t have to write some of the boilerplate you can just write there the key pieces here. So we\u2019ll get to that in a minute.Sean Owen:\nSo about to start here, we\u2019re just going to read this table of images. And since it\u2019s not that big, it\u2019s about 2.2 gigabytes. We\u2019re going to pull it down to a pandas.DataFrame here and do a simple train test split before we start training. Now, I\u2019ll say that you could adapt the same approach to much larger data sets. You could distribute the training on top of Spark with Pytorch and a tool called Horovod. But for simplicity, we\u2019re not doing that here. We\u2019re just going to train this relatively small dataset on one machine.Sean Owen:\nWe\u2019re going to define a few helper functions here. Torchvision is a companion package to Pytorch that lets you define some additional transformations that are required for the input. For example, here we need to convert the channel ordering of the images a little bit and normalize them in a way that\u2019s correct for the pre-trained layer we\u2019re going to apply to the model. So a little bit of a detail, but Torchvision helps will help us here. And again Pytorch users will know to access data you typically define a dataset class that defines how big the data set is and how you get individual elements. And that\u2019s here where we use these transformers and so on that we defined to say how it is we get from the relatively raw data in the Delta table to something that\u2019s ready for this particular model in Pytorch. It\u2019s a really, just a matter of reading the image, transforming it and returning the transformed version.Sean Owen:\nNow, before we get into the Pytorch modeling, we are going to enable this new feature of the MLflow. The MFflow is already supported auto logging for a number of popular packages like Scikit-learn, Keras and TensorFlow, and now it supports Pytorch. So by enabling auto logging for Pytorch, we don\u2019t really even have to write MLflow code in order to get some of that benefit in order to get to log what we\u2019re doing as we train a Pytorch model.Sean Owen:\nSo let\u2019s actually build the model. Now here\u2019s where we\u2019re going to use Pytorch lightning and I hope this is maybe interesting for Pytorch users that haven\u2019t seen it. As with Pytorch, we need to define a module that defines the network we are going to train and defines how we train it. But rather than write the training loop directly, we really just fill in some blanks here. For example, we have to define how that, what the network looks like and here it\u2019s really mostly dense net one 21. So we load this pre-trained model. So this is transfer learning, and we\u2019re not going to try and retrain that and add a little bit of dropout on top and add a fully connected dense layer on top of that in order to ultimately build a classifier that\u2019s going to predict from these images one or more of these 14 possible diagnoses.Sean Owen:\nSo pretty straightforward stuff for Pytorch users. And nice thing is having to find all the key parts. What a fore pass looks through the data, what the optimizer is, how to validate, how to train. We simply let Pytorch lightning, do the work down here. It can do some nice things for example, auto tune, our batch size auto tune, our learning rate, handle early stopping and things like that. So it\u2019s a nice framework and Pytorch lightning because it has all these hooks is something that MLflow can hook into to automatically log.Sean Owen:\nSo I\u2019m not going to run this in real time here since the model training does take about 17 or 18 minutes on a GPU. But if you did run this, you would find that magically with no MLflow code in there, you would get models logged if you ran the cell to MLflow and in Databricks MLflow is integrated into this experiment sidebar you see here. And if we were to pop that out, you\u2019d see this model is the one we get from Pytorch auto logging. And it has a fairly rich set of information who ran the model? I did. When, how long did it take, what was the exact revision of the notebook and the code that made that model? And of course, all the key parameters that were defined for the Pytorch model key metrics, which epic was best, what was the final validation loss? And of course we get the model and we get the last checkpoint. We get a summary of the network architecture, pretty useful information, even some helpful hints about how we might go load this model later from MLflow.Sean Owen:\nNow I\u2019d also like to show you\u2026 Well, first I should say that the model, I\u2019m not going to show you too much about its accuracy, but rest assured it actually achieves accuracy that\u2019s pretty comparable to the results you might see in the paper that introduced this dataset. So the pre-train layer and modern tools we can do okay. Out of the box. I\u2019m sure you could do better though with some, some more time a GPU time and ingenuity.Sean Owen:\nNow, the next thing is interesting. I\u2019d like to show you the serving models with MLflow. One key thing MLflow does is hand you back your model in a maybe a more useful form. Sometimes that could be a spark UTF, a function you can then apply with Spark to a bunch of data, but it can also create out of a model, a microservice, a REST API. And you\u2019ve always been able to deploy that to services like Azure ML or Amazon SageMaker. But as of recently, recent versions of MLflow, you can actually serve the model out of the model registry in something like Databricks. And that\u2019s what I\u2019m going to show you here. So this is actually my registered model for this notebook. And I\u2019m currently working on version three here and if I like I can enable serving for this registered model and suddenly I have an end point available even within Databricks that I can send images to you to get their classification.Sean Owen:\nBut I want to say a little more about that. So what these REST API is do is expose a service that can accept JSON formatted descriptions of input and return classifications as output. The only problem is the input here is really an image. It\u2019s a Tensor and there\u2019s not a great way to describe that in JSON, at least not in the form that can be automatically translated into JSON by MLflow. So to make this work, we\u2019re going to have to customize a little bit. And this I think illustrates in some ways the power of MLflow, that if you need to you can change how it works under the hood. So we\u2019re going to define a custom MLflow model that will wrap our Pytorch model and enable us to accept the image as a base 64 encoded string of bytes from which will parse the image, apply transformations, apply the Pytorch model and then return the result.Sean Owen:\nSo it\u2019s really not too hard. If you need to, you can do something like this. And this now enables us to turn this into a service where we can accept images through JSON and return their classification. So having defined this class, all we need to do is load our actual Pytorch model, wrap it up in this wrapper and log that. And that\u2019s the model we\u2019re actually deploying to MLflow to the registry to serve here now in Databricks. So you may see I\u2019ve already registered it, but just for reference this, you will find that you can register models here by clicking register model and selecting the model you\u2019re interested in. But I\u2019ve already registered the one I\u2019m interested in here.Sean Owen:\nJust to prove it works, let\u2019s try it a little bit of code to load an image and send it to the rest end point. So I\u2019m going to load a single image here from storage. And again, one of the nice things about the Delta Lake House architecture is that you can deal with data as tables. You can deal with data as files and images too. That\u2019s no problem. So I load an image from my dataset. This is what it looks like. Maybe radiologists out there can make sense of that. I don\u2019t see anything interesting, but let\u2019s see what the model thinks. So to use the service, we simply need to encode it and encode a proper JSON requests, send it to the API and render the results. And we get that back here as a pandas.DataFrame.Sean Owen:\nWhat we might see here is it looks like the models thinking this might be an example of atelectasis, which is a sort of lung collapse or infiltration but probably not a hernia. So these are probabilities. And Hey, that\u2019s useful. I mean, if this were a better model and vetted by professionals, you could imagine this would be a useful assistant for maybe radiologists that are, want some heads going down about what they might be looking for. Maybe a model can help them figure out what\u2019s even likely.Sean Owen:\nBefore I go deeper on that point, I want to introduce a new and other feature of the MLflow as of recent versions and that is Webhooks. So the model registry, as you might\u2019ve seen there, part of its role is to manage the state of versions of a model. So you may have a current production version, you create a new version of the model and it\u2019s the staging candidate and you test it. And at some point you promote it to production if you test pass and you have permission.Sean Owen:\nSo these are important events, and maybe these events creating a new model, creating a new testing candidate need to trigger something like a testing job, CICT job. So that\u2019s why MFflow now supports Webhooks triggers for actions in response to these events. It\u2019s fairly easy to register them. You will have to access the REST API directly, but you can do so like so, and listen effectively for these events. Now, for the simple example, I\u2019m just going to set up a Webhook that triggers a message to a Slack channel just for a simple demo purposes but you can imagine doing much more than that, triggering a lambda, triggering a CICT job. So I\u2019ve registered this Webhook to trigger a ping my Slack channel, whenever something happens to this registered model and we should see if this works. That\u2019s if I for example, go into a model and comment on it. I should find that it registers a new message in our Slack channel. There it is. Okay. Pretty good.Sean Owen:\nOkay. Now I want to get into another new feature here and that is Model Explanations. Sometimes we want to know why the model is doing what it\u2019s doing. And there\u2019s a popular open source tool called SHAP that can do that for you. It can actually explain at the individual prediction level, what about the input caused the model to make the prediction it does. Using SHAP isn\u2019t that hard, but in MFflow one 12, it can actually be done pretty automatically. With a line or two of code, you can get MLflow to create the model explanations for you and even log plots like the one here. This is a really a summary plot that says overall what the important features of the model are. A long side the as you may see here are the actual SHAP values, the model explanations, so that\u2019s available. You can do that to any model. For this particular model though, I want to take the opportunity to show you something else you can do with SHAP, not through auto logging, but through a little more manual usage of SHAP that may be more interesting for this dataset.Sean Owen:\nSo it turns out that SHAP can explain image classifications in an interesting way. With a little bit of code, you can try to overlay an image with a heat map showing what about the image caused the model to classify the way it did? So in this case, I actually load an image in for my data set that\u2019s definitely classified as infiltration, and I create an explainer from SHAP that can explain this model and ask it to explain. What\u2019s actually explaining the about one of the middle layers of resonant. Actually excuse me, of dense net. And this is what you get out of it. So you can see perhaps in these x-ray there\u2019s a dark spot here on the left shoulder and a dark spot here near the bottom of the right lung. And for whatever reason, the model thinks those are particularly important in its classification. And its classification is here. Okay, good. 92% chance it\u2019s infiltration, maybe edema, maybe atelectasis.Sean Owen:\nSo I think this expands on the idea that these models can be not just predict black box predictors, but explainers too. And maybe if we did build a better model, this sort of thing could make it even more useful for professionals who are looking for hence, maybe you\u2019re looking for where to look overall. Maybe the models can more easily see something that isn\u2019t immediately obvious to the human eye. And these predictions, these explanations could be created in parallel with Spark, written to the Delta tables, they could be also even logged. Some of them were within MLflow, so this all comes full circle.Sean Owen:\nThe last thing I want to show you is a new feature in Databricks called Projects. So those of you that know Databricks know that you work in the workspace and we typically work with individual notebooks, but oftentimes we really want to work with groups of notebooks because we need to version them together. And while you\u2019ve always been able to get a revision history of individual notebooks until Projects had come along, you really couldn\u2019t version and commit changes to groups of notebooks at once. And that\u2019s why that\u2019s why Projects exists.Sean Owen:\nSo it doesn\u2019t change how you work with things. I\u2019m actually working in a notebook that\u2019s inside a Project, not just a floating notebook in the workspace. But what this basically means is there\u2019s deeper get integration here. For one, I can take a look at the get branch, sorry the get repo that this notebook and these several notebooks are backed by and I can edit and commit multiple notebooks at once setting a commit message if I like. And so this makes it maybe more natural for people that are used to versioning larger projects, consisting of multiple notebooks to work with these backed by a get repo and not simply built in version control. And we hope to expand this feature over time to let you version alongside notebooks, things like maybe small configuration files or small data files as well, because sometimes that\u2019s just the more natural thing to do.Sean Owen:\nSo I hope you\u2019ve heard and seen some new features here of MLflow, Webhooks integration with Pytorch and SHAP for auto logging. Some ways in which Delta can be useful for particular machine learning problems, serving models with the registry and how that might work with an image classifier. And finally, a quick note on Projects and what they might mean for your workflow.Sylvia Simion:\nThank you, Matei, Clemens and Sean. A quick reminder, if you want to try some of the things you saw in the previous stock and demo go to databricks.com\/trial, where these tools are available. You can also continue to submit your questions via the Q&A panel as we carry on with the presentation.Sylvia Simion:\nSo now let\u2019s hear directly from our customers about how they are handling the growing importance of machine learning in their products and systems. And more importantly, how do they manage their ML initiatives related assets and the entire life cycle within the organizations?Sylvia Simion:\nOur next speaker is Keven Wang from H&M. Keven will give an overview of H&M reference architecture and eminent stack designed to address a few common challenges in AI and machine learning products like development efficiency, and to interoperability, speed to production, et cetera. Keven would also give a demo of the production workflow. Please welcome Keven.Keven Wang:\nHello everyone. My name is Keven. I work as company-Keven Wang:\nHello everyone. My name is Keven. I work as competence lead in atrium group. And today, I\u2019m going to talk about MLOps how we apply it in large scale. I work in an organization called AI foundation, atrium group. In AI Foundation, we work on a number of different use cases for different business problems from design buying to logistic, sales management, and also how we engage we are with our customer. Pretty much covering entire atrium value chain. Each of these use case is driven by a multidiscipline agile product team. They developing and deploying the product end to end. When developing this different machine learning products they are a number of common challenges, for example, how to automate as a machine learning training pipeline in your large scale, if we talk about in the only single model, but could it be solved in hundreds of our southern models and how to provide the reproducibility of your machine model?Keven Wang:\nLet\u2019s say half year back you want to be able to take the same code and same data, retrain the exact same model, how your model approval process looks like so you can bring up the new model into production with enough competent confidence. We try to address these different challenges holistically by leveraging our reference architecture or plotting. Even if they are solving different business problems, they share a common process. For example, for model training, it\u2019s about taking data, apply some transformation, training the model, and in the end take the model into model repository. For model deployment, it\u2019s about also taking the data, apply exact same transformation, make a prediction, and then save the results, deliver to the end-user. In the middle, you have some common key concern. For example, how to speed up into and feedback loop, how to monitor your model performance, your data drifting, and also your infrastructure.Keven Wang:\nAlso, how to do version control of not only your model but even your data so you can manage them the same as in a software artifact. Based on this, we came up with a number of technical component, for example, model training, model management, and also model deployment. It\u2019s important to have some of those obstruction here so we can pick up different tool for each of them and evolve them independently because machine learning is emerging area. They\u2019re new tool coming out every day, every week, and every month. We want to leverage best to simplify our work.Keven Wang:\nAfter a year of exploration and also truant, we converged to a number of tools. For example, for the model training, we have three stack for the newly started the use case. We tend to leverage the data break century architecture. Then for the more mature use case, we are scaling, and also automation is key. We tend to use either airflow or Kubeflow as main machine learning orchestrator. For the model management, the same as many other company, we love MLflow as in for the model deployment, specifically online models. Sorry, we love Kubernetes as well. And also, open-source tool like Seldom bringing lots of machine make specific features.Keven Wang:\nBesides this, system observability is quite important. We love Azure stack. So we tend to use a default tool like Azure Monitor and Power BI for most cases, and also for Kubernetes space application, Grafana and Premises is a great choice. Machine learning product is [inaudible 00:53:33] software product so we can leverage the best practice like continuous integration and continuous delivery to automate the learning process. Also, in the end, looking at these complex stack, we can\u2019t do it to results a proper infrastructure automation.Keven Wang:\nLet\u2019s talk about the model training. For newly started use case we love interactive model development or notebook. However, notebook is not a very scalable way to do product development where your codebase grow, and also your team\u2019s size grow. You tend to acumen lots of technical debt if doing notebook-only development. We have all processed now, basically extract the complex logic in the notebook, putting them into separate isolate models where we can develop locally and then using continuous integration to put all the task together and train on database.Keven Wang:\nLet\u2019s take a look how exactly it works. This is a present project where I will download some data from internet and trim random forced model and then save the model into MLflow. Let\u2019s take a look at this project structure. This SFC folder, I have a number of python models and capture all differently using functions. For example, the config management evaluation method which can explain a number of plotting and evaluation methods. Prepare data method, which included a model, which included a number of [inaudible 00:55:11] with clever data.Keven Wang:\nIn the test folder, I have my py test cases to evaluate these python models. In the notebook folder, I have my notebook, which you get a number of top py file. And also, you can see here even it\u2019s notebook, I can leverage ID to evaluate the syntax here.Keven Wang:\nNow let\u2019s say we have done all the local development, like the coding and also py test, and we want to upload this notebook to Databricks and write.Keven Wang:\nSo I will call this script. What this script does is just package all my passing models as backfile and upload to databricks and then also upload my notebook into databricks as well. Now it\u2019s done, let\u2019s take a look. This is my databriks workspace. Here my notebook has been placed into a specific folder structure. This one is my project name and my branch name, my user ID, and my notebook. So in the first say of this notebook, it\u2019ll try to install this egg file, just uploaded by this script. An egg file is placed also in a specific structure respect to the branch I\u2019m working on and also my user ID, so I will not override my colleague\u2019s work.Keven Wang:\nLet\u2019s run this notebook now. And here to initialize as a random seed as well. Now, prepare training dataset is just one method to call. Afterwards let\u2019s start with training the model. Here let\u2019s say I want to change from 100 to 150 I choose instead for this random forest model. And business training model, it would also use MLflow to keep track of important parameter and also other metrics. That\u2019s right.Keven Wang:\nOkay. We have see some key error metrics, and in the end, it will also evaluate the model and the plot, some nice chart. Looks like nice chart. Let\u2019s say we are happy with this model, with the parameter change. Now we want to commit to the code. So go back to ID. Here I will apply same change from 100 to 150, and then I would just push my code.Keven Wang:\nNow my code pushed. Let\u2019s take a look at CI pipeline. So this is my CI pipeline, my model there, and new pipeline row has been triggered. Let\u2019s take a detail look. This pipeline has including two jobs. In the first job, it will do the study called the quality check. Basically, it will run all the py linked test also unit test, publish test results and also publish test coverage report. Meanwhile, we also package my notebook and upload my notebook together with egg file into databricks and run notebook on databricks. It will monitor the notebook run until the finished.Keven Wang:\nNow it\u2019s done. Let\u2019s take a look. So this is the result on notebook run. Let\u2019s see all the print. And also, it\u2019s MLflow model registry. We should see a new model. Okay, version 12. This is a new model we just trained and in the stage is still none.Keven Wang:\nOkay. Is the first demo we can see that as a local dynamic can be nicely integrated with the notebook development with Databricks. And also, by leveraging continuous integration, we can automate the process and therefore provide a good way to keep track of model metadata and manage the model the same way as LS software artifact. Besides newly startup product teams. We also have a number of product team which are more mature and as their key concern is automation and also scalability because you need to train many model. Instead of training single model, these product team tend to train specific model for specific geographic area like countries, specific type of product, like a men\u2019s t-shirt, and also specific time period.Keven Wang:\nThen each of these is a scenario thinking about our size. We have easily can have sets on different scenarios. That is some of the models they need to train every day. For this type of use cases we tend to leverage Airflow or Kubeflow based architecture on top of Kubernetes that we can scale things up cluster up and down, and also leverage external computation power like databricks clusters, and also run local computation inside a docker container in the same cluster.Keven Wang:\nLet\u2019s move on talk about a model management, also model serving. In high level, you can divide the entire life cycle into five stages, model development, backtest, model approval, deploy to staging and then deploy into production event. We have discussed the how to do model development automatically and the result where we generate a new model in MLflow. Backtest is about to take the model deploy into dev environment, run all the backtest and afterwards in the model approval someone in your team can approve their model. It will unpack model version into dev into stage, and also deploy this new model into staging environment. Afterwards you can some system test, then again someone can improve your model. Bump up the version from stage to prod in MLflow and also and then deploy your model into production.Keven Wang:\nLet\u2019s take a look how it works in your second demo. But before we start the demo, I also want to say few words about the Seldon or Seldon Core. Seldon Core is open source library build on top of Kubernetes. It\u2019s bringing in part of the features for machine learning specific task. For example, it enable you to easily package up model as microservice. You can expose it either as gRPC or Rest API. Also, Seldon introduce some core concept called [infrasca 01:02:25]. Think about your model prediction is more than just single step, including outlier detection, feature transformation. Also, maybe you want to send your a model to our altar, which was select one of your model. Most relevant towards this specific request and then make a prediction.Keven Wang:\nEach of these step can be run in a single pod or container, and you can skin and use it independently. Now back to MLflow, we can see that version 11 of this model. My model, version 11, is in production right now. And let\u2019s say we are happy with version 12 and want to each deploy it into production. So we go back open another kit repository, my model serve, here I have a metadata file. My model info Yami, here I specify where my databricks workspace is, which is where my MLflow instances is, and also the name of my data model. And now I want to change version from 11 to 12.Keven Wang:\nSo to deploy it, I just do need to do a simple kit push. Now it\u2019s done. It automatically triggers a model deployment to pipeline. But before we look into pipeline, let\u2019s take a look at is a Rest API.Keven Wang:\nThis is a Postman. I often use it to run some rest call. So here is endpoint of my model in the dev environment, I can make a call. Then I can receive some response from my model. Looks good. And also, Seldon come up with this model metadata API, which should inquiry to get metadata information of your model. So here you can see that the name of model is my model, and the version 11 it\u2019s created yesterday. And also, here you can see some input schema, And also here you can see the output as well.Keven Wang:\nSo after the model deployment, we should have seen this model version bump up to trial. Let\u2019s go back and go to the CI pipeline. So this is another continuous integration pipeline for the model deployment. After I get the push, the pipeline gets triggered, and this one including four stages. In the first stage, it will pick up the model from a model, from MLflow model registry based on the version we give, and also it will be the doc image then pushed it in to the container registry.Keven Wang:\nAfterwards it will deploy its model into dev environment then it\u2019s ready for testing. So here I\u2019m using open-source tool like Helm to term utilize my deployment. So to deploy it in dev stage and production line, I can use the same setup script. Now it\u2019s get deployed in the dev environment. Afterwards it also be deployed into stage if I approve it and then eventually go to production, also require human approval. Now let\u2019s go back to Postman make another rest call to see if it\u2019s ready. I should the implants rolling upgrade, but now it\u2019s not yet. That\u2019s why there was some downtime. Okay, now it\u2019s up because you get the answer, and let\u2019s check the metadata. So now it\u2019s version 12. Looks good. And let\u2019s say we have done some tests in dev environment and decide to approve it to the production environment.Keven Wang:\nReview. Approve. Now it\u2019s deploying to a staging environment. Let\u2019s say in the stage environment. We want to run some system test, to push a load to see if the system perform as good as possible. I\u2019m going to use this tool called a Jmeter. In Jmeter, I can simulate up to 100 clients, send the request and return a slip. And this one client where I be ramped up in two minutes. Each of these clients will send the same rest to call through my model prediction service. Is the same, and then it will evaluate the result here. I also deploy some cool feature like auto-scaling in this model. This is my set under current file. Here I specify my [infants scrub 01:08:40] in this caseI only have a single container with a single microservice. And also I specify as a horizontal Potter scaling policy, basically it will monitor my CPU usage. If it\u2019s about 40% is just start to create more replica of my model prediction service up to 500 instances. Let\u2019s watch how many instances there are today.Keven Wang:\nSo now we have two replica. Let\u2019s start the performance test. Now we started, we can see that in beginning latency is pretty good, 50, 60, 70 milliseconds but start to ramp up whereas number of clients start to grow. I also added some cool feature like timeout. Basically, we don\u2019t want client and\u2026 We don\u2019t want our end user wait forever. So in case, the model cannot make prediction within a second it\u2019ll just return the HB 500. Then we can input some default the logic in the client side to show some default results, for example. Also, here, we can see that a new replica has been added because there\u2019s a lot to start to increase. Well, instance has been added. Also, we can see that after exceeds run some milliseconds, we start to see some red flags and some arrows returned from model. Also, now we can see there are more replica has been added. I will not wait until it finish. Let\u2019s assume we are happy with this result.Keven Wang:\nNow final step. I\u2019m going back to our DevOps and approve this model and deploy it into production. In the second demo, we have seen that by leveraging tools like Azure DevOps, we can easily automate the model deployment process. Whereas to involve human is a loop and too like Seldon really make is a model exposed to the predict service pretty easy.Keven Wang:\nFinal takeaway and MLOps is very complex. Before start looking to the technical stack, it\u2019s important to take one step back, thinking about what kind of problem you are trying to solve. How your design process looks like, and then define your architecture, ends up with your tools. Secondly, if you have a number of product team all working on the machine learning product in production, maybe it\u2019s time to think about the platform approach. Have a central team developing some key component and offer it as a service for your pro teams. Last but not least, by leveraging cloud service, you can use it. You can really evolve very fast. Thank you very much. Thank you very much.Speaker 3:\nThanks, Keven. Our next speakers are Wesly Clark from J.B. Hunt and Cara Phillips from Artis consulting. They will cover how they\u2019ve implemented a framework for self-service experimentation and deployment at other price scale at J.B. Hunt. This doc will cover the core values, concepts, and conventions of the framework, followed by a technical demo of how to implement the self-service automation of databricks resources, code, and jobs deployment into Azure DevOps, CI\/CD pipelines. Please welcome Wesley and Cara.Wesly Clark:\nThank you for joining us. We appreciate your time, and I hope you\u2019ll find our work interesting, informative and that will help you in establishing your own automated CI\/CD pipelines. My name is Wesly Clark, and I\u2019m the chief architect of enterprise analytics and AI at J.B. Hunt. And my colleague, Cara Phillips from Artis Consulting, is here with me to present a technical demo. J.B. Hunt was founded in 1961 and has grown to become one of the largest transportation and logistics companies in North America. We\u2019re currently number 346 on the fortune 500, and our digital brokerage marketplace, J.B. Hunt 360, has received widespread recognition for innovation and technology. We consider machine learning in advanced analytics as key to our future success, and I\u2019m honored to be involved in establishing these disciplines at J.B. Hunt. Artis Consulting was founded in 2002, and they focus on four pillars, data and analytics, AI and machine learning, the internet of things, and intelligent applications. They\u2019ve been a key partner in helping turn our vision into our buzz production process.Wesly Clark:\nI want to begin by orienting you to the role analytics plays in creating business value, highlighting which parts of the MLOps lifecycle this framework focuses on, and discussing the guiding principles we adhere to when implementing our solution. Then we\u2019ll get to the part you really came for the technical demo and the practical steps you can take to create your own solution.Wesly Clark:\nWe want to emphasize that everything we do in analytics, data science, and machine learning should focus on creating business value and accomplishing the objectives of our organizations. As scientists, we could easily lose ourselves in the numbers. So we intentionally refocus ourselves on the people we\u2019re trying to empower and the processes in which our solutions will be embedded.Wesly Clark:\nI\u2019ve watched quite a few fantastic talks about data engineering, hydrating the data like in creating feature stores.Wesly Clark:\nIt\u2019s about data engineering, hydrating the Delta Lake and creating feature stores. Likewise, there are plenty of presentations that focus on containerization, serving and production performance monitoring. Today, I want to focus on a secure self-service framework for automating the creation and deployment of compute environments linked to specific project branches of a product\u2019s code repository. Before I show you the framework architecture and implementation, I want to speak briefly to the guiding principles on which our solution was established.Wesly Clark:\nWe were aiming for predictability. We chose convention over configuration. We wanted it to be automated because the real power of these conventions is realized when the user doesn\u2019t have to remember the rules to see it in action or to implement it. We wanted to strike a balance between making a secure and self-service. We sought to empower our users while simultaneously providing boundaries to keep them safe. We wanted this framework to emphasize repeatability by creating configuration artifacts that follow the code through the entire ML life cycle we ensure repeatable deployments in environment creation.Wesly Clark:\nWe wanted to introduce clearly defined environments. We weren\u2019t just seeking to automate the workflow we already had, but to create new possibilities through the tools we were giving to our teams. We introduced our analyst, engineers, and scientists. Some of the most robust concepts from enterprise scale software engineering development life cycles. We wanted to be platform and cloud agnostic. We weren\u2019t multi-cloud when we started this, but Databricks was. It was important to us to choose solutions that could run anywhere. I don\u2019t have time to cover all the decisions we made in detail, but I want to give you a high level understanding of the framework.Wesly Clark:\nThe first thing I want to draw your attention to is a set of config files that are stored in the user\u2019s code bridge. The environment config file is where you would store values that change based on which environment your code is running in. Next, the cluster in library config lets you define the dependencies and compute resources needed for your code to run. It also lets you specify who should have access to your project. Lastly, the jobs config is where you would store the instructions for how your code should be deployed as it moves towards production. Next, I want to explicitly define what it means for your code to be deployed to a specific environment.Wesly Clark:\nIt means that a fresh copy of our code has been pulled into the Databricks project folder and it\u2019s synced with your repository bridge. It also means that your code runs on a dedicated cluster meeting the specific requirements defined in your branches config files. Lastly, it means that the clusters operating under the authority of a service principal that only has access to the appropriate resources in the corresponding infrastructure environment, local, dev, test and prod. That right means you\u2019re using different secrets, storing your data in files in different containers and accessing different versions of the web services depending on which environment you\u2019re running in.Wesly Clark:\nNow, let\u2019s talk a little bit more about how the CI\/CD pipeline works alongside your product code. We\u2019ll walk through a self-service cluster management scenario. Let\u2019s imagine that a user with an existing repository for their product code was going to start using the CI\/CD framework for the first time. Thankfully, the CI\/CD repository has a setup pipeline to help get them started. Step one illustrates the first phase of the setup pipeline which will transfer the config files we just talked about on the previous diagram into the user\u2019s product repo.Wesly Clark:\nStep two shows that the second phase of the setup pipeline will transfer a few YAML files and create child pipelines in the product to repo. One of these child pipelines is used to initiate job deployments to new environments and the other pipeline, which is relevant to this scenario, listens for committed changes made to the config files. Once the initial setup pipeline has finished transferring files and creating child pipelines in the product repository, let\u2019s imagine that in step three of this diagram the user modifies the cluster and library config to change the maximum number of nodes for their cluster, add a third party library to their list of dependencies and modify the access control list to add a teammate to their project.Wesly Clark:\nIn step four, after the user commits their change to the cluster and library config file, the listener pipeline would trigger and initiate a callback to the CI\/CD repository. Step five emphasizes that the majority of the functionality lives in the CI\/CD repository where a YAML pipeline would execute a series of PowerShell scripts that would validate the config file changes and convert it into three separate JSON files which are then sent separately to the Databricks cluster, library and permissions APIs.Wesly Clark:\nFinally, in step six, you see that after a few moments, these changes would be completed by the Databricks APIs and the user would see the updated cluster in the Databricks UI with the new library loaded onto it accessible only by the team members specified in the access control list. All right, one last diagram before we get to the technical demo. I want to re-emphasize the workflow this enables. Continuously creating enhancements to your product without environment conflicts. In this image you see two separate branches of the same product being worked on by two different users in the local environment.Wesly Clark:\nEach user has a separate copy of the product notebooks and config files stored in their local projects folder under their username. Each runs on a dedicated cluster set up according to the user\u2019s config, each cluster could have completely different properties and run different versions of libraries without conflict. Once you get past the local development, only one branch of a product can be deployed at any given time. Over in the dev environment an older version of the product already committed to master is on its way to being productionalized.Wesly Clark:\nIt\u2019s already past the first quality gate enforced by our CI\/CD job deployment pipeline, it also has a separate copy of the notebooks and can hit fig files stored in the dev projects folder. It is using an older copy of the library and runs on a dedicated job cluster meeting the specifications of an older version of the config files. Unfortunately, that code failed to pass the stricter quality gate to get into the more closely guarded test environment. Both test and prod are still retraining using code from a previous master release tag. Both environments have a separate copy of the notebook and config files stored in the test and prod projects folders and run on dedicated job clusters still using an even older version of the library.Wesly Clark:\nIn all environments, local, dev, test and prod each cluster acts under the authority of an appropriate environment service principal. To interact with environment specific instances of tables, file storage, external web hook and surface integrations and to publish job events. These environments specific service principles also have been granted permissions to invoke those deployed jobs so that they can be initiated from outside of Databricks using the service principle credentials. I know that was a lot of conceptual material to cover. Thank you for bearing with me through all of the abstractions and theory behind the framework. Now I\u2019m going to turn it over to my friend, Cara, to show you how you can implement something like this one step at a time.Sylvia Simion:\nThanks Wesley. Hi everyone. My name is Cara Phillips and I\u2019m a data science and MLOps consultant at Artis Consulting. As Wesley just mentioned, I\u2019m going to show you these pipelines in action. Let\u2019s start by taking a look at the file structure in the CI\/CD repo. First thing to notice are these YAML files which are the templates that contain the steps that our pipeline will execute. Right above these files we have a scripts folder. These are all of the scripts that are going to be run in each step of the pipeline. We decided to use PowerShell scripts but you can use any language that can parse JSON files and sends data to the Databricks API.Sylvia Simion:\nAt the top here we have two folders, one for data science and one for data engineering. Both the data science and data engineering teams are using these pipelines and these folders contain configuration default values that can be set at the team level. For example, the data science team can use these files to set default values for their cluster or jobs configurations, to set default permissions or to set libraries that will always be installed on their clusters. Last folder to look at here is the files for remote repository folder.Sylvia Simion:\nThis folder contains all the files we\u2019ll need to copy into the product repo. Once those files are copied over the pipelines can be built in the product repo. The process of copying these files and creating the pipelines can be done manually or as Wesley reviewed earlier by another pipeline we called the setup pipeline. Let\u2019s go over to the product repo and take a closer look at that file structure. The first folder we have is the notebooks folder. This folder contains all of the notebooks that are linked to the Databricks workspace. The remainder of the files are the ones that were copied from the CI\/CD repo.Sylvia Simion:\nFirst, we have the pipelines definitions folder, and this folder contains YAML files that will trigger the execution of the pipeline steps stored in the CI\/CD repo. The last files we\u2019re going to look at are the cluster in libraries, config JSON file, as well as the jobs config JSON file. The user will use these two files to create and manage the configuration for their clusters and jobs. The first step the user needs to do once the repo is set up is to create a new user branch from master. Let\u2019s take a closer look at the cluster and library configs JSON file which is the first one the user will configure.Sylvia Simion:\nOnce they\u2019ve created their user branch they can begin editing the config files. Let\u2019s take a closer look at the cluster in libraries config file. The first parameter they\u2019re going to configure is the workspace name. This value will determine which folder in the CI\/CD repo our default config values will come from as well as which Databricks workspace the pipeline would be authenticating to. The cluster parameters here contains a subset of parameters that the user can set for their cluster configuration. Structure of most of these values is directly equivalent to the required JSON structure for the API, with the exception of spark version.Sylvia Simion:\nHere, we created a structure where the user only needs to specify the version number, whether or not they want an ML runtime which contains many machine learning packages by default and whether or not they need GPU compute on their cluster. The pipeline maps these values to the correct key that\u2019s required by the API. The last set of parameters in this section I want to call attention to is the custom tags. These tags are very important for tracking and managing your Databricks spend. In addition to the J.B Hunt specific tags you see here, the pipeline automatically sets tags for the environment which is either a dev test or prod as well as the repo in branch that triggered the creation of the cluster.Sylvia Simion:\nThe next section is the access control list. Here the user lists the emails for everyone working on their code in the branch. The pipeline we\u2019ll use this list of emails to set the permissions on the cluster. This ensures that the created clusters reserved exclusively for the team members working on that branch. The last section in this config file is for the libraries. For each library type the user specifies a list of libraries they want installed on their cluster or Python and CRAN packages if the required package repo is different than the default repo they can specify that using the package and repo structure here.Sylvia Simion:\nNow let\u2019s make a couple changes here, save the file and watch the cluster be created. We\u2019re going to change the max workers to seven and save the file back. Now let\u2019s go take a look at the pipeline run. You see here that the pipeline was triggered when I saved the file and it is automatically running. While we wait for that to finish let\u2019s talk a bit about what\u2019s going on behind the scenes. Back in the product repo, there\u2019s a file called pipeline cluster. This file listens for changes to the cluster and libraries config JSON and calls back to the CI\/CD repo to execute the pipeline steps that are stored there.Sylvia Simion:\nLet\u2019s go over to the CI\/CD repo now and look at those steps. At the bottom of the repo here we have a YAML file called pipeline cluster config. This file contains all the steps that are going to create and manage our Databricks clusters. The first couple of steps here do some administrative work to set up the pipeline environments. Then we get to this generate cluster config step. This step parses the values provided by the user in their config file, combines it with the cluster config default template and creates the JSON to send to the clusters API in the next step.Sylvia Simion:\nThe creator edit cluster step uses that parsed JSON file to either create a new cluster if one doesn\u2019t already exist or to edit an already existing cluster. Once our cluster is created, all we have to do is add or update the permissions. The set cluster permission step takes the list of users from that config file, parses them into the proper JSON structure and sets the permissions on the cluster using the permissions API. Once the permissions are set, we now have to install the libraries. The parse requested library step takes the libraries in the config file and parses them and in the next step takes that parsed JSON and installs any new libraries and uninstalls any libraries that were removed from the config file.Sylvia Simion:\nNow let\u2019s take a look at our completed pipeline. Once we go into the run you can see that all of the steps completed successfully. That means we should see a new cluster running in Databricks with the config specified in the config file. Let\u2019s go over to Databricks and look at that cluster. As you can see here, we now have a cluster running in Databricks. The name for this cluster was defined in the pipeline by the organizational naming convention. As you can see the configuration here is exactly what we had specified in our config file.Sylvia Simion:\nLikewise, the user specified in our access control list are listed here under the permissions. Lastly, when we go into our libraries, we see that the libraries we requested have been installed in addition to a couple of libraries that were specified in the default libraries file. Wrapping it all up, step one is to copy the pipeline in the config files into the product repo and create those pipelines. Then once that\u2019s complete the user fills out their cluster and libraries config file and saves it. The pipeline then automatically is going to run and the user has their own cluster to use within minutes.Sylvia Simion:\nThe next pipeline we\u2019re going to look at is the jobs deployment pipeline. This pipeline provides automated and secure jobs deployment and editing. Let\u2019s start in our product repo with the user\u2019s workflow. When the user is ready for their code and jobs to be deployed in the dev environment they will come to the jobs config JSON file. Here they will specify how many jobs will be created and the configuration for each. First parameter they\u2019ll have to fill out is the name of the notebook. Next, they will specify if they want to use a high concurrency cluster or a jobs cluster to execute their job.Sylvia Simion:\nUsing a high concurrency cluster instead of a jobs cluster we\u2019ll reduce the cluster startup latency when a job\u2019s deployed and allow jobs to be run in parallel. Next, they will specify the cluster configuration and a set of libraries. If they\u2019re using a high concurrency cluster as in the first example here, the cluster config and libraries are set based on the configuration in the cluster and libraries config JSON. The values in the job config for these parameters will be null. If the job is going to be run on a jobs cluster like in the second and third examples here, there are several options for these two parameters.Sylvia Simion:\nIf the user specifies default for either the new cluster or libraries parameters, the config for that respective parameter will be taken from the cluster and libraries config JSON. Additionally, the user can specify none for the libraries parameter if no libraries are required. In the second job, you can see the default complaint is specified for the cluster configuration and the libraries perimeter is set to none indicating no libraries are required for this jobs cluster. The last option for these two parameters is to specify a new cluster config or set of libraries as shown here in the third job. The configs are specified using the same structure as is used in the cluster and libraries config.Sylvia Simion:\nWe have the cluster configuration here and below the libraries configuration. Once we\u2019ve saved our changes back to our branch and committed all our coach and master, we can run the jobs deployment pipeline. I\u2019m going to do that right now and I\u2019m just going to run the dev stage. While this runs, let\u2019s take a closer look at what the pipeline is doing. Back in the product repo, the pipeline jobs YAML file invokes the pipeline steps from the pipeline jobs config YAML file stored in the CI\/CD repo which we\u2019ll get right now. We have three different environments that the jobs are going to be deployed to, dev, test and prod.Sylvia Simion:\nThe same general steps are going to be repeated for each of these environments so we\u2019re going to use a build steps parameter which allows us to only have to write the code for the steps once then those steps will be repeated in each environment. You\u2019ll notice a lot of these steps are the same as what you saw in the cluster pipeline since much of the code is shared between these two pipelines. Let\u2019s take a closer look at these steps. Like with the cluster pipeline these first couple steps are just doing some administrative work to set up the pipeline environment. Then we get to the generate cluster config step.Sylvia Simion:\nThis script is going to do two things. First, it generates the default cluster config that\u2019s going to be used when the user opts to use a high concurrency cluster or when they designate default for their jobs cluster definition. The second thing it does is parse a new jobs cluster configuration when provided by the user. Once those figs are parsed the create or edit high concurrency cluster steps going to check to see if a high concurrency cluster is required for the set of jobs being deployed and create or update the cluster if needed. If a high concurrency cluster is required the next step is going to set the proper permissions for that cluster.Sylvia Simion:\nThis includes adding permissions for dev, test or prod service principles which are going to allow the cluster to be managed by other applications like Azure Data Factory or Airflow. The next step is to parse the libraries that are going to be installed on the cluster. Like with the cluster config parsing step this step is going to parse both the default set of libraries and any custom set specified by the user. After we have all those configs ready we can deploy our new jobs or edit our existing jobs in the next step.Sylvia Simion:\nFinally, once our jobs have been deployed, we need to set or update the permissions. You can define permissions for a custom set of users or groups in the default values for jobs stored in the teams folder up here in the CI\/CD repo. In addition to these permissions, the dev, tests or prod service principles will be given access so they can orchestrate these jobs from external applications. Once we have all the steps to find, we can execute them in each of the stages below which includes security and quality gates in between each environment deployment. Let\u2019s take a look at the jobs pipeline.Sylvia Simion:\nWe go into the run, we see that all the steps for the dev stage completed successfully which means we\u2019ll have three new jobs created in our Databricks workspace. Let\u2019s take a look at those. You\u2019ll see we have three jobs created for our dev environment since we configured three jobs in our jobs config file. Notice the cluster definitions for each job here. The first job is using a high concurrency cluster and the second job is using our default cluster config with one to eight workers and third is using a custom cluster config with one to four workers.Sylvia Simion:\nLet\u2019s go into the second job here and take a look at the configuration. In the configuration tab you\u2019ll see the specs for the jobs cluster that was created for this run. Then below in the advance section we can see the pipeline gave the correct permissions for the two service principles, the admin and dev as well as three ACL groups we specified in the default access control template in our teams folder. To summarize the jobs pipeline, first step is for the user to fill out their jobs config JSON in their user branch.Sylvia Simion:\nNext, they merge all their codes and master then once the code is ready to go, the jobs pipeline can be run and the job will be created and run. Today we created two pipelines to automatically create and manage our database clusters in jobs with an easy self-service workflow for the user. Thanks everyone for listening to my tech demo. I hope you learned some interesting and useful things and I\u2019m going to pass it back to Wesley to wrap everything up.Wesly Clark:\nThank you Cara for giving such a thoughtful technical demo and for all the hard work you\u2019ve put into bringing the vision of this framework into reality. Now I\u2019d like to briefly recap what we discussed today. We told you how J.B. Hunt was trying to accomplish as an organization and how our team has focused its work to ensure we are contributing to the realization of that mission. We drew your focus to the section of the MLOps life cycle where our framework operates, and where we feel the most progress of iterative improvement occurs.Wesly Clark:\nWe described the motivating principles that guided us while we implemented our solution. We visually represented the framework with a series of architectural diagrams to help you see the big picture. Then Cara gave you a closer look through a step-by-step technical demo. Finally, the only thing left to say is thank you for investing your time with us. I hope this was helpful and additional resources and details will be available to download after the presentation to help get you started. Thank you.Speaker 3:\nThank you, Cara and Wesley, and thanks to all of our previous speakers as well. We now have a few minutes for Q&As with our speakers and we\u2019ll be right back.Watch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anna-russo","text":"Anna Russo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnna RussoGlobal Director of Data Science at GucciBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nick-king\/#","text":"Nick King - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNick KingFounder & CEO at Data KineticBack to speakersNick has been working on enterprise technology platforms for the last 20 years. In his role at Data Kinetic he has focused driving the applied use of AI\/ML with enterprise companies. Previous to Data Kinetic, Nick has worked across multiple startups and open source projects from Snowplow, to DataRobot. He has also held roles at Microsoft, Google, VMware, and Cisco focusing on applied technologies and platforms.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/legal\/privacynotice","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. 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You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/big-data-analytics","text":"What is Big Data Analytics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBig Data AnalyticsAll>Big Data AnalyticsThe Difference Between Data and Big Data AnalyticsPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relatively basic form of analytics could be difficult, though, especially the integration of new data sources. With traditional data analytics, which relies on the use of relational databases (like SQL databases), made up of tables of structured data, every byte of raw data needs to be formatted in a specific way before it can be ingested into the database for analysis. This often lengthy process, commonly known as extract, transform, load (or ETL) is required for each new data source. The main problem with this 3-part process and approach is that it\u2019s incredibly time and labor intensive, sometimes requiring up to 18 months for data scientists and engineers to implement or change.  Once data was inside the database, though, in most cases it was easy enough for data analysts to query and analyze. But then along came the Internet, eCommerce, social media, mobile devices, marketing automation, Internet of Things (IoT) devices, etc., and the size, volume, and complexity of raw data became too much for all but a handful of institutions to analyze in the normal course of business.What Is Big Data Analytics?Big data analytics is the often complex process of examining large and varied data sets - or big data - that has been generated by various sources such as eCommerce, mobile devices, social media and the Internet of Things (IoT). It involves integrating different data sources, transforming unstructured data into structured data, and generating insights from the data using specialized tools and techniques that spread out data processing over an entire network. The amount of digital data that exists is growing at a fast pace, doubling every two years. Big data analytics is the solution that came with a different approach for managing and analyzing all of these data sources. While the principles of traditional data analytics generally still apply, the scale and complexity of big data analytics required the development of new ways to store and process the petabytes of structured and unstructured data involved. The demand for faster speeds and greater storage capacities created a technological vacuum that was soon filled by new storage methods, such as data warehouses and data lakes, and nonrelational databases like NoSQL, as well as data processing and data management technologies and frameworks, such as open source Apache Hadoop, Spark, and Hive. Big data analytics takes advantage of advanced analytic techniques to analyze really big data sets that include structured, semi-structured and unstructured data, from various sources, and in different sizes from terabytes to zettabytes.The Most Common Data Types Involved in Big Data Analytics Include:Web data. Customer level web behavior data such as visits, page views, searches, purchases, etc.Text data. Data generated from sources of text including email, news articles, Facebook feeds, Word documents, and more is one of the biggest and most widely used types of unstructured data.Time and location, or geospatial data. GPS and cell phones, as well as Wi-Fi connections, make time and location information a growing source of interesting data. This can also include geographic data related to roads, buildings, lakes, addresses, people, workplaces, and transportation routes, which have been generated from geographic information systems.Real-time media. Real-time data sources can include real-time streaming or event-based data.Smart grid and sensor data. Sensor data from cars, oil pipelines, windmill turbines, and other sensors is often collected at extremely high frequency.Social network data. Unstructured text (comments, likes, etc.) from social network sites like Facebook, LinkedIn, Instagram, etc. is growing. It is even possible to do link analysis to uncover the network of a given user.Linked data: this type of data has been collected using standard Web technologies like HTTP, RDF, SPARQL, and URLs.Network data. Data related to very large social networks, like Facebook and Twitter, or technological networks such as the Internet, telephone and transportation networks.Big data analytics helps organizations harness their data and use advanced data science techniques and methods, such as natural language processing, deep learning, and machine learning, uncovering hidden patterns, unknown correlations, market trends and customer preferences, to identify new opportunities and make more informed business decisions.Advantages of Using Big Data Analytics Include:Cost reduction. Cloud computing and storage technologies, such as Amazon Web Services (AWS) and Microsoft Azure, as well as Apache Hadoop, Spark, and Hive can help companies decrease their expenses when it comes to storing and processing large data sets.Improved decision making.With the speed of Spark and in-memory analytics, combined with the ability to quickly analyze new sources of data, businesses can generate immediate and actionable insights needed to make decisions in real time.New products and services. With the help of big data analytics tools, companies can more precisely analyze customer needs, making it easier to give customers what they want in terms of products and services.Fraud detection. Big data analytics is also used to prevent fraud, mainly in the financial services industry, but it is gaining importance and usage across all verticals.Additional ResourcesThe Databricks Lakehouse PlatformPerspectives on Big Data & AnalyticsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yuki-saito\/#","text":"Yuki Saito - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYuki SaitoTechnical Evangelist at NTT DATA CorporationBack to speakersYuki Saito is a cloud architect and data engineer at NTT DATA. He has a decade of experience in system development related to data management and utilization. He promotes the use of Databricks to accelerate data and AI democratization in Japanese companies.\nYuki's strength is his understanding of a wide range of technologies. In particular, he was certified as a Databricks Solutions Architect Champion for the first time in Japan. In addition, he is certified as a Japan AWS Top Engineer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/laliga","text":"Revolutionizing how sports are played and experienced | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYRevolutionizing how sports are played and experiencedLaLiga uses Databricks Lakehouse to optimize player performance and create the ultimate fan experienceWatch video INDUSTRY: Media and entertainment SOLUTION: Player analytics PLATFORM USE CASE: Lakehouse ,Delta Lake,machine learning,ETL CLOUD: Azure\u201cDatabricks Lakehouse has made what was previously impossible extremely easy. Now we can put the power of data into the hands of leagues everywhere to deliver sporting analytics and experiences like no other.\u201d\n\u2014 Guillermo Rold\u00e1n, Head of Architecture at LaLiga TechLaLiga is changing the world of sports and entertainment. Through the use of real-time streaming data generated by hundreds of cameras across stadiums, teams have access to unprecedented levels of actionable insights \u2014 revolutionizing the way the game is coached, played and enjoyed. It\u2019s all made possible with the Databricks Lakehouse Platform, which processes petabytes of video stream data to help analyze in-game information. With Lakehouse, LaLiga can provide insights that help players get better at their game and deliver personalized fan experiences. After spearheading innovation within their football league, LaLiga has now become a data and AI company by offering these capabilities to sports teams around the world through the new entity, LaLiga Tech.Bringing real-time data insights to sportsData and analytics is rapidly becoming the cornerstone for how the sports industry operates \u2014 from gaining insights into winning strategies to delivering fan experiences that drive viewership and brand loyalty. LaLiga, one of the most-watched football leagues in the world, has been a front-runner in the adoption and use of data and AI to improve the fan experience.Football clubs haven\u2019t historically used data for decision-making, but LaLiga\u2019s mission has been to change that by providing clubs with the opportunity to analyze in-game information. This helps them better understand how to get the most from their players and deliver the best experience for their passionate fanbase. With a deeper understanding of these data insights, clubs can improve match outcomes, prevent player injury and deliver the exact information that fans crave to drive team loyalty and revenue.LaLiga is rich with digital assets captured by hundreds of high-performance HD cameras embedded throughout their stadiums. These cameras capture 300,000 frames of in-game action per match, including all player and ball movement, generating petabytes of information on a daily basis. In the face of harnessing massive amounts of structured and unstructured data, LaLiga struggled to efficiently ingest the volumes of live-action data and extract insights that business stakeholders could understand and put into action.\u201cWe had several problems keeping us from truly building a data-first culture,\u201d said Guillermo Rold\u00e1n, Head of Architecture at LaLiga Tech. \u201cWe weren\u2019t able to efficiently ingest all our data. And we weren\u2019t able to effectively communicate and share with the business leaders how data is a valuable asset for our business. What we needed was a platform that would help us harness this amount of data to deliver on our mission.\u201dLaLiga is revolutionizing the game for fans and players through real-time insights on lakehouseStreaming analytics at massive scaleOnce LaLiga plugged in Databricks, their goal became a reality. The Databricks Lakehouse Platform on Microsoft Azure now serves as the foundation for their operational analytics platform by simplifying the ingestion of petabytes of video stream data for downstream analytics and real-time machine learning \u2014 without sacrificing performance.Delta Lake provides a common data layer that unifies and prepares all their data sets for analytics and ML. Today, Delta Lake underpins a cost-effective, highly scalable lakehouse for LaLiga. \u201cWe must always deliver the most current and accurate data to our business partners, otherwise they\u2019ll lose confidence in the insights,\u201d explained Guillermo. \u201cDelta Lake provides reliability that our previous infrastructure lacked.\u201dWith data flowing seamlessly, they can start the creative process of generating questions, such as, how close is a player to scoring a goal? With Power BI, they are able to deliver reports and dashboards to help business stakeholders make smarter decisions that impact team operations and revenue. With MLflow, they can build, train and deploy predictive models designed to do things like track the movement of players and the ball in the field in real time, meaning they can analyze player performance, speed and health to make in-game decisions about gameplay. On the football-fan side, Databricks enabled LaLiga to begin examining fan behavior, allowing for more personalized content experiences and ultimately turning data into both world-class entertainment and e-commerce opportunities.The dawn of a new era of data-driven sportsWith Databricks serving as the foundation for building data-driven capabilities within their football league, they are now setting their sights on expanding access to their technology to sports and entertainment organizations around the globe. For most organizations, building out data and AI capabilities requires heavy investments in time and resources \u2014 a luxury many organizations don\u2019t have. With LaLiga Tech, teams can modernize their approach to business operations and performance optimization at a fraction of the cost and complexity. As LaLiga continues to expand their reach globally, there are no limits to how many customers they can bring on and the overarching impact LaLiga Tech can have on all aspects of sports and entertainment moving forward.\u201cDatabricks has made what was previously impossible extremely easy. And with LaLiga Tech, we can now put the power of data and AI into the hands of all sporting and entertainment organizations, helping them deliver a product like no other to those who matter most \u2014 their fans,\u201d concluded Guillermo.Related ContentNewsSpain\u2019s LaLiga looks to enleague data analytics with DatabricksReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maxime-agostini","text":"Maxime Agostini - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaxime AgostiniCEO at Sarus Technologies IncBack to speakersMaxime Agostini is cofounder and CEO of Sarus, a privacy company backed by YCombinator. Sarus lets organizations leverage confidential data for analytics and machine learning with privacy guarantees. Prior to Sarus, he was cofounder and CEO of AlephD, a marketing-tech company that he led until a successful acquisition by Verizon Media.\nMaxime graduated from Ecole Polytechnique in computer science and physics and has been developing and building data-driven businesses during his whole career.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/harsh-mishra\/#","text":"Harsh Mishra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarsh MishraLead Enterprise Architect at Australian Rail Track CorporationBack to speakersHarsh Mishra, as a Lead Enterprise Architect of Systems and Integration, plays an integral role in facilitating the design and implementation of the Strengthening the Core work packages for the ARTC Digital Strategy and building integrated technology roadmaps to drive the successful foundation of the ARTC Digital Strategy.\nHe comes from a strong digital transformation background where he has successfully transformed multiple Australian company's digital and data footprints.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/automl","text":"Databricks AutoML - Automated Machine Learning | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAutoMLAugment experts. Empower citizen data scientists.Try for freeSchedule a demoDatabricks AutoML allows you to quickly generate baseline models and notebooks. ML experts can accelerate their workflow by fast-forwarding through the usual trial-and-error and focus on customizations using their domain knowledge, and citizen data scientists can quickly achieve usable results with a\u00a0low-code approach.Jump-start new ML projectsDatabricks AutoML provides the training code for every trial run to help data scientists jump-start their development. Data scientists can use this to quickly assess the feasibility of using a data set for machine learning (ML) or to get a quick sanity check on the direction of an ML project.No ML problem too bigLeverage AutoML to tackle a variety of machine learning problems ranging from classification, regression, and forecasting. AutoML uses multiple algorithms from a variety of machine learning libraries for each problem type, and lets you pick the best for your problem.Automate the grind of machine learningAutomatically set up your machine learning project with the training libraries, MLflow integration for experiment tracking and built-in ML best practices such as training and testing split, normalizing of features and hyperparameter tuning.A \u201cglass box\u201d approach to AutoMLUse generated editable notebooks to easily customize baseline models with your domain expertise. You can also leverage these notebooks to explain how your AutoML models were trained to fulfill audit and compliance requirements.ResourcesVirtual eventsAutoML: Rapid, simplified machine learning for everyoneAutomating the ML Lifecycle With Databricks Machine LearningBuilding Machine Learning PlatformsDocumentationDatabricks AutoML DocumentationeBooksState-of-the-Art Machine Learning CapabilitiesReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/nlp-oncology","text":"\n\n\n\n\n\n\n\n\noncology - Databricks\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/huaxin-gao","text":"Huaxin Gao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHuaxin GaoSoftware Engineer at AppleBack to speakersHuaxin Gao is an Apache Spark committer and a software engineer at Apple, focusing on Spark SQL. Prior to joining Apple, she worked on a number of SQL and ML projects at IBM.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/oz-katz","text":"Oz Katz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOz KatzCTO @ Treeverse, co-creator of lakeFS at Treeverse LTDBack to speakersOz Katz is the CTO and Co-founder of Treeverse, the company behind lakeFS, an open source platform that delivers resilience and manageability to object-storage based data lakes. Oz engineered and managed petabyte-scale data infrastructure at analytics giant SimilarWeb (NYSE: SMWB), which he joined after the acquisition of Swayy.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/migration","text":"Migrate to Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMigrate to DatabricksModernize your data platform by moving to the Databricks Lakehouse\nTry Databricks freeContact DatabricksReduce costs, innovate faster and simplify your data platform by migrating to the Databricks Lakehouse from your enterprise data warehouse or legacy data lake. Now you can run all your data, analytics and AI workloads on a modern unified platform, built on open standards and secured with a common governance approach.Why migrate to Databricks?Simplify your data platformGet a single modern platform for all your data, analytics and AI use cases. Unify governance and the user experience across clouds and data teams.\nScale cost-effectivelyStop managing servers, and scale on demand with serverless. Run data warehousing at scale with up to 12x better price\/performance.\nAccelerate innovationBuild AI, ML and real-time analytics capabilities faster with collaborative, self-service tools and open source technologies such as MLflow and Apache Spark\u2122.\nMigrate from Hadoop\nLearn moreMigrate from a data warehouse\nLearn moreMigrate with confidenceWe\u2019ve helped hundreds of customers migrate from legacy data platforms. Using a phased end-to-end migration process provides a predictable model to understand costs both during and post-migration. And a lakehouse-first approach for migrating all workloads ensures support for existing as well as new use cases. The result is lower risk, faster value realization and increased ROI.The 5 phases of data migrationPhase 1:\nDiscovery\nUse profilers to automate discovery. Get insights on legacy platform workloads and estimate Databricks platform consumption costs.\nPhase 2:\nAssessment\nUse analyzers for a detailed assessment of code complexity and to estimate migration project costs.\nPhase 3:\nStrategy\nFinalize technology mapping and build optimal pathways for each source platform migration, with expert guidance from Databricks.\nPhase 4:\nProduction Pilot\nRun a pilot with your use cases and use code converters where applicable to transpile legacy code to Databricks-compatible code. Develop a migration implementation plan and road map.\nPhase 5:\nExecution\nRinse and repeat for all workloads. Get help with migration execution and support from certified partners or Databricks Professional Services.\nCustomers who have successfully migrated to DatabricksCustomer StoryPersonalizing pharmacy care to improve patient outcomes\nRead moreCustomer BlogRetiring on-prem entirely, making cost-saving gains and accelerating success\nRead moreCustomer StoryMoving to the cloud ushers in a new era of data-driven retailing\nRead moreBrickbuilder SolutionsLeverage Brickbuilder Solutions from leading consulting partners \u2014 built for migrating to the Databricks LakehouseCloud Data Migration by AccentureLess guesswork, more value\nGet startedLegacy System Migration by AvanadeMove your data to unlock its full value\nGet startedMigrate to Cloud and Databricks by CapgeminiStreamline data migration to the Databricks Lakehouse Platform\nGet startedMigrate to Databricks by Celebal TechnologiesQuicker migration from on-premises at lower cost\nGet startedLeapLogic Migration Solution by ImpetusAuto-transform ETL, data warehouse, analytics and Hadoop workloads to Databricks\nGet startedData Wizard for Hadoop\/EDW Migrations by InfosysConfidently move your data to Databricks\nGet startedSnowflake-to-Databricks Migration by LovelyticsEnsure a rapid and sound migration process\nGet startedSAS Migration Accelerator by Tensile AIMigration solution developed by Tensile AI and powered by the Databricks Lakehouse PlatformGet startedData Intelligence Suite by WiproMigrate with confidence to Databricks\nGet startedThe Wisdom of Transitioning to a Data Lakehouse StrategyHow a data lakehouse approach can help you overcome the common limitations of data warehouses and data lakesDownload nowResourceseBooksMigrating From Hadoop to Data Lakehouse for DummiesMigrating From a Data Warehouse to a Data Lakehouse for DummiesEventsStep-by-Step Guide to Hadoop MigrationModernize Your Data WarehouseBlogs5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architecture7 Reasons to Migrate From Your Cloud-Based Hadoop to the Databricks Lakehouse PlatformGet startedMigration doesn\u2019t have to be a headache. Contact us today to talk about what it could look like for you.Try Databricks freeContact DatabricksProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/deep-learning","text":"What is Deep Learning?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDeep LearningAll>Deep LearningTry Databricks for freeGet StartedWhat is Deep Learning?Deep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referred to as deep neural networks. It is is a part of a broader family of machine learning methods based on learning data representations, as opposed to traditional task-specific algorithms.How Does Deep Learning Work?In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound. It performs a task repeatedly, making a little tweak to improve the outcome. Deep learning models can exceed human-level performance. Models are trained by using a large set of labeled data and neural network architectures that contain many layers. The most important part of a Deep Learning neural network is a layer of computational nodes called \"neurons\". Every neuron connects to all of the neurons in the underlying layer. Due to \"deep learning\" the neural network leverages at least two hidden layers. The addition of the hidden layers enables researchers to make more in-depth calculations. How does the algorithm work then? The thing is, each connection has its weight or importance.but, with the help of the deep neural networks we can automatically find out the most important features for classification. This is performed with the help of the Activation Function that evaluates the way the signal should take for every neuron, just like in the case of a human brainTypes of Deep Learning Layers:The input layer of nodes receives the information and transfers it to the underlying nodes;here the network fixates on patterns of local contrast as important.Hidden node layers are the ones where the computations appear, this is the layer that uses those patterns of local contrast to fixate on things that resembleIn the output node layer, the results of the computations will show up. In this layer, the features will be applied to templates.A deep neural network can create more and more complex features in each of the successive layers.Additional ResourcesDeep Learning SolutionsResource-efficient Deep Learning Model Selection on Apache SparkThe Democratization of Artificial Intelligence and Deep LearningBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/llm?itm_data=hp-hero-llm-dais23","text":"Large Language Models (LLM) - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLarge Language Models (LLM)Register nowDeep dive into all things LLM - from in-person day long trainings, to community sessions focused on LLM tooling and Responsible use, to dedicated sessions on Databricks open-source model Dolly, LLMOps and more.\nSessionsBuilding and Deploying Large Language Models on Databricks | Paid TrainingLarge Language Models like ChatGPT and Dolly have taken the world by storm. Everybody from researchers and engineers to business leaders is rushing to understand how to utilize the latest developments in large language models (LLMs). This course is designed to teach individuals how to leverage LLMs for real-world use cases, including popular topics such as Transformers, BERT, and GPT. Through interactive lectures and exercises, you will learn how to develop, implement, evaluate, and deploy LLMs on Databricks. \nView this session in the catalog\nTesting Generative AI Models: What You Need to KnowGenerative AI shows incredible promise for enterprise applications. The explosion of generative AI can be attributed to the convergence of several factors. Most significant is that the barrier to entry has dropped for AI application developers through customizable prompts (few-shot learning), enabling laypeople to generate high-quality content. The flexibility of models like ChatGPT and DALLE-2 have sparked curiosity and creativity about new applications that they can support. The number of tools will continue to grow in a manner similar to how AWS fueled app development. But excitement must be tampered by concerns about new risks imposed to business and society. Increased capability and adoption also increase risk exposure. As organizations explore creative boundaries of generative models, measures to reduce risk must be put in place. However, the enormous size of the input space and inherent complexity make this task more challenging than traditional ML models.\nIn this session, we summarize the new risks introduced by the new class of generative foundation models through several examples, and compare how these risks relate to the risks of mainstream discriminative models. Steps can be taken to reduce the operational risk, bias and fairness issues, and privacy and security of systems that leverage LLM for automation. We\u2019ll explore model hallucinations, output evaluation, output bias, prompt injection, data leakage, stochasticity, and more. We\u2019ll discuss some of the larger issues common to LLMs and show how to test for them. A comprehensive, test-based approach to generative AI development will help instill model integrity by proactively mitigating failure and the associated business risk.\nYaron Singer, CEO & co-Founder, Robust Intelligence\nView this session in the catalog\nRapidly Scaling Applied AI\/ML with Foundational Models and Applying Them to Modern AI\/ML Use CasesToday many of us are familiar with foundational models such as LLM\/ChatGPTl. However, there are many more enterprise foundational models that can be rapidly deployed, trained and applied to enterprise use cases. This approach dramatically increases the performance of AI\/ML models in production, but also gives AI teams rapid roadmaps for efficiency and delivering value to the business. Databricks provides the ideal toolset to enable this approach. In this session, we will provide a logically overview of foundational models available today, demonstrate a real-world use case, and provide a business framework for data scientists and business leaders to collaborate to rapidly deploy these use cases.\nNick King, Founder & CEO, Data Kinetic\nView this session in the catalog\nHow You Can Audit A Language ModelLanguage models like ChatGPT are incredible research breakthroughs but require auditing & risk management before productization. These systems raise concerns related to toxicity, transparency & reproducibility, intellectual property licensing & ownership, dis- & misinformation, supply chains & significant carbon footprints. How can your org. leverage these new tools without taking on undue or unknown risks?\nRecent public reference work from In-Q-Tel Labs & BNH.AI details an audit of a named entity recognition (NER) application based on the pre-trained language model RoBERTa. If you have a language model use case in mind & want to understand your risks, this presentation will cover:\n\nStudying past incidents using the AI Incident Database and using this information to guide debugging.\nFinding & fixing common data quality issues.\nApplying general public tools & benchmarks as appropriate (e.g., checklist, SuperGLUE, HELM).\nBinarizing specific tasks & debugging them using traditional model assessment and bias testing.\nConstructing adversarial attacks based on a model's most significant risks and analyzing the results in terms of performance, sentiment & toxicity.\nTesting performance, sentiment & toxicity across different & less common languages.\nConducting random attacks: random sequences of attacks, prompts or other tests that may evoke unexpected responses.\nDon't forget about security: auditing code for backdoors & training data for poisoning, ensuring endpoints are protected with authentication & throttling and analyzing third-party dependencies.\nEngaging stakeholders to help find problems system designers & developers cannot see.\n\nIt's now time to figure out how to live with AI, and that means audits, risk management & regulation.\nPatrick Hall, Principal Scientist, BNH.AI\nView this session in the catalog\nExplainable Data Drift for NLPDetecting data drift, although far from solved for Tabular data, has become a common practice as a way to monitor ML models in production. For Natural Language Processing on the other hand the question remains mostly open. In this talk, we will present and compare two approaches. First, we will demonstrate how by extracting a wide range of explainable properties per document such as topics, language, sentiment, named entities, keywords and more we are able to explore potential sources of drift. We will show how these properties can be consistently tracked over time, how they can be used to detect meaningful Data Drift as soon as it occurs and how they can be used to explain and fix the root cause. The second approach we\u2019ll present is to detect drift by using the embeddings of common foundation models (such as OpenAI\u2019s GPT3 model family) and use them to identify areas in the embedding space in which significant drift has occurred. These areas in embedding space should then be characterized in a human-readable way to enable root cause analysis of the detected drift. We\u2019ll then compare the performance and explainability of these two methods, and explore the pros and cons of using each approach.\nNoam Bressler, ML Team Lead, Deepchecks\nView this session in the catalog\nBuilding AI-powered Products with Foundation ModelsFoundation models make for fantastic demos, but in practice, they can be challenging to put into production. These models work well over datasets that match common training distributions (e.g. generating web text or internet images), but may fail on domain-specific tasks or long-tail edge cases\u2014the settings that matter most to organizations building differentiated products! We propose a data-centric development approach that organizations can use to adapt foundation models to their own private\/proprietary datasets. We'll describe several techniques, including supervision \"warmstarts\" and interactive prompting (spoiler alert: no code needed!). To make these techniques come to life, we'll walk through real case studies describing how we've seen data-centric development drive AI-powered products, from \"AI assist\" use cases (e.g. copywriting assistants) to \"fully automated\" solutions (e.g. loan processing engines).\nVincent Chen, Director of Product \/ Founding Engineer, Snorkel AI\nView this session in the catalog\nColossal-AI: Scaling AI Models in Big Model EraThe proliferation of large models based on Transformer has outpaced advances in hardware, resulting in an urgent need for the ability to distribute enormous models across multiple GPUs. Despite this growing demand, best practices for choosing an optimal strategy are still lacking due to the breadth of knowledge required across HPC, DL, and distributed systems. These difficulties have stimulated both AI and HPC developers to explore the key questions:\u00a0\n\nHow can training and inference efficiency of large models be improved to reduce costs?\nHow can larger AI models be accommodated even with limited resources?\u00a0\nWhat can be done to enable more community members to easily access large models and large-scale applications?\u00a0\n\nIn this presentation, we investigated efforts to solve the questions mentioned above. Firstly, diverse parallelization is an important tool to improve the efficiency of large model training and inference. Heterogeneous memory management can help enhance the model accommodation capacity of processors like GPUs. Furthermore, user-friendly DL systems for large models significantly reduce the specialized background knowledge users need, allowing more community members to get started with larger models more efficiently. We will provide participants with a system-level open-source solution, Colossal-AI. More information can be found at https:\/\/github.com\/hpcaitech\/ColossalAI.\nJames Demmel, Dr. Richard Carl Dehmel Distinguished Professor, University of California, Berkeley; Yang You, Presidential Young Professor, National University of Singapore\nView this session in the catalog\nGenerative AI at scale using GAN and Stable DiffusionGenerative AI is under the spotlight and it has diverse applications but there are also many considerations when deploying a generative model at scale. This presentation will make a deep dive into multiple architectures and talk about optimization hacks for the sophisticated data pipelines that generative AI requires.\u00a0\nThe presentation will cover:\n\nHow to create and prepare a dataset for training at scale in single GPU and multi GPU environments\nHow to optimize your data pipeline for training and inference in production considering the complex deep learning models that need to be run.\nTradeoff between higher quality outputs versus training time and resources and processing times.\n\nPaula Martinez, CEO & Cofounder, Marvik; Rodrigo Beceiro, CTO & Cofounder, Marvik\nView this session in the catalog\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/data-streaming","text":"Streaming di dati | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWStreaming di datiSemplifica applicazioni, ML e analitiche in tempo realeCominciaGuarda la demoDatabricks Lakehouse Platform semplifica notevolmente lo streaming dei dati per offrire analisi, machine learning e applicazioni in tempo reale su un'unica piattaforma.Consenti ai team di gestione dati di costruire carichi di lavoro per i dati in streaming con i linguaggi e gli strumenti che gi\u00e0 conoscono. Semplifica lo sviluppo e la gestione operativa automatizzando gli aspetti di produzione associati alla costruzione e alla manutenzione di carichi di lavoro dei dati in tempo reale. Elimina i silos di dati grazie a un'unica piattaforma per dati in streaming e in batch.Costruisci pipeline e applicazioni di streaming pi\u00f9 velocementeUsa i linguaggi e gli strumenti che gi\u00e0 conosci con le API unificate per batch e streaming in SQL e Python. Sblocca analisi, ML e applicazioni in tempo reale per tutta l'organizzazione.Semplifica le attivit\u00e0 operative con strumenti automatizzatiImplementa e gestisci facilmente pipeline in tempo reale e applicazioni in produzione. Gli strumenti automatizzati semplificano l'orchestrazione delle attivit\u00e0, la tolleranza e il ripristino di guasti, le verifiche e i controlli automatici (checkpoint), l'ottimizzazione delle prestazioni e l'autoscalabilit\u00e0.Unifica la governance per tutti i dati in tempo reale su diversi cloudUnity Catalog mette a disposizione del lakehouse un modello di governance omogeneo per tutti i dati in streaming e in batch, semplificando le modalit\u00e0 di scoperta, accesso e condivisione dei dati in tempo reale.Come funziona?Acquisizione e trasformazione di dati in streamingAnalisi, ML e applicazioni in tempo realeStrumenti operativi automatizzatiMotore di elaborazione dei flussi di dati di nuova generazioneGovernance e storage unificatiAcquisizione e trasformazione di dati in streamingRendi pi\u00f9 semplici i processi di acquisizione dei dati ed ETL per pipeline di dati in streaming con Delta Live Tables. Sfrutta un semplice approccio dichiarativo all'ingegneria dei dati che consente ai team di lavorare con i linguaggi e gli strumenti che gi\u00e0 conoscono, come SQL e Python. Le pipeline in batch e in streaming possono essere costruite ed eseguite in un unico luogo, con impostazioni di aggiornamento controllabili e automatizzate, risparmiando tempo e riducendo la complessit\u00e0 operativa. Indipendentemente dalla destinazione dei dati, la costruzione di pipeline di dati in streaming su Databricks Lakehouse Platform evita perdite di tempo nel passaggio da dati grezzi a dati puliti.\"Un numero maggiore di unit\u00e0 aziendali sta utilizzando la piattaforma in modalit\u00e0 self-service, cosa che prima non era possibile. Non potr\u00f2 mai dire abbastanza dell'impatto positivo che Databricks ha avuto sulla Columbia\".- Lara Minor, responsabile senior dei dati aziendali, Columbia SportswearMaggiori informazioniAnalisi, ML e applicazioni in tempo realeLo streaming dei dati consente di migliorare immediatamente la precisione e la fruibilit\u00e0 di analisi e AI. L'azienda beneficia di informazioni approfondite in tempo reale grazie alle pipeline di dati in streaming. Quando esegui analisi SQL e report BI, addestri modelli ML o costruisci applicazioni operative in tempo reale, la tua azienda pu\u00f2 contare sui dati pi\u00f9 aggiornati per accedere ad approfondimenti in tempo reale, previsioni pi\u00f9 accurate e decisioni pi\u00f9 rapide, per restare un passo avanti alla concorrenza.\u201cDobbiamo fornire i dati pi\u00f9 aggiornati e precisi ai nostri partner, altrimenti perderanno fiducia nelle informazioni... Databricks Lakehouse ha reso estremamente semplice ci\u00f2 che prima era impossibile.\u201d- Guillermo Rold\u00e1n, responsabile dell'architettura di LaLiga TechMaggiori informazioniStrumenti operativi automatizzatiNel processo di costruzione e implementazione di pipeline di dati in streaming, Databricks automatizza molti dei compiti operativi complessi richiesti per la produzione, come il dimensionamento automatico dell'infrastruttura sottostante, l'orchestrazione delle dipendenze della pipeline, la gestione di errori e il ripristino, l'ottimizzazione delle prestazioni e altro ancora.La funzione Enhanced Autoscaling ottimizza l'uso del cluster allocando automaticamente le risorse di calcolo per ogni carico di lavoro. Queste funzionalit\u00e0, insieme al controllo automatico della qualit\u00e0 dei dati e alla gestione delle eccezioni, contribuiscono a ridurre il tempo impiegato nella costruzione e manutenzione degli strumenti operativi, consentendo di concentrarsi sul valore ricavato dai dati.Maggiori informazioniMotore di elaborazione dei flussi di dati di nuova generazioneSpark Structured Streaming \u00e8 la tecnologia chiave che sblocca lo streaming di dati sulla Databricks Lakehouse Platform, mettendo a disposizione un'API unificata per l'elaborazione in batch e streaming. Databricks Lakehouse Platform \u00e8 l'ambiente migliore in cui eseguire i carichi di lavoro di Apache Spark con un servizio gestito che vanta un record di disponibilit\u00e0 (uptime) del 99,95%. I carichi di lavoro Spark vengono ulteriormente accelerati da Photon, il motore lakehouse di nuova generazione compatibile con le API di Apache Spark, che offre un rapporto prestazioni-costo da record con scalabilit\u00e0 automatica a migliaia di nodi.Maggiori informazioniGovernance e storage unificatiEseguendo lo streaming dei dati su Databricks si possono sfruttare i componenti che costituiscono le fondamenta della Lakehouse Platform: Unity Catalog e Delta Lake. I dati grezzi vengono ottimizzati con Delta Lake, l'unico framework di storage open-source progettato fin dall'inizio per dati in streaming e in batch.Unity Catalog offre una governance integrata e dettagliata per tutti gli asset di dati e AI, con un unico modello omogeneo di scoperta, accesso e condivisione dei dati su diversi cloud. Unity Catalog offre inoltre supporto nativo per Delta Sharing, il primo protocollo aperto per la condivisione semplice e sicura dei dati con altre organizzazioni.IntegrazioniAssicura la massima flessibilit\u00e0 ai team di gestione dei dati utilizzando Partner Connect e un ecosistema di partner tecnologici per realizzare un'integrazione diretta con gli strumenti di streaming dei dati pi\u00f9 diffusi.Streaming di datiReferenze\u201cUtilizziamo Databricks per gestire dati ad alta velocit\u00e0 in movimento. La soluzione ci aiuta a rispondere molto pi\u00f9 velocemente alle esigenze dei nostri pazienti, in negozio e online. Attualmente abbiamo in corso una dozzina di iniziative, tutte alimentate con dati forniti da Databricks.\"\u2014 Sashi Venkatesan, Director of Product Engineering, Walgreens\u201cOra che il rilevamento delle frodi avviene in tempo reale, possiamo battere i truffatori e anticipare le loro mosse finalizzate a ingannare il sistema o realizzare sblocchi illegali, perpetrare furti di identit\u00e0 o sfruttare robocall e robotext.\u201d\u2014 Kate hopkins, Vice president, AT&TScopri di pi\u00f9Delta Live TablesDatabricks WorkflowsUnity CatalogDelta LakeSpark Structured StreamingContenuti associatieBook e demoCostruire il Data Lakehouse, di Bill Inmon, padre del data warehouseGovernance di dati, analisi e intelligenza artificialeThe Data Team\u2019s Guide to the Databricks Lakehouse PlatformDemo di streaming con Delta Live TablesEventiGestire la trasformazione dei dati con Delta Live TablesSerie di webinar sull'acquisizione di dati senza problemiDATA+AI SUMMIT 2022Data +AI World Tour 2022BlogPipeline di dati in streaming a bassa latenza con Delta Live Tables e Apache KafkaSemplificare l'acquisizione di dati in streaming in Delta LakeApprofondimenti in tempo reale: I tre motivi principali per cui i clienti amano lo streaming dei dati con DatabricksProject Lightspeed: elaborazione di stream pi\u00f9 veloce e pi\u00f9 semplice con Apache SparkPanoramica di tutte le nuove funzionalit\u00e0 di streaming strutturato sviluppate nel 2021 per Databricks e Apache Spark \u2014 The Databricks BlogPronto per cominciare?Prova gratuitaEntra nella communityProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/sponsors\/#","text":"Sponsors - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricing2023 SponsorsBecome a sponsorIf you are interested in sponsoring Data + AI Summit 2023, please contact our Sponsorship Management Team.\nOrganizing SponsorPrivacyPlatinum SponsorPrivacyPrivacyPrivacyDiamond SponsorsPrivacyPrivacyPrivacyPrivacyGold + SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyGold SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacySilver SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyBronze SponsorsPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyPrivacyDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chao-sun\/#","text":"Chao Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChao SunSoftware Engineer at AppleBack to speakersChao is currently a software engineer working at Apple, focusing on open source Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/apache-kylin","text":"What is Apache Kylin?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache KylinAll>Apache KylinTry Databricks for freeGet StartedWhat is Apache Kylin?Apache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/Spark. In addition, it easily integrates with BI tools via ODBC driver, JDBC driver, and REST API. It was created by eBay in 2014, graduated to Top Level Project of Apache Software Foundation just one year later, in 2015 and won the Best Open Source Big Data Tool in 2015 as well as in 2016. Currently, it is being used by thousands of companies worldwide as their critical analytics application for Big Data. While other OLAP engines struggle with the data volume, Kylin enables query responses in the milliseconds. It provides sub-second level query latency over datasets scaling to petabytes. It gets its amazing speed by precomputing the various dimensional combinations and the measure aggregates via Hive queries and populating HBase with the results. How Does Apache Kylin Work?The Kylin query engine which can be accessed in Kylin\u2019s user-friendly UI, via an API or via JDBC will leverage the Apache Calcite query processor and HBase features for rapid lookups. Kylin relies upon the Hadoop Eco-system:Hive \u2013 Input source, pre-join star schema during cube buildingMapReduce \u2013 Aggregate metrics during cube buildingHDFS \u2013 Store intermediate files during cube buildingHBase \u2013 Store and query data cubesCalcite \u2013 SQL parsing, code generation, optimization How can Apache Kylin help your organization?Very Fast OLAP Engine at Scale - Kylin is designed to reduce query latency on Hadoop for 10+ billions of rows of data to secondsANSI SQL Interface on Hadoop - Kylin offers ANSI SQL on Hadoop and supports most ANSI SQL query functions. It can easily be used by both analysts and engineers as no programming neededSeamless Integration with BI Tools - Kylin currently offers integration capability with BI Tools like Tableau, JDBC\/ODBC\/Rest APIInteractive Query Capability - Users can interact with Hadoop data via Kylin at sub-second latencyMOLAP cube query serving on billions of rows - \u00a0Users have the ability to define a data model and pre-build in Kylin even if it has more than 10+ billions of raw data records.Open-source ODBC driver - \u00a0Kylin\u2019s ODBC driver is built from scratch and works very well with Tableau.Additional ResourcesApache Kylin: Speed Up Cubing with Apache SparkBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tomer-patel\/#","text":"Tomer Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTomer PatelSoftware Engineering Manager at Akamai TechnologiesBack to speakersTomer Patel is an Engineering Manager at Akamai. He manages, builds, implements, and maintains scaled cyber security analytics applications on top of Azure and Databricks. \nHe currently manages 4 teams that focus on Data Engineering, Interactive Analytics product, and Devops.\nTomer has a Bachelor's degree in Computer Science from The Hebrew University of Jerusalem and a Master of Business Administration (MBA) from Bar-Ilan University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joseph-bradley\/#","text":"Joseph Bradley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoseph BradleyLead Product Specialist at DatabricksBack to speakersJoseph Bradley works as a Lead Solutions Architect at Databricks, specializing in Machine Learning, and is an Apache Spark committer and PMC member. Previously, he was a Staff Software Engineer at Databricks and a postdoc at UC Berkeley, after receiving his Ph.D. in Machine Learning from Carnegie Mellon.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maggie-davis\/#","text":"Maggie Davis - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaggie DavisPrincipal, Data Engineering at SlalomBack to speakersMaggie Davis brings 10+ years of strong experience in distributed data engineering, cloud architecture, and devops practices. She most recently worked with clients on developing a large-scale lakehouse to master customer data using ML as well as an automated package destruction tracking solution to identify covid-19 vaccine distribution issues on Databricks. Maggie currently is a Principal of Data Engineering at Slalom Consulting.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arun-pamulapati\/#","text":"Arun Pamulapati - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArun PamulapatiSr. Staff Security Field Engineer at DatabricksBack to speakersArun is a security engineer with Databricks for 5 years and has 20+ years of experience in building data products including over a decade of experience in big data analytics. Arun led and co-created the Security Analysis Tool (SAT) and is a core member of the Security Field Engineering team at Databricks. He has worked with customers in both the private and regulated industries on security. Arun has Bachelor's in Computer Sci and holds Cloud security, Bigdata, and AI\/ML industry certifications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thorsten-jacobs\/#","text":"Thorsten Jacobs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThorsten JacobsSr. Solutions Architect at DatabricksBack to speakersThorsten is a Senior Solutions Architect at Databricks and is based in Stockholm, Sweden. Data was always important during his career, as he holds a PhD in physics and previously worked as a Consultant and Data Scientist.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mark-dandrea","text":"Mark D'Andrea - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMark D'AndreaGlobal Chief Revenue Officer at AccuweatherBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-marsh","text":"Paul Marsh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MarshSenior Director Application Development at New York JetsBack to speakersPaul Marsh is the Sr. Director of Application Development at the New York Jets. In his current role, Paul is responsible for the development and management of the Jets data infrastructure including its Databricks installation and the other technologies that make up the organization's data stack. Paul has been with the Jets organization for 19 years, including 14 years overseeing application development at the organization. Paul holds an BA in History from Binghampton University as well as a Masters of Science in E-Commerce from Fairleigh Dickinson University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners","text":"Partners | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks PartnersDatabricks has over\u00a01200+ partners globally that provide data, analytics and AI solutions and services to our joint customers using the Databricks Lakehouse Platform. These partners enable you to leverage Databricks to unify all your data and AI workloads for more meaningful insights.\u201cDatabricks brings the data volume while Tableau brings the rapid visualization. These solutions work perfectly in tandem at the core of our platform to give our clients the performance they need to deliver cutting-edge autonomous vehicle capabilities.\u201d\u2014 Patrick McAuliffe, Lead Engineer, InciteCloud PartnersDatabricks runs on AWS, Microsoft Azure, Google Cloud and Alibaba Cloud, with deep integration to each provider\u2019s infrastructure, data and AI servicesLearn moreTechnology PartnersTechnology partners integrate their solutions with Databricks to provide complementary capabilities for ETL, data ingestion, BI, ML and governanceLearn moreConsulting PartnersConsulting partners are experts uniquely positioned to help you strategize, implement and scale data, analytics and AI initiatives with DatabricksLearn moreBecome a partnerOur partners work together with Databricks to build and deliver innovative solutions for customers. Join the Databricks Partner Program and get access to exclusive tools, training, Solution Accelerators and go-to-market programs.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/delta-lake-on-databricks","text":"Delta Lake su Databricks - Programma una demo oggi stesso!Skip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDelta LakeAffidabilit\u00e0, sicurezza e prestazioni per il data lakeProva gratuitaguarda la demoChe cos'\u00e8 Delta Lake?Delta Lake \u00e8 un livello di storage con formato aperto che offre affidabilit\u00e0, sicurezza e prestazioni per il data lake, per operazioni sia in streaming sia in batch. Sostituendo i silos di dati con un'unica sede per dati strutturati, semi-strutturati e non strutturati, Delta Lake costituisce le fondamenta di una lakehouse altamente scalabile con costi contenuti.Dati affidabili di alta qualit\u00e0Crea un'unica fonte affidabile per tutti i dati, inclusi i flussi\u00a0in tempo reale, in modo che i team possano lavorare sempre sui dati pi\u00f9 aggiornati. Grazie al supporto di transazioni ACID e all'applicazione di schemi, Delta Lake offre l'affidabilit\u00e0 che solitamente manca ai data lake tradizionali. Si possono cos\u00ec ottenere informazioni approfondite dai dati in tutta l'organizzazione, effettuare analisi e realizzare altri progetti con i dati direttamente sul data lake aziendale, per estrapolare informazioni fino a\u00a050 volte pi\u00f9 velocemente.Condivisione di dati aperta e sicuraDelta Sharing\u00a0\u00e8 il primo protocollo aperto per la condivisione sicura dei dati, che semplifica la condivisione con altre organizzazioni indipendentemente dal luogo in cui i dati risiedono. L'integrazione nativa con\u00a0Unity Catalog\u00a0consente di gestire e revisionare centralmente i dati condivisi fra diverse organizzazioni. Si possono cos\u00ec condividere in modo sicuro dati con fornitori e partner, per coordinare meglio le attivit\u00e0 rispettando al tempo stesso le esigenze di sicurezza e conformit\u00e0. Le integrazioni con gli strumenti e le piattaforme pi\u00f9 diffusi consentono di visualizzare, interrogare, arricchire e governare i dati condivisi utilizzando gli strumenti preferiti.Prestazioni velocissimeBasato su Apache Spark\u2122, Delta Lake offre scalabilit\u00e0 e velocit\u00e0 elevate. Inoltre, essendo ottimizzato con funzionalit\u00e0 ad alte prestazioni come l'indicizzazione, Delta Lake ha garantito ad alcuni clienti l'esecuzione di carichi di lavoro ETL con tempi fino al 48% pi\u00f9 rapidi.Aperto e agileTutti i dati in Delta Lake sono conservati nel formato aperto Apache Parquet, che rende i dati leggibili con qualsiasi lettore compatibile. Le API sono aperte e compatibili con Apache Spark. Con Delta Lake su Databricks, avrai accesso a un vasto ecosistema open-source ed eviterai l'isolamento dei dati causato dall'utilizzo di formati proprietari.Ingegneria dei dati automatizzata e affidabileSemplifica l'ingegneria dei dati con Delta Live Tables \u2013 un modo semplice per costruire e gestire pipeline di dati per avere dati freschi di alta qualit\u00e0 su Delta Lake. La soluzione aiuta i team di ingegneria dei dati semplificando lo sviluppo e la gestione delle attivit\u00e0 ETL attraverso lo sviluppo di pipeline dichiarative, una maggiore affidabilit\u00e0 dei dati e attivit\u00e0 produttive in cloud, per contribuire alla costruzione della piattaforma lakehouse.Sicurezza e governance su larga scalaDelta Lake riduce il rischio mediante un controllo degli accessi granulare per la governance dei dati, una funzionalit\u00e0 normalmente non disponibile sui data lake. I dati nel data lake possono essere aggiornati in modo rapido e preciso per garantire la conformit\u00e0 a regolamenti come il GDPR e mantenere una governance migliore attraverso un registro delle modifiche. Queste funzionalit\u00e0 sono integrate in maniera nativa e potenziate su Databricks nell'ambito di Unity Catalog, il primo data catalog multicloud per il Lakehouse.Casi d'usoBusiness Intelligence sui datiMetti istantaneamente a disposizione dati nuovi in tempo reale per le query degli analisti, per ottenere informazioni immediate sull'attivit\u00e0 dell'azienda facendo girare i carichi di lavoro di business intelligence direttamente sul data lake. Delta Lake consente di gestire un'architettura lakehouse multicloud che offre le prestazioni di un data warehouse al costo di un data lake, con un rapporto prezzo\/prestazioni per i carichi di lavoro SQL fino a 6 volte migliore rispetto ai tradizionali data warehouse in cloud.Maggiori informazioniUnificare batch e streamingEsegui operazioni in batch e in streaming su un'unica architettura semplificata che evita sistemi complessi e ridondanti e sfide operative. In Delta Lake, una tabella \u00e8 sia una tabella batch, sia una sorgente e destinazione (source and sink) di streaming. Acquisizione di dati in streaming, caricamento di dati storici in batch e query interattive sono tutte operazioni che funzionano \"out of the box\" e si integrano direttamente con Spark Structured Streaming.Rispettare le disposizioni normativeDelta Lake elimina i problemi di acquisizione di dati distorti, difficolt\u00e0 nella cancellazione di dati per garantire la conformit\u00e0 o problemi di modifica dei dati per acquisire i dati variati. Delta Lake offre transazioni ACID sui data lake per garantire che ogni operazione vada a buon fine oppure venga completamente annullata per essere ripetuta in un secondo tempo, senza richiedere la creazione di nuove pipeline di dati. Inoltre, Delta Lake registra tutte le transazioni passate effettuate sul data lake, agevolando l'accesso e l'utilizzo di versioni precedenti dei dati a scopo di conformit\u00e0 a regolamenti quali GDPR e CCPA.Data Ingestion NetworkI connettori nativi acquisiscono facilmente i dati in Delta Lake, in modo veloce e affidabile, da tutte le applicazioni, tutti i database e tutti i sistemi di storage di file.Clienti\u201cDatabricks ci ha garantito il time-to-market e i miglioramenti nelle attivit\u00e0 analitiche e operative di cui avevamo bisogno per rispondere alle nuove esigenze del settore della sanit\u00e0\u201d.\n\u2013 Peter James, Chief Architect, Healthdirect AustraliaMaggiori informazioni\"Sfruttando Databricks e Delta Lake, siamo gi\u00e0 riusciti a democratizzare i dati su larga scala, riducendo al tempo stesso i costi di esecuzione dei carichi di lavoro in produzione del 60%, con un risparmio di milioni di dollari\u201d.\n\u2014 Steve Pulec, Chief Technology Officer, YipitData\nMaggiori informazioni \u2192Maggiori informazioni\u201cDelta Lake offre funzionalit\u00e0 ACID che semplificano le attivit\u00e0 sulla pipeline dei dati, aumentando l'affidabilit\u00e0 della pipeline stessa e l'omogeneit\u00e0 dei dati. Al tempo stesso, funzionalit\u00e0 come la memorizzazione nella cache e l'autoindicizzazione offrono un accesso efficiente ai dati\u201d.\n\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearMaggiori informazioni\u201cDelta Lake ha creato un approccio snello alla gestione delle pipeline di dati. Questo ha portato a una riduzione dei costi operativi, accelerando al tempo stesso le tempistiche per acquisire informazioni approfondite per le analisi e la data science a valle\u201d.\n\u2014 Parijat Dey, Assistant Vice President of Digital Transformation and Technology, Viacom18Maggiori informazioniRisorse\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video sui vantaggi del data engineering con Databricks.\nEsplora risorseeBookIl grande libro dei casi d'uso dell'ingegneria dei datiGovernance di dati, analisi e intelligenza artificialeTutto sulla gestione dei datiCostruire il Data Lakehouse, di Bill Inmon, padre del data warehouseDibattiti tecnici e formazionePrimi passi con Delta Lake \u2013 Serie Tech TalkWebinarIl buono, il brutto, il cattivoTuffati nel lakehouse con Delta LakePronto per cominciare?Prova Databricks gratisDocumentazione Delta LakeProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/financial-services","text":"Lakehouse f\u00fcr Finanzdienstleistungen | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse f\u00fcr FinanzdienstleistungenDas daten- und KI-gesteuerte Finanzdienstleistungsinstitut der ZukunftErste SchrittePlanen Sie eine DemoVier Datenherausforderungen im FinanzdienstleistungsbereichData-Governance und Datenmanagement\nMangelnde Datenflexibilit\u00e4t und Modellreproduzierbarkeit erschweren die Erf\u00fcllung der f\u00fcr Finanzdienstleistungen geltenden gesetzlichen Anforderungen.Tiefere Kundeneinblicke\nDatensilos verhindern einen vollst\u00e4ndigen \u00dcberblick \u00fcber das Kundenverhalten, Cross-Selling-M\u00f6glichkeiten und die Einblicke, die f\u00fcr eine Hyperpersonalisierung im gro\u00dfen Ma\u00dfstab erforderlich sind.Entscheidungen in Echtzeit\nAnbieterabh\u00e4ngige und unzusammenh\u00e4ngende Tools behindern die F\u00e4higkeit, Echtzeitanalysen durchzuf\u00fchren, die intelligentere finanzielle Entscheidungen f\u00f6rdern und demokratisieren.Zugriff auf Daten von Drittanbietern\nHerk\u00f6mmliche Technologien sind nicht in der Lage, Finanz- und Kundeninformationen aus den schnell wachsenden unstrukturierten und alternativen Datens\u00e4tzen zu nutzen und bieten keine offenen Datenaustauschfunktionen, die die Zusammenarbeit f\u00f6rdern.Lakehouse f\u00fcr FinanzdienstleistungenEinheitliche Daten- und KI-Plattform\nEine einzige Plattform, die alle Ihre Daten- und Analytics-Workloads zusammenf\u00fchrt, um transformative Innovationen f\u00fcr moderne Finanzdienstleister zu erm\u00f6glichen.\n\u00a0\nL\u00f6sungen von Partnern\nDie weltweit f\u00fchrenden L\u00f6sungsanbieter erstellen Lakehouses f\u00fcr Finanzdienstleistungen. Nutzen Sie vorgefertigte Angebote, die die datengesteuerte Transformation beschleunigen.\nTools zur Beschleunigung von Gesch\u00e4ftsergebnissen\nDatabricks und seine Partner haben eine umfassende Palette von L\u00f6sungsbeschleunigern entwickelt, die es ihnen erleichtern, g\u00e4ngige Anwendungsf\u00e4lle f\u00fcr Finanzdienstleistungen zu bew\u00e4ltigen \u2013 von ESG-Investitionen bis hin zur Betrugspr\u00e4vention.\nBranchenzusammenarbeit\nErm\u00f6glichen Sie einen sicheren und offenen Datenaustausch mit unserem Daten-\u00d6kosystem, zu dem S&P Global, Intercontinental Exchange, FactSet und Nasdaq geh\u00f6ren, um Innovationen freizusetzen, die eine nachhaltige Wertsch\u00f6pfung f\u00f6rdern.\nTransformation von Finanzdienstleistungen mit Lakehouse\n\u201eDie Daten- und KI-Vision von Nasdaq wird von Databricks Lakehouse unterst\u00fctzt. Wir verwenden es, um riesige Mengen komplexer Finanz- und alternativer Daten zu verarbeiten und so Daten und Einblicke f\u00fcr unsere Kunden zu gewinnen. Databricks ist auch ein wichtiger Teil unserer Bem\u00fchungen, die Datenbereitstellung und -nutzung zu modernisieren. Es erm\u00f6glicht uns die nahtlose Bereitstellung von Daten direkt in analytische Arbeitsbereiche, sodass unsere Kunden gesch\u00e4ftskritische Daten schnell analysieren und integrieren k\u00f6nnen, ohne Terabytes von Daten bewegen zu m\u00fcssen.\u201c\u2013 Bill Dague, Head of Nasdaq Data Link, NasdaqWarum Lakehouse f\u00fcr Finanzdienstleistungen?\nVereinigen Sie Daten und KI auf einer offenen und kollaborativen Plattform, die es Ihnen erm\u00f6glicht, Risiken zu minimieren, hervorragende Kundenerlebnisse zu liefern und Innovationen zu beschleunigen.Geregelter Ansatz f\u00fcr Risikomanagement und Compliance\nVereinfachen Sie die Komplexit\u00e4t des regulatorischen Berichtswesens, des Risikomanagements und der Einhaltung von Vorschriften, indem Sie die Erfassung, Verarbeitung und \u00dcbertragung von Daten sicher rationalisieren, um bessere Data-Governance-Verfahren zu erm\u00f6glichen.Personalisierte Produkte und Services\nVereinheitlichen Sie eine Vielzahl von Daten \u2013 von Markt- bis hin zu alternativen Daten \u2013 und erm\u00f6glichen Sie so extrem personalisierte Erlebnisse, die Cross-Selling-Chancen, Kundenzufriedenheit und Share of Wallet f\u00f6rdern.Einblicke in Echtzeit, intelligentere Entscheidungen\nErfassen Sie schnell und in gro\u00dfem Umfang alle Ihre Datenquellen, um bessere Investitionsentscheidungen zu treffen, neue Betrugsmuster schnell zu erkennen und Echtzeitfunktionen f\u00fcr das Risikomanagement bereitzustellen.Offener Datenaustausch und Datenmonetarisierung\nBringen Sie gro\u00dfe Mengen interner und externer Daten zusammen, um innovative Finanzl\u00f6sungen auszutauschen, neue Datenprodukte zu monetarisieren und fortschrittliche Analytics-Funktionen f\u00fcr jede Cloud oder jedes Tool bereitzustellen, ohne sich an propriet\u00e4re Technologien zu binden.E-Book herunterladenPartner und L\u00f6sungenHinwendung zu offenen Formaten und zur Standardisierung von Daten f\u00fcr Analytics und KIRisikomanagementStellen Sie Daten schnell in Value-at-Risk-Modellen bereit, um mit neuen Risiken und Bedrohungen Schritt zu halten.Erste SchritteModernisierung von Altkarten und zentralen Banking-PortfoliosKonvertieren Sie externe Quellsysteme im Handumdrehen und implementieren Sie eine vollst\u00e4ndig konfigurierbare und industrialisierte Konvertierungsfunktionalit\u00e4t.Erste SchrittePerson 360Vervollst\u00e4ndigen, vereinheitlichen und erfassen Sie Kundenprofile umfassend in einem intelligenten Datenmodell.Erste SchritteAlle Partnerl\u00f6sungen anzeigenCybersicherheit in gro\u00dfem Ma\u00dfstabErkennen Sie Bedrohungen schnell, untersuchen Sie die Auswirkungen und reduzieren Sie Risiken mit Splunk und Databricks.Erste SchritteESG-BewertungVerschaffen Sie sich einen quantitativen \u00dcberblick \u00fcber die Nachhaltigkeit und stellen Sie sicher, dass die Unternehmen f\u00fcr ihr Handeln verantwortlich sind.Erste SchritteModernes RisikomanagementWenden Sie einen agileren Ansatz f\u00fcr das Risikomanagement an, indem Sie Daten und KI im Lakehouse vereinheitlichenErste SchritteIdentifizieren von Betrug mit Geodaten-Analytics und KINutzen Sie Geodaten, um das Ausgabeverhalten der Kunden besser zu verstehen, sowohl in Bezug auf ihre Person als auch in Bezug auf ihre Bankgesch\u00e4fte.Erste SchritteAnreicherung von Transaktionen mit H\u00e4ndlerklassifizierungAutomatisieren Sie die Transaktionsanreicherung, um das Verhalten Ihrer Kunden besser zu verstehen und die Personalisierung voranzutreiben.Erste SchritteRegelbasierte KI-Modelle zur Bek\u00e4mpfung von FinanzbetrugModernisieren Sie Betrugsverhinderungsstrategien, um Betriebskosten zu senken und das Vertrauen der Kunden zu st\u00e4rken.Erste SchritteRechtzeitige und zuverl\u00e4ssige \u00dcbermittlung von Meldungen an die Beh\u00f6rdenKombinieren Sie Datenmodelle der Finanzdienstleistungsbranche mit der Cloud, um hohe Governance-Standards mit geringem Entwicklungsaufwand zu erm\u00f6glichen.Erste SchritteModernisierung von InvestitionsdatenplattformenNutzen Sie die volle Leistungsf\u00e4higkeit der Finanzmarktdaten, um sich auf die Produktbereitstellung f\u00fcr Kunden zu konzentrieren.Erste SchritteGeldw\u00e4schebek\u00e4mpfungErm\u00f6glichen Sie KI-gesteuerte Anwendungsf\u00e4lle wie Fuzzy-Match und Bildanalysen, um Geldw\u00e4sche und finanziellen Terrorismus zu bek\u00e4mpfen.Erste SchritteAlle L\u00f6sungen anzeigenLakehouse f\u00fcr Finanzdienstleistungen in AktionGemeinsam gewinnen: Wie Daten und KI die Zusammenarbeit im Lakehouse f\u00f6rdernJETZT REGISTRIEREN\u00a0\u2192Ressourcen\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu Daten und KI f\u00fcr Finanzdienstleistungen.\nRessourcen erkundeneBooks und Infografiken[Infografik] Daten, um ein neues Zeitalter des Risikomanagements zu verankernErfahren Sie, wie Sie die Macht von Daten und KI im Finanzdienstleistungsbereich einfach nutzen k\u00f6nnen.Alternative und fremde Daten bei Finanzdienstleistungen nutzen \u2192ESG mit Data Analytics und KI vom Modewort zur Realit\u00e4t machen \u2192 Betrugspr\u00e4vention mit Daten und k\u00fcnstlicher Intelligenz: Ein Leitfaden f\u00fcr moderne Bedrohungen \u2192 Videos und DownloadsSchl\u00fcssige und transparente ESG-Anlagemethoden\u00a0\u2192Cybersicherheit im Finanzdienstleistungsbereich\u00a0\u2192Daten- und KI-gesteuerte Innovationen im Finanzdienstleistungsbereich beschleunigen\u00a0\u2192ESG-Analytics: Erkl\u00e4rungsvideo \u2192Risikomanagement modernisieren \u2192Moderne Dateninvestitionsplattformen mit Lakehouse f\u00fcr Finanzdienstleistungen\u00a0\u2192L\u00f6sungsblatt zu Industry Lakehouse BlueprintsBlogsAccelerator f\u00fcr Banken und Fintechs mit KreditkartentransaktionenEin datengest\u00fctzter Ansatz f\u00fcr Umwelt, Soziales und Governance \u2192Eine moderne Risikomanagement-Plattform im Finanzdienstleistungsbereich entwickeln \u2192Ihre Daten verwenden, um Kreditkartenbetrug zu stoppen: Capital One und andere bew\u00e4hrte Methoden \u2192Strategien f\u00fcr die Modernisierung von InvestitionsdatenplattformenKundenerlebnis mit Transaktionsanreicherung verbessern \u2192 Wichtige Erkenntnisse f\u00fcr Finanzdienstleister auf dem Data and AI Summit 2022\u00a0\u2192Lakehouse f\u00fcr FinanzdienstleistungenM\u00f6chten Sie loslegen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENPlanen Sie eine DemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/oz-katz\/#","text":"Oz Katz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOz KatzCTO @ Treeverse, co-creator of lakeFS at Treeverse LTDBack to speakersOz Katz is the CTO and Co-founder of Treeverse, the company behind lakeFS, an open source platform that delivers resilience and manageability to object-storage based data lakes. Oz engineered and managed petabyte-scale data infrastructure at analytics giant SimilarWeb (NYSE: SMWB), which he joined after the acquisition of Swayy.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/kr\/blog","text":"Databricks \ube14\ub85c\uadf8Skip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWLoading...\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\u0000\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/preventing-fraud-with-data-ai","text":"Preventing fraud with Data + AI | DatabrickseBookPreventing fraud with Data + AIA primer for modern threatsFraud is a costly and growing problem. For every $1 of fraud, companies pay 3.36x in chargebacks and replacement and operational costs. Identity fraud losses soared to $56 billion in 2020.Fraudsters continue to increase the scale, speed and sophistication of attacks \u2014 from 2019 to 2020, fraud grew at an average rate of 33% \u2014 threatening the revenue and growth of companies.In this eBook, we cover:Why data and machine learning are ideal applications for fraud preventionHow to future-proof your organization using the Databricks Lakehouse PlatformWhat financial services leaders are doing with data and AI to combat fraudGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/board-of-directors","text":"Databricks \uc774\uc0ac\ud68c | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 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(United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/kr\/korea","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricing2023\ub144 6\uc6d4 26\uc77c (\uc6d4) ~ 29\uc77c (\ubaa9) Data + AI Summit 2023\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \ucee4\ubba4\ub2c8\ud2f0\ub97c \uc704\ud55c \uae00\ub85c\ubc8c \uc774\ubca4\ud2b8\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uae00\ub85c\ubc8c \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \ucee4\ubba4\ub2c8\ud2f0\ub97c \uc704\ud55c \uc774\ubca4\ud2b8\uac00 6\uc6d4 26\uc77c(\uc6d4)\ubd80\ud130 29\uc77c(\ubaa9)\uae4c\uc9c0 \uc0cc\ud504\ub780\uc2dc\uc2a4\ucf54\uc5d0\uc11c \uac1c\ucd5c\ub429\ub2c8\ub2e4. \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc5c5\uacc4\uc640 \uc0b0\uc5c5\uc744 \uc120\ub3c4\ud558\ub294 \uacbd\uc601\uc9c4\uacfc 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1\uc77c \ub610\ub294 2\uc77c\uc758 \uc790\uaca9\uc99d \uc2dc\ud5d8 \uacfc\uc815\uc774 \ud3ec\ud568\ub41c \uc0c8\ub85c\uc6b4 \ubc88\ub4e4\ub85c \uc778\uc99d\uc744 \ubc1b\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\n\uad50\uc721 \ub458\ub7ec\ubcf4\uae30\uc131\uc7a5\uc804\ubb38\uac00 \ub124\ud2b8\uc6cc\ud06c\ub97c \ud655\ub300\ud558\uace0 \ube0c\ub808\uc774\ud06c\uc544\uc6c3 \uc138\uc158, \ubaa8\uc784 \uc774\ubca4\ud2b8 \ubc0f \uc18c\uc15c \uacf5\uac04\uc5d0\uc11c \ub2e4\ub978 \ub370\uc774\ud130 \ubc0f AI \uc2e4\ubb34\uc790\ub4e4\uacfc \uad50\ub958\ud574 \ubcf4\uc138\uc694.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub97c \uc801\uc6a9\ud558\uc5ec \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\ub97c \ud558\ub098\uc758 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ud1b5\ud569\ud55c \uc131\uacf5\uc0ac\ub840\ub97c \uc54c\uc544\ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. 50,000\uba85 \uc774\uc0c1\uc758 \ub370\uc774\ud130 \uc804\ubb38\uac00\uac00 Data + AI Summit \uacbd\ud5d8\uc5d0 \ucc38\uc5ec\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.\nTwitter\uc5d0\uc11c \uc18c\ud1b5\ud558\uae30\uc544\uc820\ub2e42023\ub144 6\uc6d4 26\uc77c \uc6d4\uc694\uc77c\uc0ac\uc804 \ucee8\ud37c\ub7f0\uc2a4 \uad50\uc721\n\uc790\uaca9\uc99d \uc2dc\ud5d8\n2023\ub144 6\uc6d4 27\uc77c \ud654\uc694\uc77c\uc0ac\uc804 \ucee8\ud37c\ub7f0\uc2a4 \uad50\uc721\n\ub124\ud2b8\uc6cc\ud0b9\n\uc790\uaca9\uc99d \uc2dc\ud5d8\nMeet Up\n2023\ub144 6\uc6d4 28\uc77c \uc218\uc694\uc77c\uae30\uc870 \uc5f0\uc124\n\ube0c\ub808\uc774\ud06c\uc544\uc6c3\n\uc5d1\uc2a4\ud3ec \ud640\n\uc0b0\uc5c5\ubcc4 \uc138\ubd80 \ud3ec\ub7fc\n\uc790\uaca9\uc99d \uc2dc\ud5d8\n\ud658\uc601 \ub9ac\uc149\uc158\n2023\ub144 6\uc6d4 29\uc77c \ubaa9\uc694\uc77c\uae30\uc870 \uc5f0\uc124\n\ube0c\ub808\uc774\ud06c\uc544\uc6c3\n\uc5d1\uc2a4\ud3ec \ud640\n\uc0b0\uc5c5\ubcc4 \uc138\ubd80 \ud3ec\ub7fc\n\uc790\uaca9\uc99d \uc2dc\ud5d8\n\ud074\ub85c\uc9d5 \ud30c\ud2f0\n\uc9c0\uae08 \ub4f1\ub85d \ubc0f \ucc38\uac00 \uc2e0\uccad\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-shtelma\/#","text":"Michael Shtelma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael ShtelmaLead Specialist Solutions Architect at DatabricksBack to speakersMichael Shtelma is a Lead Specialist Solutions Architect at Databricks. Michael focuses on developing and operationalizing large-scale Machine Learning use cases on the Databricks platform. Before Databricks, Michael worked for Teradata, helping Teradata customers build data and machine learning solutions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sunil-ranganathan","text":"Sunil Ranganathan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSunil RanganathanDirector, MLOPs at TredenceBack to speakersSunil is an experienced product leader with over 18 years of experience in building data analytics and AI\/ML based products and solutions. In his current role at Tredence Analytics, he is responsible for leading the MLOPs practice and building out industry specific AI\/ML solutions. In his earlier role at 247.ai, Sunil was focused on building ML based products in the Conversational AI space.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/datascience-ml","text":"Data Science & ML Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Science & ML PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorAll-Purpose Compute for Interactive WorkloadsRun interactive data science and machine learning workloads. Also good for data engineering, BI and data analytics.Select planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudLoading...Compare featuresProduct FeatureAll-Purpose ComputeAll-Purpose Compute PhotonManaged Apache SparkPhoton Engine\n(Massively parallel processing)Job Scheduling with LibrariesJob Scheduling with NotebooksAutopilot ClustersDatabricks Runtime for MLManaged MLflowDelta Lake with Delta EngineNotebooks and CollaborationEcosystem IntegrationsBroad Support of Different VM Instance TypesYes\n(See the Pricing calculator for hourly DBU emission by instance type)\nYes\n(DBU emission rate 2.0x vs. non-Photon. See the Pricing calculator.)\nGovernance and ManageabilitySee Platform Capabilities and Add-Ons for detailsEnterprise SecuritySee Platform Capabilities and Add-Ons for detailsPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements.\nCalculate priceStart free trialContact usFAQWhat is Photon? Photon is the next-generation engine on the Databricks Lakehouse Platform that provides extremely fast query performance at low cost.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/industries\/federal-government","text":"\u9023\u90a6\u653f\u5e9c\u6a5f\u95a2\u5411\u3051\u30c7\u30fc\u30bf\u5206\u6790\u30fbAI | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 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{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/08\/announcing-the-availability-of-data-lineage-with-unity-catalog.html","text":"Automated and Real-time Data Lineage With Unity Catalog - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing the Availability of Data Lineage With Unity Catalogby Paul Roome, Tao Feng and Sachin ThakurJune 8, 2022 in Platform BlogShare this postUpdate: Data Lineage is now generally available on AWS and Azure.We are excited to announce that data lineage for Unity Catalog, the unified governance solution for all data and AI assets on lakehouse, is now available in preview.This blog will discuss the importance of data lineage, some of the common use cases, our vision for better data transparency and data understanding with data lineage, and a sneak peek into some of the data provenance and governance features we\u2019re building.What is data lineage and why is it important?Data lineage describes the transformations and refinements of data from source to insight. Lineage includes capturing all the relevant metadata and events associated with the data in its lifecycle, including the source of the data set, what other data sets were used to create it, who created it and when, what transformations were performed, what other data sets leverage it, and many other events and attributes. With a data lineage solution, data teams get an end-to-end view of how data is transformed and how it flows across their data estate.As more and more organizations embrace a data-driven culture and set up processes and tools to democratize and scale data and AI, data lineage is becoming an essential pillar of a pragmatic data management and governance strategy.To understand the importance of data lineage, we have highlighted some of the common use cases we have heard from our customers below.Impact analysisData goes through multiple updates or revisions over its lifecycle, and understanding the potential impact of any data changes on downstream consumers becomes important from a risk management standpoint. With data lineage, data teams can see all the downstream consumers \u2014 applications, dashboards, machine learning models or data sets, etc. \u2014 impacted by data changes, understand the severity of the impact, and notify the relevant stakeholders. Lineage also helps IT teams proactively communicate data migrations to the appropriate teams, ensuring business continuity.Data understanding and transparencyOrganizations deal with an influx of data from multiple sources, and building a better understanding of the context around data is paramount to ensure the trustworthiness of the data. Data lineage is a powerful tool that enables data leaders to drive better transparency and understanding of data in their organizations. Data lineage also empowers data consumers such as data scientists, data engineers and data analysts to be context-aware as they perform analyses, resulting in better quality outcomes. Finally, data stewards can see which data sets are no longer accessed or have become obsolete to retire unnecessary data and ensure data quality for end business users .Debugging and diagnosticsYou can have all the checks and balances in place, but something will eventually break. Data lineage helps data teams perform a root cause analysis of any errors in their data pipelines, applications, dashboards, machine learning models, etc. by tracing the error to its source. This significantly reduces the debugging time, saving days, or in many cases, months of manual effort.Compliance and audit readinessMany compliance regulations, such as the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Health Insurance Portability and Accountability Act (HIPPA), Basel Committee on Banking Supervision (BCBS) 239, and Sarbanes-Oxley Act (SOX), require organizations to have clear understanding and visibility of data flow. As a result, data traceability becomes a key requirement in order for their data architecture to meet legal regulations. Data lineage helps organizations be compliant and audit-ready, thereby alleviating the operational overhead of manually creating the trails of data flows for audit reporting purposes.Effortless transparency and proactive control with data lineageThe lakehouse provides a pragmatic data management architecture that substantially simplifies enterprise data infrastructure and accelerates innovation by unifying your data warehousing and AI use cases on a single platform. We believe data lineage is a key enabler of better data transparency and data understanding in your lakehouse, surfacing the relationships between data, jobs, and consumers, and helping organizations move toward proactive data management practices. For example:As the owner of a dashboard, do you want to be notified next time that a table your dashboard depends upon wasn\u2019t loaded correctly?As a machine learning practitioner developing a model, do you want to be alerted that a critical feature in your model will be deprecated soon?As a governance admin, do you want to automatically control access to data based on its provenance?All of these capabilities rely upon the automatic collection of data lineage across all use cases and personas \u2014 which is why the lakehouse and data lineage are a powerful combination.Here are some of the features we are shipping in the preview:Data lineage for tablesData lineage for table columnsData Lineage for notebooks, workflows, dashboardsBuilt-in security: Lineage graphs in Unity Catalog are privilege-aware and share the same permission model as Unity Catalog. If users do not have access to a table, they will not be able to explore the lineage associated with the table, adding an additional layer of security for privacy considerations.Easily exportable via REST API: Lineage can be visualized in the Data Explorer in near real-time, and retrieved via REST API to support integrations with our catalog partners.Getting started with data lineage in Unity CatalogData lineage is available with Databricks Premium and Enterprise tiers for no additional cost. If you already are a Databricks customer, follow the data lineage guides (AWS | Azure) to get started. If you are not an existing Databricks customer, sign up for a free trial with a Premium or Enterprise workspace.Try Databricks for freeGet StartedRelated postsAnnouncing Gated Public Preview of Unity Catalog on AWS and AzureApril 20, 2022 by Matei Zaharia, Jonathan Keller, Zeashan Pappa and Sachin Thakur in Product\nUpdate: Unity Catalog is now generally available on AWS and Azure. At the Data and AI Summit 2021, we announced Unity Catalog, a...\nEvolution to the Data LakehouseMay 19, 2021 by Bill Inmon and Mary Levins in Data Strategy\nThis is a guest authored article by the data team at Forest Rim Technology. We thank Bill Inmon, CEO, and Mary Levins, Chief...\nHow Audantic Uses Databricks Delta Live Tables to Increase Productivity for Real Estate Market SegmentsMay 5, 2022 by Joel Lowery, Jitesh Soni, Prithish Mathews and Amit Kara in Platform Blog\nThis is a collaborative post from Audantic and Databricks. We\u2019d like to thank co-author Joel Lowery, Chief Information Officer - Audantic, for his c...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/it\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Clienti di Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWClienti di DatabricksScopri come aziende innovative in tutti i settori utilizzano Databricks Lakehouse Platform per operare con successoStorie in evidenza\n\n\nCustomer Story\n\nAT&T democratizes data to prevent fraud, reduce churn and increase CLV\nDatabricks Lakehouse has helped AT&T accelerate AI across operations, including decreasing fraud by 70%\u201380%\n\nRead more\n\n\nREFERENZA\n\nShell innova con soluzioni energetiche per un mondo pi\u00f9 pulito\nDatabricks Lakehouse aiuta a democratizzare i dati e modernizzare le operazioni a livello globale\n\nPer saperne di pi\u00f9\n\n\nCustomer Story\n\nBurberry adopts data-driven content creation\nBurberry sees a 70% improvement in time savings for generating image insights with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nABN AMRO transforms banking on a global scale\nABN AMRO puts data and Al into action with Databricks Lakehouse\n\nRead more\n\n\nCustomer Story\n\nRolls-Royce delivers a greener future for air travel\nRolls-Royce decreases carbon through real-time data collection with Databricks Lakehouse\n\nWatch video\n\n\nCustomer Story\n\nSEGA drives the future of gaming with data and Al\nSEGA uses Databricks Lakehouse to democratize data and deliver gaming experiences at scale\n\nWatch videoScopri tutti i clientiL'effetto team di datiI team di gestione dei dati sono la forza coesa che risolve i problemi pi\u00f9 complessi del mondo.Scopri come \u2192La tua pu\u00f2 essere la prossima storia di successoContattiRisorseREFERENZAScopri come Databricks aiuta Cond\u00e9 Nast a proporre contenuti personalizzati ai propri clienti.Maggiori informazioniWebinarScopri come Apple e Disney+ hanno unificato con successo analisi e AIGuardaPodcastIl ruolo dei dati e dell'IA nell'equit\u00e0 dell'assistenza sanitaria \u00e8 stato illustrato dal CDAO di HumanaGuardaPronto per cominciare?Prova gratuitaContattiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/blog\/2021\/07\/16\/aml-solutions-at-scale-using-databricks-lakehouse-platform.html","text":"Enhanced AML Transaction Monitoring With the Lakehouse Platform - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAML Solutions at Scale Using Databricks Lakehouse Platformby Sri Ghattamaneni, Ricardo Portilla and Anindita MahapatraJuly 16, 2021 in Engineering BlogShare this postAnti-Money Laundering (AML) compliance has been undoubtedly one of the top agenda items for regulators providing oversight of financial institutions across the globe. As AML evolved and became more sophisticated over the decades, so have the regulatory requirements designed to counter modern money laundering and terrorist financing schemes. The Bank Secrecy Act of 1970 provided guidance and framework for financial institutions to put in proper controls to monitor financial transactions and report suspicious fiscal activity to relevant authorities. This law provided set the framework for how financial institutes combat money laundering and financial terrorism.Why anti-money laundering is so complexCurrent AML operations bear little resemblance to those of the last decade. The shift to digital banking, with financial institutions (FI's) processing billions of transactions daily, has resulted in the ever increasing\u00a0 scope of money laundering,\u00a0 even with stricter transaction\u00a0 monitoring systems and robust Know Your Customer (KYC) solutions. In this blog, we\u00a0 share our experiences working with our FI customers to build\u00a0 enterprise-scale AML solutions on the\u00a0 lakehouse platform that both provides strong oversight and delivers innovative, scalable solutions to adapt to the reality of modern online money laundering threats.Building an AML solution with lakehouseThe operational burden of processing billions of transactions a day comes from the need to store the data from multiple sources and power intensive, next-gen AML solutions. These solutions provide powerful risk analytics and reporting while supporting the use of\u00a0 advanced machine learning models to reduce false positives and improve downstream investigation efficiency. FIs have already taken steps to solve the infrastructure and scaling problems by moving from on-premises to cloud for better security, agility and the economies of scale required to store massive amounts of data.But then there is the issue of how to make sense of the massive amounts of structured and unstructured data collected and stored on cheap object storage. While cloud vendors provide an inexpensive way to store the data, making sense of the data for downstream AML risk management and compliance activities starts with storage of the data in high-quality and performant formats for downstream consumption. The Databricks Lakehouse Platform does exactly this. By combining the low storage cost benefits of data lakes with the robust transaction capabilities of data warehouses, FIs can truly build the modern AML platform.On top of the data storage challenges outlined above, AML analysts face some key domain-specific challenges:Improve time-to-value parsing unstructured data such as images, textual data and network linksReduce DevOps burden for supporting critical ML capabilities such as entity resolution, computer vision and graph analytics on entity metadataBreak down silos by introducing analytics engineering and dashboarding layer on AML transactions and enriched tablesLuckily, Databricks helps solve these by leveraging Delta Lake to store and combine both unstructured and structured data to build entity relationships; moreover, Databricks' Delta engine provides efficient access using the new Photon compute to speed up BI queries on tables. On top of these capabilities, ML is a first-class citizen in lakehouse, which means analysts and data scientists do not waste time subsampling or moving data to share dashboards and stay one-step ahead of bad actors.Detecting AML patterns with graph capabilitiesOne of the main data sources that AML analysts use as part of a case is transaction data. Even though this data is tabular and easily accessible with SQL, it becomes cumbersome to track chains of transactions that are three or more layers deep with SQL queries. For this reason, it is important to have a flexible suite of languages and APIs to express simple concepts such as a connected network of suspicious individuals transacting illegally together. Luckily, this is simple to accomplish using GraphFrames, a graph API pre-installed in the Databricks Runtime for Machine Learning.\u00a0In this section, we will show how graph analytics can be used to detect AML schemes such as synthetic identity and layering \/ structuring. We are going to utilize a dataset consisting of transactions, as well as entities derived from transactions, to detect the presence of these patterns with Apache Spark\u2122, GraphFrames and Delta Lake. The persisted patterns are saved in Delta Lake so that Databricks SQL can be applied on the gold-level aggregated versions of these findings, offering the power of graph analytics to end-users.Scenario 1 -- Synthetic identitiesAs mentioned above, the existence of synthetic identities can be a cause for alarm. Using graph analysis, all of the entities from our transactions can be analyzed in bulk to detect a risk level. In our analysis, this is done in three phases:Based on the transaction data, extract the entitiesCreate links between entities based on address, phone number or emailUse GraphFrames connected components to determine whether multiple entities (identified by an ID and other attributes above) are connected via one or more links.Based on how many connections (i.e. common attributes) exist between entities, we can assign a lower or higher risk score and create an alert based on high-scoring groups. Below is a basic representation of this idea.First, we create an identity graph using an address, email and phone number to link individuals if they match any of these attributes.\ne_identity_sql = '''\nselect entity_id as src, address as dst from aml.aml_entities_synth  where address is not null\nUNION\nselect entity_id as src, email as dst from aml.aml_entities_synth  where email_addr is not null\nUNION\nselect entity_id as src, phone as dst from aml.aml_entities_synth  where phone_number is not null\n'''\n\nfrom graphframes import *\nfrom pyspark.sql.functions import *\naml_identity_g = GraphFrame(identity_vertices, identity_edges)\nresult = aml_identity_g.connectedComponents()\n\nresult \\\n .select(\"id\", \"component\", 'type') \\\n .createOrReplaceTempView(\"components\")Next, we'll run queries to identify when two entities have overlapping personal identification and scores. Based on the results of these querying graph components, we would expect a cohort consisting of only one matching attribute (such as address), which isn't\u00a0 too much cause for concern. However, as more attributes match, we should expect to be alerted. As shown below, we can flag cases where all three attributes match, allowing SQL analysts to get daily results from graph analytics run across all entities.Scenario 2 - StructuringAnother common pattern is called structuring, which occurs when multiple entities collude and send smaller 'under the radar' payments to a set of banks, which subsequently route larger aggregate amounts to a final institution (as depicted below on the far right). In this scenario, all parties have stayed under the $10,000 threshold amount, which would typically alert authorities. Not only is this easily accomplished with graph analytics, but the motif finding technique can be automated to extend to other permutations of networks and locate other suspicious transactions in the same way.Now we'll write the basic motif-finding code to detect the scenario above using graph capabilities. Note that the output here is semi-structured JSON; all data types, including unstructured types,\u00a0 are easily accessible in the lakehouse -- we will save these particular results for SQL reporting.\nmotif = \"(a)-[e1]->(b); (b)-[e2]->(c); (c)-[e3]->(d); (e)-[e4]->(f); (f)-[e5]->(c); (c)-[e6]->(g)\"\nstruct_scn_1 = aml_entity_g.find(motif)\n\njoined_graphs = struct_scn_1.alias(\"a\") \\\n .join(struct_scn_1.alias(\"b\"), col(\"a.g.id\") == col(\"b.g.id\")) \\\n .filter(col(\"a.e6.txn_amount\") + col(\"b.e6.txn_amount\") > 10000)Using motif finding, we extracted interesting patterns where money is flowing through 4 different entities and kept under a $10,000 threshold. We join our graph metadata back to structured datasets to generate insights for an AML analyst to investigate further.Scenario 3 -- Risk score propagationThe identified high-risk entities will have an influence (a network effect) on their circle. So, the risk score of all the entities that they interact with must be adjusted to reflect the zone of influence. Using an iterative approach, we can follow the flow of transactions to any given depth and adjust the risk scores of others affected in the network. As mentioned previously, running graph analytics avoids multiple repeated SQL joins and complex business logic, which can impact performance due to memory constraints. Graph analytics and Pregel API was built for that exact purpose. Initially developed by Google, Pregel allows users to recursively \"propagate\" messages from any vertex to its corresponding neighbours, updating vertex state (their risk score here) at each step. We can represent our dynamic risk approach using Pregel API as follows.The diagram above shows the starting state of the network and two subsequent iterations. Say we started with one bad actor (Node# 3) with a risk score of 10. We want to penalize all the people who transact with that node (namely Nodes 4, 5 and 6) and receive funds by passing on, for instance, half the risk score of the bad actor, which then is added to their base score. In the next iteration, all nodes that are downstream from Nodes 4, 5, 6 will get their scores adjusted.Node #Iteration #0Iteration #1Iteration #2100020003101010405550556055700580009002.510000\u00a0Using the Pregel API from GraphFrame, we can do this computation and persist the modified scores for other applications downstream to consume.\nfrom graphframes.lib import Pregel\n\nranks = aml_entity_g.pregel \\\n    .setMaxIter(3) \\\n    .withVertexColumn(\n       \"risk_score\", \n       col(\"risk\"), \n       coalesce(Pregel.msg()+ col(\"risk\"),\n       col(\"risk_score\"))\n    ) \\\n    .sendMsgToDst(Pregel.src(\"risk_score\")\/2 )  \\\n    .aggMsgs(sum(Pregel.msg())) \\\n    .run()\nAddress matchingA pattern we want to briefly touch upon is address matching of text to actual street view images. Oftentimes, there is a need for an AML analyst to validate the legitimacy of addresses that are linked to entities on file. Is this address a commercial building, a residential area or a simple postbox? However, analysing pictures is often a tedious, time-consuming and manual process to obtain, clean and validate. A\u00a0 lakehouse data architecture allows us to automate most of this task using Python and ML runtimes with PyTorch and pre-trained open-source models. Below is an example of a valid address to the human eye. To automate validation, we will use a pre-trained VGG model for which there are hundreds of valid objects we can use to detect a residence.Using the code below, which can be automated to run daily, we'll now have a label attached to all our images -- we've loaded all the image references and labels up into a SQL table for simpler querying also. Notice in the code below how simple it is to query a set of images for the objects inside them -- the ability to query such unstructured data with Delta Lake is an enormous time-saver for analysts, and speeds up the validation process to minutes instead of days or weeks.\nfrom PIL import Image\nfrom matplotlib import cm\n\nimg = Image.fromarray(img)\n...\n\nvgg = models.vgg16(pretrained=True)\nprediction = vgg(img)\nprediction = prediction.data.numpy().argmax()\nimg_and_labels[i] = labels[prediction]\nAs we start to summarize, we notice some interesting categories appear. As seen below from the breakdown, there are a few obvious labels such as patio, mobile home and motor scooter we would expect to see as items detected in a residential address. On the other hand, the CV model has labeled a solar dish from surrounding objects in one image. (note: since we are restricted to an open source model not trained on a custom set of images, the solar dish label is not accurate.) Upon further analysis of the image, we drill down and immediately see that i) there is not a real solar dish here and more importantly ii) this address is not a real residence (pictured in our side-by-side comparison above). The Delta Lake format allows us to store a reference to our unstructured data along with a label for simple querying in our classification breakdown below.Entity resolutionThe last category of AML challenges that we'll focus on is entity resolution. Many open-source libraries tackle this problem, so for some basic entity fuzzy matching, we chose to highlight Splink, which\u00a0 achieves the linkage at scale and offers configurations to specify matching columns and blocking rules.In the context of the entities derived from our transactions, it is a simple exercise to insert our Delta Lake transactions into the context of Splink.\nsettings = {\n  \"link_type\": \"dedupe_only\",\n  \"blocking_rules\": [\n      \"l.txn_amount = r.txn_amount\",\n  ],\n  \"comparison_columns\": [  \n      {\n          \"col_name\": \"rptd_originator_address\",\n      },\n      {\n          \"col_name\": \"rptd_originator_name\",\n      }\n  ]\n}\n\nfrom splink import Splink\nlinker = Splink(settings, df2, spark)\ndf2_e = linker.get_scored_comparisons()\nSplink works by assigning a match probability that can be used to identify transactions in which entity attributes are highly similar, raising a potential alert with respect to a reported address, entity name or transaction amount. Given the fact that entity resolution can be highly manual for matching account information, having open-source libraries that automate this task and save the information in Delta Lake can make investigators much more productive for case resolution. While there are several options available for entity matching, we recommend using Locality-Sensitive Hashing (LSH) to identify the right algorithm for the job. You can learn more about LSH and its benefits in this blog post.As reported above, we quickly found some inconsistencies for the NY Mellon bank address, with \"Canada Square, Canary Wharf, London, United Kingdom\" similar to \"Canada Square, Canary Wharf, London, UK\". We can store our de-duplicated records back to a delta table that can be used for AML investigation.AML lakehouse dashboardDatabricks SQL on the lakehouse is closing the gap with respect to traditional data warehouses in terms of simplified data management, performance with new query engine Photon and user concurrency. This is important since many organizations do not have the budget for overpriced proprietary AML software to support the myriad use cases, such as combatting the financing of terrorism (CFT), that help fight financial crime. In the market, there are dedicated solutions that can perform the graph analytics above, dedicated solutions to address BI in a warehouse, and dedicated solutions for ML. The AML lakehouse design unifies all three. AML data platform teams can leverage Delta Lake at the lower cost of cloud storage while easily integrating open source technologies to produce curated reports based on graph technology, computer vision and SQL analytics engineering. Below we will show a materialization of the reporting for AML.The attached notebooks produced a transactions object, entities object, as well as summaries such as structuring prospects, synthetic identity tiers and address classifications using pre-trained models. In the Databricks SQL visualization below, we used our Photon SQL engine to execute summaries on these and built-in visualization to produce a reporting dashboard within minutes. There are full ACLs on both tables, as well as the dashboard itself, to allow users to share with executives and data teams --\u00a0 a scheduler to run this report periodically is also built-in. The dashboard is a culmination of AI, BI and analytics engineering built into the AML solution.The open banking transformationThe rise of open banking enables FIs to provide a better customer experience via data sharing between consumers, FIs and third-party service providers through APIs. An example of this is Payment Services Directive (PSD2), which transformed financial services in the EU region as part of Open Banking Europe regulation. As a result, FIs have access to more data from multiple banks and service providers, including customer account and transaction data. This trend has expanded within the world of fraud and financial crimes with the latest guidance from FinCEN under section 314(b) of USA Patriot Act;\u00a0 covered FIs can now share information with other FIs and within domestic and foreign branches regarding individuals, entities, organizations and so on that are suspected to be involved in potential money laundering.While information sharing provision helps with transparency and protects the United States financial systems against money laundering and terrorism financing, the information exchange must be done using protocols with proper data and security protections. To solve the problem of securing information sharing, Databricks recently announced Delta Sharing, an open and secure protocol for data sharing. Using familiar open source API's, such as Pandas and Spark, data producers and consumers can now share data using secure and open protocols and maintain a full audit of all the data transactions to maintain compliance with FinCEN regulations.ConclusionThe lakehouse architecture is the most scalable and versatile platform to enable analysts in their AML analytics. Lakehouse supports use cases ranging from fuzzy match to image analytics to BI with built-in dashboards, and all of these capabilities will allow organizations to reduce total cost of ownership compared to proprietary AML solutions. The Financial Services team at Databricks is working on a variety of business problems in the Financial Services space and enabling data engineering and data science professionals to start the Databricks journey through Solution Accelerators like AML.Try the notebooks on Databricks to accelerate your AML development strategy today and contact us to learn more about how we assist customers with similar use cases.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jim-hibbard\/#","text":"Jim Hibbard - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJim HibbardSenior Developer Advocate at DatabricksBack to speakersJim Hibbard is a Developer Advocate at Databricks. Prior to that, he worked at Seattle Children\u2019s Hospital where he developed frameworks and methods for integrating medical records with multi-omics datasets to improve care. He is currently working on improving machine learning infrastructure and model management as part of the extended MLflow team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/the-future-of-analytics-and-ai-is-open?itm_data=gcp-promo-gcplaunch","text":"The Future of Analytics and AI Is Open | DatabricksLaunch Event: Databricks on Google CloudThe Future of Analytics and AI Is OpenAvailable On-demandDatabricks on Google Cloud delivers an open platform on the open cloud for analytics and AI that empowers customers to innovate faster. Tight integration between Databricks and Google Cloud\u2019s BigQuery, Looker, and AI Platform provide a simple, unified analytics experience. Databricks on Google Cloud is built on Google Kubernetes Engine to leverage the managed services of Google Kubernetes Engine from a fully containerized environment.Sign up to hear from Thomas Kurian, CEO, Google Cloud, Ali Ghodsi, CEO, Databricks, and many more about how Databricks and Google Cloud provides an open, integrated platform for data engineering, data science, machine learning, and analytics.Details and speakersAgenda:Executive Keynote\nSpeakers: Thomas Kurian, CEO, Google Cloud, and Ali Ghodsi, CEO, Databricks.How Reckitt Uses AI to Improve Marketing ROI\nSpeakers: Harish Kumar, Global Data Science Director, Reckitt, and Hiral Jasani, Senior Product Marketing Manager, Databricks.Introducing Databricks on Google Cloud\nSpeakers: David Meyer, SVP Product, Databricks, and Sudhir Hasbe, Senior Director Product Management, Google Cloud.Building a Lakehouse with Databricks and Google Cloud Discussion and Demo\nSpeakers: Marco Tranquillin, EMEA CE Practice Lead, Data Analytics, Google Cloud, and Maggie Chu, Senior Solutions Architect, Databricks.Collaborative Data Science Discussion and Demo\nSpeakers: Lilly McNealus, Head of AI Platform Outbound Product Management & Strategy, Google Cloud, and Brooke Wenig, Machine Learning Practice Lead, Databricks.\u00a0Event Info:Available On-demandSpeakersAli GhodsiCEODatabricksThomas KurianCEOGoogle CloudDavid MeyerSVP ProductDatabricksHarish KumarGlobal Data Science DirectorReckittWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2018\/05\/01\/how-to-avoid-drowning-in-dsrs-in-a-data-lake.html","text":"How to Avoid Drowning in GDPR Data Subject Requests in a Data Lake - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHow to Avoid Drowning in GDPR Data Subject Requests in a Data Lakeby Justin Olsson, Sr. Legal Counsel and Michael ArmbrustMay 1, 2018 in ProductShare this postWith GDPR enforcement rapidly approaching (May 25, 2018), many companies are still trying to figure out how to comply. \u00a0A big pain point, particularly for companies who utilize data lakes to store vast amounts of data, is how to comply with one of the main requirements under the GDPR - data subject requests, also known as \u201cDSRs\u201d.\nWhat is a DSR?One of the most operationally significant parts of the GDPR for companies is the data subject request. \u00a0The GDPR provides all European data subjects (that is, any individual person located in Europe) with a set of enumerated rights related to their personal data including the right to:\naccess (i.e., the right to know what personal data a controller or processor has about the individual),rectification (i.e., the right to update incorrect personal data),erasure (i.e., the right to be forgotten), andportability (i.e., the right to export personal data in a machine-readable format).Companies have, unless the request is \u201ccomplex\u201d or \u201cnumerous\u201d, thirty days from receipt of the data subject request to comply with the request (keeping in mind any applicable exceptions).\nSo what\u2019s the big deal?Finding data in a data lake is hard; being sure that you\u2019ve found all data about a particular individual is very hard. And many data lakes do not even enable users to perform \u201cdelete\u201d operations, even once the data is located, so actually removing it may be practically impossible. In the best case, finding and removing such data is computationally difficult, expensive, and time consuming. \u00a0And if a company receives more than just a few data subject requests in a short period of time, the resources spent to comply with the requests could be significant. Further, failure to comply with the GDPR could result in significant penalties, potentially as high as \u20ac20 million (or even more - up to 4% of a company\u2019s global annual revenues).\nSo that sounds bad. Is there anything that can be done?Fortunately, Databricks offers a solution. Enter Databricks Delta, a unified data management system built into the Databricks platform, that brings data reliability and performance optimizations to cloud data lakes.\nDatabricks Delta\u2019s structured data management system adds transactional capabilities to your data lake that enable you to easily and quickly search, modify, and clean your data using standard SQL DML statements (e.g. DELETE, UPDATE, MERGE INTO). To accomplish this, first ingest your raw data into Delta tables which adds metadata to your files. Once ingested, you can easily search and modify individual records within your Delta tables to meet DSR obligations. The final step is to make Delta your single source of truth by erasing any underlying raw data. This removes any lingering records from your raw data sets. We suggest setting up a retention policy with AWS or Azure of thirty days or less to automatically remove raw data so that no further action is needed to delete the raw data to meet DSR response timelines under the GDPR.\nCan you provide an example of how this works?Let\u2019s say your organization received a DSR to delete information related to Justin Olsson ([email\u00a0protected]). After ingesting your raw data into Delta tables, Databricks Delta would enable you to find and delete information related to user [email\u00a0protected] by running two commands:\n(1) DELETE FROM data WHERE email LIKE '[email\u00a0protected]';\n(2) VACUUM data;\n\nThe first command identifies records that have the string \"[email\u00a0protected]\" stored in the column email, accounting for varying case (e.g., [email\u00a0protected] would also match), and deletes the data containing these records, rewriting the respective underlying files with the user\u2019s data removed. The second command cleans up the Delta table, removing any stale records that have been logically deleted and those that are outside of the default retention period (e.g., 7 days).\nAfter running these commands, and waiting for your default retention period to delete the underlying raw files, you would be able to state that you had removed records relating to the user [email\u00a0protected] from your data lake.\nOkay, that sounds great , but if I put my data in a Delta table, won\u2019t I be locked in? \u00a0What if I want to go somewhere else?Nope! Databricks Delta is architected with portability in mind. Databricks Delta uses an open file format (parquet) and you can at any time (either if you ever decide to stop using Delta or if you need to output data to a system that cannot read Delta tables) quickly and easily convert your data back into a format that can be read by other tools. \u00a0While doing so, particularly on an ongoing basis, would leave you with the additional DSR obligation of deleting or exporting any personal data that might be contained in the data that was moved out of Databricks Delta, it too will have benefitted from flowing through Databricks Delta, as it will be in a much more structured format, dramatically simplifying that process as well.\nLearn more and watch a live demoWatch our on-demand webinar, Is Your Data Lake GDPR Ready? How to Avoid Drowning in Data Requests, for a\u00a0 demo and tips for overcoming the challenges of DSRs in a big data world.\nThis webinar will cover:\nThe GDPR requirements of data subject requestsThe challenges big data and data lakes create for organizationsHow Databricks improves data lake management and makes it possible to surgically find and modify or remove individual recordsBest practices for GDPR data governanceLive demo on how to easily fulfill data requests with DatabricksWatch the recorded session now.Try Databricks for freeGet StartedSee all Product postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-sanky","text":"Michael Sanky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael SankyRVP, Industry Solutions, Healthcare and Life Sciences at DatabricksBack to speakersBusiness leader focusing on strategy, products, and business development in the intersection of science and IT. Helping Life Sciences companies accelerate and improve discovery by combining Technology and Human Ingenuity to enable Collaboration, Data Science, Digital Twins, AI, and Analytics in the Cloud.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/data-streaming","text":"Data Streaming | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData StreamingReal-time analytics, ML and applications made simpleGet startedWatch demoThe\u00a0Databricks Lakehouse Platform\u00a0dramatically simplifies data streaming to deliver real-time analytics, machine learning and applications on one platform.Enable your data teams to build streaming data workloads with the languages and tools they already know. Simplify development and operations by automating the production aspects associated with building and maintaining real-time data workloads. Eliminate data silos with a single platform for streaming and batch data.Build streaming pipelines and applications fasterUse the languages and tools you already know with unified batch and streaming APIs in SQL and Python. Unlock real-time\u00a0analytics,\u00a0ML\u00a0and\u00a0applications\u00a0for the entire organization.Simplify operations with automated toolingEasily deploy and manage your\u00a0real-time pipelines\u00a0and applications in production. Automated tooling simplifies task orchestration, fault tolerance\/recovery, automatic checkpointing, performance optimization, and autoscaling.Unify governance for all your real-time data across cloudsUnity Catalog\u00a0gives your lakehouse one consistent governance model for all your streaming and batch data, simplifying how you discover, access and\u00a0share\u00a0real-time data.How does it work?Streaming data ingestion and transformationReal-time analytics, ML and applicationsAutomated operational toolingNext-generation stream processing engineUnified governance and storageStreaming data ingestion and transformationSimplify data ingestion and ETL for streaming data pipelines with\u00a0Delta Live Tables. Leverage a simple declarative approach to\u00a0data engineering\u00a0that empowers your teams with the languages and tools they already know, like SQL and Python. Build and run your batch and streaming data pipelines in one place with controllable and automated refresh settings, saving time and reducing operational complexity. No matter where you plan to send your data, building streaming data pipelines on the Databricks Lakehouse Platform ensures you don\u2019t lose time between raw and cleaned data.\u201cMore business units are using the platform in a self-service manner that was not possible before. I can\u2019t say enough about the positive impact that Databricks has had on Columbia.\u201d\u2014 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearLearn moreReal-time analytics, ML and applicationsWith streaming data, immediately improve the accuracy and actionability of your analytics and AI. Your business benefits from real-time insights as a downstream impact of streaming data pipelines. Whether you\u2019re performing\u00a0SQL analytics\u00a0and\u00a0BI reporting,\u00a0training your ML models\u00a0or building real-time operational applications, give your business the freshest data possible to unlock real-time insights, more accurate predictions and faster decision-making to stay ahead of the competition.\u201cWe must always deliver the most current and accurate data to our business partners, otherwise they\u2019ll lose confidence in the insights . . . Databricks Lakehouse has made what was previously impossible extremely easy.\u201d\u2014 Guillermo Rold\u00e1n, Head of Architecture, LaLiga TechLearn moreAutomated operational toolingAs you build and deploy streaming data pipelines, Databricks automates many of the complex operational tasks required for production. This includes automatically scaling the underlying infrastructure, orchestrating pipeline dependencies, error handling and recovery, performance optimization and more.\u00a0Enhanced Autoscaling\u00a0optimizes cluster utilization by automatically allocating compute resources for each unique workload. These capabilities along with automatic data quality testing and exception management help you spend less time on building and maintaining operational tooling so you can focus on getting value from your data.Learn moreNext-generation stream processing engineSpark Structured Streaming\u00a0is the core technology that unlocks data streaming on the Databricks Lakehouse Platform, providing a unified API for batch and stream processing. The Databricks Lakehouse Platform is the\u00a0best place to run your Apache Spark workloads\u00a0with a managed service that has a proven track record of 99.95% uptime. Your Spark workloads are further accelerated by\u00a0Photon, the next-generation lakehouse engine compatible with Apache Spark APIs delivering\u00a0record-breaking\u00a0performance-per-cost while automatically scaling to thousands of nodes.Learn moreUnified governance and storageData streaming on Databricks means you benefit from the foundational components of the\u00a0Lakehouse Platform\u00a0\u2014 Unity Catalog and Delta Lake. Your raw data is optimized with\u00a0Delta Lake, the only open source storage framework designed from the ground up for both streaming and batch data.\u00a0Unity Catalog\u00a0gives you fine-grained, integrated governance for all your data and AI assets with one consistent model to discover, access and share data across clouds. Unity Catalog also provides native support for\u00a0Delta Sharing, the industry\u2019s first open protocol for simple and secure data sharing with other organizations.IntegrationsProvide maximum flexibility to your data teams \u2014 leverage\u00a0Partner Connect\u00a0and an ecosystem of\u00a0technology partners\u00a0to seamlessly integrate with popular data streaming tools.Data StreamingCustomer Stories\u201cWe use Databricks for high-speed data in motion. It really helps us transform the speed at which we can respond to our patients\u2019 needs either in-store or online. We have about a dozen initiatives right now and all of those are served out of the data in Databricks.\u201d\u2014 Sashi Venkatesan, Director of Product Engineering, Walgreens\u201cNow that our fraud detection is real time, we can outwit fraudsters and stay ahead of their efforts in areas like fraudsters gaming the system, illegal unlocks, robocalls and robotexts, and identity theft.\u201d\u2014 Kate Hopkins, Vice President, AT&TDiscover moreDelta Live TablesDatabricks WorkflowsUnity CatalogDelta LakeSpark Structured StreamingRelated contenteBooks and demosRise of the Data Lakehouse by Bill Inmon, father of the data warehouseData, Analytics and AI governanceThe Data Team\u2019s Guide to the Databricks Lakehouse PlatformDelta Live Tables Streaming DemosEventsTackle Data Transformation With Delta Live TablesHassle-Free Data Ingestion Webinar SeriesData + AI Summit 2022Data +AI World Tour 2022BlogsLow-Latency Streaming Data Pipelines With Delta Live Tables and Apache KafkaSimplifying Streaming Data Ingestion Into Delta LakeReal-Time Insights: The Top Three Reasons Why Customers Love Data Streaming with DatabricksProject Lightspeed: Faster and Simpler Stream Processing With Apache SparkAn Overview of All the New Structured Streaming Features Developed in 2021 for Databricks and Apache Spark \u2014 The Databricks BlogReady to get started?Try for freeJoin the communityProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/migration","text":"Migrazione a Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWMigrazione a DatabricksModernizza la tua piattaforma dati passando a Databricks Lakehouse\nprova Databricks gratisContatta DatabricksRiduci i costi, accelera l'innovazione e semplifica la piattaforma dati migrando a Databricks Lakehouse dal data warehouse aziendale o dal data lake esistente. In questo modo potrai gestire tutti i carichi di lavoro di dati, analisi e AI su una moderna piattaforma unificata, basata su standard aperti e protetta da un approccio di governance comune.Perch\u00e9 migrare a Databricks?Semplifica la piattaforma di gestione dei datiImplementa un'unica piattaforma moderna per tutti i casi d'uso di gestione dei dati, analisi e AI. Unifica la governance e l'esperienza del cliente per tutti i cloud e i team di gestione dei dati.\nCrescere con costi contenutiSmetti di gestire i server ed espanditi quando ne hai bisogno con il sistema serverless. Esegui applicazioni di data warehouse su larga scala con un rapporto prezzo\/prestazioni fino a 12 volte migliore.\nAccelerare l'innovazioneCostruisci funzionalit\u00e0 di AI, ML e analisi in tempo reale pi\u00f9 velocemente grazie a strumenti collaborativi self-service e tecnologie open-source come MLflow e Apache Spark\u2122.\nMigrazione da Hadoop\nMaggiori informazioniMigrazione da un data warehouse\nMaggiori informazioniMigrare in tutta tranquillit\u00e0Abbiamo aiutato centinaia di clienti a migrare da piattaforme dati esistenti. Utilizzando un processo di migrazione completo articolato in diverse fasi, offriamo un modello prevedibile per valutare i costi sia durante sia dopo la migrazione. Inoltre, l'approccio incentrato sul lakehouse per migrare tutti i carichi di lavoro garantisce il supporto per tutti i casi d'uso, esistenti e nuovi. Il risultato? Rischio ridotto, tempi pi\u00f9 rapidi di realizzazione del valore e ROI maggiore.Le 5 fasi di migrazione dei datiFase 1:\nScoperta\nUsa i profilatori per automatizzare la scoperta. Ottieni informazioni approfondite sui carichi di lavoro della piattaforma esistente e stima i costi di consumo della piattaforma Databricks.\nFase 2:\nValutazione\nUsa gli analizzatori per una valutazione dettagliata della complessit\u00e0 del codice e per stimare i costi del progetto di migrazione.\nFase 3:\nStrategia\nFinalizza la mappatura tecnologica e costruisci percorsi ottimali per la migrazione di ogni piattaforma sorgente, lasciandoti guidare dagli esperti di Databricks.\nFase 4:\nPilota in produzione\nEsegui un progetto pilota con i tuoi casi d'uso e convertitori di codice, laddove possibile, per convertire il vecchio codice in codice compatibile con Databricks. Sviluppa un piano e una roadmap per realizzare la migrazione.\nFase 5:\nEsecuzione\nRipulisci e ripeti per tutti i carichi di lavoro. Ottieni aiuto per l'esecuzione della migrazione e assistenza da partner certificati o Databricks Professional Services.\nClienti che hanno effettuato la migrazione a Databricks con successoREFERENZAPersonalizzare le cure farmaceutiche per migliorare gli esiti per i pazienti\nMaggiori informazioniBlog dei clientiEliminare completamente l'on-premise, guadagnare tagliando i costi e arrivare pi\u00f9 velocemente al successo\nMaggiori informazioniREFERENZAIl passaggio al cloud apre una nuova era del commercio al dettaglio guidato dai dati\nMaggiori informazioniSoluzioni BrickbuilderSfrutta le soluzioni Brickbuilder sviluppate dai nostri principali partner di consulenza per la migrazione a Databricks LakehouseMigrazione dei dati in cloud con AccentureMeno congetture, pi\u00f9 valore\nCominciaMigrazione dei servizi esistenti con AvanadeTrasferisci i dati per sfruttare tutto il loro valore\nCominciaMigrazione al cloud e a Databricks con CapgeminiMigrazione snella dei dati sulla Databricks Lakehouse Platform\nCominciaMigrazione a Databricks con Celebal TechnologiesMigrazione pi\u00f9 veloce dai sistemi on-premise con costi inferiori\nCominciaSoluzione di migrazione LeapLogic di ImpetusAuto-trasformazione dei carichi di lavoro ETL, data warehouse, analisi e Hadoop su Databricks\nCominciaData Wizard for Hadoop\/EDW Migrations di InfosysTrasferisci i dati su Databricks in tutta tranquillit\u00e0\nCominciaMigrazione da Snowflake a Databricks con LovelyticsProcesso di migrazione rapido e sicuro\nCominciaSAS Migration Accelerator di Tensile AISoluzione di migrazione sviluppata da Tensile AI e basata sulla Databricks Lakehouse PlatformCominciaData Intelligence Suite di WiproMigrare in tutta tranquillit\u00e0 a Databricks\nCominciaAdottare una strategia di data lakehouse: una scelta saggiaPerch\u00e9 un approccio incentrato sul data lakehouse pu\u00f2 aiutare a superare i limiti dei data warehouse e dei data lakeSCARICARisorseeBookMigrazione da Hadoop al data lakehouse per principiantiMigrazione da data warehouse a data lakehouse per principiantiEventiGuida passo-passo alla migrazione da HadoopModernizzare il data warehouseBlog5 mosse fondamentali per una migrazione efficace da Hadoop all'architettura lakehouse7 ragioni per migrare da Hadoop in cloud alla Databricks Lakehouse PlatformCominciaLa migrazione non deve essere per forza un problema. Contattaci oggi stesso per conoscere le soluzioni ideali per te.prova Databricks gratisContatta DatabricksProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/product\/repos","text":"Repos | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks ReposShip code faster with repository-level Git operations in DatabricksTry for freeSchedule a demoHow does it work?Standardize development across data projectsGit workflows and operations in Databricks help integrate data projects into larger software operations at your company. Pull changes, commit, compare and more, from the Databricks Repos UI or API.Automate Git workflowsThe Repos REST API enables you to integrate data projects into CI\/CD pipelines. You can use popular CI\/CD tools to call the Repos API and update a repo to the latest version of a specific Git branch.Use your existing Git providerNative integration with your preferred Git provider. Clone remote repos, manage branches, pull and push changes, and visually compare differences in Databricks.Repo-level access controlIn addition to platform-level encryption, Repos features allow lists to control access to critical Git repositories, and secrets detection to scan for access key leaks.ResourceseBookDiscover the most exciting new ML use cases with code samples, how-tos and commentaryRead nowDocumentationRepos for Git integration | Databricks on AWSRead nowBlogFind out how Repos enables a better developer experience in DatabricksRead nowReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tony-wang\/#","text":"Tony Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTony WangPhD student at StanfordBack to speakersTony Wang is a PhD student at Stanford University working on an open-source query engine in Python: https:\/\/github.com\/marsupialtail\/quokka, for emerging data applications like vector embeddings and feature engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/darth-vader","text":"Darth Vader - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDarth VaderSith Lord at The Galactic EmpireBack to speakersOnce the heroic Jedi Knight named Anakin Skywalker, Darth Vader was seduced by the dark side of the Force. Forever scarred by his defeat on Mustafar, Vader was transformed into a cybernetically-enhanced Sith Lord. At the dawn of the Empire, Vader led the Empire\u2019s eradication of the Jedi Order and the search for survivors. He remained in service of the Emperor -- the evil Darth Sidious -- for decades, enforcing his Master\u2019s will and seeking to crush the Rebel Alliance and other detractors.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/malav-shah","text":"Malav Shah - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMalav ShahSenior Data Scientist at DIRECTVBack to speakersMalav Shah is a Senior Data Scientist at DIRECTV. He joins DIRECTV from AT&T, where he worked on multiple consumer businesses \u2013 including broadband, wireless, and video \u2013 and deployed ML models across a wide array of use cases spanning the full customer lifecycle. Malav holds a Master\u2019s Degree in Computer Science with a specialization in ML from Georgia Tech, a degree he puts to good use every day by applying modern ML techniques to help the company deliver innovative entertainment experiences.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/parth-chandra\/#","text":"Parth Chandra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingParth ChandraSoftware Engineer at AppleBack to speakersParth Chandra is a software engineer at Apple working on Spark performance and scalability. He is a PMC (emeritus) member of Apache Drill, and Apache Arrow. Prior to Apple he most recently worked at Mapr on Apache Drill.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/resources\/ebook\/the-big-book-of-data-engineering","text":"The Big Book of Data Engineering | Databrickse-booksLivro Completo da Engenharia de DadosAprenda com casos de uso do mundo realDescubra as melhores pr\u00e1ticas de engenharia de dados da atualidadeFique por dentro das tend\u00eancias mais recentes em engenharia de dados baixando sua c\u00f3pia do Livro Completo da Engenharia de Dados. Voc\u00ea se beneficiar\u00e1 de conjuntos de dados, amostras de c\u00f3digo e pr\u00e1ticas recomendadas para converter dados brutos em dados acion\u00e1veis. Voc\u00ea tamb\u00e9m ver\u00e1 casos de uso completos da vida real de empresas l\u00edderes como J.B. Hunt, ABN AMRO e Atlassian.Baixe agora para saber como:Habilitar an\u00e1lises de pontos de venda em tempo realConstruir um lakehouse de seguran\u00e7a cibern\u00e9ticaDesbloquear o poder dos dados de sa\u00fadeExecutar seu ciclo de vida de dados na plataforma Databricks LakehouseBaixe o eBookProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stefania-leone\/#","text":"Stefania Leone - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStefania LeoneSr. Manager Product Management at DatabricksBack to speakersStefania is a product manager at Databricks working on the Databricks Runtime. She holds a PhD in Computer Science from ETH Zurich.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDelta SharingUn standard ouvert pour le partage s\u00e9curis\u00e9 des assets de donn\u00e9esD\u00e9marrerRegarder la d\u00e9moDelta Sharing de Databricks est une solution ouverte pour le partage s\u00e9curis\u00e9 de donn\u00e9es en direct, depuis votre lakehouse vers n'importe quelle plateforme informatique.Avantages cl\u00e9sPartage ouvert multiplateformePartagez facilement les donn\u00e9es aux formats Delta Lake et Apache Parquet vers n'importe quelle plateforme informatique.Partagez des donn\u00e9es en direct sans r\u00e9plicationPartagez des donn\u00e9es en direct sans devoir les r\u00e9pliquer ni les copier sur un autre syst\u00e8me.Gouvernance centralis\u00e9eCentralisez la gestion, la gouvernance, l'audit et le suivi de consommation des donn\u00e9es partag\u00e9es sur une m\u00eame plateforme.Une marketplace pour les produits de donn\u00e9esCr\u00e9ez et packagez une fois pour toutes des produits de donn\u00e9es (ensembles de donn\u00e9es, mod\u00e8les ML et notebooks), puis distribuez-les librement sur une marketplace centrale.Des salles blanches de donn\u00e9es qui prot\u00e8gent la vie priv\u00e9eCollaborez facilement avec vos clients et vos partenaires sur tout type de cloud au sein d'un environnement s\u00e9curis\u00e9, tout en prot\u00e9geant la confidentialit\u00e9 des donn\u00e9es.Comment \u00e7a marcheInt\u00e9gration native avec la plateforme DatabricksL'int\u00e9gration native avec le Unity Catalog vous permet de g\u00e9rer et d'auditer les donn\u00e9es partag\u00e9es dans toutes les organisations, de fa\u00e7on centralis\u00e9e. Cela vous permet \u00e9galement de partager en toute confiance des assets de donn\u00e9es avec vos fournisseurs et partenaires pour une meilleure coordination de votre activit\u00e9, tout en r\u00e9pondant aux crit\u00e8res de s\u00e9curit\u00e9 et de conformit\u00e9.G\u00e9rer les partages en toute simplicit\u00e9Cr\u00e9ez et g\u00e9rez des fournisseurs, des destinataires et des partages avec une interface utilisateur simple \u00e0 utiliser, des commandes SQL ou des API REST avec prise en charge compl\u00e8te de CLI et TerraformD\u00e9couvrez et obtenez des produits de donn\u00e9es sur une marketplace ouverteD\u00e9couvrez, \u00e9valuez et acc\u00e9dez avec facilit\u00e9 \u00e0 un large \u00e9ventail de produits de donn\u00e9es\u00a0: des ensembles de donn\u00e9es, des mod\u00e8les de machine learning, des tableaux de bord et des notebooks. Vous pouvez y acc\u00e9der de partout, sans avoir besoin d'\u00eatre sur la plateforme Databricks.Des salles blanches de donn\u00e9es qui prot\u00e8gent la vie priv\u00e9eCollaborez avec vos clients et vos partenaires sur n\u2019importe quel cloud, au sein d'un environnement s\u00e9curis\u00e9. Partagez les donn\u00e9es de vos data lakes en toute s\u00e9curit\u00e9, sans r\u00e9plication. Rencontrez vos collaborateurs sur le cloud de leur choix et offrez-leur la possibilit\u00e9 d'ex\u00e9cuter des calculs et des charges de travail complexes dans n\u2019importe quel langage (SQL, R, Scala, Java et Python), pour une flexibilit\u00e9 maximale. Accompagnez vos collaborateurs dans les cas d'usage courants \u00e0 l'aide de mod\u00e8les, notebooks et tableaux de bord pr\u00e9d\u00e9finis, afin d'acc\u00e9l\u00e9rer la production d'insights.Cas d\u2019utilisationPartage entre les diff\u00e9rentes divisions internesCr\u00e9ez un Data Mesh avec Delta Sharing pour \u00e9changer des donn\u00e9es entre diff\u00e9rentes unit\u00e9s commerciales et filiales, sans jamais compromettre leur s\u00e9curit\u00e9.Partage B2BMon\u00e9tisation des donn\u00e9esClients\u00ab\u00a0Delta Sharing nous a aid\u00e9s \u00e0 rationaliser notre processus de livraison pour les grands ensembles de donn\u00e9es. Nos clients peuvent ainsi utiliser leur propre environnement informatique pour consulter des donn\u00e9es r\u00e9centes, tri\u00e9es et s\u00e9lectionn\u00e9es avec un effort d'int\u00e9gration minime, voire inexistant. Quant \u00e0 nous, nous pouvons \u00e9largir notre catalogue de produits de donn\u00e9es uniques et de grande qualit\u00e9.\u00a0\u00bb\u2014 William Dague, Responsable des donn\u00e9es alternatives\u00ab\u00a0En tant qu'entreprise ax\u00e9e sur les donn\u00e9es, nous devons absolument garantir \u00e0 nos clients l'acc\u00e8s \u00e0 nos donn\u00e9es. La Plateforme Lakehouse de Databricks, avec Delta Sharing, harmonise parfaitement ce processus pour nous permettre de toucher une base d'utilisateurs bien plus large, quels que soient le cloud ou la plateforme utilis\u00e9e et sans faire de compromis sur la s\u00e9curit\u00e9.\u00a0\u00bb\u2014 Felix Cheung, VP Ing\u00e9nierie\u00ab\u00a0Gr\u00e2ce aux puissantes capacit\u00e9s du Delta Sharing de Databricks, Pumpjack Dataworks b\u00e9n\u00e9ficie d'une exp\u00e9rience d'onboarding plus fluide. Nous n'avons plus besoin d'exporter, importer ou remod\u00e9liser les donn\u00e9es\u00a0: pour nos clients, c'est une valeur ajout\u00e9e imm\u00e9diate. En effet, l'acc\u00e9l\u00e9ration des r\u00e9sultats se traduit par davantage d'opportunit\u00e9s commerciales pour nos clients et leurs partenaires.\u00a0\u00bb\u2014 Corey Zwart, Chef de l\u2019ing\u00e9nierie\u00ab\u00a0Avec Delta Sharing, nos clients ont acc\u00e8s \u00e0 des ensembles de donn\u00e9es s\u00e9lectionn\u00e9s presque instantan\u00e9ment et peuvent les int\u00e9grer aux outils d'analytique de leur choix. Les discussions avec nos clients s'enrichissent\u00a0: les d\u00e9bats de haut niveau sur l'analytique remplacent les s\u00e9ances de questions-r\u00e9ponses techniques sur l'ingestion des donn\u00e9es et nous permettent d'\u00e9laborer des exp\u00e9riences client fructueuses. Nos relations avec nos clients \u00e9voluent. Nous nous attachons \u00e0 livrer de nouveaux ensembles de donn\u00e9es et \u00e0 rafra\u00eechir les pr\u00e9c\u00e9dents via Delta Sharing pour les tenir inform\u00e9s des grandes tendances de leur secteur.\u00a0\u00bb\u2014 Anup Segu, Chef des technologies de data engineeringUn \u00e9cosyst\u00e8me ouvertAcc\u00e9dez \u00e0 la version la plus r\u00e9cente directement aupr\u00e8s du fournisseur, dans SQL, Python ou les outils de BI.RessourcesKeynote et Webinar[Keynote]Gouvernance des donn\u00e9es et partage au bord du lac au Data + AI Summit 2022Acc\u00e9l\u00e9rer la valeur commerciale avec Delta SharingBlogsAnnonce de la disponibilit\u00e9 g\u00e9n\u00e9rale du partage DeltaDelta Sharing\u00a0: une norme ouverte pour le partage de donn\u00e9es s\u00e9curis\u00e9Les trois principaux cas d'usage du partage de donn\u00e9es avec Delta SharingFiche solution et ebook[eBook] D\u00e9couvrez la nouvelle solution de Delta SharingDelta Sharing\u00a0: une norme ouverte pour le partage de donn\u00e9es s\u00e9curis\u00e9Rise of the Data Lakehouse par Bill Inmon, p\u00e8re de l\u2019entrep\u00f4t de donn\u00e9esPr\u00eat \u00e0 vous lancer avec Databricks\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/seth-babcock\/#","text":"Seth Babcock - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSeth BabcockHead of Connected Aviation Tech Ops Solutions and Analytics at Collins AerospaceBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vuong-nguyen","text":"Vuong Nguyen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVuong NguyenSenior Solutions Architect at DatabricksBack to speakersA Senior Solutions Architect at Databricks based in London, with a strong passion to help customers with their data governance, data sharing and platform automation needs. Regular contributor to open source projects such as the Databricks Terraform Provider and Delta Sharing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/egor-gryaznov\/#","text":"Egor Gryaznov - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEgor GryaznovCTO and Co-founder at BigeyeBack to speakersEgor Gryaznov is the co-founder and Chief Technology Officer at Bigeye, the enterprise data observability platform. Egor has spent his career empowering data teams by building powerful solutions for common problems that they face. Before starting Bigeye, Egor was a staff engineer at Uber, where he built and scaled the company\u2019s first data warehouse, from infrastructure to data modeling. In his free time, Egor enjoys cooking and playing with\/being bossed around by his infant son.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#95b5f7e7f4fbf1d5f1f4e1f4f7e7fcf6fee6bbf6faf8","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c3816bf6482f3\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/de\/discover\/demos","text":"Databricks Product & Partner Demo Hub \u2013 Solution Accelerator Demo \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDemo HubMit diesen einfachen On-Demand-Videos erhalten Sie einen direkten Einblick in Databricks aus Sicht des Anwenders. F\u00fcr alle nachstehenden Demos sind erg\u00e4nzende Materialien wie Notebooks, Videos und E-Books angegeben, damit Sie sie selbst auf Databricks ausprobieren k\u00f6nnen.Jetzt kostenfrei testenProduktdemosDatabricks-PlattformIn dieser Demo geben wir einen allgemeinen \u00dcberblick \u00fcber die Databricks Lakehouse-Plattform. Wir werden dabei unter anderem ansprechen, wie sich Open-Source-Projekte wie Apache Spark\u2122, Delta Lake, MLflow und Koalas in das Databricks-\u00d6kosystem einpassen.Mehr InformationenDatabricks SQLDatabricks WorkflowsUnity CatalogData Science und Machine LearningDelta-FreigabeDelta LakeDelta Live TablesDelta Lake-Datenintegration (Auto Loader und COPY INTO)PartnerdemosAzure Databricks Cloud IntegrationDie Azure Databricks Lakehouse-Plattform bietet Ihnen das Beste aus Data Lakes und Data Warehouses \u2013 auf einer einfachen, offenen und kollaborativen Plattform, die sich sicher in Ihre bestehenden Azure-Services integrieren l\u00e4sst. In dieser Demo skizzieren wir einige der g\u00e4ngigsten Azure Databricks-Integrationen, z.\u00a0B. Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics oder Power\u00a0BI.Mehr InformationenDatabricks und AWS-CloudintegrationDatabricks auf Google Cloud implementierenPartner ConnectBranchenl\u00f6sungenVon der Idee zum Machbarkeitsnachweis in nur zwei WochenDatabricks Solution Accelerators sind speziell entwickelte Leitf\u00e4den, voll funktionsf\u00e4hige Notebooks und Best Practices, die Ergebnisse beschleunigen. Databricks-Kunden sparen Stunden beim Entdecken, Entwerfen, Entwickeln und Testen, wobei viele in nur zwei Wochen von der Idee zum Machbarkeitsnachweis gelangen.Accelerators erkundenErstellen Sie Ihr Databricks-Konto1\/2VornameNachnameBerufliche E-Mail-AdresseUnternehmenStellenbezeichnungRufnummer (Optional)Bitte ausw\u00e4hlenLandErste SchritteProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mat-keep\/#","text":"Mat Keep - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMat KeepSenior Director, MongoDB Products Team at MongoDBBack to speakersMat Keep is a Senior Director in the Product team at MongoDB. Working with developer communities, MongoDB users and industry analysts, Mat helps shape the product roadmap and then takes those new products to market. Mat has been with MongoDB for 10 years. Prior to MongoDB, he worked in product roles for MySQL, Oracle, and Sun Microsystems and comes from a background as an analyst\/programmer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacolon-walker","text":"Jacolon Walker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacolon WalkerCo-founder & CTO at MonadBack to speakersJacolon is the Co-founder & CTO of Monad. A 15-year veteran of the security industry, Jacolon has built and overseen SOC, appsec, incident response, threat intelligence and security engineering programs at companies like Palantir, Opendoor, and Collective Health. Jacolon holds a B.S. in Computer Science from the University of Texas at Dallas. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/driving-innovation-data-ai-financial-services?itm_data=aws-resources-eBookFinancialServices","text":"Driving Innovation in Financial Services With a Unified Approach to Data + AI | DatabrickseBookDriving Innovation in Financial Serviceswith a unified approach to Data + AIData and AI are changing how financial institutions generate and utilize insights from data. As a result, the traditional advantages that financial institutions enjoyed, such as capital and scale, are no longer the main differentiators going forward. The winners of tomorrow will thrive based on their ability to attract engineering talent and unlock the value of data with the right tools and technologies.In this eBook, you will learn:Why financial institutions struggle with data and AIHow data is transforming financial servicesHow Databricks fuels data-driven innovationGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jamie-baker","text":"Jamie Baker - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJamie BakerDirector of Product at MatillionBack to speakersJamie Baker is an accomplished product, domain leader\/manager, solutions consultant, and an industry-recognized subject matter expert, with a proven track record delivering enterprise on-premise and SaaS software products and solutions across IT infrastructure and Data Integration markets. Jamie has presented at global IT conferences on capacity management, digital transformation, and ITIL process implementation and maturity.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yaron-singer\/#","text":"Yaron Singer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYaron SingerCEO & Co-Founder at Robust IntelligenceBack to speakersYaron Singer is the CEO & co-founder of Robust Intelligence, and the Gordon McKay Professor of Computer Science and Applied Mathematics at Harvard. Before Harvard he was a researcher at Google and obtained his PhD from UC Berkeley. He's the recipient of the NSF CAREER award, the Sloan fellowship, Facebook faculty award, Google faculty award, 2012 Best Student Paper Award at the ACM conference on Web Search & Data Mining, 2010 Facebook Graduate Fellowship, and 2009 Microsoft Research PhD Fellowship.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/production-ready","text":"Elastic Scalability | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWElastic ScalabilityOptimized for speed, reliability, and scalability for all workloadsGet startedSchedule a demoTake data applications from development to production faster using pre-configured data environments and APIs for automation. Streamline operations with autoscaling infrastructure and monitoring.Benefits for DevOps TeamsFully configured data environmentsEnable your data teams to deliver value quickly with ready-to-use data environments configured with infrastructure, tools, libraries, users and governance policiesProductionize faster with automationAPIs for everything from version control, workspace provisioning, user management, clusters, and jobs to ML model management and tracking, allow DevOps teams to automate the data and ML lifecycle.Streamline operationsUse on-demand autoscaling infrastructure and integrations for real-time monitoring to streamline operations in production. Improve performance and reduce downtime of your data pipelines and ML applications.FeaturesFully Configured EnvironmentsWorkspaces API:\u00a0Workspace organizes objects (notebooks, libraries, and experiments) into folders. The\u00a0API\u00a0gives the account owner the ability to create team\u00a0workspaces\u00a0at scale.SCIM API:\u00a0Native support for System for Cross-domain Identity Management (SCIM) allows customers to automatically onboard and off-board users.Clusters and Jobs APIs:\u00a0Deploy thousands of clusters and jobs at scale reliably and consistently backed by a massive scale, low-latency API endpoint.Multiple Workspaces:\u00a0Quickly spin up 1000\u2019s of new workspaces as needed in the same account with the right access and security policies applied. You can manage the workspace using the workspace UI, the Databricks CLI, and the Databricks REST API.Easy DevopsAPIs:\u00a0Databricks takes an API first approach to building features on the platform. With each feature, the APIs are built first before a UI is developed.CI\/CD Integrations:\u00a0Streamline your application development process with integrations to DevOps tools such as\u00a0Git,\u00a0Jenkins,\u00a0Terraform,\u00a0CircleCI, and Azure Devops.Streamline OperationsMonitoring:\u00a0Integrate easily with monitoring apps to view real-time metrics, application and infrastructure logs.Auto-Scaling:\u00a0Databricks clusters spin-up and scale for processing massive amounts of data when needed and spin down when not in use.Pools:\u00a0Enable clusters to start and scale faster by creating a managed cache of virtual machine instances that can be acquired for use when needed.Regions:\u00a0Databricks is available in various regions around the world on\u00a0Azure\u00a0and\u00a0AWS.\u201cWith simplified administration and governance, Databricks\u2019 Unified Data Analytics Platform has allowed us to bring data-based decision making to teams across our organization. The ease of adding users, native security integrations with cloud providers and APIs-for-everything have enabled us to bring the data and tools we need, to every employee in Wehkamp,\u201d\u2013 Tom Mulder, Lead Data Scientist at Wehkamp.ResourcesDocumentationDevelopers ToolsSCIMWorkspacesClustersJobsGitJenkinsPoolsRegionsTest the platform for yourselfUse the Quick Start Guide to get the most out of your 14 day free trialStart your free trialProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/data-lakehouse","text":"Data Lakehouse Platform di Databricks - Programma una demo oggi stesso! | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks Lakehouse PlatformUnifica i casi di utilizzo di data warehouse e AI su un'unica piattaformaProva gratuita\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowSemplice. Aperta. Multicloud.Databricks Lakehouse Platform unisce gli aspetti migliori di data lake e data warehouse per offrire l'affidabilit\u00e0, la governance solida e le prestazioni dei data warehouse insieme all'apertura, alla flessibilit\u00e0 e al supporto del machine learning dei data lake.Questo approccio unificato semplifica lo stack moderno eliminando i silos di dati che normalmente separano e complicano data engineering, analisi, BI, data science e machine learning. La piattaforma \u00e8 basata su tecnologie open-source e standard aperti per offrire la massima flessibilit\u00e0. Inoltre, l'approccio comune alla gestione dei dati, alla sicurezza e alla governance aiuta a operare in modo pi\u00f9 efficiente e a fare innovazione pi\u00f9 velocemente.SempliceL'approccio unificato semplifica l'architettura dei dati eliminando i silos di dati che solitamente separano analisi, BI, data science e machine learning. Con un lakehouse si possono eliminare le complessit\u00e0 e le spese che impediscono di realizzare il pieno potenziale delle iniziative di analisi e AI.ApertaDelta Lake costituisce le fondamenta aperte del lakehouse, offrendo affidabilit\u00e0 e prestazioni da record mondiale direttamente sui dati presenti nel data lake. Cos\u00ec, \u00e8 possibile evitare \"gabbie dorate\" proprietarie, condividere facilmente i dati e costruire uno stack moderno per la gestione dei dati, con un accesso illimitato all'ecosistema di progetti di dati open-source e all'ampia rete di partner Databricks.Scopri di pi\u00f9 su 450+ Partner in tutto il panorama dei datiUlteriori informazioniMulticloudDatabricks Lakehouse Platform offre un'esperienza omogenea di gestione, sicurezza e governance su tutti i cloud. Non \u00e8 necessario investire nel reinventare i processi per ogni piattaforma cloud utilizzata per supportare le attivit\u00e0 di gestione dei dati e AI. I team di gestione dei dati possono invece concentrare tutto il lavoro di gestione dei dati sulla ricerca di nuove informazioni.Ulteriori informazioniSblocca il potenziale dei tuoi dati e dei tuoi team di datiScopri di pi\u00f9 su come Databricks Lakehouse Platform abilita i tuoi carichi di lavoro di dati e intelligenza artificialeIngegneria dei datiDatabricks SQLMachine LearningContenuti associati\nTutte le risorse di cui hai bisogno in un unico posto.\nEsplora la libreria di risorse per trovare e-book e video sui vantaggi del data engineering con Databricks.\nEsplora risorseLakehouseChe cos'\u00e8 una lakehouse?Manuale per principianti: piattaforma moderna per la gestione di dati in cloudL'ascesa del paradigma LakehouseRise of the Data Lakehouse di Bill Inmon, padre del data warehouseDelta LakeThe Big Book of Data EngineeringDelta Lake: La guida definitiva di O\u2019ReillyGuida definitiva a Delta LakeDelta Lake: la tecnologia alla base del LakehouseMachine LearningeBook: La standardizzazione nel ciclo di vita del Machine LearningEvento virtuale: Costruire piattaforme di Machine LearningPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/adverse-drug-event-detection","text":"Adverse Drug Event Detection | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution acceleratorAdverse Drug Event DetectionPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedMonitor drug safety with real-world data and NLPTo ensure ongoing drug safety, pharma companies need to monitor and report adverse drug events post-market launch. This is challenging given that most adverse events are captured in unstructured text like emails, phone calls and social media posts. Our joint Solution Accelerator with John Snow Labs makes it easy to extract, process and analyze adverse drug events from real-world text data using natural language processing (NLP).Easily extract adverse events from large volumes of text data with NLPAutomatically classify and correlate adverse events and drug entitiesUse built-in visualizations to assess the frequency of eventsDownload notebookResourcesBlogRead nowOn-demand workshopWatch nowBlogRead nowDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#c2a6a3b6a3a0b0aba1a9b1efb6adb182a6a3b6a3a0b0aba1a9b1eca1adaf","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c382a1e2382ba\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/company\/diversity","text":"Diversity and Inclusion | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe future of data is open to allDiversity, Equity and Inclusion at DatabricksDriven by data. Powered by people.We\u2019re on a mission to diversify big data \u2014 starting with our team. We believe different backgrounds, experiences, perspectives, insights and skills fuel innovation and deepen our connection to one another and our customers. We strive to cultivate a culture of belonging where everyone is empowered to do the best work of their careers. From ensuring equal pay for equal work to building programming that celebrates, educates and uplifts our team, Diversity, Equity and Inclusion (DEI) is woven into everything we do.Fair Pay Workplace Certified\nWe\u2019re proud to be one of the first six organizations certified by\u00a0Fair Pay Workplace. As part of our efforts to achieve pay parity, Databricks underwent a rigorous evaluation of our pay data and practices and committed to staying accountable through ongoing pay equity analyses.\nGaingels and Flucas Ventures\nOur commitment to diversity, equity and inclusion encompasses our entire team \u2014\u00a0from the people who work with us to the people who invest in us. That\u2019s why we\u2019re proud to partner with an array of world-class investors, including\u00a0Gaingels\u00a0and\u00a0Flucas Ventures, which focus on funding companies that demonstrate a deep commitment to DEI.\n\u201cWe know that the more data we have, the better our insights. The same is true of diversity and inclusion \u2014 Databricks thrives by including the widest possible diversity of backgrounds, experiences and viewpoints.\u201d\u2014 Ali Ghodsi, Co-founder and CEO, DatabricksOur communitiesWe believe empowering our employees is the key to unlocking our full potential. Our vibrant Employee Resource Groups (ERGs) are employee-led collectives that play a critical role in creating an inclusive and supportive environment at Databricks. These diverse communities of employees and allies create space for connection and celebration and bring awareness to meaningful issues.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\nOur experiences\u201cAt Databricks, I build teams that I would want to belong to. That means having the safety to be my authentic self and providing that same comfort zone to everyone around me. The impact of that care we show for one another and our dedication to inclusion is huge for our entire community.\u201d\u2014 Stacy Kerkela, Director of EngineeringRead more\u201cHaving a LatinX Network at Databricks makes me feel a stronger sense of community \u2013 an open community \u2013 because at Databricks, our Employee Resource Groups welcome and educate all people, regardless of their background.\u201d\u2014 Miguel Peralvo, Senior Solutions ArchitectRead more\u201cMany companies are focused on increasing gender diversity, but it\u2019s great to be part of a company that is visibly taking action to help move the needle.\u201d\u2014 Allie Emrich, Program Management, ProductRead moreInclusion in actionReportPartnerships With ColorStack and Rewriting the CodeOur University Recruiting team partners with\u00a0ColorStack\u00a0and\u00a0Rewriting the Code\u00a0to help more women as well as Black and LatinX students pursue a career in technology.\nRead moreReportWomen in Tech Mentorship ProgramAt Databricks, we recognize the importance of offering professional growth and advancement opportunities for historically underrepresented communities.Read moreReport2021 InHerSight AwardWe\u2019re excited to be featured among the best computer software workplaces for women, according to women. Learn more by visiting our InHerSight profile.Read moreLet\u2019s build the future of data, togetherWe\u2019re on a mission to simplify and democratize data and AI \u2014 and we can\u2019t do it without you.Explore opportunitiesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/migration","text":"Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 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\ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc774\ub3d9\ud558\uc5ec \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ud604\ub300\ud654\nDatabricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30Databricks\uc5d0 \ubb38\uc758\ud558\uae30\uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub098 \uae30\uc874 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uba74 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uace0, \ub354\uc6b1 \ube60\ub974\uac8c \ud601\uc2e0\ud560 \uc218 \uc788\uc73c\uba70, \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\uc774 \ub2e8\uc21c\ud654\ub429\ub2c8\ub2e4. \uc774\uc81c \uac1c\ubc29\uc801 \ud45c\uc900\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uace0 \uacf5\ud1b5\uc801\uc778 \uac70\ubc84\ub10c\uc2a4 \uc804\ub7b5\uc73c\ub85c \ubcf4\ud638\ub418\ub294 \ud604\ub300\uc801 \ud1b5\ud569 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud574\uc57c \ud558\ub294 \uc774\uc720\ub294 \ubb34\uc5c7\uc77c\uae4c\uc694?\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub2e8\uc21c\ud654\ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\uc5d0 \ud558\ub098\uc758 \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\uc138\uc694. \ud074\ub77c\uc6b0\ub4dc\uc640 \ub370\uc774\ud130 \ud300 \ubaa8\ub450\uc5d0\uc11c \uac70\ubc84\ub10c\uc2a4\uc640 \uc0ac\uc6a9\uc790 \uacbd\ud5d8\uc744 \ud1b5\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\ud6a8\uacfc\uc801\uc73c\ub85c \ube44\uc6a9 \uc870\uc815\uc11c\ubc84\ub97c \uad00\ub9ac\ud560 \ud544\uc694 \uc5c6\uc774 \uc11c\ubc84\ub9ac\uc2a4\ub85c \ud544\uc694\ud560 \ub54c\ub9c8\ub2e4 \ud655\uc7a5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uac00\uaca9 \ub300\ube44 \ucd5c\ub300 12\ubc30 \ud5a5\uc0c1\ub41c \uc131\ub2a5\uc73c\ub85c 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\uace0\uac1d\uace0\uac1d \uc0ac\ub840\uc57d\uad6d \uad00\ub9ac\ub97c \uac1c\uc778\ud654\ud558\uc5ec \ud658\uc790 \uce58\ub8cc \ud6a8\uacfc \uac1c\uc120\n\uc790\uc138\ud788 \uc77d\uae30\uace0\uac1d \ube14\ub85c\uadf8\uc628\ud504\ub808\ubbf8\uc2a4 \uc0ac\uc6a9\uc744 \uc644\uc804\ud788 \uc911\ub2e8\ud558\uace0 \ube44\uc6a9\uc774 \uc808\uac10\ub418\ub294 \ud61c\ud0dd\uacfc \uc131\uacf5\uae4c\uc9c0 \uac78\ub9ac\ub294 \uc2dc\uac04 \ub2e8\ucd95\n\uc790\uc138\ud788 \uc77d\uae30\uace0\uac1d \uc0ac\ub840\ud074\ub77c\uc6b0\ub4dc \uc774\ub3d9\uc73c\ub85c \ub370\uc774\ud130 \uc911\uc2ec \ub9ac\ud14c\uc77c\uc758 \uc0c8\ub85c\uc6b4 \uc2dc\ub300 \uac1c\ub9c9\n\uc790\uc138\ud788 \uc77d\uae30Brickbuilder Solutions\uc8fc\uc694 \ucee8\uc124\ud305 \ud30c\ud2b8\ub108\uac00 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uae30 \uc704\ud574 \uac1c\ubc1c\ud55c Brickbuilder Solutions\ub97c \uc0ac\uc6a9\ud574 \ubcf4\uc138\uc694Accenture \uc9c0\uc6d0 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \ub9c8\uc774\uadf8\ub808\uc774\uc158\ucd94\uce21\uc740 \uc904\uc774\uace0, \uac00\uce58 \uc2e4\ud604\uc740 \ud655\ub300\n\uc2dc\uc791\u0000\ud558\uae30Avanade \uc9c0\uc6d0 \ub808\uac70\uc2dc \uc2dc\uc2a4\ud15c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130\ub97c \uc774\ub3d9\ud558\uc5ec \uac00\uce58\ub97c \ucd5c\ub300\ub85c \ud65c\uc6a9\ud558\uc138\uc694\n\uc2dc\uc791\ud558\uae30Capgemini \uc9c0\uc6d0 \ud074\ub77c\uc6b0\ub4dc \ubc0f Databricks\ub85c\uc758 \ub9c8\uc774\uadf8\ub808\uc774\uc158Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc73c\ub85c\uc758 \ub370\uc774\ud130 \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uac04\uc18c\ud654\n\uc2dc\uc791\ud558\uae30Celebal Technologies \uc9c0\uc6d0 Databricks\ub85c\uc758 \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc800\ub834\ud55c \ube44\uc6a9\uc73c\ub85c \uc628\ud504\ub808\ubbf8\uc2a4\uc5d0\uc11c \ub354 \ube60\ub974\uac8c \ub9c8\uc774\uadf8\ub808\uc774\uc158\n\uc2dc\uc791\ud558\uae30Impetus \uc9c0\uc6d0 LeapLogic \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uc194\ub8e8\uc158ETL, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4, \ubd84\uc11d \ubc0f Hadoop \uc6cc\ud06c\ub85c\ub4dc\ub97c Databricks\ub85c \uc790\ub3d9 \ubcc0\ud658\n\uc2dc\uc791\ud558\uae30Infosys \uc9c0\uc6d0 Hadoop\/EDW \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc6a9 \ub370\uc774\ud130 \ub9c8\ubc95\uc0acDatabricks\ub85c \ub370\uc774\ud130\ub97c \uc790\uc2e0\uac10 \uc788\uac8c \uc774\ub3d9\n\uc2dc\uc791\ud558\uae30Lovelytics \uc9c0\uc6d0 Snowflake-Databricks \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc2e0\uc18d\ud558\uace0 \uac74\uc804\ud55c \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ud504\ub85c\uc138\uc2a4 \ubcf4\uc7a5\n\uc2dc\uc791\ud558\uae30Tensile AI\uc758 SAS \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130Tensile AI\uc5d0\uc11c \uac1c\ubc1c\ud558\uace0 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc6b4\uc601\ub418\ub294 \ub9c8\uc774\uadf8\ub808\uc774\uc158 \uc194\ub8e8\uc158\uc2dc\uc791\ud558\uae30Wipro\uc758 \uc778\ud154\ub9ac\uc804\uc2a4 \uc2a4\uc704\ud2b8\uc790\uc2e0\uac10 \uc788\uac8c Databricks\ub85c \u0000\ub9c8\uc774\uadf8\ub808\uc774\uc158\n\uc2dc\uc791\ud558\uae30\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc804\ub7b5\uc73c\ub85c \uc804\ud658\ud558\ub294 \uc9c0\ud61c\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc811\uadfc \ubc29\uc2dd\uc774 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc640 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc758 \uc77c\ubc18\uc801\uc778 \ud55c\uacc4\ub97c \uadf9\ubcf5\ud558\ub3c4\ub85d \uc9c0\uc6d0\ud558\ub294 \ubc29\ubc95\uc9c0\uae08 \ub2e4\uc6b4\ub85c\ub4dc\ub9ac\uc18c\uc2a4eBook\ub204\uad6c\ub098 \uc27d\uac8c \ubc30\uc6b8 \uc218 \uc788\ub294 \ud558\ub461\uc5d0\uc11c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c\uc758 \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc655\ucd08\ubcf4\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\uc774\ubca4\ud2b8\ud558\ub461 \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ub2e8\uacc4\ubcc4 \uac00\uc774\ub4dc\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \ud604\ub300\ud654\ube14\ub85c\uadf8\ud558\ub461\uc5d0\uc11c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uae30 \uc704\ud55c 5\uac00\uc9c0 \ub2e8\uacc4\ud074\ub77c\uc6b0\ub4dc \uae30\ubc18 \ud558\ub461\uc5d0\uc11c Databricks \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud574\uc57c \ud558\ub294 \uc774\uc720\uc2dc\uc791\ud558\uae30\ub9c8\uc774\uadf8\ub808\uc774\uc158\uc774 \ub450\ud1b5\uac70\ub9ac\uac00 \ub420 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4. \uc9c0\uae08 Databricks\uc5d0 \ubb38\uc758\ud558\uc5ec \uc790\uc2e0\uc5d0 \ub9de\ub294 \uc194\ub8e8\uc158\uc744 \uc0c1\ub2f4\ud574 \ubcf4\uc138\uc694.Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30Databricks\uc5d0 \ubb38\uc758\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/trust\/trust","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueTrustOur trusted platform is built by embedding security throughout the software development and delivery lifecycle. We follow rigorous operational security practices such as penetration testing, vulnerability assessments and strong internal access controls. We believe transparency is the key to winning trust \u2014 we publicly share how we operate, and work closely with our customers and partners to address their security needs. We have offerings for PCI-DSS, HIPAA and FedRAMP compliance, and we are ISO 27001, ISO 27017, ISO 27018 and SOC 2 Type II\u00a0compliant.Contractual commitment\n\u00a0\nBeyond the documentation and best practices that you will find in our Security and Trust Center, we also provide a contractual commitment to security written in plain language to all our customers. This commitment is captured in the\u00a0Security Addendum\u00a0of our customer agreement, which describes the security measures and practices that we follow to keep your data safe.\n\u00a0\n\u00a0\nVulnerability management\n\u00a0\nDetecting and quickly fixing vulnerable software that you rely on is among the most important responsibilities of any software or service provider. We take this responsibility seriously and share our remediation timeline commitments in our\u00a0Security Addendum.\n\u00a0\nInternally, we have automated vulnerability management to effectively track, prioritize, coordinate and remediate vulnerabilities in our environment. We perform daily authenticated vulnerability scans of Databricks and third-party\/open-source packages used by Databricks, along with static and dynamic code analysis (SAST and DAST) using trusted security scanning tools, before we promote new code or images to production. Databricks also employs third-party experts to analyze our public-facing sites and report potential risks.\n\u00a0\nDatabricks has funded a Vulnerability Response Program for monitoring emerging vulnerabilities before they\u2019re reported to us by our scanning vendors. We accomplish this using internal tools, social media, mailing lists and threat intelligence sources (e.g., US-CERT and other government, industry and open-source feeds). Databricks monitors open vulnerability platforms, such as\u00a0CVE Trends\u00a0and\u00a0Open CVDB. We have an established process for responding to these so we can quickly identify the impact on our company, product or customers. This program allows us to quickly reproduce reported vulnerabilities and resolve zero-day vulnerabilities.\n\u00a0\nOur Vulnerability Management Program is committed to treating Severity-0 vulnerabilities, such as zero days, with the highest urgency, prioritizing their fix above other rollouts.\n\u00a0\n\u00a0\nPenetration testing and bug bounty\n\u00a0\nWe perform penetration testing through a combination of our in-house offensive security team, qualified third-party penetration testers and a year-round public bug bounty program. We use a mixture of fuzzing, secure code review and dynamic application testing to evaluate the integrity of our platform and the security of our application. We conduct penetration tests on major releases, new services and security-sensitive features. The offensive security team works with our incident response team and security champions within engineering to resolve findings and infuse learnings throughout the company.\n\u00a0\nWe typically perform 8-10 external third-party penetration tests and 15-20 internal penetration tests per year, and all material findings must be addressed before a test can be marked as passed. As part of our commitment to transparency, we publicly share our platform-wide third-party test report in our\u00a0due diligence package.Close AllBug bountyOur\u00a0public bug bounty\u00a0program, facilitated by HackerOne, allows a global collective of cybersecurity researchers and penetration testers to test Databricks for security vulnerabilities. Some of the key decisions we\u2019ve made to make the program successful include:Encouraging an engaged community of hackers to be active on our program by providing transparency to our HackerOne program statistics such as response rate and payoutsPromptly responding to bug bounty submissions, with an average time-to-bounty under a weekPerforming variant analysis on every valid submission to identify alternative ways that an exploit may be used, and verifying 100% of fixesAdding bonuses that drive attention to the most important areas of the productWe work hard to make our program successful and to learn from each submission. Our open and collaborative approach to our bug bounty program has resulted in over 100 security researchers being thanked for over 200 reports. Thank you all for helping us keep Databricks secure!Customer penetration and vulnerability testingWe want our customers to have confidence in the workloads they run on Databricks. If your team would like to run a vulnerability scan or penetration test against Databricks, we encourage you to:Run vulnerability scans on data plane systems located inside of your cloud service provider account.Run tests against your code, provided that those tests are entirely contained within the data plane (or other systems) located in your cloud service provider account and are evaluating your controls.Join the\u00a0Databricks Bug Bounty\u00a0program to access a dedicated deployment of Databricks to perform penetration tests. Any penetration test against our multi-tenant control plane requires participation in the program.\u00a0\nSecurity investigations and incident response\n\u00a0\nWe use Databricks as our SIEM and XDR platform to process over 9 terabytes of data per day for detection and security investigations. We ingest and process logs and security signals from cloud infrastructure, devices, identity management systems, and SaaS applications. We use structured streaming pipelines and Delta Live Tables to identify the most relevant security events using a data-driven approach and statistical ML models to generate novel alerts, or to correlate, de-duplicate and prioritize existing alerts from known security products. We model our runbooks on adversary tactics, techniques and procedures (TTP) tracked using the\u00a0MITRE ATT&CK\u00a0framework. Our security investigations team uses collaborative Databricks notebooks to create repeatable investigation processes, continually evolve incident investigation playbooks, and perform threat hunting against more than 2 petabytes of historic event logs handling complex searches over unstructured and semi-structured data.\n\u00a0\nOur incident response team stays up to date and helps Databricks prepare for incident management scenarios by:\n\u00a0\n\nParticipating in industry-reputed courses from vendors like SANS and attending security conferences like fwd:cloudsec, Black Hat, BSides, RSA\nPerforming regular tabletop exercises with executive leadership and internal teams to practice security response scenarios relevant to Databricks products and corporate infrastructure\nCollaborating with engineering teams to prioritize platform observability to allow effective security detection and response\nRegularly updating hiring and training strategies based on an evolving incident response skills and capabilities matrix\n\nInternal accessWe apply strict policies and controls to internal employee access to our production systems, customer environments and customer data.Close AllCloud console accessWe require multifactor authentication to access core infrastructure consoles such as the cloud service provider consoles (AWS, GCP and Azure). Databricks has policies and procedures to avoid the use of explicit credentials, such as passwords or API keys, wherever possible. For example, only appointed security team members can process exception requests for new AWS IAM principals or policies.Databricks access to production systemsDatabricks employees can access the production system under very specific circumstances (such as emergency break-fix). Access is governed by a Databricks-built system that validates access and performs policy checks. Access requires that employees are connected to our VPN, and authenticate using our single sign-on solution with multifactor authentication.Learn more \u2192Separation of dutiesOur internal security standards call for the separation of duties wherever possible. For example, we centralize our cloud identity provider\u2019s authentication and authorization process to separate authorizing access (Mary should access a system) from granting access (Mary can now access a system).Least privilege\u00a0We prioritize least privilege access, both in internal systems and for our access to production systems. Least privilege is explicitly built into our internal policies and reflected in our procedures. For example, most customers can control whether Databricks employees have access to their workspace, and we programmatically apply numerous checks before access can be granted and automatically revoke access after a limited time.Learn more \u2192Secure software development lifecycleDatabricks has a software development lifecycle (SDLC) that builds security into all design, development and production steps \u2014 from feature requests to production monitoring \u2014 supported by tooling designed to trace a feature through the lifecycle. We have automatic security scanning and automated vulnerability tracking of systems, libraries and code.Close AllDesignDatabricks leverages an\u00a0Ideas Portal\u00a0that tracks feature requests and allows voting both for customers and employees. Our feature design process includes privacy and security by design. After an initial assessment, high-impact features are subject to a security design review from the product security team in association with the security champions from engineering, along with threat modeling and other security-specific checks.DevelopmentWe use an agile development methodology that breaks up new features into multiple sprints. Databricks does not outsource the development of the Databricks platform, and all developers are required to go through secure software development training \u2014 including the OWASP Top 10 \u2014 when hired and annually thereafter. Production data and environments are separated from development, QA and staging environments. All code is checked into a source control system that requires single sign-on with multifactor authentication and granular permissions. Code merges require approval from the functional engineering owners of each area impacted, and all code is peer reviewed. The product security team manually reviews security-sensitive code to eliminate business logic errors.Security scanningWe use best-of-breed tools to identify vulnerable packages or code. Automation in a preproduction environment runs authenticated host and container vulnerability scans of the operating system and installed packages, along with dynamic and static code analysis scans. Engineering tickets are created automatically for any vulnerabilities and assigned to relevant teams. The product security team also triages critical vulnerabilities to assess their severity in the Databricks architecture.Quality assuranceWe run quality checks (such as unit tests and end-to-end tests) at multiple stages of the SDLC process, including at code merge, after code merge, at release and in production. Our testing includes positive tests, regression tests and negative tests. Once deployed, we have extensive monitoring to identify faults, and users can get alerts about system availability via the\u00a0Status Page. In the event of any P0 or P1 issue, Databricks automation triggers a \u201c5 whys\u201d root cause analysis methodology that selects a member of the postmortem team to oversee the review. Findings are communicated to executive leadership, and follow-up items are tracked.Release ManagementDatabricks has a formal release management process that includes a formal go\/no-go decision before releasing code. Changes go through testing designed to avoid regressions and validate that new functionality has been tested on realistic workloads. Additionally, there is a staged rollout with monitoring to identify issues early. To implement separation of duties, only our deployment management system can release changes to production, and multiperson approval is required for all deployments.RolloutWe follow an immutable infrastructure model, where systems are replaced rather than patched to improve reliability and security and to avoid the risk of configuration drift. When new system images or application code is launched, we transfer workloads to new instances that launch with the new code. This is true both for the control plane and the data plane (see the\u00a0Security Features section for more on the Databricks architecture). Once code is in production, a verification process confirms that artifacts are not added, removed or changed without authorization.DocumentationThe final phase of the SDLC process is creating customer-facing documentation. Databricks docs are managed much like our source code, and documentation is stored within the same source control system. Significant changes require both technical and docs team review before they can be merged and published.Visit documentation \u2192Security Policy and Communication DetailsDatabricks follows RFC 9116, ISO\/IEC 30111:2019(E), and ISO\/IEC 29147:2018(E) standards for security vulnerability handling and communications. For details on our secure communications and PGP signature, please refer to our\u00a0security.txt\u00a0file.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/tungsten","text":"What is the Spark Tungsten Project?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTungstenAll>TungstenTry Databricks for freeGet StartedWhat is the Tungsten Project?Tungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance closer to the limits of modern hardware.Tungsten Project Includes These Initiatives:Memory Management and Binary Processing: leveraging application semantics to manage memory explicitly and eliminate the overhead of JVM object model and garbage collectionCache-aware computation: algorithms and data structures to exploit memory hierarchyCode generation: using code generation to exploit modern compilers and CPUsNo virtual function dispatches: this reduces multiple CPU calls which can have a profound impact on performance when dispatching billions of times.Intermediate data in memory vs CPU registers: Tungsten Phase 2 places intermediate data into CPU registers. This is an order of magnitudes reduction in the number of cycles to obtain data from the CPU registers instead of from memoryLoop unrolling and SIMD: Optimize Apache Spark\u2019s execution engine to take advantage of modern compilers and CPUs\u2019 ability to efficiently compile and execute simple for loops (as opposed to complex function call graphs).The focus on CPU efficiency is motivated by the fact that Spark workloads are increasingly bottlenecked by CPU and memory use rather than IO and network communication. The trend is shown by recent research on the performance of big data workloads.Additional ResourcesDeep Dive into Project Tungsten: Bringing Spark Closer to Bare MetalFrom DataFrames to Tungsten: A Peek into Spark\u2019s FutureSpark SQL: Another 16x Faster After TungstenBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/leadership-team","text":"Leadership Team | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLeadershipWith a long-term vision, our leadership team leverages decades of experience to chart a new course for data and AIMeet our teamExecutive teamFoundersBoard of directorsAli GhodsiCo-founder and Chief Executive OfficerAndy KofoidPresident, Global Field OperationsDavid ConteChief Financial OfficerAmy ReichanadterChief People OfficerTr\u00e2m PhiSVP and General CounselRon GabriskoChief Revenue OfficerRick SchultzChief Marketing OfficerHatim ShafiqueChief Operating OfficerFerm\u00edn SernaChief Security OfficerNaveen ZutshiChief Information OfficerVinod MarurSVP of EngineeringDavid MeyerSVP of ProductsAdam ConwaySVP of ProductsArsalan Tavakoli-ShirajiCo-founder and SVP of Field EngineeringProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/genomics","text":"What is Genomics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGenomicsAll>GenomicsTry Databricks for freeGet StartedGenomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DNA atoms. The field of genomics is interested in the genome as a whole structure; as a result, it can be defined as a study of the complete genetic material of an organism. Although DNA was first isolated in 1869, genomics has only started in the 1970s when the scientists determined the DNA sequence of simple organisms. The greatest breakthrough in the field of genomics occurred in 1995 when the entire genome sequence of a free-living organism, the Haemophilus influenza, was completed. The Human Genome Project was launched in 1990 with the aim to sequence all 3 billion letters of a human genome. Chromosome 22 was the first chromosome to be sequenced as a part of this project in 1999. The International Human Genome Sequencing Consortium published the first draft of the human genome in the journal Nature in February 2001 with the sequence of the entire genome's three billion base pairs some 90 percent complete. The full sequence was completed and published in April 2003. The evolving field of genomics generally includes several key research areas: Bioinformatics -is an interdisciplinary field that integrates computers, software tools, and databases for retrieving, analyzing and understanding of large amounts of biological informationProteomics - is a complex field of study focusing on the study of changes in protein expression patterns as related to diseases and environmental conditions.Structural genomics - is a field of genomics that involves the characterization of genome structures.Human genomics - As the name suggests, human genomics concentrates on studying the human genome sequence.Bacteriophage genomics - It refers to the study of bacteriophage genomes or genomics of viruses that infect bacteria. The scope of the study is to find an alternative treatment for those illnesses that have as a root cause an antibiotic-resistant bacteria.Metagenomics - It concentrates on the study of metagenomes or genetic material that is obtained from environmental samplesCyanobacteria genomics - This branch of genomics studies cyanobacteria, a phylum of bacteria that obtains its energy through photosynthesis.Pharmacogenomics - This field of genomic research is focused on the impact of genetic variation on a drug's efficacy and toxicityAdditional ResourcesUnified Analytics Platform for GenomicsData Analytics and Machine Learning for the Life Sciences IndustryGenomics DocumentationBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/09\/7-reasons-to-migrate-from-your-cloud-based-hadoop-to-the-databricks-lakehouse-platform.html","text":"7 Reasons to Migrate from your Cloud-based Hadoop to Databricks - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic Sector7 Reasons to Migrate From Your Cloud-Based Hadoop to the Databricks Lakehouse Platformby Chris Moon, Abhishek Dey and Ganesh RajagopalJune 9, 2022 in Platform BlogShare this postOver the past several years, many enterprises have migrated their legacy on-prem Hadoop workloads to cloud-based managed services like EMR, HDInsight, or DataProc. However, customers have started recognizing that the same challenges faced within their on-prem Hadoop environment (like reliability and scalability) get inherited into their existing cloud-based Hadoop platform. They observe that any cluster launch takes a long time to provision and even more time to autoscale during peak hours. As a result, they maintain long-running, overprovisioned clusters to manage the workload demands. A lot of time is spent on troubleshooting, infrastructure, resource management overhead and stitching different managed services on the cloud to maintain an end to end pipeline.Finally, this leads to wasted resources, complicating security and governance and escalating unnecessary costs. Customers ultimately want their data teams to be able to focus on solving business challenges, rather than troubleshooting inherited Hadoop platform issues.In this blog, we'll discuss the values and benefits of migrating from a cloud-based Hadoop platform to the Databricks Lakehouse Platform.Here are some notable benefits and reasons to consider migration from those cloud-based Hadoop services to Databricks.\u00a0Simplify your architecture with the Lakehouse PlatformCentralized data governance and securityBest-in-class performance for all data workloadsIncreased productivity gains and business valueDriving innovation with data and AIA cloud agnostic platformBenefits of Databricks Partner ecosystemLet's discuss in more detail and learn about these 7 reasons.1) Simplify your architecture with the Lakehouse PlatformThe Databricks Lakehouse Platform combines the best elements of data lakes and data warehouses to deliver the reliability, governance and performance of data warehouses with the openness, flexibility and machine learning support of data lakes.Often, cloud-based Hadoop platforms are used for specific use cases like data engineering and need to be augmented with other services and products for streaming, BI, and data science use cases. This leads to a complicated architecture that creates data silos and isolated teams, posing security and governance challenges.The Lakehouse Platform provides a unified approach that simplifies your data stack by eliminating these complexities.2) Centralized data governance and securityDatabricks brings fine-grained governance and security to lakehouse data with Unity Catalog. Unity Catalog allows organizations to manage fine-grained data permissions using standard ANSI SQL or a simple UI, enabling them to unlock their lakehouse for consumption safely. It works uniformly across clouds and data types.Unity Catalog moves beyond just managing tables to other data assets, such as machine learning models and files. As a result, enterprises can simplify how they govern all their data and AI assets. It is a critical architectural tenet for enterprises and one of the key reasons customers migrate to Databricks instead of using a cloud-based Hadoop platform.At a high level, Unity Catalog provides the following key capabilities:Centralized metadata and user managementCentralized data access controlsData lineageData access auditingData search and discoverySecure data sharing with Delta SharingApart from Unity Catalog, Databricks has features like Table Access Controls (TACLs), and IAM role credential passthrough which enable you to meet your data governance needs. For more details, visit the Data Governance documentation.Additionally, with Delta Lake, you automatically reap the benefits of schema enforcement and schema evolution support out of the box.Using Delta Sharing, you can securely share data across organizations in real time, independent of the platform on which the data resides. It is natively integrated into the Databricks Lakehouse Platform so you can centrally discover, manage and govern all of your shared data on one platform.3) Best-in-class performance for all data workloadsCustomers get best-in-class performance by migrating to the Databricks Photon engine, which provides high-speed query performance at a low cost for all types of workloads directly on top of the lakehouse.With Photon, most analytics workloads can meet or exceed data warehouse performance without moving data into a data warehouse.Photon is compatible with Apache Spark\u2122 APIs and SQL, so getting started is as easy as turning it on.Written from the ground up in C++, Photon takes advantage of modern hardware for faster queries, providing better price\/performance than other cloud data warehouses. For more details, please visit the blog post at data-warehousing-performance-recordApart from this, Databricks Enhanced Autoscaling optimizes cluster utilization by automatically allocating cluster resources based upon workload volume, with minimal impact on the data processing latency of your pipelines. Cluster scaling is a significant concern with cloud-based Hadoop platforms, and in some cases, it takes up to 30 minutes to autoscale.As a result of Databricks' superior performance compared to the cloud-based Hadoop platforms, the overall total cost of ownership dramatically decreases. Customers realize a reduced infrastructure spend and better price\/performance simultaneously.4) Increased productivity gains and business valueCustomers can move faster, collaborate better and operate more efficiently when they migrate to Databricks.Databricks removes the technical barriers that limit collaboration among analysts, data scientists, and data engineers, enabling data teams to work together more efficiently. Customers see higher productivity among data scientists, data engineers and sql analysts eliminating manual overhead.Databricks' customers significantly accelerate time-to-value, and increase revenues by enabling data engineering, data science and BI teams to build end-to-end pipelines. On the other hand, they realized that it was impossible to achieve the same using a cloud-based Hadoop platform, where multiple services must be stitched together to deliver the needed data products.With increased productivity, Databricks helps unlock new business use cases, accelerating and expanding value realization from business-oriented use cases.A recent Forrester study titled The Total Economic Impact\u2122 (TEI) of the Databricks Unified Data Analytics Platform found that organizations deploying Databricks realize nearly $29 million in total economic benefits and a return on investment of 417% over a three-year period. They also concluded that the Databricks platform pays for itself in less than six months.5) Driving innovation with data and AIDatabricks is a comprehensive, unified platform that caters to all personas critical in delivering business value from data, like data engineers, data scientists & ML engineers, as well as SQL & BI analysts. Any member of your data team can quickly build an end-to-end data pipeline, starting with data ingestion, curation, feature engineering, model training, and validation to deployment within Databricks. On top of that, the data processing can be interchangeably implemented in both batch and streaming, utilizing the Lakehouse architecture.Unlike cloud-based Hadoop platforms, Databricks constantly strives to innovate and provide its users with a modern data platform experience. Here are some of the notable platform features available to anyone using Databricks:Lakehouse interoperability using Delta on any cloud storageDelta Lake is an open format storage layer that delivers reliability, security and performance on your data lake \u2014 for both streaming and batch operations. By replacing data silos with a single home for structured, semi-structured and unstructured data, Delta Lake is the foundation of a cost-effective, highly scalable lakehouse. Compared to other alternative open format storage layers like Iceberg and Hudi, Delta Lake is the most performant and widely used format in the Lakehouse architecture.ETL development using Delta Live TablesDelta Live Tables (DLT) is the first ETL framework that uses a simple declarative approach to building reliable data pipelines and automatically managing your infrastructure at scale, so that data analysts and engineers can spend less time on tooling and focus on getting value from data. With DLT, engineers are able to treat their data as code and apply modern software engineering best practices like testing, error handling, monitoring and documentation to deploy reliable pipelines at scale.Easy & automatic data ingestion with Auto LoaderOne of the most common challenges is simply ingesting and processing data from cloud storage into your Lakehouse consistently and automatically. Databricks Auto Loader simplifies the data ingestion process by scaling automated data loading from cloud storages in streaming or batch mode.Bring your warehouse to the data lake using Databricks SQLDatabricks SQL (DB SQL) allows customers to operate a multi-cloud lakehouse architecture within their data lake, and provides up to 12x better price\/performance than traditional cloud data warehouses, open-source big data frameworks, or distributed query engines.Managing the complete machine learning lifecycle with MLflowMLflow, an open-source platform developed by Databricks, helps manage the complete machine learning lifecycle with enterprise reliability, security and scale. One immediately realizes the benefits of being able to perform experiment tracking, model management and model deployment with ease.Automate your Machine Learning Lifecycle with AutoMLDatabricks AutoML allows you to generate baseline machine learning models and notebooks quickly. ML experts can accelerate their workflow by fast-forwarding through the usual trial-and-error and focusing on customizations using their domain knowledge, and citizen data scientists can quickly achieve usable results with a low-code approach.Build your Feature Store within the LakehouseDatabricks provides data teams with the ability to create new features, explore and reuse existing ones, publish features to low-latency online stores, build training data sets and retrieve feature values for batch inference using Databricks Feature Store. It is a centralized repository of features. It enables feature sharing and discovery across your organization and also ensures that the same feature computation code is used for model training and inference.Reliable orchestration with WorkflowsDatabricks Workflows is the fully-managed orchestration service for all your data, analytics, and AI needs. You can create and run reliable production workloads on any cloud while providing deep and centralized monitoring with simplicity for end-users. Workflows allow users to build ETL pipelines that are automatically managed, including ingestion, and lineage, using Delta Live Tables. You can also orchestrate any combination of Notebooks, SQL, Spark, ML models, and dbt as a Jobs workflow, including calls to other systems.6) A cloud agnostic platformA multi-cloud strategy is becoming essential for organizations that need an open platform to do unified data analytics, all the way from ingestion, to BI and AI.With data in multiple clouds, organizations can't afford to be constrained by one cloud's native services, since their existence now depends on the data residing on their cloud storage.Organizations need a multi-cloud platform that provides visibility, control, security and governance in a consistent manner for all their teams regardless of which clouds they are using.The Databricks Lakehouse Platform empowers customers to leverage multiple clouds through a unified data platform that uses open standards.As a cloud-agnostic platform, Databricks workloads run similarly across any cloud platform while leveraging the existing data lake on each cloud storage. As a user, once you migrate the workloads to Databricks, you can use the same open source code interchangeably on any cloud. It mitigates the risks of locking you in a cloud-native Hadoop platform.7) Benefits of Databricks Partner ecosystemDatabricks is an integral part of the modern data stack, enabling digital natives and enterprises to mobilize data assets for more informed decisions fast. It has a rich partner ecosystem (over 450 partners globally) that allows this to occur seamlessly across the various phases of a data journey, from data ingestion, building data pipelines, data governance, data science and machine learning to BI\/Dashboards.Within Databricks, Partner Connect allows you to integrate your lakehouse with popular data platforms like dbt, Fivetran, Tableau, Labelbox, etc. and set it up in a few clicks with pre-built integrations.Unlike cloud-based Hadoop platforms, with Databricks, you can build your end to end pipeline with just a few clicks and rapidly expand the capabilities of your lakehouse. To find out more about Databricks technology partners, visit www.databricks.com\/technology.Next StepsMigration from one platform to another is not an easy decision to make. It involves\nevaluating the current architecture, reviewing the challenges and pain points, and validating the suitability and sustainability of the new platform. However, organizations always look to do more with their data and stay competitive by empowering their data teams with innovative technologies to do more analytics and AI, while reducing infrastructure maintenance and administration burdens. To achieve these near and long-term goals, customers need a solution that goes beyond the legacy on-prem or cloud-based Hadoop solutions. Explore each of the 7 reasons in this blog and see how these can bring values to your business.Migrating From Hadoop to Data Lakehouse for Dummies\nGet faster insights at a lower cost when you migrate to the Lakehouse.Download NowTry Databricks for freeGet StartedRelated posts5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse ArchitectureAugust 6, 2021 by Harsh Narula in Data Strategy\nThe decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision...\nTop Considerations When Migrating Off of HadoopJuly 22, 2021 by Manveer Sahota and Ron Guerrero in Data Strategy\nApache Hadoop was created more than 15 years ago as an open source, distributed storage and compute platform designed for large data sets...\nThe Hidden Value of Hadoop MigrationFebruary 18, 2021 by Brian Dirking in Company Blog\nFor years Hadoop was the default technology for big data analytics. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lorenzo-de-tomasi\/#","text":"Lorenzo De Tomasi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLorenzo De TomasiData Architect, Data Platforms Lead at Barilla at Barilla G. e R. Fratelli S.p.A.Back to speakersLorenzo De Tomasi is a skilled AI and Data Engineering manager. Holding a Computer Science Engineering degree, he worked as a Data Scientist at Luxottica Group, developing computer vision algorithms for quality processes. Now, he leads Advanced Analytics technology at Barilla Group, implementing complex Machine Learning, Deep Learning, and Advanced Analytics solutions in Marketing, Finance, RDQ, Sales, and more.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\ucf58\ud150\uce20\ub97c \uc81c\uacf5\ud55c \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\uc138\uc694.\uc790\uc138\ud788\uc6e8\ube44\ub098Apple\uacfc Disney+\uc5d0\uc11c \ud1b5\ud569\ud615 \ubd84\uc11d\uacfc AI\ub97c \uc131\uacf5 \uc218\ub2e8\uc73c\ub85c \ud65c\uc6a9\ud558\ub294 \ubc95\uc9c0\uae08 \uc2dc\uccad\ud558\uae30\ud31f\uce90\uc2a4\ud2b8Humana \uc120\uc784 \ubd80\uc0ac\uc7a5(SVP), \ucd5c\uace0 \ub370\uc774\ud130 \ubc0f \ubd84\uc11d \ucc45\uc784\uc790(CDAO)\uc778 Slawek Kierner \ub2d8 \uc804\ud558\ub294 \ub370\uc774\ud130 + AI\uac00 \uc758\ub8cc \uc11c\ube44\uc2a4 \ud615\ud3c9\uc131\uc5d0\uc11c \uc218\ud589\ud558\ub294 \uc5ed\ud560\uc9c0\uae08 \uc2dc\uccad\ud558\uae30\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ubb38\uc758\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pamela-pettit","text":"Pamela Pettit - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPamela PettitSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/luk-verhelst\/#","text":"Luk Verhelst - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLuk VerhelstData Architect at Volvo Group (consultant)Back to speakersOccupation:\nData architect (consultant)\nClient: Volvo Group\nPersonal:\nBased in Brussels, born in 72, 3 kids (youngest is Linus, an ode to...)\nPrevious:\n- Started software engineering in 90s\n- IT management roles until 2018\n- Since 2018 data architecture roles\n- Graduated Media and Communication studiesLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/azure-databricks-events","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sirui-sun","text":"Sirui Sun - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSirui Sun DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zoe-durand","text":"Zoe Durand - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZoe DurandSenior Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ali-ghodsi","text":"Ali Ghodsi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAli GhodsiCo-founder and CEO at DatabricksBack to speakersAli Ghodsi, the CEO and co-founder of Databricks, is responsible for the growth and international expansion of the company. He previously served as the VP of Engineering and Product Management before taking the role of CEO in January 2016. In addition to his work at Databricks, Ali serves as an adjunct professor at UC Berkeley and is on the board at UC Berkeley\u2019s RISELab. Ali was one of the original creators of the open source project, Apache Spark, and ideas from his academic research in the areas of resource management and scheduling and data caching have been applied to Apache Mesos and Apache Hadoop. Ali received his MBA from Mid-Sweden University in 2003 and a Ph.D. from KTH\/Royal Institute of Technology in Sweden in 2006 in the area of Distributed Computing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/migrating-warehouse-lakehouse","text":"\n\n\n\n\n\n\n\nMigrating from a Data Warehouse to a Data Lakehouse\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/product\/feature-store","text":"Databricks Feature Store | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWFeature StoreThe first feature store co-designed with a data platform and MLOps frameworkTry for freeSchedule a demoProvide data teams with the ability to create new features, explore and reuse existing ones, publish features to low-latency online stores, build training data sets and retrieve feature values for batch inference.Features as reusable assetsFeature Registry provides a searchable record of all features, their associated definition, source data, and their consumers, eliminating considerable rework across teams. Data scientists, analysts and ML engineers can search for features based on the consumed raw data and either use features directly or fork existing features.Consistent features for training and servingFeature Provider serves the features in two modes. Batch mode provides features at high throughput for training ML models or batch inference. Online mode provides features at low latency for serving ML models or for the consumption of the same features in BI applications. Features used in model training are automatically tracked with the model and, during model inference, the model itself retrieves them directly from the feature store.Secure features with built-in governanceFeature store integrations provide the full lineage of the data used to compute features. Features have associated ACLs to ensure the right level of security. Integration with MLflow ensures that the features are stored alongside the ML models, eliminating drift between training and serving time.ResourcesVirtual EventLearn moreDocumentationDatabricks Feature Store DocumentationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=legal","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal\/privacyshieldnotice","text":"Privacy Shield Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy Shield NoticeWe do not rely on the Privacy Shield for transfers of personal data but continue to adhere to the commitments we made when we certified to the Privacy Shield.Databricks, Inc. has self-certified to the EU\u2013U.S. and Swiss-U.S. Privacy Shield Frameworks as set forth by the U.S. Department of Commerce regarding the collection, use, and retention of personal data transferred from the EEA, United Kingdom and Switzerland to the United States. Databricks has certified to the U.S. Department of Commerce that it adheres to the Privacy Shield Principles with respect to such information.If you have any questions or complaints about our handling of your personal data under the Privacy Shield, please contact us at [email\u00a0protected] with the subject \u201cPrivacy Shield\u201d. Databricks will respond to your request within 45 days. If you have an unresolved privacy or data use concern that we have not addressed satisfactorily, you may contact our U.S.-based third party dispute resolution provider (free of charge) at https:\/\/www.jamsadr.com\/eu-us-privacy-shield. If neither Databricks nor our dispute resolution provider resolves your complaint, you may have the possibility, under certain conditions, to invoke binding arbitration through the Privacy Shield Panel.Databricks is responsible for personal data that we receive under the Privacy Shield, including where we transfer such personal data to a third party acting as our agent. Please be aware that we may be required to disclose personal data that we receive under the Privacy Shield in response to lawful requests by public authorities, including to meet national security or law enforcement requirements. Databricks\u2019 commitments under the Privacy Shield are subject to the investigatory and enforcement powers of the U.S. Federal Trade Commission (FTC). To learn more about the Privacy Shield program, and to view our certification, please visit the U.S. Department of Commerce\u2019s website here.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/product\/aws?itm_data=menu-item-awsProduct","text":"Databricks on AWS \u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 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\u3067\u30c7\u30fc\u30bf\u5206\u6790\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u30b7\u30f3\u30d7\u30eb\u306b\u3001\u30b9\u30b1\u30fc\u30e9\u30d6\u30eb\u306b\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u306e\u30dd\u30c6\u30f3\u30b7\u30e3\u30eb\u3092\u6700\u5927\u9650\u306b\u5f15\u304d\u51fa\u3059\u65b9\u6cd5\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u69cb\u7bc9\u4e8b\u4f8b | DoorDash\u3001Grammarly\u696d\u754c\u7c73\u30d8\u30eb\u30b9\u30b1\u30a2 Prognos \u793e\u4e8b\u4f8b\uff1aAI\u30fb\u6a5f\u68b0\u5b66\u7fd2\u306e\u6d3b\u7528\u3092\u901a\u3058\u3066\u5927\u898f\u6a21\u306a\u81e8\u5e8a\u691c\u67fb\u30c7\u30fc\u30bf\u304b\u3089\u5b9f\u8df5\u7684\u306a\u77e5\u898b\u3092\u5f97\u308b\u653f\u5e9c\u6a5f\u95a2\u306e\u4e8b\u4f8b\uff1a\u6a5f\u68b0\u5b66\u7fd2\u304c\u653f\u5e9c\u6a5f\u95a2\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u5206\u6790\u3092\u5909\u9769\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u0000\u0000\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jim-thorstad","text":"Jim Thorstad - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJim ThorstadSolutions Architect at DatabricksBack to speakersTBDLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks-azure?itm_data=azurepage-closingtrialbutton-azuretrial","text":"Try Databricks on Azure \u2013 DatabricksTry Databricks on AzureDiscover how easy it is to simplify your data architecture by unifying all of your analytics and AI workloads on a simple open lakehouse platform.Azure Databricks is optimized for Azure and tightly integrated with Azure Data Lake Storage, Azure Data Factory, Power BI and many more Azure services.Join thousands of customers who already use this game-changing platform for their data teams.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks VenturesInvesting in the future of data, analytics and AI\nDatabricks Ventures invests in innovative companies that share our view of the future for data, analytics and AI. Our inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.Portfolio company benefitsExclusive insight into the product roadmap and support for building deep technical integrationsGuidance and best practices from the network of Databricks mentorsBroader reach by partnering with Databricks go-to-market programsLakehouse Fund investment\nfocusA shared vision to build the future of data, analytics and AI on the lakehouse architectureInvestments in early to growth-stage companies in partnership with a lead investorProjects and entrepreneurs that share Databricks\u2019 commitment to open source and building on open platforms, much like the Databricks LakehouseOur PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\nLearn moreArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\nLearn moredbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\nLearn moreHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.Learn moreThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.Learn moreThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.Learn moreLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.Learn moreMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.Learn morePerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.Learn moreRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.Learn moreTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.Learn moreFAQsWhy partner with Databricks Ventures?\nDepending on the size and stage of the investment, Databricks will provide unique access to product roadmap direction, technical integration support, and go-to-market support; access to Databricks mentors for guidance and best practices; and exposure in Databricks\u2019 global go-to-market programs, including our Data + AI Summit series.What are Databricks Ventures\u2019 investment criteria?\nWe are investing in innovative founders of private companies who share our view of the future for data and AI and are committed to extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.What stages does Databricks invest in?\nWe invest in early through growth-stage private companies within the data, analytics and AI ecosystem.Does Databricks Ventures lead investment rounds?\nNo, we do not lead rounds. Our strategy is to invest alongside a lead institutional investor.What is Databricks Ventures\u2019 typical investment size?\nDatabricks Ventures takes minority positions in rounds led by institutional VCs; typical check size varies based on stage of company and size of funding round.Does Databricks take board seats?No, Databricks does not plan to take board seats in portfolio companies.Build your startup on DatabricksDatabricks for Startups offers free credits, expert advice and go-to-market support.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/legal\/supplemental-privacy-notice-california-residents","text":"Supplemental Privacy Notice for California Residents | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesSupplemental Privacy Notice for California ResidentsLast updated: January 3, 2023We provide the following information to California residents pursuant to the California Consumer Privacy Act, as amended by the California Privacy Rights Act (\u201cCCPA\u201d). This information supplements our general Privacy Notice. For a description of all of our data collection, use and disclosure practices, please read our Privacy Notice in its entirety. Terms that are capitalized but not defined below have the meanings set forth in our Privacy Notice.Categories of Personal InformationBelow, we describe the categories of Personal Information (as defined in the CCPA), that we have collected within the preceding 12 months and may collect on a going-forward basis:Identifiers\u00a0Personal information categories listed in the California Customer Records statute (Cal. Civ. Code \u00a7 1798.80(e)) (e.g., name, address, email address)Characteristics of protected classifications under California or federal lawCommercial information (e.g., transaction data)Internet or other similar network activityGeolocation data (e.g., general location derived from an IP address)Sensory data (e.g., audio, video)Professional or employment-related informationEducation informationInferences drawn from the preceding categories of Personal InformationWithin these categories of Personal Information, we may also collect the following categories of Sensitive Personal Information (as defined in the CCPA): Account log-in, financial account, debit card, or credit card number, in combination with any required security or access codes, password, or credentials allowing access to the accountCategories of Recipients of Personal InformationFor each category of Personal Information (including Sensitive Personal Information) listed above, we disclose this information as described in the \u201cHow we share your information\u201c section of our Privacy Notice. In addition, we disclose Identifiers and Internet or other similar network activity to advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising).Sources of Personal InformationWe obtain the categories of Personal Information listed above directly from you or from devices on which you use our Databricks Services, as well as from the following categories of sources: our corporate affiliates, publicly-available databases, third-party business partners, social media sites, and other third-party sources, and as described in our \u201cInformation We Collect About You\u201c section of the Privacy Notice.Purposes for Which We Use Personal InformationWe use Personal Information for a variety of business and commercial purposes, as described in the \u201cHow We Use Your Information\u201c section of our Privacy Notice, which is linked above.\u00a0Retention Period CriteriaDatabricks retains the Personal Information described above for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in our Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.CCPA Rights and RequestsYou may make the following types of requests under the CCPA with respect to Personal Information that we process on our own behalf. Note: If you wish to make a CCPA request with respect to Personal Information submitted through or otherwise made available to the Platform Services, please direct your request to the relevant Customer directly, as that data is governed by the terms of our agreement with our Customer.Requests to Know, Correct, and Delete: You may request:\u00a0(i) Access to a copy of the specific pieces of Personal Information that we have collected about you;\u00a0\u00a0(ii) Correction of Personal Information that we maintain about you, if it is inaccurate; and\/or\u00a0(iii) Deletion of Personal Information, subject to certain exceptions.You can submit a request online by filling out a request form here or emailing us at [email\u00a0protected]. We will respond to your request consistent with the CCPA, and subject to any exceptions that may apply under the CCPA. We may need to request additional Personal Information from you, such as email address, state of residency, or mailing address, in order to verify your identity and protect against fraudulent requests. If you maintain a password-protected account with us, we may verify your identity through our existing authentication practices for your account and require you to re-authenticate yourself before disclosing or deleting your Personal Information.Requests to Opt-Out of Sale or Sharing: You also may opt out of the \u201csale\u201d or \u201csharing\u201d of your Personal Information, as \u201csale\u201d and \u201csharing\u201d are defined under CCPA.We do not sell Personal Information in the traditional sense of exchanging information for monetary payment. However, because the definitions of \u201csale\u201d and \u201csharing\u201d under the CCPA may include the disclosure of your information to certain types of advertising and marketing partners, we provide California residents with the right to opt-out of any such sale or sharing of their Personal Information. As noted above, we may disclose or make available Identifiers or Internet or other similar activity to advertising partners. We allow you to opt out of such disclosures, as they may constitute \u201csale\u201d or \u201csharing\u201d as defined under the CCPA. We do not knowingly \u201csell\u201d or \u201cshare\u201d the Personal Information of individuals under 16 years of age.You may opt-out of the Sale or Sharing of Personal Information for purposes of online analytics and advertising by visiting our \u201cYour Privacy Choices\u201c page. We also recognize opt-out preference signals as required by the CCPA.Authorized AgentsTo make a request as an authorized agent on behalf of a California resident, you may use the submission methods noted above. As part of our verification process, we may request that you provide, as applicable, proof concerning your status as an authorized agent.\u00a0If you are making a Request to Know, Correct, or Delete on behalf of a California resident and have not provided us with a qualifying power of attorney from the resident, we may also require the resident to verify their own identity directly with us; or directly confirm with us that they provided you permission to submit the request.Nondiscrimination\u00a0You have the right to be free from unlawful discriminatory treatment for exercising any of your CCPA rights.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amanda-milberg","text":"Amanda Milberg - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmanda MilbergSenior Partner Sales Engineer at DataikuBack to speakersAmanda is a Senior Partner Sales Engineer with a strong interest in NLP and AI \/ Machine Learning business solutions. Amanda has a proven track record of assisting large institutions in business transformation efforts in the advanced analytics space and an innate ability to explain deep technical concepts to a broad audience.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/legal\/privacynotice","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gregory-little","text":"Gregory Little - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGregory LittleDCDAO for Enterprise Platforms and Business Optimization at DoD CFO Transformation OfficeBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/data-sharing","text":"What is Data Sharing?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData SharingAll>Data SharingTry Databricks for freeGet StartedWhat is data sharing?Data sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or externally - is an enabling technology for new business opportunities. Sharing data as well as consuming data from external sources allows to \u200b\u200bcollaborate with partners, establish new partnerships and generate new revenue streams with data monetization.Traditional data sharing technologiesFirstly, there are technologies such as SFTP (SSH File Transfer Protocol), or cloud object storage that allow the implementation of home-grown solutions. However, SFTP doesn't scale well for a large number of clients and only serves files offloaded to an FTP server. Using pre-signed object store URLs for sharing data scales to the bandwidth of the object store cloud service, but only works for one particular cloud vendor.Commercial\/closed source data sharing offeringsSecondly, there are data sharing solutions baked into vendor products, such as Oracle, AWS Redshift, or Snowflake. These solutions are convenient to use within a product and they share tables instead of files, but they aren't open and therefore don't permit data sharing with a different platform.Open source, modern data sharing solutionsOpen source-based solutions eliminate the lock-in of commercial solutions and bring a number of additional benefits such as community-developed integrations with popular, open source data processing frameworks. In addition, open protocols allow the easy integration of commercial clients, such as BI tools.Delta SharingDelta Sharing is the world's first open protocol for secure data sharing, making it simple to share data with other organizations regardless of which computing platforms they use.Share live data directly \u2014 Easily share existing, live data in your Delta Lake without copying it to another system.Supports diverse clients \u2014 Data recipients can directly connect to Delta Shares from Pandas, Apache Spark\u2122, Rust, and other systems without having to first deploy a specific compute platform. Reduce the friction to get your data to your users.Security and governance \u2014 \u200b\u200bDelta Sharing allows you to easily govern, track, and audit access to your shared data sets.Scalability \u2014 Share large scale datasets reliably and efficiently by leveraging cloud storage systems like S3, ADLS, and GCS.Delta Sharing on DatabricksDatabricks natively integrates with Delta Sharing in our Unity Catalog, providing a streamlined experience for sharing data both within and across organizations. Administrators can manage shares using a new CREATE SHARE SQL command or REST APIs and audit all accesses centrally. Recipients can then consume the data from any platform on any cloud.\u00a0\u00a0Delta Sharing: An open ecosystemThe Delta Sharing ecosystem of open source and commercial partners is growing every day. Easily share data with anyone, no matter where.\u00a0\u00a0Learn more about data sharing on DatabricksSign up to join the Databricks Delta Sharing waitlist for preview access and updates.Additional ResourcesDelta Sharing DemoDelta Sharing on DatabricksDelta Sharing - delta.ioIntroducing Delta Sharing: An Open Protocol for Secure Data SharingDelta Sharing Databricks ODSC WebinarBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/solutions","text":"Aceleradores de solu\u00e7\u00f5es da Databricks - Casos de uso da DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks para cada setorSolu\u00e7\u00f5es de an\u00e1lises de dados e IA sem compromisso criadas especificamente para o seu setorIntrodu\u00e7\u00e3oAgendar uma demonstra\u00e7\u00e3oDescubra o lakehouse para o seu setorComunica\u00e7\u00f5es, m\u00eddia e entretenimentoDesperte mais aten\u00e7\u00e3o, capture a imagina\u00e7\u00e3oSaiba maisServi\u00e7os financeirosDesenvolva confian\u00e7a, garanta tranquilidadeSaiba maisSa\u00fade e ci\u00eancias da vidaDescubra e ofere\u00e7a melhores cuidadosSaiba maisVarejo e bens de consumoGuie seus clientes em suas jornadas e promova sua marcaSaiba maisExplore todos os setoressearchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listSolu\u00e7\u00f5es para cada setorDa ideia \u00e0 prova de conceito (PoC) em apenas duas semanasOs aceleradores de solu\u00e7\u00f5es da Databricks s\u00e3o guias criados especificamente para acelerar os resultados usando notebooks totalmente funcionais e pr\u00e1ticas recomendadas. Os clientes Databricks economizam tempo de descoberta, design, desenvolvimento e testes. Muitos v\u00e3o da ideia \u00e0 prova de conceito (PoC) em apenas duas semanas.Explorar aceleradoresPronto para come\u00e7ar?Descubra o que a Databricks pode fazer por voc\u00ea com uma avalia\u00e7\u00e3o gratuita.Inicie seu testeProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suze-howse\/#","text":"Suze Howse - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuze HowseHead of Enterprise Data at Marks and SpencerBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/manu-sharma","text":"Manu Sharma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingManu SharmaCEO at LabelboxBack to speakersManu is an engineer, designer, and serial entrepreneur. He is the Founder & CEO of Labelbox, an AI infrastructure software company. Previously, he developed products at Planet Labs and DroneDeploy and co-founded renewable energy and space exploration companies. He studied aerospace engineering and a wide range of robotics, electrical engineering, and industrial design subjects. He is an active pilot and holds M.S. & B.S. degrees from Stanford University and Embry-Riddle Aeronautical University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/donghwa-kim\/#","text":"Donghwa Kim - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDonghwa KimSr. Director of IT Architecture at Ontada, a McKesson CompanyBack to speakersDonghwa Kim is the Sr. Director of Architecture at Ontada, a McKesson company. He is responsible for delivering the next generation Data and Analytics platform using Databricks Lakehouse. Prior to joining Ontada, he worked as the enterprise architect for migrating a large scale on-prem data warehouse into Databricks at Veterans Affairs (VA) and at Centers for Medicare and Medicaid Services (CMS). He has over 20 years of IT experiences within healthcare and finance industries. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/product\/data-streaming","text":"Datenstreaming | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatenstreamingEchtzeit-Analytics, ML und Anwendungen leicht gemachtErste SchritteDemo ansehenDie Databricks Lakehouse Platform vereinfacht das Datenstreaming erheblich und bietet Echtzeitanalysen, Machine Learning und Anwendungen auf einer Plattform.Erm\u00f6glichen Sie es Ihren Datenteams, Streamingdaten-Workloads mit den Sprachen und Tools zu erstellen, die sie bereits kennen. Vereinfachen Sie die Entwicklung und den Betrieb, indem Sie die Produktionsaspekte automatisieren, die mit dem Aufbau und der Wartung von Daten-Workloads in Echtzeit verbunden sind. Beseitigen Sie Datensilos mit einer einzigen Plattform f\u00fcr Streaming- und Batch-Daten.Schnelleres Erstellen von Streaming-Pipelines und -AnwendungenVerwenden Sie die Sprachen und Tools, die Sie bereits kennen, mit vereinheitlichten Batch- und Streaming-APIs in SQL und Python. Nutzen Sie Echtzeit-Analytics, ML und Anwendungen f\u00fcr das gesamte Unternehmen.Den Betrieb mit automatisierten Tools vereinfachenStellen Sie Ihre Echtzeit-Pipelines und Anwendungen einfach in der Produktion bereit und verwalten Sie sie. Automatisierte Tools vereinfachen die Orchestrierung von Aufgaben, die Fehlertoleranz\/Notfallwiederherstellung, die automatische \u00dcberpr\u00fcfung, die Leistungsoptimierung und die automatische Skalierung.Vereinheitlichung der Governance f\u00fcr alle Ihre Echtzeitdaten \u00fcber Clouds hinwegUnity Catalog bietet Ihrem Lakehouse ein einheitliches Governance-Modell f\u00fcr all Ihre Streaming- und Batch-Daten und vereinfacht so die Erkennung, den Zugriff und die gemeinsame Nutzung von Echtzeitdaten.Wie funktioniert es?Aufnahme und Transformation von StreamingdatenEchtzeitanalysen, ML und AnwendungenAutomatisierte operative ToolsStream-Verarbeitungs-Engine der n\u00e4chsten GenerationVereinheitlichte Verwaltung und SpeicherungAufnahme und Transformation von StreamingdatenVereinfachen Sie die Datenaufnahme und ETL f\u00fcr Streaming-Datenpipelines mit Delta-Live-Tables. Nutzen Sie einen einfachen deklarativen Ansatz f\u00fcr das Daten-Engineering, der Ihren Teams die Sprachen und Tools zur Verf\u00fcgung stellt, die sie bereits kennen, wie SQL und Python. Erstellen und betreiben Sie Batch- wie auch Streaming-Pipelines an zentraler Stelle mit steuerbaren und automatisierten Aktualisierungseinstellungen, um Zeit zu sparen und die betriebliche Komplexit\u00e4t zu verringern. Unabh\u00e4ngig davon, wohin Sie Ihre Daten senden m\u00f6chten, sorgt der Aufbau von Streaming-Daten-Pipelines auf der Databricks Lakehouse Platform daf\u00fcr, dass Sie keine Zeit zwischen Rohdaten und bereinigten Daten verlieren.\u201eImmer mehr Gesch\u00e4ftsbereiche nutzen die Plattform im gesamten Unternehmen auf eine Selfservice-Weise, die zuvor nicht m\u00f6glich war. Ich kann den positiven Einfluss nicht genug loben, den Databricks auf Columbia hatte.\u201c\u2013 Lara Minor, Senior Enterprise Data Manager, Columbia SportswearMehr InformationenEchtzeitanalysen, ML und AnwendungenVerbessern Sie mit Streamingdaten sofort die Genauigkeit und Umsetzbarkeit Ihrer Analytics und KI. Ihr Unternehmen profitiert von Echtzeiterkenntnissen als nachgelagerter Effekt von Streamingdaten-Pipelines. Unabh\u00e4ngig davon, ob Sie SQL-Analysen und BI-Reporting durchf\u00fchren, Ihre ML-Modelle trainieren oder operative Echtzeitanwendungen entwickeln \u2013 geben Sie Ihrem Unternehmen die aktuellsten Daten, um Einblicke in Echtzeit, genauere Prognosen und schnellere Entscheidungen zu erhalten, sodass Sie der Konkurrenz immer einen Schritt voraus bleiben.\u201eWir m\u00fcssen unseren Gesch\u00e4ftspartnern immer die aktuellsten und genauesten Daten zur Verf\u00fcgung stellen, andernfalls verlieren sie das Vertrauen in die Erkenntnisse ... Databricks Lakehouse hat das, was bisher unm\u00f6glich war, extrem einfach gemacht.\u201c\u2013 Guillermo Rold\u00e1n, Head of Architecture, LaLiga TechMehr InformationenAutomatisierte operative ToolsW\u00e4hrend Sie Streamingdaten-Pipelines erstellen und bereitstellen, automatisiert Databricks viele der komplexen operativen Aufgaben, die f\u00fcr die Produktion erforderlich sind. Dazu geh\u00f6ren die automatische Skalierung der zugrunde liegenden Infrastruktur, die Orchestrierung von Pipeline-Abh\u00e4ngigkeiten, Fehlerbehandlung und Notfallwiederherstellung, Leistungsoptimierung und mehr.Enhanced Autoscaling optimiert die Cluster-Auslastung, indem automatisch Datenverarbeitungsressourcen f\u00fcr jeden einzelnen Workload zugewiesen werden. Diese Funktionen zusammen mit automatischen Datenqualit\u00e4tstests und Ausnahmemanagement helfen Ihnen, weniger Zeit f\u00fcr die Erstellung und Wartung betrieblicher Tools aufzuwenden, sodass Sie sich darauf konzentrieren k\u00f6nnen, das Optimum aus Ihren Daten herauszuholen.Mehr InformationenStream-Verarbeitungs-Engine der n\u00e4chsten GenerationSpark Structured Streaming ist die Kerntechnologie, die Datenstreaming auf der Databricks Lakehouse Platform erm\u00f6glicht und eine einheitliche API f\u00fcr die Batch- und Stream-Verarbeitung bietet. Die Databricks Lakehouse Platform ist der beste Ort, um Ihre Apache Spark-Workloads mit einem verwalteten Service auszuf\u00fchren, der nachweislich eine Verf\u00fcgbarkeit von 99,95 % aufweist. Ihre Spark-Workloads werden durch Photon weiter beschleunigt, die Lakehouse-Engine der n\u00e4chsten Generation, die mit den Apache Spark-APIs kompatibel ist und ein au\u00dfergew\u00f6hnlich gutes Preis-\/Leistungsverh\u00e4ltnis bietet und gleichzeitig automatisch auf Tausende von Knoten skaliert.Mehr InformationenVereinheitlichte Verwaltung und SpeicherungData Streaming auf Databricks bedeutet, dass Sie von den grundlegenden Komponenten der Lakehouse-Plattform \u2013 Unity Catalog und Delta Lake \u2013 profitieren. Ihre Rohdaten werden mit Delta Lake optimiert, dem einzigen Open-Source-Speicher-Framework, das von Grund auf f\u00fcr Streaming- und Batch-Daten entwickelt wurde.Unity Catalog bietet Ihnen eine detaillierte, integrierte Steuerung all Ihrer Daten- und KI-Assets mit einem konsistenten Modell f\u00fcr die Erkennung, den Zugriff und die gemeinsame Nutzung von Daten in allen Clouds. Unity Catalog bietet auch native Unterst\u00fctzung f\u00fcr Delta Sharing, das branchenweit erste offene Protokoll f\u00fcr den einfachen und sicheren Datenaustausch mit anderen Unternehmen.IntegrationenBieten Sie Ihren Datenteams maximale Flexibilit\u00e4t \u2013 nutzen Sie Partner Connect und ein \u00d6kosystem aus Technologiepartnern, um nahtlos beliebte Datenstreaming-Tools zu integrieren.DatenstreamingKundenberichte\u201eWir verwenden Databricks f\u00fcr Hochgeschwindigkeitsdaten in Bewegung. Es hilft uns wirklich, die Geschwindigkeit zu verbessern, mit der wir auf die Bed\u00fcrfnisse unserer Patienten entweder im Gesch\u00e4ft oder online reagieren k\u00f6nnen. Wir haben gerade ein Dutzend Initiativen und alle diese Initiativen werden aus den Daten in Databricks bereitgestellt.\u201c\u2013 Sashi Venkatesan, Director of Product Engineering, Walgreens\u201eJetzt, da unsere Betrugserkennung in Echtzeit erfolgt, k\u00f6nnen wir Betr\u00fcger erkennen und ihren Bem\u00fchungen bei der Manipulierung des Systems, illegalen Entsperrungen, Robocalls und Robotexten sowie Identit\u00e4tsdiebstahl immer einen Schritt voraus sein.\u201c\u2013 Kate hopkins, Vice president, AT&TMehr entdeckenDelta Live TablesDatabricks WorkflowsUnity CatalogDelta LakeStrukturiertes Spark-Streaming\u00c4hnliche InhalteE-Books und Demos\u201eErrichten eines Data Lakehouse\u201c von Bill Inmon, dem Vater des Data WarehouseDaten, Analysen und KI-GovernanceDatenteam-Leitfaden zur Databricks Lakehouse-PlattformStreaming-Demos von Delta-Live-TablesVeranstaltungenDatentransformation \u2013 mit Delta-Live-Tables kein ProblemProblemlose Datenerfassung Webinar-ReiheDATA+AI SUMMIT 2022Data +AI World Tour 2022BlogsStreamingdaten-Pipelines mit niedriger Latenz mit Delta-Live-Tables und Apache KafkaVereinfachung der Aufnahme von Streamingdaten in Delta LakeEchtzeit-Einblicke: Die drei wichtigsten Gr\u00fcnde, warum Kunden Datenstreaming mit Databricks liebenProjekt Lightspeed: Schnellere und einfachere Stream-Verarbeitung mit Apache SparkEin \u00dcberblick \u00fcber alle neuen strukturierten Streaming-Funktionen, die 2021 f\u00fcr Databricks und Apache Spark entwickelt wurden \u2013 Der Databricks-BlogM\u00f6chten Sie loslegen?Kostenlos testenMitglied der Community werdenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/kr\/product\/machine-learning","text":"Databricks \uba38\uc2e0 \ub7ec\ub2dd | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \u0000\u0000\uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 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\uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc911\uc2ec\uc801 \uba38\uc2e0 \ub7ec\ub2dd\uc73c\ub85c AI \ud504\ub85c\uc81d\ud2b8 \uac00\uc18d\ud654\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \uc608\uc57d\n\ub3cc\ub9ac\uc640 \uac19\uc740 \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378 \uad6c\ucd95\nApril 26, 2023 | 2 PM AEST | 12PM SGT | 9.30AM IST\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30Databricks \uba38\uc2e0 \ub7ec\ub2dd \uc2ec\uce35 \ud0d0\uad6c\uad00\ub9ac\ud615 MLFlow\ubaa8\ub378 \ub808\uc9c0\uc2a4\ud2b8\ub9acML \ub7f0\ud0c0\uc784\ud611\uc5c5 \ub178\ud2b8\ubd81Feature StoreAutoML\uc124\uba85 \uac00\ub2a5\ud55c AI\ub9ac\ud3ec\uc9c0\ud1a0\ub9ac\ubaa8\ub378 \ubaa8\ub2c8\ud130\ub9c1\ubaa8\ub378 \uc81c\uacf5Databricks \uba38\uc2e0 \ub7ec\ub2dd\uc740 \uc624\ud508 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98 \uae30\ubc18\uc73c\ub85c, ML \ud300\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc900\ube44\ud558\uace0 \ucc98\ub9ac\ud558\ub3c4\ub85d\uc9c0\uc6d0\ud558\uace0 \ud300 \uac04 \ud611\uc5c5\uc744 \uac04\uc18c\ud654\ud558\uba70 \uc2e4\ud5d8\ubd80\ud130 \ud504\ub85c\ub355\uc158\uae4c\uc9c0 \uc804\uccb4 ML \uc218\uba85 \uc8fc\uae30\ub97c \ud45c\uc900\ud654\ud569\ub2c8\ub2e4.$600\ub9cc \uc774\uc0c1 \uc808\uac10CONA Services\ub294 \uc644\uc804\ud55c ML \uc218\uba85 \uc8fc\uae30\uc5d0 Databricks\ub97c \ud65c\uc6a9\ud558\uc5ec \uc218\uc2ed\ub9cc \uac1c\uc758 \ub9e4\uc7a5\uc5d0 \ub300\ud574 \uacf5\uae09\ub9dd\uc744 \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4.\uc790\uc138\ud788R$390\ub9cc \uc808\uac10\uba38\uc2e0 \ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uc218\uc694\ub97c \uc815\ud655\ud558\uac8c \uc608\uce21\ud558\uace0, \ucef4\ud4e8\ud305 \ube44\uc6a9\uc744 25% \uc808\uac10\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788$5,000\ub9cc \uc774\uc0c1 \ube44\uc6a9 \uc808\uac10Amgen\uc740 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ud611\uc5c5\uc744 \uac1c\uc120\ud558\uc5ec \uc57d\ubb3c \ubc1c\uacac \uae30\uac04\uc744 \ub2e8\ucd95\ud558\uace0, \uc6b4\uc601 \ube44\uc6a9\uc744 \uc808\uac10\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ub370\uc774\ud130\uc758 \ubaa8\ub4e0 \uce21\uba74\uc744\nML\uc5d0 \ub9de\uac8c \uac04\uc18c\ud654Databricks ML\uc740 \uc624\ud508 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud1a0\ub300\ub97c \uae30\ubc18\uc73c\ub85c(Delta Lake\u200b \uc0ac\uc6a9) \ube4c\ub4dc\ud558\uc5ec, \uba38\uc2e0 \ub7ec\ub2dd \ud300\uc5d0\uc11c \uaddc\ubaa8\uc640 \uad00\uacc4\uc5c6\uc774 \uc5b4\ub5a4 \uc720\ud615\uc758 \ub370\uc774\ud130\ub4e0 \uc561\uc138\uc2a4, \ud0d0\uc0c9\ud558\uace0 \uc900\ube44\ud558\ub3c4\ub85d \uc9c0\uc6d0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc758 \uc9c0\uc6d0\uc5d0 \uc758\uc874\ud558\uc9c0 \uc54a\uace0 \uc140\ud504 \uc11c\ube44\uc2a4 \ubc29\uc2dd\uc73c\ub85c \uc5ec\ub7ec \uac00\uc9c0 \ud2b9\uc9d5\uc744 \ud504\ub85c\ub355\uc158 \ud30c\uc774\ud504\ub77c\uc778\uc73c\ub85c \uc804\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc2e4\ud5d8 \ucd94\uc801\uacfc \uac70\ubc84\ub10c\uc2a4 \uc790\ub3d9\ud654\uad00\ub9ac\ud615 MLflow\ub294 \uc2e4\ud5d8\uacfc \ub85c\uadf8 \ub9e4\uac1c\ubcc0\uc218, \uba54\ud2b8\ub9ad, \ub370\uc774\ud130\uc640 \ucf54\ub4dc \ubc84\uc804 \uad00\ub9ac\ub97c \uc790\ub3d9\uc73c\ub85c \ucd94\uc801\ud558\uba70 \ud2b8\ub808\uc774\ub2dd\uc744 \uc2e4\ud589\ud560 \ub54c\ub9c8\ub2e4 \ubaa8\ub378 \uc544\ud2f0\ud329\ud2b8\ub3c4 \ucd94\uc801\ud569\ub2c8\ub2e4. \uc774\uc804 \uc2e4\ud589\uc744 \uc2e0\uc18d\ud558\uac8c \ud655\uc778\ud558\uace0 \uacb0\uacfc\ub97c \ube44\uad50\ud558\uba70 \ud544\uc694\ud55c \uacbd\uc6b0 \uacfc\uac70 \uacb0\uacfc\ub97c \uc7ac\ud604\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \ud504\ub85c\ub355\uc158\ud560 \ubaa8\ub378\uc758 \uac00\uc7a5 \uc88b\uc740 \ubc84\uc804\uc744 \ud655\uc778\ud588\ub2e4\uba74, \uc774\ub97c \ubaa8\ub378 \ub808\uc9c0\uc2a4\ud2b8\ub9ac\uc5d0 \ub4f1\ub85d\ud558\uba74 \ubc30\ud3ec \uc218\uba85 \uc8fc\uae30\uc5d0 \ub530\ub77c \ud578\ub4dc\uc624\ud504\ub97c \uac04\uc18c\ud654\ud560 \uc218 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Databricks\ub294 \ud504\ub85c\ub355\uc158\uc758 \ubaa8\ub378\uc5d0\uc11c \uc18c\uc2a4 \ub370\uc774\ud130 \uc2dc\uc2a4\ud15c\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0 \uc804\uccb4\uc801\uc778 \uac00\uc2dc\uc131\uacfc \ub9ac\ub2c8\uc9c0\ub97c \uc81c\uacf5\ud558\uae30 \ub54c\ubb38\uc5d0, \ubaa8\ub4e0 ML \uc218\uba85 \uc8fc\uae30\uc5d0\uc11c \ubaa8\ub378\uacfc \ub370\uc774\ud130 \ud488\uc9c8\uc744 \ubd84\uc11d\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \ubc1b\uace0 \ubb38\uc81c\uac00 \uc2ec\uac01\ud574\uc9c0\uae30 \uc804\uc5d0 \ubbf8\ub9ac \ubc1c\uacac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ub9ac\ud3ec\uc9c0\ud1a0\ub9acRepos\ub294 \uc5d4\uc9c0\ub2c8\uc5b4\uac00 Databricks\uc758 Git \uc6cc\ud06c\ud50c\ub85c\ub97c \ub530\ub97c \uc218 \uc788\uc73c\uba70, \ub370\uc774\ud130 \ud300\uc5d0\uc11c\ub3c4 \uc790\ub3d9 CI\/CD \uc6cc\ud06c\ud50c\ub85c\uc640 \ucf54\ub4dc \uc774\uc2dd\uc131\uc744 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\uc774\ud130 \uc0ac\uc77c\ub85c, \ub290\ub9b0 \uc131\ub2a5, Hadoop\uc774\ub098 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub192\uc740 \ube44\uc6a9\uc5d0 \uc9c0\uce58\uc168\ub098\uc694? \ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc704\ud55c \ud604\ub300\uc801 \ud50c\ub7ab\ud3fc, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc138\uc694.Databricks\ub85c \ub9c8\u0000\uc774\uadf8\ub808\uc774\uc158\ub9ac\uc18c\uc2a4\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\u0000\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2dd \uc8fc\uc81c\uc5d0 \ub300\ud55c ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ucc3e\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBookMLOps Big Book\uc0c8\ub85c\uc6b4 Delta Sharing \uc194\ub8e8\uc158 \uc54c\uc544\ubcf4\uae30\ub9c8\uc774\uadf8\ub808\uc774\uc158 \uac00\uc774\ub4dc: \ud558\ub461\uc5d0\uc11c Databricks\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ub370\ubaa8 \ubc0f \ube14\ub85c\uadf8Databricks \u0000\u0000\uba38\uc2e0 \ub7ec\ub2dd \uc194\ub8e8\uc158 \uc2ec\uce35 \ud0d0\uad6c\ud558\ub461\uc5d0\uc11c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uae30 \uc704\ud55c 5\uac00\uc9c0 \ub2e8\uacc4\uac00\uc0c1 \uc774\ubca4\ud2b8AutoML: \ubaa8\ub450\ub97c \uc704\ud55c \ube60\ub974\uace0 \uac04\ub2e8\ud55c \uba38\uc2e0 \ub7ec\ub2ddMLOps \uac00\uc0c1 \uc774\ubca4\ud2b8: \ub300\uaddc\ubaa8 MLOps \ud45c\uc900\ud654Databricks \uba38\uc2e0 \ub7ec\ub2dd\uc73c\ub85c ML \uc218\uba85 \uc8fc\uae30 \uc790\ub3d9\ud654MLOps \uac00\uc0c1 \uc774\ubca4\u0000\u0000\ud2b8 \"\ub300\uaddc\ubaa8 \uba38\uc2e0 \ub7ec\ub2dd \uc6b4\uc6a9\"\uba38\uc2e0 \ub7ec\ub2dd \ud50c\ub7ab\ud3fc \uad6c\ucd95Delta Lake: \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ucd08\ud558\ub461 \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ub2e8\uacc4\ubcc4 \uac00\uc774\ub4dc\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dan-houston\/#","text":"Dan Houston - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDan HoustonManager, Data Science and Exploration Advanced Analytics at USPSBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/08\/26\/announcing-general-availability-of-delta-sharing-on-aws-and-azure.html","text":"Announcing General Availability of Delta Sharing - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing General Availability of Delta Sharingby Matei Zaharia, Celia Kung, Xiaotong Sun, Steve Mahoney, Itai Weiss, Sachin Thakur and Jay BhankhariaAugust 26, 2022 in AnnouncementsShare this postToday we are excited to announce that Delta Sharing is generally available (GA) on AWS and Azure. With the GA release, you can expect the highest level of stability, support, and enterprise readiness from Databricks for mission-critical workloads on the Databricks Lakehouse Platform.In this blog, we explore how organizations leverage Delta Sharing to maximize the business value of their data, some of the key features available in the GA release, and how to get started with Delta Sharing on the Databricks Lakehouse Platform.Customers win with the open standard for data sharing from the lakehouseData sharing has become important in the digital economy as enterprises look to easily and securely exchange data with their customers, partners, suppliers, and internal lines of business (LOBs) to better collaborate and unlock value from that data. But the lack of a standards-based data sharing protocol has resulted in solutions tied to a single vendor or commercial product, introducing vendor lock-in risks. These customer challenges led us, at Databricks, to build an open data sharing solution, Delta Sharing.Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform. Data recipients don't have to be on the Databricks Lakehouse Platform or on the same cloud or on any cloud at all. Data providers can share existing large-scale data sets based on the Apache Parquet or Delta Lake formats, without replicating or copying data sets to another system. Data recipients benefit from always having access to the latest version of data with the ability to query, visualize, transform, ingest or enrich shared data with their tools of choice, reducing time-to-value. As governance and security are top concerns for many organizations, Delta Sharing is natively integrated with Unity Catalog, allowing you to manage, govern, audit, and track usage of the shared data on one platform.Delta Sharing \u2013 An open standard for secure sharing of data assetsSince launching Delta Sharing in the private preview last year, hundreds of customers have embraced Delta Sharing, and today, petabytes of data is being shared through Delta Sharing.Nasdaq: \"Delta Sharing helped us streamline our data delivery process for large data sets. This enables our clients to bring their own compute environment to read fresh curated data with little-to-no integration work, and enables us to continue expanding our catalog of unique, high-quality data products\" - William Dague, Head of Alternative DataShell: \"We recognise that openness of data will play a key role in achieving Shell's Carbon Net Zero ambitions. Delta sharing provides Shell with a standard, controlled, and secure protocol for sharing vast amounts of data easily with our partners to work towards these goals without requiring our partners be on the same data sharing platform\" - Bryce Bartmann, Chief Digital Technology AdvisorSafeGraph: \"As a data company, giving our customers access to our data sets is critical. The Databricks Lakehouse Platform with Delta Sharing really streamlines that process, allowing us to securely reach a much broader user base regardless of cloud or platform\" - Felix Cheung, VP of EngineeringYipitData: \"With Delta Sharing, our clients can access curated data sets nearly instantly and integrate them with analytics tools of their choice. The dialogue with our clients shifts from a low-value, technical back-and-forth on ingestion to a high-value analytical discussion where we drive successful client experiences. As our client relationships evolve, we can seamlessly deliver new data sets and refresh existing ones through Delta Sharing to keep clients appraised of key trends in their industries.\" - Anup Segu, Data Engineering Tech LeadPumpjack Dataworks: \"Leveraging the powerful capabilities of Delta Sharing from Databricks enables Pumpjack Dataworks to have a faster onboarding experience, removing the need for exporting, importing and remodeling of data, which brings immediate value to our clients. Faster results yield greater commercial opportunity for our clients and their partners\" - Corey Zwart, Chief Technology OfficerWhat's new in Delta Sharing with GA?While Delta Sharing has a slate of amazing features in the GA release, provided below are some of the key features we are shipping with this release:Seamless Databricks to Databricks SharingFor Databrick customers, Delta Sharing makes data sharing on the lakehouse extremely simple, efficient and secure. With just a few UI clicks or SQL commands, data providers can easily share their existing data with recipients on Databricks, without replicating the data. For example, a data provider using Databricks on AWS can share existing data with a recipient using Databricks on Azure or vice-versa. You can explore the user guide for full details. In Databricks to Databricks sharing, the data provider does not need to manage token credentials for recipients who are using Databricks; the sharing connection is established securely through the Databricks platform. All you need is a Databricks account to login and the rest is taken care of by the platform. In addition to cross-account data sharing, another important use case is internal data sharing. If you have multiple Unity Catalog metastores under the same account in different regions, you can easily share data among those metastores by using Delta Sharing without copying any data. SQL workflow example from a data provider's perspective:\n-- create a share and add a table to it\nCREATE SHARE first_share;\nALTER SHARE first_share ADD TABLE my_table AS default.first_table;\n\n-- create a Databricks recipient using their sharing identifier and grant them access to the share\nCREATE RECIPIENT acme USING ID 'aws:us-west-2:3f9b6bf4-...-29bb621ec110';\nGRANT SELECT ON SHARE first_share TO RECIPIENT acme;\nSQL workflow example from a data recipient's perspective:\n-- list the providers who shared data with me\nSHOW PROVIDERS;\n\n-- view the data shared by provider acme_provider\nSHOW SHARES IN PROVIDER acme_provider;\n\n-- create a catalog from the share\nCREATE CATALOG my_catalog USING SHARE `acme_provider`.`first_share`;\n\n-- query the shared data\nSELECT * FROM my_catalog.default.first_table;\nSharing Change Data FeedDelta Sharing now supports sharing Change Data Feed (CDF). In addition to sharing a table, a data provider can choose to include the table's CDF, allowing recipients to query changes between specific versions or timestamps of the table. With this feature, recipients can query just the new data or the incremental changes instead of the entire table each time. A data provider can easily share a table with CDF, and a data recipient can query table changes with a simple syntax:\n-- data provider: sharing a table with CDF enabled\nALTER SHARE my_share ADD my_table AS default.cdf_table WITH CHANGE DATA FEED\n\n-- data recipient: query table changes from versions 5 to 10\nSELECT * FROM table_changes('`default`.`cdf_table`', 5, 10)\nEnhanced security featuresIn the GA release of Delta Sharing, we have also a set of security features to make sharing even more secure. One example of those security features is IP Access List. Data providers can now configure an IP access list for each of their recipients using open connectors. It ensures that credential download and data access can only be initiated from the target IP address. We also added a few more Delta Sharing related permissions (e.g. CREATE SHARE, CREATE RECIPIENT) and introduced owner concept for Delta Sharing objects like Share and Recipient. With those primitives, Delta Sharing on Databricks offers a more flexible access control model, and non-admin users can also perform sharing operations.Getting Started with Delta Sharing on DatabricksWatch the demo below to learn more about how Delta Sharing can help you seamlessly share live data from your lakehouse to any computing platform.To play this video, click here and accept cookies If you already are a Databricks customer, follow the guide to get started (AWS | Azure). Read the release notes to learn more about what's included in this GA release. If you are not an existing Databricks customer, sign up for a free trial with a Premium or Enterprise workspace.Try Databricks for freeGet StartedRelated postsIntroducing Delta Sharing: An Open Protocol for Secure Data SharingMay 26, 2021 by Matei Zaharia, Michael Armbrust, Steve Weis, Todd Greenstein and Cyrielle Simeone in Announcements\nUpdate: Delta Sharing is now generally available on AWS and Azure. Get an early preview of O'Reilly's new ebook for the step-by-step guidance...\nTop Three Data Sharing Use Cases With Delta SharingJanuary 14, 2022 by Jay Bhankharia, Itai Weiss, Matei Zaharia and Sachin Thakur in Platform Blog\nUpdate: Delta Sharing is now generally available on AWS and Azure. Data sharing has become an essential component to drive business value as...\nSecurity Best Practices for Delta SharingAugust 1, 2022 by Andrew Weaver, Itai Weiss, Milos Colic and Som Natarajan in Product\nUpdate: Delta Sharing is now generally available on AWS and Azure. 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{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/technology","text":"Databricks-Technologiepartner \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks-TechnologiepartnerVernetzen Sie sich mit Databricks-Technologiepartnern, um Datenerfassung, Business Intelligence und Governance-Funktionen in die Databricks Lakehouse-Plattform zu integrieren.\u201eMit Databricks und Fivetran k\u00f6nnen wir Marketingerkenntnisse in Zukunft deutlich verbessern. Aus technischer Sicht interagieren die beiden Tools harmonisch miteinander, und die Integration f\u00fchlt sich sehr nativ an.\u201c\u2013 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP bei Paul HewittDatabricks-Technologiepartner integrieren ihre L\u00f6sungen mit Databricks, um erg\u00e4nzende Funktionen f\u00fcr ETL, Datenerfassung, Business Intelligence, Machine Learning und Governance zur Verf\u00fcgung zu stellen.Diese Integrationen erm\u00f6glichen es Kunden, die Zuverl\u00e4ssigkeit und Skalierbarkeit der Databricks Lakehouse-Plattform zu nutzen, um Innovation schneller umzusetzen und gleichzeitig wertvolle Erkenntnisse aus Daten zu gewinnen.Partner ConnectB\u00fcndeln Sie alle Ihre Daten-, Analyse- und KI-Tools auf einer offenen Plattform. Mit Partner Connect bietet Databricks eine schnelle und einfache M\u00f6glichkeit, Ihre vorhandenen Tools mithilfe validierter Integrationen mit Ihrem Lakehouse zu vernetzen und neue L\u00f6sungen zu entdecken und auszuprobieren.Partner werdenMehr InformationenLoading...ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pedro-boareto\/#","text":"Pedro Boareto - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPedro BoaretoChapter Leader of Analytics Engineering at BradescoBack to speakersExpert in Big Data and Analytics, currently leading Analytics Engineering in Bradesco's Open Banking Project and phD student. He has a background in industrial engineering, with a master's in industrial and system engineering focused on healthcare process improvements. Has extensive experience in automation, data warehousing, cost optimization, and architecture solutions. He's also a voluntary data analyst at a public hospital. In his free time, he enjoys movies, exercise, and cooking.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/solutions\/industries\/media-and-entertainment","text":"Databricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3088\u308b\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u696d\u754c\u5411\u3051\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jegadeesan-pugazhenthi","text":"Jegadeesan Pugazhenthi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJegadeesan PugazhenthiLead Big Data Engineer at AT&TBack to speakersWorking as Lead Big Data Engineer at AT&T. Have been at the forefront of adoption of new technologies at AT&T including successful adoption of Big Data platform as part of AT&T Big Data COE. Currently leading the effort on adoption of cloud technologies and migration of on-prem applications to cloud platforms like Databricks. Instrumental in migrating petabytes of data to the cloud. Leading continuous cloud optimization efforts resulting in significant cloud cost savings.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joe-walsh","text":"Joe Walsh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoe WalshDirector of Measurement & Attribution at EffectvBack to speakersJoe is the Director of Measurement & Attribution at Effectv, a Comcast Company, where his main focus is creating innovative, 1st party solutions to help advertisers measure the performance of their media against outcomes that matter most to their business. Prior to joining Effectv, Joe was Head of TV Analytics at LiveRamp where he leveraged the Data + Math measurement platform to empower brands and agencies with industry-leading cross-screen insights. Prior to LiveRamp, Joe was Head of Analytics at dataxu (acquired by Roku), where he helped transform the business from a traditional DSP to an industry-leading advanced TV platform. Joe is a die-hard Boston sports fan, and holds a Bachelors degree in Economics and a Masters in Econometrics, both from the University of Massachusetts, Amherst.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bradley-axen","text":"Bradley Axen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBradley AxenMachine Learning Engineer at BlockBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/blog","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/industries\/financial-services","text":"\uae08\uc735 \uc11c\ube44\uc2a4\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\u0000\u0000\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \uc608\uc57d\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/manufacturing-industry-solutions","text":"Manufacturing Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDiscover Lakehouse for ManufacturingLower costs, boost productivity and unify your data ecosystem on the only data platform built for the way manufacturers use dataSign upContact usLower TCO. Better performance. Greater scalability.Lakehouse for ManufacturingWhen you can unify all your data, analytics and AI workloads \u2014 with sharing and governance built in \u2014 internal and external teams get access to the data they need, when they need it.Impact across the entire value chainCustomer EngagementPrecise outcomes and frictionless experiences for customersWith a 360-degree view of customers, operations and assets, you can deliver the highest uptime, quality of service and economic value across the product lifecycle, powering personalized customer outcomes, proactive field service delivery and differentiated mission-critical solutions.Operational EfficiencyEmployee ProductivityProduct InnovationManufacturing Solutions and PartnersNo-compromise data analytics and AI solutions purpose-built for manufacturersDatabricks Solution Accelerators are purpose-built guides \u2014 fully functional notebooks and best practices \u2014 that speed up manufacturing results. Save time on discovery, design, development and testing in use cases like digital twins, overall equipment effectiveness, forecasting and more.Overall Equipment Effectiveness and KPI MonitoringAchieve performant and scalable end-to-end equipment monitoring\nIncrementally ingest and process data from sensor\/IoT devices in a variety of formats, and compute and surface KPIs and metrics to drive valuable insights.Get startedPart-Level ForecastingForecast demand at the part level for streamlined manufacturing\nPerform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales.Get startedDigital TwinsIncrease operational efficiency and improve decision-making\nProcess real-world data in real time, compute insights at scale and deliver to multiple downstream applications, and optimize plant operations with data-driven decisions.Get startedExplore manufacturing acceleratorsWe\u2019ve partnered with leading consulting firms to deliver innovative, industry-specific solutions. Databricks Brickbuilder Solutions help you cut costs and increase value from your data. Backed by decades of industry expertise \u2014 and built for the Databricks Lakehouse Platform \u2014 Brickbuilder Solutions are tailored to your exact needs.Intelligent Manufacturing Harness your data, drive interoperability and provide enhanced insights at scale using analytics and AI.Learn moreQuality InspectorAutomate your quality control with computer vision to detect defects, foreign objects, anomalies or incorrect setup.Learn morePredictive Supply Risk ManagementDrive nth-tier visibility into order flows and supplier performance to boost efficiency, manage exceptions and improve resiliency.Learn moreSee all partner solutions\u201cDatabricks Lakehouse empowers us to lower the barrier of entry for data access across our organization so we can build the most innovative and reliable electric vehicles in the world.\u201d\n\u2013 Wassym Bensaid, Vice President of Software Development, Rivian\n\u201cThe usage of Databricks over the years has broadened significantly. We started out using Databricks as a big data and AI platform, but the scope has broadened. We have an entirely different class of citizen engineers and data scientists who are using it as a modern business intelligence tool to make smarter business decisions.\u201d\n\u2014 Daniel Jeavons, General Manager, Advanced Analytics CoE, Shell\n\u201cThe Databricks platform has helped us minimize risks to engine availability, reduce lead times for spare parts and drive more efficiency in stock turns \u2014 all of this enables us to deliver TotalCare, the aviation industry\u2019s leading Power-by-the-Hour (PBH) maintenance program.\u201d\n\u2014 Stuart Hughes, Chief Information and Digital Officer, Rolls-Royce Civil Aerospace\nResourceseBookPut Your ERP Data to WorkWebinarsImproving Predictive Maintenance for Manufacturers With Data + AIeBookExplore the Lakehouse for ManufacturingReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/att","text":"Customer Story: AT&T | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYProtecting 182 million wireless customers from harm80%Decrease in fraud attacksMillionsOf dollars saved in potential fraud costsWatch video INDUSTRY: Communication service providers SOLUTION: Threat detection,customer retention,subscriber churn prediction PLATFORM USE CASE: Lakehouse,Delta Lake,machine learning CLOUD: Azure\u201cDatabricks Lakehouse has provided a unified platform that brings together data and AI to deliver predictive solutions that help to protect our customers and our business by stopping fraud before it happens.\u201d\n\u2014 Kate Hopkins, Vice President, AT&TAT&T is dedicated to providing its 182 million wireless customers with secure, reliable and frictionless communications. With 10 million transactions occurring every second, staying ahead of fraudsters \u2014 from robocalls and texts to gaming and identity theft \u2014 requires harnessing the power of data and AI to stop attacks before they happen. But AT&T\u2019s legacy on-premises architecture created infrastructure complexity and failed to deliver the innovation needed for an optimal customer experience. By modernizing their data infrastructure in the cloud with Databricks Lakehouse, AT&T was able to implement a unified approach to data and AI. They now have over 100 ML models in production that better protect customers and their business, using real-time data, automatic alerts and recommendations to arm employees across AT&T\u2019s operations. With a unified Lakehouse for data and AI, AT&T has already significantly reduced fraud, and has a robust roadmap to deliver more data-driven solutions that will help to democratize AI across the business.Outgrowing a legacy on-premises data architectureAT&T had been operating their on-prem environment for years. While they were utilizing data analytics for different use cases, it became clear that they\u2019d outgrown their legacy infrastructure as the types and amount of data expanded. Critical interventions in fraud detection and security required the participation of dozens of teams across different systems to first acquire fraud insight data, and then feed that data to retail, call center, and online systems for alerting and notification. The process was protracted, inefficient, resource-heavy and expensive. More importantly, it was reactive instead of proactive. The rule-based technology used to detect fraud made it difficult to stay ahead of bad actors, especially with the growing number of sophisticated fraud attempts plaguing both customers and their own business.Similar to fraud detection, AT&T also struggled to gain the real-time insights and automation necessary to optimize dispatch. On their legacy system, AT&T could not unify data points to match a technician\u2019s troubleshooting skills to the customer issue and location. Each unsuccessful attempt to solve an issue increased operational costs while impacting customer experience.Kate Hopkins, Vice President of AT&T, says, \u201cWe wanted to take care of these things automatically. How can we stop robocalling and robotexting? How can we match a tech with the right skills to solve a problem, while also taking into account traffic and weather to predict when they\u2019ll arrive at the house? We couldn\u2019t answer these questions on-prem. It was clear that we had largely tapped the technology that was available to us.\u201dAT&T Uses Databricks Lakehouse to Stop Fraud Before It HappensAT&T is using data and AI to deliver predictive solutions that protect its customers from fraud. Moving from an on-premises architecture to a cloud-based lakehouse allows AT&T to take in all kinds of data, standardize it and then run ML models that drive fraud alerts in real time.Proactively stopping fraud with Databricks LakehouseAT&T chose to migrate to the Databricks Lakehouse Platform because of the open nature of the software and their alignment with the Databricks roadmap. Kate explains, \u201cEvery company is moving workloads to the cloud to some extent, but we picked a bolder path. With tools like Databricks and Delta Lake we can get the benefits of the cloud faster. While the other carriers may be doing more lift and shift, we don\u2019t think that\u2019s a recipe for transformation. We\u2019re going to the next level.\u201dTo do so, AT&T first launched Databricks with their data science team. They pumped their on-premises data into Delta Lake, moved their workloads to the cloud, and created a Center of Excellence (CoE) with training and community support to expand adoption and data democratization going forward. Focusing on fraud detection as their first use case, the data science team was able to develop predictive solutions with unified data and AI, and seamless collaboration that stops fraud before it happens. Kate says, \u201cWe\u2019re able to ingest huge amounts of structured and unstructured data coming from different systems, standardize it, and then build ML models that deliver alerts and recommendations that empower employees in our call centers, stores, and online.\u201d Building on the positive experience of the data science team, Databricks is being introduced to the data science organizations in AT&T\u2019s business units.Reducing the impact of fraud before it happensSince moving away from their rules-based fraud system and creating ML models for real-time, automatic fraud detection, AT&T has reduced fraud by up to 80% with over 100 fraud detection ML models in production. \u201cNow that our fraud detection is real time, we can outwit fraudsters and stay ahead of their efforts in areas like fraudsters gaming the system, illegal unlocks, robocalls and robotexts, and identify theft,\u201d says Hopkins.Fraud detection is just one example of how AT&T can make an impact with scalable, democratized data access and AI on the Databricks Lakehouse Platform. Moving forward, AT&T will continue to increase adoption for use cases benefiting dispatch, service reliability, quality of coverage, and sales growth. Their goal is to be completely off the AT&T on-prem data lake by 2023.Looking forward, Hopkins says, \u201cWe still get a lot of business benefits from data analytics, but it doesn\u2019t compare to the scale of benefits we can engender when we apply AI. We\u2019re looking to continue that trend and accelerate it. We know that there\u2019s a lot of potential and now we can realize it.\u201dRelated ContentBlogUnlocking the Power of Data: AT&T\u2019s Modernization Journey to the LakehouseReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/product\/unity-catalog","text":"Unity Catalog | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWUnity Catalog\ub370\uc774\ud130 \ubd84\uc11d \ubc0f AI\ub97c \uc704\ud55c \ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4\n\u00a0\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowUnity Catalog\ub294 \uc5b4\ub290 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c\ub098 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \uc800\uc7a5\ub41c \ud30c\uc77c, \ud14c\uc774\ube14, \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378, \ub300\uc2dc\ubcf4\ub4dc \ub4f1\uc758 \ubaa8\ub4e0 \ub370\uc774\ud130 \ubc0f AI \uc790\uc0b0\uc744 \uad00\ub9ac\ud558\ub294 \ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4 \uc194\ub8e8\uc158\uc785\ub2c8\ub2e4.\ub370\uc774\ud130 \ubc0f AI\ub97c \uc704\ud55c \uc911\uc559 \uc9d1\uc911\ud615 \uac70\ubc84\ub10c\uc2a4ANSI SQL\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \uacf5\ud1b5\uc801\uc778 \uac70\ubc84\ub10c\uc2a4 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ud30c\uc77c, \ud14c\uc774\ube14, \ub300\uc2dc\ubcf4\ub4dc, ML \ubaa8\ub378\uc744 \ud55c \uacf3\uc5d0\uc11c \uad00\ub9ac\ud569\ub2c8\ub2e4.\uae30\ubcf8 \ub0b4\uc7a5\ub41c \ub370\uc774\ud130 \uac80\uc0c9 \ubc0f \ud0d0\uc0c9 \uae30\ub2a5\ubaa8\ub4e0 \ub370\uc774\ud130 \uc790\uc0b0\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ube60\ub974\uac8c \ucc3e\uc544\uc11c \ubd84\uc11d\ud558\uace0 \ucc38\uc870\ud568\uc73c\ub85c\uc368 \uc0dd\uc0b0\uc131\uc744 \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc131\ub2a5 \ubc0f \ud655\uc7a5\ub0ae\uc740 \uc9c0\uc5f0\uc73c\ub85c \uba54\ud0c0\ub370\uc774\ud130\ub97c \uc81c\uacf5\ud558\uace0 \ud14c\uc774\ube14\uc744 \uc790\ub3d9 \ud29c\ub2dd\ud558\ub294 \ud5a5\uc0c1\ub41c \ucffc\ub9ac \uc131\ub2a5\uc744 \u0000\uc81c\uacf5\ud569\ub2c8\ub2e4.\ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \ub300\ud55c \uc790\ub3d9 \ub9ac\ub2c8\uc9c0SQL, R, Python, Scala \ud615\uc2dd\uc758 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\uc640 \uc790\uc0b0 \uc720\ud615(\uc608: \ud14c\uc774\ube14, \ub178\ud2b8\ubd81, \uc6cc\ud06c\ud50c\ub85c, \ub300\uc2dc\ubcf4\ub4dc)\uc5d0 \ub300\ud55c \uc138\ubd84\ud654\ub41c \uc790\ub3d9 \ub9ac\ub2c8\uc9c0\ub97c \ud1b5\ud574 \ub370\uc774\ud130 \uc5d0\ucf54\uc2dc\uc2a4\ud15c \uc804\uccb4\ub97c \uc544\uc6b0\ub974\ub294 \ud1b5\ud569\uc801\uc778 \ud22c\uba85 \ubdf0\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.\uae30\uc874 \ub3c4\uad6c\uc640 \ud1b5\ud569\uae30\uc874 \ub370\uc774\ud130 \uce74\ud0c8\ub85c\uadf8\uc640 \uac70\ubc84\ub10c\uc2a4 \uc194\ub8e8\uc158\uc744 \ud65c\uc6a9\ud560 \uc218 \uc788\ub294 \uc720\uc5f0\uc131\uc73c\ub85c \ubbf8\ub798\uc5d0 \ub300\ube44\ud55c \ub370\uc774\ud130 \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub97c \uc900\ube44\ud558\uc138\uc694.\uc791\ub3d9 \ubc29\uc2dd\ubaa8\ub4e0 \ub370\uc774\ud130 \uc790\uc0b0\uc744 \ud55c \uacf3\uc5d0\uc11c \uad00\ub9ac \ubc0f \ud1b5\uc81c\uac1c\ubc29\uc801 \ud45c\uc900 ANSI SQL\uc5d0 \uae30\ubc18\ud55c \uacf5\ud1b5\uc801\uc778 \uac70\ubc84\ub10c\uc2a4 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ud30c\uc77c, \ud14c\uc774\ube14, \ub300\uc2dc\ubcf4\ub4dc, ML \ubaa8\ub378\uc758 \uac70\ubc84\ub10c\uc2a4\ub97c \ub2e8\uc21c\ud654\ud574 \ubcf4\uc138\uc694. \uacc4\uc815 \uc218\uc900\uc5d0\uc11c \uc561\uc138\uc2a4 \uc815\ucc45\uc744 \ud55c \ubc88\uc5d0 \uc815\uc758\ud558\uace0 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\uc640 \uc6cc\ud06c\uc2a4\ud398\uc774\uc2a4\uc5d0 \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c, Unity Catalog\ub294 \ub370\uc774\ud130\uc5d0 \ub300\ud574 \uc218\ud589\ud55c \uc791\uc5c5\uc758 \uac10\uc0ac \ub85c\uadf8\ub97c \ucea1\ucc98\ud558\uc5ec \uc138\ubd84\ud654\ub41c \uac10\uc0ac\ub97c \ud55c \uacf3\uc5d0\uc11c \uc81c\uacf5\ud558\uba70, \uace0\uac1d\uc774 \uaddc\uc815\uc744 \uc900\uc218\ud558\uace0 \uc694\uad6c \uc0ac\ud56d\uc744 \uac10\uc0ac\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\u00a0\uc138\ubd84\ud654\ub41c \uc561\uc138\uc2a4 \uc81c\uc5b4 \uae30\ub2a5 \uad00\ub9ac\ud45c\uc900 SQL \ud568\uc218\ub85c \ud589 \ud544\ud130\uc640 \uc5f4 \ub9c8\uc2a4\ud06c\ub97c \uc815\uc758\ud568\uc73c\ub85c\uc368, \ud589\uacfc \uc5f4\uc5d0 \ub300\ud55c \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \uc138\ubd84\ud654\ud558\uc5ec \uc81c\uc5b4\ud569\ub2c8\ub2e4. Databricks\ub294 \ud655\uc7a5\uc131\uacfc \ud1b5\ud569\uc744 \uac1c\uc120\ud558\uae30 \uc704\ud55c \uae30\ub2a5\uc744 \uafb8\uc900\ud788 \uac1c\ubc1c\ud558\uace0 \uc788\uc73c\uba70, \uace7 \ucd9c\uc2dc\ub420 \uc18d\uc131 \uae30\ubc18 \uc561\uc138\uc2a4 \uc81c\uc5b4 \uae30\ub2a5\uc744 \ud1b5\ud574 \uc0ac\uc6a9\uc790 \uc9c0\uc815 \ud0dc\uadf8(\uc18d\uc131)\uc5d0 \ub530\ub77c \uc561\uc138\uc2a4 \uc815\ucc45\uc744 \uc815\uc758\ud560 \uc218 \uc788\uac8c \ub420 \uac83\uc785\ub2c8\ub2e4.\uc548\uc804\ud55c \ud1b5\ud569 \ub370\uc774\ud130 \uac80\uc0c9 \uacbd\ud5d8\ub370\uc774\ud130 \uc560\ub110\ub9ac\uc2a4\ud2b8, \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\ub97c \uc704\ud55c \ud1b5\ud569 \ub370\uc774\ud130 \uac80\uc0c9 \uacbd\ud5d8\uc73c\ub85c \ubaa8\ub4e0 \ub370\uc774\ud130 \uc790\uc0b0\uc5d0\uc11c \uad00\ub828 \ub370\uc774\ud130\ub97c \ube60\ub974\uac8c \ucc3e\uc544\uc11c \ubd84\uc11d\ud558\uace0 \ucc38\uc870\ud558\uc138\uc694. Unity Catalog\uc758 \ub370\uc774\ud130 \uac80\uc0c9\uc740 \uae30\ubcf8\uc801\uc73c\ub85c \ubcf4\uc548\uc774 \uc801\uc6a9\ub429\ub2c8\ub2e4. \uc0ac\uc6a9\uc790\uc758 \uc561\uc138\uc2a4 \uad8c\ud55c\uc5d0 \ub530\ub77c \uac80\uc0c9 \uacb0\uacfc\uac00 \uc81c\ud55c\ub418\uace0 \uac1c\uc778\uc815\ubcf4 \ubcf4\ud638\ub97c \uace0\ub824\ud558\uc5ec \ubcf4\uc548 \uacc4\uce35\uc744 \ucd94\uac00\ud569\ub2c8\ub2e4.\ubaa8\ub4e0 \uaddc\ubaa8\uc5d0\uc11c \ucffc\ub9ac \uc131\ub2a5 \ud5a5\uc0c1Unity Catalog\ub294 \ub0ae\uc740 \uc9c0\uc5f0\uc73c\ub85c \uba54\ud0c0\ub370\uc774\ud130\ub97c \uc81c\uacf5\ud558\uace0 \ud14c\uc774\ube14\uc744 \uc790\ub3d9 \ud29c\ub2dd\ud558\ub294 \ud5a5\uc0c1\ub41c \ucffc\ub9ac \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\uae30 \ub54c\ubb38\uc5d0 \ubaa8\ub4e0 \uaddc\ubaa8\uc5d0\uc11c \ub354\uc6b1 \ube60\ub974\uac8c \ucffc\ub9ac\uac00 \uc2e4\ud589\ub429\ub2c8\ub2e4. \ube44\ub3d9\uae30\uc2dd \uc790\ub3d9 \ub370\uc774\ud130 \uce58\ubc00\ud654\ub85c \ud30c\uc77c \uc6a9\ub7c9\uc744 \ucd5c\uc801\ud654\ud558\uace0, \ubc31\uadf8\ub77c\uc6b4\ub4dc\uc5d0\uc11c \uc785\ucd9c\ub825(I\/O) \uc9c0\uc5f0\uc744 \uc790\ub3d9\uc73c\ub85c \ub2e8\ucd95\ud569\ub2c8\ub2e4.\uc2e4\uc2dc\uac04 \uc790\ub3d9 \ub370\uc774\ud130 \ub9ac\ub2c8\uc9c0SQL, Python, Scala \ubc0f R \ud615\uc2dd\uc758 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\uc5d0\uc11c \uc2e4\uc2dc\uac04 \uc790\ub3d9 \ub370\uc774\ud130 \ub9ac\ub2c8\uc9c0\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c\uc758 \ub370\uc774\ud130 \ud750\ub984\uc744 \uc644\uc804\ud558\uac8c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \ud488\uc9c8 \uac80\uc0ac\ub97c \uc2e0\uc18d\ud558\uac8c \uc2e4\ud589\ud558\uace0, \ub370\uc774\ud130 \ubcc0\uacbd \uc0ac\ud56d\uc758 \uc601\ud5a5\uc744 \ubd84\uc11d\ud558\uba70, \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc5d0 \uc788\ub294 \ubaa8\ub4e0 \uc624\ub958\ub97c \ub514\ubc84\uae45\ud574\ubcf4\uc138\uc694. \ud14c\uc774\ube14, \uc5f4, \ub178\ud2b8\ubd81, \uc6cc\ud06c\ud50c\ub85c, \ub300\uc2dc\ubcf4\ub4dc\uc5d0\uc11c \ubaa8\ub450 \ub9ac\ub2c8\uc9c0\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Unity Catalog\uc758 \ub9ac\ub2c8\uc9c0 \uadf8\ub798\ud504\ub294 \uad8c\ud55c\uc744 \uc778\uc2dd\ud558\uc5ec, \uc0ac\uc6a9\uc790\uc758 \uc561\uc138\uc2a4 \uad8c\ud55c\uc5d0 \ub530\ub77c \ub9ac\ub2c8\uc9c0 \uadf8\ub798\ud504\uc758 \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \uc81c\ud55c\ud569\ub2c8\ub2e4. \ub610\ud55c, REST API\ub97c \ud1b5\ud574 \ub9ac\ub2c8\uc9c0\ub97c \uac00\uc838\uc640\uc11c \ub2e4\ub978 \uce74\ud0c8\ub85c\uadf8\uc640\uc758 \ud1b5\ud569\uc744 \uc9c0\uc6d0\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\uc548\uc804\ud55c \uc870\uc9c1 \uac04 \ub370\uc774\ud130 \uacf5\uc720Unity Catalog\ub294 \uc548\uc804\ud55c \ub370\uc774\ud130 \uacf5\uc720\ub97c \uc704\ud55c \uc138\uacc4 \ucd5c\ucd08\uc758 \uac1c\ubc29\uc801 \ud504\ub85c\ud1a0\ucf5c\uc778 Delta Sharing\uc744 \uae30\ubcf8\uc73c\ub85c \uc9c0\uc6d0\ud568\uc73c\ub85c\uc368, Delta Lake\uc640 Apache Parquet \ud615\uc2dd\uc758 \uae30\uc874 \ub370\uc774\ud130\ub97c \ubaa8\ub4e0 \ucef4\ud4e8\ud305 \ud50c\ub7ab\ud3fc\uc73c\ub85c \uac04\ud3b8\ud558\uac8c \uacf5\uc720\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4. \uace0\uac1d\uc774 Databricks \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\uac70\ub098, \ub3d9\uc77c\ud55c \ud074\ub77c\uc6b0\ub4dc\ub97c \uc0ac\uc6a9\ud560 \ud544\uc694\uac00 \uc5c6\uace0 \uc2ec\uc9c0\uc5b4 \ud074\ub77c\uc6b0\ub4dc\ub97c \uc774\uc6a9\ud558\uc9c0 \uc54a\uc544\ub3c4 \ub429\ub2c8\ub2e4. \ub77c\uc774\ube0c \ub370\uc774\ud130\ub97c \ubcf5\uc81c\ud558\uac70\ub098 \ub2e4\ub978 \uc2dc\uc2a4\ud15c\uc73c\ub85c \ubcf5\uc0ac\ud558\uc9c0 \uc54a\uace0\ub3c4 \uacf5\uc720\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4. Power BI, Tableau, Spark, pandas \ubc0f Java\uc640 \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569\ub418\uae30 \ub54c\ubb38\uc5d0 \ub370\uc774\ud130\ub97c \ubc1b\ub294 \ucabd\uc5d0\uc11c \uc6d0\ud558\ub294 \ub3c4\uad6c\ub85c \ubc14\ub85c \uacf5\uc720\ub41c \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e8\uc77c \ud50c\ub7ab\ud3fc \ud55c \uacf3\uc5d0\uc11c \uacf5\uc720\ub41c \ub370\uc774\ud130\ub97c \uad00\ub9ac, \ud1b5\uc81c, \uac10\uc0ac \ubc0f \ucd94\uc801\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\uae30\uc874 \ub3c4\uad6c\uc640\uc758 \uc6d0\ud65c\ud55c \ud1b5\ud569Unity Catalog\ub294 \uae30\uc874 \ub370\uc774\ud130 \uce74\ud0c8\ub85c\uadf8, \ub370\uc774\ud130 \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c, \uac70\ubc84\ub10c\uc2a4 \uc194\ub8e8\uc158\uacfc \ud568\uaed8 \uc791\ub3d9\ud558\ubbc0\ub85c \uac12\ube44\uc2fc \ub9c8\uc774\uadf8\ub808\uc774\uc158 \ube44\uc6a9 \uc5c6\uc774 \uae30\uc874 \ud22c\uc790\ub97c \ud65c\uc6a9\ud558\uace0 \ubbf8\ub798 \uc9c0\ud5a5\uc801\uc778 \uac70\ubc84\ub10c\uc2a4 \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130 \ubc0f \ud074\ub77c\uc6b0\ub4dc \uc2a4\ud1a0\ub9ac\uc9c0\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\uc640 \uce74\ud0c8\ub85c\uadf8 \ud30c\ud2b8\ub108\uace0\uac1d\u201cUnity Catalog \ub355\ubd84\uc5d0 \ud68c\uc0ac \uc804\ubc18\uc801\uc73c\ub85c \ub370\uc774\ud130 \uad00\ub9ac\uc640 \uc561\uc138\uc2a4 \uc81c\uc5b4\ub97c \ub2e8\uc21c\ud654\ud560 \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. Compass \ub370\uc774\ud130 \ud300\uc740 100\uac1c \uc774\uc0c1\uc758 \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \uc548\uc804\ud558\uac8c \u0000\uc628\ubcf4\ub529\ud558\uace0, Unity Catalog\uc5d0 \ubaa8\ub4e0 \uc6cc\ud06c\uc2a4\ud398\uc774\uc2a4\ub97c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc600\uc73c\uba70, \uc8fc\uc694 \uc774\ud574\uad00\uacc4\uc790\ub4e4\uc774 \uace0\uac1d, \uc81c\ud488, \uc0ac\uc6a9\ub7c9, \uc218\uc775 \ub4f1\uc758 \ubd84\uc57c\uc5d0 \ub300\ud55c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\ub294 \uace8\ub4dc \ub808\uc774\uc5b4\ub97c \uac1c\ubc1c\ud568\uc73c\ub85c\uc368 \ud68c\uc0ac \uc804\uccb4\uc5d0 \uc644\uc804\ud55c \uc561\uc138\uc2a4 \uad00\ub9ac \uae30\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 \ub2e8\uc77c \ud1b5\ud569 \ucd9c\ucc98\ub97c \uad6c\ud604\ud588\uc2b5\ub2c8\ub2e4.\u201d\u2014 Rajesh Nagpal, \uc120\uc784 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uc774\uc0ac\u201cUnity Catalog \ub355\ubd84\uc5d0 \uc5ed\ud560 \uae30\ubc18 \uc561\uc138\uc2a4 \uc81c\uc5b4 \uad6c\ud604\uc774 \uc0c1\ub2f9\ud788 \ub2e8\uc21c\ud654\ub418\uc5c8\uace0, \uce74\ud0c8\ub85c\uadf8, \ub370\uc774\ud130\ubca0\uc774\uc2a4, \ud14c\uc774\ube14, \uc5f4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ubcf4\ud638\ud560 \uc218 \uc788\u0000\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc800\ud76c\ub294 \ubaa8\ub4e0 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uc801\uc808\ud55c \uc218\uc900\uc758 \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \ub9e4\ub044\ub7fd\uac8c \ud504\ub85c\ube44\uc800\ub2dd\ud558\uace0, \uc5c4\uaca9\ud55c \uaddc\uc815\uacfc \uac1c\uc778\uc815\ubcf4 \ubcf4\ud638\uc815\ucc45\uc5d0 \ub530\ub77c \ub370\uc774\ud130 \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \uc790\uc2e0\uac10 \uc788\uac8c \uad00\ub9ac\ud558\uace0 \ubcf4\ud638\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u201d\u2014 Chris Locklin, \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uad00\ub9ac\uc790, Grammarly\u201cMilliman\uc740 Unity Catalog\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubc29\ub300\ud55c \ub370\uc774\ud130 \uc790\uc0b0\uc744 \uc0ac\uc6a9\uc790\uc640 \uc9c1\uc811 \uc5f0\uacb0\ud568\uc73c\ub85c\uc368, \uc561\uc138\uc2a4 \uad00\ub9ac\ub97c \ub2e8\uc21c\ud654\ud558\uace0 \uc2a4\ud1a0\ub9ac\uc9c0 \ubcf5\uc7a1\uc131\uc744 \ub0ae\ucd94\uc5c8\uc2b5\ub2c8\ub2e4. Unity Catalog \ub355\ubd84\uc5d0 \uc5c4\uaca9\ud55c \uc758\ub8cc \uc11c\ube44\uc2a4 \uae30\uc900\uc744 \ucda9\uc871\ud558\uace0, \ud611\uc5c5\uc801 \ub370\uc774\ud130 \ud0d0\uc0c9\uc744 \uc81c\uacf5\ud558\uba70, \uc2a4\ud1a0\ub9ac\uc9c0 \ubcf5\uc7a1\uc131\uae4c\uc9c0 \ub0ae\ucd9c \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. Unity Catalog\ub97c \uc0ac\uc6a9\ud55c \ud6c4\ub85c \uace0\uac1d\uc758 \uc694\uad6c \uc0ac\ud56d\uc5d0 \ub9de\ucdb0 \ube60\ub978 \ud655\uc7a5\uc774 \uac00\ub2a5\ud558\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\u201d\u2014 Dan McCurley, \ud074\ub77c\uc6b0\ub4dc \uc194\ub8e8\uc158 \uc544\ud0a4\ud14d\ud2b8, Milliman\u201cUnity Catalog \ub355\ubd84\uc5d0 \uc55e\uc73c\ub85c \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc815\uc758 \uc790\ub3d9\ucc28\uac00 \ubc1c\uc804\ud558\uace0 \uac1c\uc120\ud574\ub098\uac00\uba74\uc11c \uc644\uc804\ud55c \uc7a0\uc7ac\ub825\uc744 \uc2e4\ud604\ud560 \uc218 \uc788\ub294 \ucc28\uc138\ub300 \ud50c\ub7ab\ud3fc\uc744 \uad6c\ucd95\ud558\uace0, \uace0\uac1d\uc758 \uc8fc\ud589 \u0000\u0000\uacbd\ud5d8\uc744 \ud5a5\uc0c1\ud558\uba74\uc11c\ub3c4 \uc804\uae30\ud654\ub41c \uad50\ud1b5\uc758 \ud658\uacbd\uc801 \uc7a5\uc810\uc744 \uadf9\ub300\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\uc81c \ub2e4\uc591\ud55c \ud300\uacfc \uc5c5\ubb34 \uacf5\uac04\uc5d0\uc11c \uc911\uc559 \uc9d1\uc911\ud615 \ub370\uc774\ud130 \uce74\ud0c8\ub85c\uadf8\uc640 \uc561\uc138\uc2a4 \uad00\ub9ac\uac00 \uac00\ub2a5\ud574\uc84c\uace0, \uc9c0\uae08\uaecf \uacbd\ud5d8\ud574\ubcf4\uc9c0 \ubabb\ud55c \ud611\uc5c5\uacfc \ud601\uc2e0\uc758 \uae30\ud68c\uac00 \uc5f4\ub838\uc2b5\ub2c8\ub2e4.\"\u2014 Venkat Sivasubramanian, \ube45\ub370\uc774\ud130 \ubd80\ubb38 \uc774\uc0ac\u201cUnity Catalog\ub294 \uc800\ud76c\uc5d0\uac8c \ud601\uc2e0\uc801 \ub3c4\uad6c\uc600\uc2b5\ub2c8\ub2e4. \uc800\ud76c \uc560\ub110\ub9ac\uc2a4\ud2b8\ub294 Databricks \uc6cc\ud06c\uc2a4\ud398\uc774\uc2a4\uc5d0\uc11c \uc2e4\uc2dc\uac04\uc73c\ub85c AWS \uc678\ubd80 \ud14c\uc774\ube14\uc5d0 \uc561\uc138\uc2a4\ud558\uace0, Delta Lake \ud14c\uc774\ube14\uacfc \uc870\uc778\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. Glue \ud14c\uc774\ube14\uc744 \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\uc9c0 \uc54a\uace0\ub3c4 Databricks SQL\uc774 \uc81c\uacf5\ud558\ub294 \uc131\ub2a5\uc758 \uc7a5\uc810\uc744 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Unity Catalog\ub97c \uc0ac\uc6a9\ud558\uace0 \ub098\uc11c\ub294 \ub370\uc774\ud130\ub97c \uc62e\uae30\uc9c0 \uc54a\uace0\ub3c4 \uc5ec\ub7ec \ud300\uc774 \uc11c\ub85c \ud611\uc5c5\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\u201d\u2014 Rajat Gupta, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uad00\ub9ac\uc790, Warner Bros. Discovery\ub9ac\uc18c\uc2a4\ud0a4\ub178\ud2b8 \ubc0f \uc6e8\ube44\ub098[\ud0a4\ub178\ud2b8]Data + AI Summit 2022\uc5d0\uc11c \ubc1c\ud45c\ub41c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4 \ubc0f \uacf5\uc720[\uc628\ub514\ub9e8\ub4dc \uc6e8\ube44\ub098]\ub370\uc774\ud130 \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub97c \ub2e8\uc21c\ud654\ud558\ub294 \ubc29\ubc95eBook \ubc0f \ube14\ub85c\uadf8[eBook] \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4Unity Catalog\uc5d0\uc11c \ub370\uc774\ud130 \ub9ac\ub2c8\uc9c0 \uc815\uc2dd \ucd9c\uc2dcUnity Catalog\ub97c \ud1b5\ud55c \ub370\uc774\ud130 \ub9ac\ub2c8\uc9c0 \uc9c0\uc6d0 \ubc1c\ud45cDatabricks Unity Catalog \uc18c\uac1c: \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ub370\uc774\ud130 \ubc0f AI\ub97c \uc704\ud55c \uc138\ubd84\ud654\ub41c \uac70\ubc84\ub10c\uc2a4\uad00\ub828 \ubb38\uc11cAWS \uad00\ub828 \ubb38\uc11cAzure \uad00\ub828 \ubb38\uc11c\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/br\/events","text":"Eventos Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWEventos DatabricksReuni\u00f5es, webinars, confer\u00eancias... descubra os pr\u00f3ximos eventos Databricks.Data + AI Summit 202326 a 29 de junhoEscolha sua experi\u00eancia: venha pessoalmente ou participe das confer\u00eancias e de uma sele\u00e7\u00e3o de sess\u00f5es ao vivo onlineParticipeLoading...Browse All Upcoming EventsProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/driving-innovation-data-ai-financial-services","text":"Driving Innovation in Financial Services With a Unified Approach to Data + AI | DatabrickseBookDriving Innovation in Financial Serviceswith a unified approach to Data + AIData and AI are changing how financial institutions generate and utilize insights from data. As a result, the traditional advantages that financial institutions enjoyed, such as capital and scale, are no longer the main differentiators going forward. The winners of tomorrow will thrive based on their ability to attract engineering talent and unlock the value of data with the right tools and technologies.In this eBook, you will learn:Why financial institutions struggle with data and AIHow data is transforming financial servicesHow Databricks fuels data-driven innovationGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=DeltaLake-FooterCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/customers","text":"Kunden von\u2028Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWKunden von DatabricksEntdecken Sie, wie innovative Unternehmen aus allen Branchen die Databricks Lakehouse-Plattform f\u00fcr ihren Erfolg nutzenEmpfehlungen\n\n\nKundenbericht\n\nModernisierung von Finanzdienstleistungen mit Daten und KI\nTrotz der steigenden Akzeptanz von Big Data und KI sehen sich die meisten Finanzdienstleister immer noch mit erheblichen Herausforderungen bei Datentypen, Datenschutz und Umfang konfrontiert.\n\nWeiterlesen\n\n\nKundenbericht\n\nVorhersagen und Steigern des Customer Lifetime Value mit ML\nKolibri Games befindet sich im Herzen Berlins und ist bekannt f\u00fcr seinen erfrischenden, von Spielern gef\u00fchrten Ansatz. Kolibri Games ist ein aufgehender Stern in der Szene der Spiele f\u00fcr Mobilger\u00e4te. Die Hittitel Idle Miner Tycoon und Idle Factory Tycoon ziehen monatlich \u00fcber 10\u00a0Millionen aktive Benutzer an.\n\nWeiterlesen\n\n\nKundenbericht\n\nShell f\u00fchrt innovative Energiel\u00f6sungen f\u00fcr eine sauberere Welt ein\nDatabricks Lakehouse tr\u00e4gt dazu bei, Daten zu demokratisieren und Abl\u00e4ufe weltweit zu modernisieren\n\nWeiterlesen\n\n\nKundenbericht\n\nDigitalisierung der Solaranlagen zur F\u00f6rderung der betrieblichen Exzellenz\nSolytic, ein Unternehmen, das Solaranlagen \u00fcberwacht und deren Daten analysiert, hat ein Ziel: die Nutzung von Solarenergie f\u00fcr jedermann zu vereinfachen.\n\nWeiterlesen\n\n\nKundenbericht\n\nVerbinden Sie Millionen von Kunden mit dem gr\u00f6\u00dften 5G-Netzwerk\nAls einer der bekanntesten Mobilfunkanbieter in den USA hat sich T-Mobile zum Ziel gesetzt, das gr\u00f6\u00dfte und schnellste 5G-Netz bereitzustellen.\n\nWeiterlesen\n\n\nKundenbericht\n\nAufbau einer energieeffizienten Welt\nDa die weltweite Nachfrage nach energieeffizienten L\u00f6sungen weiter steigt\u00a0\u2013 von Klimasystemen \u00fcber Solarmodule bis hin zu Windturbinen und Elektroautos\u00a0\u2013 kann die Bedeutung von Daten f\u00fcr einen intelligenteren Betrieb nicht hoch genug eingesch\u00e4tzt werden.\u00a0\n\nWeiterlesenAlle Kunden erkundenDer Daten-Team EffektDatenteams bilden eine vereinte Streitmacht, wenn es darum geht, die schwierigsten Probleme der Welt zu l\u00f6sen.Erfahren Sie, wie \u2192Ist Ihr Unternehmen die n\u00e4chste Erfolgsgeschichte?KontaktRessourcenKundenberichtSo stellt Cond\u00e9 Nast seinen Kunden mithilfe von Databricks personalisierte Inhalte bereit.Mehr InformationenKundenberichtFinden Sie heraus, wie Apple und Disney+ mit Unified Analytics und KI riesige Erfolge feiernMehr InformationenKundenberichtErfahren Sie von Slawek Kierner, SVP, Chief Data & Analytics Officer bei Humana, mehr \u00fcber die Rolle von Daten und KI im GesundheitswesenAnsehenM\u00f6chten Sie loslegen?Kostenlos testenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/resources\/google-cloud-free-trial?itm_data=gcp-toppromo-gcpfreetrial","text":"Google Cloud Free Trial \u2013 DatabricksTry Databricks on Google Cloud for FreeGet Started with a Free 14-day Trial of Databricks on Google Cloud.One open lakehouse platform to store and manage all of your data for data engineering, data science, and analytics.What you get:Databricks account on Google CloudSingle Sign-on into Databricks with Google Cloud IdentitySingle-click cluster set up running on Google Kubernetes Engine (GKE), processing data in your own accountBuilt-in integration with Google Cloud Storage, Big Query, Pub\/Sub and LookerAbility to run production ELT\/ETL pipelines at massive scaleFully collaborative notebooks with multi-language supportOut-of-the-box native support for ML frameworks like MLflow, scikit-learn, TensorFlow and KerasPlease tell us about yourselfProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/onik-kurktchian\/#","text":"Onik Kurktchian - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOnik KurktchianHead of S&P Global Marketplace Workbench at S&P GLOBALBack to speakersOnik Kurktchian is a Product Manager and\u202fleads the Analytical Platforms and Services in S&P Global Market Intelligence. He is part of the\u202fteam\u202fthat is responsible for creating products and services that enable data exploration and workflow solutions across all client segments. Previously, he has worked as a Product Specialist across multiple S&P products between Desktop, Excel and Feed Solutions. Onik holds an MSc from LSE in Economic History and a BSc from Queen Mary in Economics & Finance. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/15\/announcing-new-partner-integrations-in-partner-connect.html","text":"Announcing New Partner Integrations in Partner Connect - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing New Partner Integrations in Partner ConnectNew, validated integrations make it easier to ingest, analyze and trust data in your lakehouseby Hiral Jasani, Bilal Aslam, Zaheera Valani and Katie CummiskeyJune 15, 2022 in Company BlogShare this postWe are excited to announce six new integrations in Databricks Partner Connect. Our expanding partnerships enable our users to integrate the freshest data into the Databricks Lakehouse Platform, use pre-built deep learning models to process clinical and biomedical text at scale, use cutting-edge notebooks for analytics and data science collaboration and automatically track and improve data quality. This is part of our commitment to bringing the best partners in the world to our customers through Partner Connect, a one-stop portal for discovering, trying, and connecting the best-validated data, analytics, and AI tools with Databricks.\nThis quarter, we have added the following partner integrations to Partner Connect.\nData IngestionArcionArcion is a cloud-native, change data capture-based data replication platform that integrates data from relational databases such as Oracle, Oracle Exadata, and Oracle RAC, IBM DB2, Microsoft SQL Server, and SaaS applications such as Salesforce into Delta Lake on Databricks. Arcion offers transactional integrity, automatic schema conversion, and zero latency. This makes it an ideal solution for business-critical analytics and AI workloads that benefit from real-time, freshest possible data, for example, click-stream data, customer 360, threat protection, etc. Arcion is also one of the first zero-code data mobility platforms in the Databricks Ventures portfolio. Click here to view a demo.\nData TransformationMatillionMatillion ETL for Delta Lake on Databricks brings no-code\/low-code data integration to a lakehouse architecture. Users across the business can take ownership of their data, leveraging best-in-class data transformation from Matillion ETL to enable on-demand machine learning, faster reporting, and BI improvements powered by Delta Lake. Availability in Partner Connect allows users to easily extract and load business-critical data from operational databases, files, NoSQL, and API sources into Delta Lake without any prior pre-configuration.\nArtificial intelligence and machine learningJohn Snow Labs\nOver the past year, John Snow Labs has developed solutions for key use cases, such as detecting adverse events, extracting oncology insights and automating the removal of PHI, that are optimized to run on Databricks to help healthcare and life science companies transform large volumes of unstructured text data into patient insights. With Partner Connect, John Snow Labs' Spark NLP for Healthcare - a best-of-breed and the most widely-used NLP library - is easily available to all Databricks customers. This allows healthcare organizations to unify clinical and biomedical text data at scale into a single, high-performance lakehouse platform for analytics and data science.\nHex\nTogether, Databricks and Hex are powering the next generation of analytics. Databricks provides unparalleled data processing and storage, and Hex makes that data available for data science exploration and analytics. Hex simply and securely connects to the Databricks Lakehouse, so users can query structured and unstructured data in collaborative SQL and Python-powered notebooks, and then share their work as interactive data apps that are usable by anyone. Hex empowers users of all skill sets to make decisions backed by data. Learn more about how Hex & Databricks work seamlessly together and sign up for a free trial today.\nData qualityAnomalo\nAnomalo automatically detects data issues and understands their root cause, ensuring you can trust the quality of your data in your Databricks Lakehouse before it is consumed by BI, analytics, and machine learning frameworks. Unlike traditional rules-based approaches to data quality, Anomalo provides automated checks for data quality using machine learning. When issues are detected, Anomalo provides a rich set of visualizations to contextualize and explain issues as well as an instant root-cause analysis that points to the likely source of the problem. This means customers spend more time making data-driven decisions, and less time investigating and fire-fighting issues with data. To learn more about Anomalo, please visit Anomalo.com, or request a demo here.\nLightup\nLightup empowers data-driven companies to quickly and continuously perform accurate and comprehensive data quality checks with ease. With deep integration with Databricks Lakehouse Platform, Lightup provides an additional layer of data reliability across the Lakehouse \u2014 empowering enterprises to perform in-place data quality checks \u2014 accelerating data migrations from legacy big data systems to Databricks, all with a single click.\nStart optimizing the data quality in your Lakehouse today! To learn more about Lightup, visit lightup.ai.\nCustomer spotlight: Enabling data literacy at AktifyPartner Connect eliminates the complexity of finding, and configuring partner tools securely with Databricks to support your analytics and AI use cases. For example, Aktify, a conversational AI company, is on a mission to delight customers by powering conversations using robust machine learning. A one-click Tableau connector in Partner Connect allows all users at Aktify to spin up their own Tableau dashboards to answer key business questions instead of waiting on data engineers. As a result, Aktify now has over two dozen data professionals focused on high-value tasks working collaboratively and sharing data insights seamlessly.\n\"We no longer stage data in Snowflake as all data (including ~85 GB of operational data) is instantly available in the Databricks Lakehouse,\" explained Brandon Smith, the Director of Data & Analytics at Aktify. \"Partner Connect also helps the team discover new data and AI solutions, bringing us closer to our vision of organization-wide data literacy.\"Get started with Partner ConnectSign up for a free trial of Databricks to try Partner Connect at no additional cost. Stay tuned as we announce integrations with Matillion, Hightouch, Preset, Thoughtspot and many others in the coming months.\nYou will have the opportunity to meet all Partner Connect partners in-person or online at the Data + AI Summit, the world's largest data and AI conference from June 27-30. If you haven't already, be sure to register here for talks, technical demos, hands-on training and networking.Try Databricks for freeGet StartedRelated postsNow Generally Available: Introducing Databricks Partner Connect to Discover and Connect Popular Data and AI Tools to the LakehouseNovember 18, 2021 by Hiral Jasani and Himanshu Raja in Platform Blog\nDatabricks is thrilled to announce Partner Connect, a one-stop portal for customers to quickly discover a broad set of validated data, analytics, and...\nBuild Your Business on Databricks With Partner ConnectNovember 18, 2021 by Dave Eyler, Pankaj Dugar and Zaheera Valani in Platform Blog\nAt Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and...\nLaunching dbt Cloud in Databricks Partner ConnectApril 14, 2022 by Bilal Aslam, Hiral Jasani, Shant Hovsepian, Dave Eyler, Daniel Rosenthal and Bemnet Merha in Partners\nWe are delighted to announce that dbt Cloud, the fastest and most reliable way to build, manage and monitor dbt projects, is now...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/legal\/privacynotice","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/try-databricks-aws?itm_data=AwsPage-TrialButton-AWSTrial#account.","text":"Try Databricks on AWS \u2013 Free for 14 Days \u2013 DatabricksTry Databricks on AWS free for 14 daysSimplify your data architecture by unifying your data, analytics and AI workloads on a common platform.Databricks enables a single, unified data architecture on S3 for SQL analytics, data science and machine learning.Join thousands of customers that use Databricks on AWS as a game-changing platform for their data teams.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-stevens\/#","text":"Chris Stevens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris StevensSenior Staff Software Engineer at DatabricksBack to speakersChris Stevens is a Senior Staff Software Engineer and manager at Databricks. His work focuses on the intersection of the control and data planes, ranging from workload execution protocols and query routing to warehouse auto-scaling and cache management. His background is in operating systems where he worked on Windows NT and co-created Minoca OS.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-mracek","text":"Paul Mracek - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MracekSenior Solutions Architect at DatabricksBack to speakersPaul Mracek has 15 years of Data and AI experience. He joined Databricks in 2021 and has supported Honeywell since 2022.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adi-polak","text":"Adi Polak - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdi PolakData & AI Technologist at TechnologistBack to speakersAdi is a world-leading specialist in the field of Data & AI. In her role as Vice President of DevEx at Treeverse, Adi contributes to lakeFS, Git for data project loved by Data & AI practitioners. In her work, she brings her vast industry research and engineering experience to bear in educating and helping teams design, architect, and build cost-effective data systems and machine learning pipelines that emphasize scalability, expertise, and business goals. Adi is a proud Databricks beacon, frequent worldwide presenter and the author of O\u2019Reilly\u2019s book, \u201cScaling Machine Learning with Spark.\u201dLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/blog\/2020\/01\/30\/what-is-a-data-lakehouse.html?itm_data=lakehouse-link-lakehouseblog","text":"What Is a Lakehouse? - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorWhat Is a Lakehouse?by Ben Lorica, Michael Armbrust, Reynold Xin, Matei Zaharia and Ali GhodsiJanuary 30, 2020 in Engineering BlogShare this postOver the past few years at Databricks, we've seen a new data management architecture that emerged independently across many customers and use cases: the lakehouse. In this post we describe this new architecture and its advantages over previous approaches.Data warehouses have a long history in decision support and business intelligence applications. Since its inception in the late 1980s, data warehouse technology continued to evolve and MPP architectures led to systems that were able to handle larger data sizes. But while warehouses were great for structured data, a lot of modern enterprises have to deal with unstructured data, semi-structured data, and data with high variety, velocity, and volume. Data warehouses are not suited for many of these use cases, and they are certainly not the most cost efficient.As companies began to collect large amounts of data from many different sources, architects began envisioning a single system to house data for many different analytic products and workloads. About a decade ago companies began building data lakes - repositories for raw data in a variety of formats. While suitable for storing data, data lakes lack some critical features: they do not support transactions, they do not enforce data quality, and their lack of consistency \/ isolation makes it almost impossible to mix appends and reads, and batch and streaming jobs. For these reasons, many of the promises of the data lakes have not materialized, and in many cases leading to a loss of many of the benefits of data warehouses.The need for a flexible, high-performance system hasn\u2019t abated. Companies require systems for diverse data applications including SQL analytics, real-time monitoring, data science, and machine learning. Most of the recent advances in AI have been in better models to process unstructured data (text, images, video, audio), but these are precisely the types of data that a data warehouse is not optimized for. A common approach is to use multiple systems - a data lake, several data warehouses, and other specialized systems such as streaming, time-series, graph, and image databases. Having a multitude of systems introduces complexity and more importantly, introduces delay as data professionals invariably need to move or copy data between different systems.What is a lakehouse?New systems are beginning to emerge that address the limitations of data lakes. A lakehouse is a new, open architecture that combines the best elements of data lakes and data warehouses. Lakehouses are enabled by a new system design: implementing similar data structures and data management features to those in a data warehouse directly on top of low cost cloud storage in open formats. They are what you would get if you had to redesign data warehouses in the modern world, now that cheap and highly reliable storage (in the form of object stores) are available.A lakehouse has the following key features:Transaction support: In an enterprise lakehouse many data pipelines will often be reading and writing data concurrently. Support for ACID transactions ensures consistency as multiple parties concurrently read or write data, typically using SQL.Schema enforcement and governance: The Lakehouse should have a way to support schema enforcement and evolution, supporting DW schema architectures such as star\/snowflake-schemas. The system should be able to reason about data integrity, and it should have robust governance and auditing mechanisms.BI support: Lakehouses enable using BI tools directly on the source data. This reduces staleness and improves recency, reduces latency, and lowers the cost of having to operationalize two copies of the data in both a data lake and a warehouse.Storage is decoupled from compute: In practice this means storage and compute use separate clusters, thus these systems are able to scale to many more concurrent users and larger data sizes. Some modern data warehouses also have this property.Openness: The storage formats they use are open and standardized, such as Parquet, and they provide an API so a variety of tools and engines, including machine learning and Python\/R libraries, can efficiently access the data directly.Support for diverse data types ranging from unstructured to structured data: The lakehouse can be used to store, refine, analyze, and access data types needed for many new data applications, including images, video, audio, semi-structured data, and text.Support for diverse workloads: including data science, machine learning, and SQL and analytics. Multiple tools might be needed to support all these workloads but they all rely on the same data repository.End-to-end streaming: Real-time reports are the norm in many enterprises. Support for streaming eliminates the need for separate systems dedicated to serving real-time data applications.These are the key attributes of lakehouses. Enterprise grade systems require additional features. Tools for security and access control are basic requirements. Data governance capabilities including auditing, retention, and lineage have become essential particularly in light of recent privacy regulations. Tools that enable data discovery such as data catalogs and data usage metrics are also needed. With a lakehouse, such enterprise features only need to be implemented, tested, and administered for a single system.Read the full research paper on the inner workings of the Lakehouse.Some early examplesThe Databricks Lakehouse Platform has the architectural features of a lakehouse. Microsoft's\u00a0Azure Synapse Analytics\u00a0service, which\u00a0integrates with Azure Databricks, enables a similar lakehouse pattern.\u00a0Other managed services such as BigQuery and Redshift Spectrum have some of the lakehouse features listed above, but they are examples that focus primarily on BI and other SQL applications. Companies who want to build and implement their own systems have access to open source file formats (Delta Lake, Apache Iceberg, Apache Hudi) that are suitable for building a lakehouse.Merging data lakes and data warehouses into a single system means that data teams can move faster as they are able use data without needing to access multiple systems. The level of SQL support and integration with BI tools among these early lakehouses are generally sufficient for most enterprise data warehouses. Materialized views and stored procedures are available but users may need to employ other mechanisms that aren't equivalent to those found in traditional data warehouses. The latter is particularly important for \u201clift and shift scenarios\u201d, which require systems that achieve semantics that are almost identical to those of older, commercial data warehouses.What about support for other types of data applications? Users of a lakehouse have access to a variety of standard tools (Spark, Python, R, machine learning libraries) for non BI workloads like data science and machine learning. Data exploration and refinement are standard for many analytic and data science applications. Delta Lake is designed to let users incrementally improve the quality of data in their lakehouse until it is ready for consumption.A note about technical building blocks. While distributed file systems can be used for the storage layer, objects stores are more commonly used in lakehouses. Object stores provide low cost, highly available storage, that excel at massively parallel reads - an essential requirement for modern data warehouses.From BI to AIThe lakehouse is a new data management architecture that radically simplifies enterprise data infrastructure and accelerates innovation in an age when machine learning is poised to disrupt every industry. In the past most of the data that went into a company's products or decision making was structured data from operational systems, whereas today, many products incorporate AI in the form of computer vision and speech models, text mining, and others. Why use a lakehouse instead of a data lake for AI? A lakehouse gives you data versioning, governance, security and ACID properties that are needed even for unstructured data.Current lakehouses reduce cost but their performance can still lag specialized systems (such as data warehouses) that have years of investments and real-world deployments behind them. Users may favor certain tools (BI tools, IDEs, notebooks) over others so lakehouses will also need to improve their UX and their connectors to popular tools so they can appeal to a variety of personas. These and other issues will be addressed as the technology continues to mature and develop. Over time lakehouses will close these gaps while retaining the core properties of being simpler, more cost efficient, and more capable of serving diverse data applications.Read the FAQ on Data Lakehouse for more details.Building the Data Lakehouse.\nExplore the next generation of data architecture with the father of the data warehouse, Bill Inmon.Download NowTry Databricks for freeGet StartedRelated postsWhat Is a Lakehouse?January 30, 2020 by Ben Lorica, Michael Armbrust, Reynold Xin, Matei Zaharia and Ali Ghodsi in Engineering Blog\nOver the past few years at Databricks, we've seen a new data management architecture that emerged independently across many customers and use cases...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andrew-blance","text":"Andrew Blance - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndrew BlanceInnovation Consultant at WaterstonsBack to speakersAndrew is an innovation consultant at Waterstons, an IT consultancy. His role involves working with clients and research partners to carry out projects with emerging technologies. He co-hosts a podcast called Brains on the Outside, where he pitches ridiculous business ideas. Once, Durham University deemed him sensible enough to make him a Doctor of particle physics. He can run 5km pretty fast and thinks modern Star Trek isn't as bad as people make it out to be.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/glossary\/orchestration","text":"What is Orchestration?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWOrchestrationAll>OrchestrationWhat is Orchestration?Orchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of multiple tasks that are automated and can involve multiple systems.The goal of orchestration is to streamline and optimize the execution of frequent, repeatable processes and thus to help data teams more easily manage complex tasks and workflows. Anytime a process is repeatable, and its tasks can be automated, orchestration can be used to save time, increase efficiency, and eliminate redundancies. For example, you can simplify data and machine learning with jobs orchestration.What is the difference between process orchestration and process automation?While automation and orchestration are highly complementary, they mean different things. Automation is programming a task to be executed without the need for human intervention. Orchestration is the configuration of multiple tasks (some may be automated) into one complete end-to-end process or job. Orchestration software also needs to react to events or activities throughout the process and make decisions based on outputs from one automated task to determine and coordinate the next tasks.What is application orchestration?Application orchestration is when you integrate two or more software applications together. You might do this in order to automate a process, or to enable real-time syncing of data. Most software development efforts need some kind of application orchestration\u2014without it, you\u2019ll find it much harder to scale application development, data analytics, machine learning and AI projects.The process allows you to manage and monitor your integrations centrally, and add capabilities for message routing, security, transformation and reliability. This approach is more effective than point-to-point integration, because the integration logic is decoupled from the applications themselves and is managed in a container instead.What is service orchestration?Service orchestration works in a similar way to application orchestration, in that it allows you to coordinate and manage systems across multiple cloud vendors and domains\u2014which is essential in today\u2019s world. The approach covers microservice orchestration, network orchestration and workflow orchestration.Individual services don\u2019t have the native capacity to integrate with one another, and they all have their own dependencies and demands. The more complex the system, the more important it is to orchestrate the various components. That way, you can scale infrastructures as needed, optimize systems for business objectives and avoid service delivery failures.What exactly is container orchestration?You may have come across the term \u201ccontainer orchestration\u201d in the context of application and service orchestration. So, what is container orchestration and why should we use it?Container orchestration is the automation of container management and coordination. Software teams use the best container orchestration tools to control and automate tasks such as provisioning and deployments of containers, allocation of resources between containers, health monitoring of containers, and securing interactions between containers.How does container orchestration work?Software orchestration teams typically use container orchestration tools like Kubernetes and Docker Swarm. You start by describing your app\u2019s configuration in a file, which tells the tool where to gather container images and how to network between containers.The tool also schedules deployment of containers into clusters and finds the most appropriate host based on pre-set constraints such as labels or metadata. It then manages the container\u2019s lifecycle based on the specifications laid out in the file.But why do we need container orchestration? And what is the purpose of automation and orchestration? Well, automating container orchestration enables you to scale applications with a single command, quickly create new containerized applications to handle growing traffic, and simplify the installation process. It also improves security.What is cloud orchestration?Cloud orchestration is the process of automating the tasks that manage connections on private and public clouds. It also integrates automated tasks and processes into a workflow to help you perform specific business functions.The rise of cloud computing, involving public, private and hybrid clouds, has led to increasing complexity. This creates a need for cloud orchestration software that can manage and deploy multiple dependencies across multiple clouds. Cloud service orchestration includes tasks such as provisioning server workloads and storage capacity and orchestrating services, workloads and resources.Remember that cloud orchestration and automation are different things: Cloud orchestration focuses on the entirety of IT processes, while automation focuses on an individual piece. Orchestration simplifies automation across a multi-cloud environment, while ensuring that policies and security protocols are maintained.What is security orchestration?Security orchestration ensures your automated security tools can work together effectively, and streamlines the way they\u2019re used by security teams. The aim is that the tools can communicate with each other and share data\u2014thus reducing the potential for human error, allowing teams to respond better to threats, and saving time and cost.What is Security Orchestration Automation and Response (SOAR)? The acronym describes three software capabilities as defined by Gartner:Orchestration\u2014Threat and vulnerability managementAutomation\u2014Security operations automationResponse\u00ad\u2014Security incident responseThis approach combines automation and orchestration, and allows organizations to automate threat-hunting, the collection of threat intelligence and incident responses to lower-level threats.What is an orchestration layer?An orchestration layer is required if you need to coordinate multiple API services. It enables you to create connections or instructions between your connector and those of third-party applications. That effectively creates a single API that makes multiple calls to multiple different services to respond to a single API request.It also manages data formatting between separate services, where requests and responses need to be split, merged or routed. By adding this abstraction layer, you provide your API with a level of intelligence for communication between services. An orchestration layer assists with data transformation, server management, handling authentications and integrating legacy systems.In the cloud, an orchestration layer manages interactions and interconnections between cloud-based and on-premises components. These include servers, networking, virtual machines, security and storage.What is journey orchestration?What is customer journey orchestration? Journey orchestration takes the concept of customer journey mapping a stage further. It uses automation to personalize journeys in real time, rather than relying on historical data. The goal remains to create and shape the ideal customer journey.Journey orchestration also enables businesses to be agile, adapting to changes and spotting potential problems before they happen.Orchestration toolsThe orchestration needed for complex tasks requires heavy lifting from data teams and specialized tools to develop, manage, monitor, and reliably run such pipelines. These tools are typically separate from the actual data or machine learning tasks. This lack of integration leads to fragmentation of efforts across the enterprise and users having to switch contexts a lot.As companies undertake more business intelligence (BI) and artificial intelligence (AI) initiatives, the need for simple, scalable and reliable orchestration tools has increased. A variety of tools exist to help teams unlock the full benefit of orchestration with a framework through which they can automate workloads.Service orchestration tools help you integrate different applications and systems, while cloud orchestration tools bring together multiple cloud systems. Orchestration tools also help you manage end-to-end processes from a single location and simplify process creation to create workflows that were otherwise unachievable.For example, Databricks helps you unify your data warehousing and AI use cases on a single platform. Click here to learn how to orchestrate Databricks workloads.What is application release orchestration?Application release orchestration (ARO) enables DevOps teams to automate application deployments, manage continuous integration and continuous delivery pipelines, and orchestrate release workflows. The aim is to improve the quality, velocity and governance of your new releases.As well as deployment automation and pipeline management, application release orchestration tools enable enterprises to scale release activities across multiple diverse teams, technologies, methodologies and pipelines. Some well-known ARO tools include GitLab, Microsoft Azure Pipelines, and FlexDeploy.What is process orchestration?While automated processes are necessary for effective orchestration, the risk is that using different tools for each individual task (and sourcing them from multiple vendors) can lead to silos. You need to integrate your tools and workflows, and that\u2019s what is meant by process orchestration.Process orchestration involves unifying individual tasks into end-to-end processes and streamlining system integrations with universal connectors, direct integrations, or API adapters. IT teams can then manage the entire process lifecycle from a single location.Benefits include reducing complexity by coordinating and consolidating disparate tools, improving mean time to resolution (MTTR) by centralizing the monitoring and logging of processes, and integrating new tools and technologies with a single orchestration platform. This type of software orchestration makes it possible to rapidly integrate virtually any tool or technology.The purpose of data orchestration platformsData orchestration is an automated process for taking siloed data from multiple storage locations, combining and organizing it, and making it available for analysis. The process connects all your data centers, whether they\u2019re legacy systems, cloud-based tools or data lakes. The data is transformed into a standard format, so it\u2019s easier to understand and use in decision-making.Most companies accumulate a crazy amount of data, which is why automated tools are necessary to organize it. What is big data orchestration? It\u2019s the process of organizing data that\u2019s too large, fast or complex to handle with traditional methods. Data orchestration also identifies \u201cdark data\u201d, which is information that takes up space on a server but is never used.Data orchestration platforms are ideal for ensuring compliance and spotting problems. For example, a payment orchestration platform gives you access to customer data in real-time, so you can see any risky transactions.What is orchestration in DevOps?DevOps orchestration is the coordination of your entire company\u2019s DevOps practices and the automation tools you use to complete them. The aim is to minimize production issues and reduce the time it takes to get new releases to market.Orchestrating your automated tasks helps maximize the potential of your automation tools. This brings us back to the orchestration vs automation question: Basically, you can maximize efficiency by automating numerous functions to run at the same time, but orchestration is needed to ensure those functions work together.For example, DevOps orchestration for a cloud-based deployment pipeline enables you to combine development, QA and production.What is Docker orchestration?Docker is a user-friendly container runtime that provides a set of tools for developing containerized applications. It allows you to package your code into an image, which is then used to create a container. Therefore, Docker orchestration is a set of practices and technologies for managing Docker containers.This type of container orchestration is necessary when your containerized applications scale to a large number of containers. It\u2019s used for tasks like provisioning containers, scaling up and down, managing networking and load balancing.The Docker ecosystem offers several tools for orchestration, such as Swarm. Kubernetes is commonly used to orchestrate Docker containers, while cloud container platforms also provide basic orchestration capabilities.Orchestrating data and machine learning pipelines in DatabricksDatabricks makes it easy to orchestrate multiple tasks in order to easily build data and machine learning workflows.Orchestrating multi-step tasks makes it simple to define data and ML pipelines using interdependent, modular tasks consisting of notebooks, Python scripts, and JARs. Data teams can easily create and manage multi-step pipelines that transform and refine data, and train machine learning algorithms, all within the familiar workspace of Databricks, saving teams immense time, effort, and context switches.In the example above, a Job consisting of multiple tasks uses two tasks to ingest data: Clicks_Ingest and Orders_Ingest. This ingested data is then aggregated together and filtered in the \u201cMatch\u201d task, from which new machine learning features are generated (Build_Features), persistent (Persist_Features), and used to train new models (Train).Jobs orchestration is fully integrated in Databricks and requires no additional infrastructure or DevOps resources. Customers can use the Jobs API or UI to create and manage jobs and features, such as email alerts for monitoring.Your data team does not have to learn new skills to benefit from this feature. This feature also enables you to orchestrate anything that has an API outside of Databricks and across all clouds, e.g. pull data from CRMs. Get started today with the new Jobs orchestration now by enabling it yourself for your workspace (AWS | Azure | GCP).Additional ResourcesData engineering on DatabricksJob orchestration docuemtationBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/jp\/discover\/demos","text":"Databricks \u88fd\u54c1\u3001\u30d1\u30fc\u30c8\u30ca\u30fc\u3068\u306e\u9023\u643a\u3001\u30bd\u30b7\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u306e\u30c7\u30e2 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u0000\u0000\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/resources\/ebook\/data-engineering-data-science-and-analytics-with-databricks-on-google-cloud","text":"Data Engineering, Data Science and Analytics With Databricks on Google Cloud | DatabrickseBookData Engineering, Data Science and Analytics With Databricks on Google CloudData engineering and data science use cases, including code samples and notebooksIn this eBook, explore two practical data engineering and data science use cases you can put to work right now to get familiar with Databricks on Google Cloud. It includes code samples and example notebooks for a hands-on experience.You\u2019ll get a deep dive into these use cases:How to build a data pipeline using Delta Lake on Google Cloud Storage, and pull data from Databricks and BigQuery to visualize in LookerHow to automate experiment tracking with Managed MLflow, version a MLflow model with MLflow Model Registry and write inferences to BigQueryGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ajmal-aziz","text":"Ajmal Aziz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAjmal AzizSolutions Architect at DatabricksBack to speakersAjmal Aziz is a Solutions Architect at Databricks based in Melbourne. He is passionate about helping customers scale their machine learning and analytics applications. Ajmal received his MPhil from the University of Cambridge where he learned the art of punting. In his spare time, he likes to go hiking and bouldering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/maciej-szpakowski","text":"Maciej Szpakowski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMaciej SzpakowskiCo-founder at ProphecyBack to speakersMaciej is the co-founder @ Prophecy, where he's building the first low-code data engineering platform. Having previously built a startup making medical research accessible through ML\/Spark, he dreams of a world where data is not feared but leveraged.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/daniel-tenedorio\/#","text":"Daniel Tenedorio - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDaniel TenedorioSr. Staff Software Engineer at DatabricksBack to speakersDaniel Tenedorio is a software engineer at Databricks, working on Spark Core and Spark SQL. He interacts with the Apache Spark\u2122 open-source community to develop and review query processing features. Daniel has a breadth of experience in database management systems development from building and launching features underpinning multiple major production services over time.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-unified-ai","text":"What is Unified AI Framework?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnified AI FrameworkAll>Unified AI FrameworkTry Databricks for freeGet StartedUnified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute resources while Caffe focused on model deployment on Android and Raspberry Pi devices. Unlike the narrow scope of Facebook\u2019s Unified AI, Unified Analytics is a category of solutions that look at the entire lifecycle of AI - all the way from preparing datasets, feature engineering, model development, training, to deployment of models into production. It truly unified data with AI throughout the dev-to-production lifecycle. Databricks\u2019 Unified Analytics Platform powered by Apache Spark enables organizations to accelerate innovation by bringing together data and AI technologies, improving collaboration between data engineers and data scientists, and making it simpler to prepare data, train models, and deploy them into production. Databricks platform lets data scientists choose from a broad set of AI frameworks - Spark MLlib, TensorFlow, Pytorch, Caffee2 and others.Additional ResourcesUnified Approach to Interpret Machine Learning Model: SHAP + LIMEOn-Demand Webinar: Geospatial Analytics and AI in the Public SectorBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/leena-dalvi\/#","text":"Leena Dalvi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLeena DalviAssistant Vice President, Enterprise Data & Analytics at Navy Federal Credit UnionBack to speakersLeena is an exceptionally energetic and passionate Data Transformation and Governance leader with over 20 years of strategic and hands-on Leadership and Data Management experience in the Financial Services industry. She is a results-oriented leader and visionary with a passion for data governance who can think strategically and act as a change agent to transform an organization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#90fdf9fbf5befdfffffef5e9d0f4f1e4f1f2e2f9f3fbe3bef3fffd","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c38e84d5b05b1\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/professional-services","text":"Databricks Professional Services | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Professional ServicesContact us to learn moreDelivering rapid success on projects with world-class data engineering, data science and project management expertise. Databricks Professional Services can help you at any point in your data and AI journey:BenefitsAccelerate your data and AI journey\nOur offerings and expert services help you in your data and AI journey to provide optimal and tailored acceleration from the initial workspace onboarding to building out DataOps and Center of Excellence practices at enterprise scale.\nDe-risk your project\nWhether you are migrating from legacy workloads to Databricks, building out new data products or data and AI pipeline and machine learning projects, let us be your partner and trusted advisor to minimize risk and maximize value at each step of your journey.\nOperationalize at scale\nBuilding a data pipeline POC or single node model development is relatively manageable. The challenge lies in how you successfully adopt and scale data and AI practices across the company. Let us help you meet this challenging goal with our prescriptive offerings and expertise.\nOfferingsDelivering rapid success on projects with world-class data engineering, data science and project management expertiseJumpstartAccelerate your project timelines by familiarizing yourself with the Databricks platform and key capabilities that follow best practices.Migration AssuranceApply proven, structured approaches and risk mitigation strategies to help ensure seamless migrations to the Databricks Lakehouse Platform.Lakehouse Build-outAccelerate implementing one simplified platform for data analytics, data science and ML \u2014 setting the foundation for your lakehouse vision.Machine LearningEnd to end machine learning from prototype to production.Center of ExcellenceBuild your Lakehouse Center of Excellence (CoE) with Databricks' proven methodology and framework.Custom ServicesContact us for a custom Statement of Work for your unique requirements.Our professional services experts have proven success in delivering full lifecycle projects to meet complex, very specific and targeted requirements.Resident solutions architects | data scientistsHighly experienced and technical resources with strong leadership and consulting skills. To ensure your success, we leverage our extensive partner ecosystem and co-deliver with them as required.Databricks and Spark experts5+ years of experience\nStrong big data background\nHands-on implementation skills\nProject planning and executionAssist with design and architecture\nHelp align project to platform capabilities\nProvide inputs to project timelines and resource needs\nImplementation and production planningArchitect solutions for scaleability\nAssist with prototype development\nAddress DevOps integration requirements\nAssist in implementing a COEDevelop common standards and frameworks\nBe available as a resource for multiple teams\nFacilitate interactions with other Databricks teams\nResourcesSuccess Credit Program OverviewRedemption Request FormWhy Databricks AcademyPeople are at the heart of customer success and with training and certification through Databricks Academy, you will learn to master data analytics from the team that started the Spark research project at UC Berkeley. Get better faster with Databricks Academy.Upscale your skills nowReady to get started?Contact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected]om and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=lakehouseplatform-promocard-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pamela-pettit\/#","text":"Pamela Pettit - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPamela PettitSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matteo-quattrocchi","text":"Matteo Quattrocchi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatteo QuattrocchiDirector, Policy-EMEA at BSABack to speakersMatteo is Director, Policy \u2014 EMEA at BSA | The Software Alliance in Brussels. In this role, he works with BSA members to develop and advance policy positions on a range of key issues, with a focus on artificial intelligence, copyright and government access to data. Prior to joining BSA, Matteo worked at the U.S. Mission to the EU in the Public Affairs Office, and in lobbying and law firms. Matteo holds an LL.M. from Georgetown University, and a Master\u2019s in European Law at LUISS (Italy).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-unified-analytics","text":"What is Unified Data Analytics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnified Data AnalyticsAll>Unified Data AnalyticsUnified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it easier for enterprises to build data pipelines across various siloed data storage systems and to prepare labeled datasets for model building, which allows organizations to do AI on their existing data and iteratively do AI on massive data sets.Unified Data Analytics also provides access to a broad set of AI algorithms that can be applied to these labeled datasets iteratively to fine-tune the models. Lastly, Unified Analytics solutions also provide collaboration capabilities for data scientists and data engineers to work effectively across the entire development-to-production lifecycle. The organizations that succeed in unifying their domain data at scale and unifying that data with the best AI technologies will be the ones that succeed with AI. Additional ResourcesUnified Cloud Data Analytics PlatformModern Cloud Data Platform for DummiesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/llm\/#","text":"Large Language Models (LLM) - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLarge Language Models (LLM)Register nowDeep dive into all things LLM - from in-person day long trainings, to community sessions focused on LLM tooling and Responsible use, to dedicated sessions on Databricks open-source model Dolly, LLMOps and more.\nSessionsBuilding and Deploying Large Language Models on Databricks | Paid TrainingLarge Language Models like ChatGPT and Dolly have taken the world by storm. Everybody from researchers and engineers to business leaders is rushing to understand how to utilize the latest developments in large language models (LLMs). This course is designed to teach individuals how to leverage LLMs for real-world use cases, including popular topics such as Transformers, BERT, and GPT. Through interactive lectures and exercises, you will learn how to develop, implement, evaluate, and deploy LLMs on Databricks. \nView this session in the catalog\nTesting Generative AI Models: What You Need to KnowGenerative AI shows incredible promise for enterprise applications. The explosion of generative AI can be attributed to the convergence of several factors. Most significant is that the barrier to entry has dropped for AI application developers through customizable prompts (few-shot learning), enabling laypeople to generate high-quality content. The flexibility of models like ChatGPT and DALLE-2 have sparked curiosity and creativity about new applications that they can support. The number of tools will continue to grow in a manner similar to how AWS fueled app development. But excitement must be tampered by concerns about new risks imposed to business and society. Increased capability and adoption also increase risk exposure. As organizations explore creative boundaries of generative models, measures to reduce risk must be put in place. However, the enormous size of the input space and inherent complexity make this task more challenging than traditional ML models.\nIn this session, we summarize the new risks introduced by the new class of generative foundation models through several examples, and compare how these risks relate to the risks of mainstream discriminative models. Steps can be taken to reduce the operational risk, bias and fairness issues, and privacy and security of systems that leverage LLM for automation. We\u2019ll explore model hallucinations, output evaluation, output bias, prompt injection, data leakage, stochasticity, and more. We\u2019ll discuss some of the larger issues common to LLMs and show how to test for them. A comprehensive, test-based approach to generative AI development will help instill model integrity by proactively mitigating failure and the associated business risk.\nYaron Singer, CEO & co-Founder, Robust Intelligence\nView this session in the catalog\nRapidly Scaling Applied AI\/ML with Foundational Models and Applying Them to Modern AI\/ML Use CasesToday many of us are familiar with foundational models such as LLM\/ChatGPTl. However, there are many more enterprise foundational models that can be rapidly deployed, trained and applied to enterprise use cases. This approach dramatically increases the performance of AI\/ML models in production, but also gives AI teams rapid roadmaps for efficiency and delivering value to the business. Databricks provides the ideal toolset to enable this approach. In this session, we will provide a logically overview of foundational models available today, demonstrate a real-world use case, and provide a business framework for data scientists and business leaders to collaborate to rapidly deploy these use cases.\nNick King, Founder & CEO, Data Kinetic\nView this session in the catalog\nHow You Can Audit A Language ModelLanguage models like ChatGPT are incredible research breakthroughs but require auditing & risk management before productization. These systems raise concerns related to toxicity, transparency & reproducibility, intellectual property licensing & ownership, dis- & misinformation, supply chains & significant carbon footprints. How can your org. leverage these new tools without taking on undue or unknown risks?\nRecent public reference work from In-Q-Tel Labs & BNH.AI details an audit of a named entity recognition (NER) application based on the pre-trained language model RoBERTa. If you have a language model use case in mind & want to understand your risks, this presentation will cover:\n\nStudying past incidents using the AI Incident Database and using this information to guide debugging.\nFinding & fixing common data quality issues.\nApplying general public tools & benchmarks as appropriate (e.g., checklist, SuperGLUE, HELM).\nBinarizing specific tasks & debugging them using traditional model assessment and bias testing.\nConstructing adversarial attacks based on a model's most significant risks and analyzing the results in terms of performance, sentiment & toxicity.\nTesting performance, sentiment & toxicity across different & less common languages.\nConducting random attacks: random sequences of attacks, prompts or other tests that may evoke unexpected responses.\nDon't forget about security: auditing code for backdoors & training data for poisoning, ensuring endpoints are protected with authentication & throttling and analyzing third-party dependencies.\nEngaging stakeholders to help find problems system designers & developers cannot see.\n\nIt's now time to figure out how to live with AI, and that means audits, risk management & regulation.\nPatrick Hall, Principal Scientist, BNH.AI\nView this session in the catalog\nExplainable Data Drift for NLPDetecting data drift, although far from solved for Tabular data, has become a common practice as a way to monitor ML models in production. For Natural Language Processing on the other hand the question remains mostly open. In this talk, we will present and compare two approaches. First, we will demonstrate how by extracting a wide range of explainable properties per document such as topics, language, sentiment, named entities, keywords and more we are able to explore potential sources of drift. We will show how these properties can be consistently tracked over time, how they can be used to detect meaningful Data Drift as soon as it occurs and how they can be used to explain and fix the root cause. The second approach we\u2019ll present is to detect drift by using the embeddings of common foundation models (such as OpenAI\u2019s GPT3 model family) and use them to identify areas in the embedding space in which significant drift has occurred. These areas in embedding space should then be characterized in a human-readable way to enable root cause analysis of the detected drift. We\u2019ll then compare the performance and explainability of these two methods, and explore the pros and cons of using each approach.\nNoam Bressler, ML Team Lead, Deepchecks\nView this session in the catalog\nBuilding AI-powered Products with Foundation ModelsFoundation models make for fantastic demos, but in practice, they can be challenging to put into production. These models work well over datasets that match common training distributions (e.g. generating web text or internet images), but may fail on domain-specific tasks or long-tail edge cases\u2014the settings that matter most to organizations building differentiated products! We propose a data-centric development approach that organizations can use to adapt foundation models to their own private\/proprietary datasets. We'll describe several techniques, including supervision \"warmstarts\" and interactive prompting (spoiler alert: no code needed!). To make these techniques come to life, we'll walk through real case studies describing how we've seen data-centric development drive AI-powered products, from \"AI assist\" use cases (e.g. copywriting assistants) to \"fully automated\" solutions (e.g. loan processing engines).\nVincent Chen, Director of Product \/ Founding Engineer, Snorkel AI\nView this session in the catalog\nColossal-AI: Scaling AI Models in Big Model EraThe proliferation of large models based on Transformer has outpaced advances in hardware, resulting in an urgent need for the ability to distribute enormous models across multiple GPUs. Despite this growing demand, best practices for choosing an optimal strategy are still lacking due to the breadth of knowledge required across HPC, DL, and distributed systems. These difficulties have stimulated both AI and HPC developers to explore the key questions:\u00a0\n\nHow can training and inference efficiency of large models be improved to reduce costs?\nHow can larger AI models be accommodated even with limited resources?\u00a0\nWhat can be done to enable more community members to easily access large models and large-scale applications?\u00a0\n\nIn this presentation, we investigated efforts to solve the questions mentioned above. Firstly, diverse parallelization is an important tool to improve the efficiency of large model training and inference. Heterogeneous memory management can help enhance the model accommodation capacity of processors like GPUs. Furthermore, user-friendly DL systems for large models significantly reduce the specialized background knowledge users need, allowing more community members to get started with larger models more efficiently. We will provide participants with a system-level open-source solution, Colossal-AI. More information can be found at https:\/\/github.com\/hpcaitech\/ColossalAI.\nJames Demmel, Dr. Richard Carl Dehmel Distinguished Professor, University of California, Berkeley; Yang You, Presidential Young Professor, National University of Singapore\nView this session in the catalog\nGenerative AI at scale using GAN and Stable DiffusionGenerative AI is under the spotlight and it has diverse applications but there are also many considerations when deploying a generative model at scale. This presentation will make a deep dive into multiple architectures and talk about optimization hacks for the sophisticated data pipelines that generative AI requires.\u00a0\nThe presentation will cover:\n\nHow to create and prepare a dataset for training at scale in single GPU and multi GPU environments\nHow to optimize your data pipeline for training and inference in production considering the complex deep learning models that need to be run.\nTradeoff between higher quality outputs versus training time and resources and processing times.\n\nPaula Martinez, CEO & Cofounder, Marvik; Rodrigo Beceiro, CTO & Cofounder, Marvik\nView this session in the catalog\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/cybersecurity-analytics-and-ai","text":"Cybersecurity analytics and AI | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for SplunkScale cybersecurity analytics with Splunk and DatabricksRapidly detect threats, investigate the impact and reduce risks with the Databricks add-on for SplunkModernize your data infrastructure and analytics capabilities to better protect from cyber threats. Learn how to scale advanced analytics, augment your SIEM (e.g., Splunk) and lower overall costs while maintaining your current processes and procedures.Download the Databricks add-on for SplunkBenefits and business valueReduce costsIngest all security data for a fraction of the cost of a SIEM logging tool\nImprove security posture with high-performance analyticsAnalyze terabytes of streaming and batch data with statistics, ML and AI. Enrich threat indicators and metadata on terabytes of streaming data.\nAccelerate detection and response timesCollaborate, share, iterate and automate the detection, investigation and threat-hunting lifecycles\nReference ArchitectureAdditional assetsAdd-onDatabricks Add-On for SplunkEventsDatabricks Government SymposiumEmpower Splunk and other SIEMs with the Databricks Lakehouse for CybersecurityeBookLakehouse for Financial ServicesDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks nomm\u00e9 leader | DatabricksMagic Quadrant\u2122 2022 Gartner\u00aeDatabricks nomm\u00e9 leaderSyst\u00e8mes de gestion de base de donn\u00e9es cloudDatabricks nomm\u00e9 leader dans le Magic Quadrant\u2122 Gartner\u00ae 2022 dans la cat\u00e9gorie CDBMS (Cloud Database Management System)Pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutive, Databricks a l'honneur d'\u00eatre nomm\u00e9 leader dans le Magic Quadrant 2022 du cabinet Gartner pour les syst\u00e8mes de gestion de base de donn\u00e9es cloud.Cette r\u00e9compense valide notre vision du lakehouse\u00a0: une plateforme unifi\u00e9e pour la gestion de donn\u00e9es, le data engineering, mais aussi l'analytique et l'IA.T\u00e9l\u00e9chargez le rapport pour d\u00e9couvrir pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader et obtenir des \u00e9clairages suppl\u00e9mentaires sur les avantages que pr\u00e9sente une plateforme lakehouse pour votre organisation.Consulter le rapport Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/br\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks no Google CloudA plataforma lakehouse aberta encontra a nuvem aberta para unificar data engineering, data science e an\u00e1lisesComece agoraDatabricks no Google Cloud \u00e9 um servi\u00e7o codesenvolvido que permite armazenar todos os seus dados em uma plataforma lakehouse simples e aberta que combina o melhor dos data warehouses e data lakes para unificar todas as suas an\u00e1lises e cargas de trabalho de IA. A forte integra\u00e7\u00e3o com Google Cloud Storage, BigQuery e Google Cloud AI Platform permite que a Databricks opere perfeitamente em dados e servi\u00e7os de IA no Google Cloud.\nData engineering confi\u00e1velSQL Analytics em todos os seus dadosData science colaborativaMachine learning de produ\u00e7\u00e3o\nPor que usar a Databricks no Google Cloud?AbertaDesenvolvido com base em padr\u00f5es abertos, APIs abertas e infraestrutura aberta para que voc\u00ea possa acessar, processar e analisar dados em seus termos.OtimizadoImplante a Databricks no Google Kubernetes Engine, o primeiro tempo de execu\u00e7\u00e3o da Databricks baseado em Kubernetes em qualquer nuvem, para obter insights mais rapidamente.IntegradoObtenha acesso \u00e0 Databricks com um clique a partir do Google Cloud Console, com seguran\u00e7a, cobran\u00e7a e gerenciamento integrados.Saiba mais desses clientes\n\"A Databricks no Google Cloud simplifica o processo de condu\u00e7\u00e3o de qualquer n\u00famero de casos de uso em uma plataforma de compute escal\u00e1vel, reduzindo os ciclos de planejamento necess\u00e1rios para entregar uma solu\u00e7\u00e3o para cada pergunta de neg\u00f3cio ou declara\u00e7\u00e3o de problema que usamos.\"\u2014 Harish Kumar, diretor global de ci\u00eancia de dados da ReckittIntegra\u00e7\u00e3o simplificada com o Google CloudGoogle Cloud StorageGoogle Cloud StoragePermita acesso de leitura\/grava\u00e7\u00e3o de dados no armazenamento em nuvem do Google (GCS) e aproveite o formato aberto do Delta Lake para adicionar poderosas capacidades de confiabilidade e desempenho na Databricks.Google Kubernetes EngineBigQueryBig Cloud IdentityPlataforma de IA do Google CloudCobran\u00e7a do Google CloudLookerEcossistema de parceirosRecursosEventos virtuaisWorkshop virtual: o Data Lake abertoNot\u00edciasDatabricks faz parceria com a Google Cloud para entregar sua plataforma \u00e0s empresas globaisBlogs e relat\u00f3riosAnunciando o lan\u00e7amento da Databricks no Google CloudApresentando a Databricks no Google Cloud \u2014 agora em vers\u00e3o pr\u00e9via p\u00fablicaFicha t\u00e9cnica da Databricks no Google CloudDatabricks no Google Cloud agora com disponibilidade geralData engineering, data science e an\u00e1lises com Databricks no Google CloudTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jay-bhankharia\/#","text":"Jay Bhankharia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJay BhankhariaSenior Director, Data Partnerships at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-apache-spark","text":"What is Apache Spark?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache SparkAll>Apache SparkTry Databricks for freeGet StartedWhat Is Apache Spark?Apache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.\u00a0Apache Spark started in 2009 as a research project at the University of California, Berkeley. Researchers were looking for a way to speed up processing jobs in Hadoop systems. It is based on Hadoop MapReduce and it extends the MapReduce model to efficiently use it for more types of computations, which includes interactive queries and stream processing.\u00a0Spark provides native bindings for the Java, Scala, Python, and R programming languages. In addition, it includes several libraries to support build applications for machine learning [MLlib], stream processing [Spark Streaming], and graph processing [GraphX]. Apache Spark consists of Spark Core and a set of libraries. Spark Core is the heart of Apache Spark and it is responsible for providing distributed task transmission, scheduling, and I\/O functionality. The Spark Core engine uses the concept of a Resilient Distributed Dataset (RDD) as its basic data type. The RDD is designed so it will hide most of the computational complexity from its users. Spark is intelligent on the way it operates on data; data and partitions are aggregated across a server cluster, where it can then be computed and either moved to a different data store or run through an analytic model. You will not be asked to specify the destination of the files or the computational resources that need to be used in order to store or retrieve files. What Are the Benefits of Apache Spark?SpeedSpark executes very fast by caching data in memory across multiple parallel operations. The main feature of Spark is its in-memory engine that increases the processing speed; making it up to 100 times faster than MapReduce when processed in-memory, and 10 times faster on disk, \u00a0when it comes to large scale data processing. Spark makes this possible by reducing the number of reading\/writing to disk operations.Real-time stream processingApache Spark can handle real-time streaming along with the integration of other frameworks. Spark ingests data in mini-batches and performs RDD transformations on those mini-batches of data.Supports Multiple WorkloadsApache Spark can run multiple workloads, including interactive queries, real-time analytics, machine learning, and graph processing. One application can combine multiple workloads seamlessly.Increased UsabilityThe ability to support several programming languages makes it dynamic. It allows you to quickly write applications in Java, Scala, Python, and R; giving you a variety of languages for building your applications.Advanced AnalyticsSpark supports SQL queries, machine learning, stream processing, and graph processing.Additional ResourcesAbout Apache SparkLearning Apache Spark 2nd Edition eBook8 Steps for a Developer to Learn Apache Spark with Delta Lake eBookBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/08\/03\/key-takeaways-for-financial-services-at-data-ai-summit-2022.html","text":"Key takeaways for Financial Services at Data + AI Summit 2022 - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorKey Takeaways for Financial Services at Data + AI Summit 2022Top 5 product announcements for the financial services industryby Anna Cuisia, Ricardo Portilla and Eon RetiefAugust 3, 2022 in IndustriesShare this postData + AI Summit, the largest gathering of the open source data and AI community, returned as a hybrid event at the Moscone Center from June 27-30. With incredible breakout sessions by global financial services institutions (FSIs) like Northwestern Mutual, Nasdaq, and HSBC to mainstage keynotes from Intuit and Coinbase and live interactive demos from Databricks solution architects and partners like Avanade, Deloitte, and Confluent, we heard about innovation with data and AI in ways previously unimagined in financial services.Financial Services ForumFor our financial services attendees, the most exciting part of Data + AI Summit was the Financial Services Forum - a two-hour event that brought together leaders from across global brands in banking, insurance, capital markets and fintech to share innovative data and AI use cases from their data journeys. With the theme of \"The Future of Financial Services Is Open With Data and AI at Its Core,\" Junta Nakai, Global Head of Financial Services and Sustainability Leader at Databricks, spoke of the need for FSIs to have a short and clear path to \"AI in action\" to preserve margins, find new revenue streams, and shorten development timelines, given today's prolonged inflationary environment. He also gave an overview of the Databricks Lakehouse for Financial Services, a single platform that brings together all data and analytics workloads to power transformative innovations in modern financial services institutions.In their opening keynote, TD Bank's Paul Wellman (Executive Product Owner, Data as a Service) and Upal Hossain (AVP, Data as a Service), shared their data transformation journey and accelerated transition to the cloud, migrating over 100 million files and ~8,000 ETL jobs at petabyte scale with Delta Lake and the Azure cloud.Later, Geping Chen, Head of Data Engineering from GEICO, talked about personalization and the use of Telematics IoT in auto insurance as the biggest upcoming trend in the financial services industry - among other exciting industry topics.Attendees also learned best practices for achieving business outcomes with data + AI regarding people, process, and technology from Jack Berkowitz, Chief Data Officer, ADP; Jeff Parkinson, VP, Core Data Engineering, Northwestern Mutual; Ken Priyadarshi, AI Leader, EY Global; Gary Jones, Chief Data Engineer and Mona Soni, Chief Technology Officer, S&P Global Sustainable1; Arup Nanda, Managing Director, CTO Enterprise Cloud Data Ecosystem, JP Morgan; Christopher Darringer, Lead Engineer and Shraddha Shah, Data Engineer at Point 72 Asset Management.Financial Services Breakout Sessions and DemosCheck out these financial services breakout sessions to hear from our customers about the business benefits, cost and productivity savings, and advanced analytics they're now able to realize with Databricks:Nasdaq: A Modern Approach to Big DataHSBC: Cutting the Edge in Fighting CybercrimeCapital One: Running a Data Management SystemHow Robinhood Built a Streaming LakehouseDeloitte: AI Fueled Forecasting, The Next Generation of Financial Planning5 Key Announcements That Will Transform the Financial Services Industry1. Integrated data governance with Databricks Unity Catalog (GA expected in coming weeks after DAIS).We announced the upcoming GA of Unity Catalog (UC), which allows customers to enable fine-grained access controls on data and meet their privacy requirements. Unity Catalog is the catalog and governance layer for Databricks Lakehouse and offers a range of capabilities, including:The best way to secure access to data in Databricks across all compute\/language typesThe best way to allow for secure data sharing, powered by Delta Sharing on DatabricksA single source of truth for data and access control across Databricks workspacesEasy to control with SQL based grants to give people\/groups\/principals access to dataAPI-driven to help with easy automation and workflow processesFor financial institutions, UC provides the ability to centralize catalog management at the account level (i.e., across multiple clouds). Unity Catalog also makes it easy to automate discovery and lineage - automated lineage is something even the biggest players in the cataloging space still struggle with.2. MLfLow 2.0 \u2013 Personalization gets a boost from model serving and MLflow Pipelines, making model development and deployment fast and scalable.MLflow Pipelines enable Data Scientists to create production-grade ML pipelines that combine modular ML code with software engineering best practices to make model development and deployment fast and scalable. These new features around model monitoring will be impactful for FSIs. It's common for many financial institutions to have a significant number of models, especially considering the global scale for retail and institutional businesses. It becomes impossible to do proper model drift monitoring without an automated framework.MLflow Pipelines will help improve model governance frameworks because FSIs can now apply CI\/CD practices around constructing and managing ML model infrastructure setup.3. Delta Lake will be fully open source.Delta Lake 2.0 lowers the barrier to entry for adopting a Lakehouse architecture. As organizations think about on-prem or Hadoop migrations to the Databricks Lakehouse, they can use a consistent foundation to make Lakehouse a simpler transition. Moving to the Lakehouse has never been easier and for workloads that are not yet on Databricks, organizations can show the total cost of ownership (TCO) savings. Other benefits include:With Delta Lake 2.0, users can now reap the benefits of better performance (3.5x better overall performance compared to other solutions) to save on computation costsDelta Lake 2.0 offers an unrivaled level of maturity and proven real-world performance (663% increase in contributor strength over the past 3 years)Delta Lake 2.0 will open source all APIs, including OPTIMIZE and ZORDER - FSIs are no longer forced to sacrifice performance and choose alternatives like Apache Iceberg and due to limited functionalityAnyone can now achieve a simplified architecture with Delta's all-encompassing framework - no need to leverage third-party services for features like data sharing4. Next generation streaming\u2013Project Lightspeed\u2013is a game-changer for Financial Services, leveraging fresh data for insight generation. This announcement was one of the major streaming announcements Databricks has made - although streaming has always been a large and successful part of our business for improving performance to achieve higher throughput, lower latency, and lower cost. The announcement includes improving ecosystem support for connectors, enhancing functionality for processing data with new operators and APIs, simplifying deployment, operations, monitoring and troubleshooting.For example, two major themes in Financial Services that are driving business today are personalization and regulatory reporting. The first category includes use cases from personalized insurance pricing to next-best-action. Regulatory reporting may include trade reporting or clearing and settlement. The key to unlocking the use cases above is the ability to stream data sources and process them in near real-time. Any FSI looking to make advances on these use cases will require these cutting-edge, native streaming capabilities.5. Databricks Marketplace helps data consumers turn data into insights quicker and supports data providers' growth as they distribute and monetize data assetsDatabricks Marketplace is an open marketplace for exchanging data assets such as datasets, notebooks, dashboards, and machine learning models. To accelerate insights, data consumers can discover, evaluate, and access more data products from third-party vendors than ever before.Financial Services institutions can accelerate projects to monetize data and build alternative streams of revenue (e.g. monetizing unique datasets and models) more seamlessly to a broad audience. The Databricks Marketplace will set the stage for FSIs to accelerate having data as an asset on the balance sheet.Beyond these featured announcements, there were other exciting announcements like Databricks Serverless Model Endpoints, Project Enzyme, Delta Sharing and Data Cleanrooms. We encourage you to check out the Day 1 and Day 2 keynotes to learn more about our product announcements.Try Databricks for freeGet StartedRelated postsBrickbuilder Solutions: Partner-developed industry solutions for the lakehouseMarch 17, 2022 by Michael Lumb in Company Blog\nToday, Databricks is excited to introduce Brickbuilder Solutions, data and AI solutions expertly designed by leading consulting companies to address industry-specific business requirements.*...\nDesign Patterns for Real-time Insights in Financial ServicesMay 20, 2022 by Ricardo Portilla in Engineering Blog\nPersonalization is a competitive differentiator for most every financial services institution (FSIs, for short), from banking to insurance and now investment management platforms...\nHyper-Personalization Accelerator for Banks and Fintechs Using Credit Card TransactionsMarch 3, 2022 by Antoine Amend in Engineering Blog\nJust as Netflix and Tesla disrupted the media and automotive industry, many fintech companies are transforming the Financial Services industry by winning the...\nSee all Industries postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/legal\/cookienotice","text":"Cookie Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesCookie NoticeWhen you use Databricks websites and applications (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d), we use standard automated data collection tools such as Cookies, Web Beacons, and other identifiers for the purposes described below.\u201cCookies\u201d are small text files that are placed on your hard drive by a web server when you access our Sites or Services. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pascal-van-bellen\/#","text":"Pascal van Bellen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPascal van BellenSenior Consultant at ORAYLIS GmbHBack to speakersPascal van Bellen has been working in BI & BigData for more than 7 years. \nHaving already worked in this area for several years, he is involved in building solutions with Azure Databricks.\nPascal is a Senior Consultant at Oraylis GmbH in Germany and is responsible for implementation of large scale modern data platforms in various Azure cloud scenarios.\nAs a certified Databricks champion he is particularly interested in the development of large scale BigData use cases using Databricks and Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks VenturesInvesting in the future of data, analytics and AI\nDatabricks Ventures invests in innovative companies that share our view of the future for data, analytics and AI. Our inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.Portfolio company benefitsExclusive insight into the product roadmap and support for building deep technical integrationsGuidance and best practices from the network of Databricks mentorsBroader reach by partnering with Databricks go-to-market programsLakehouse Fund investment\nfocusA shared vision to build the future of data, analytics and AI on the lakehouse architectureInvestments in early to growth-stage companies in partnership with a lead investorProjects and entrepreneurs that share Databricks\u2019 commitment to open source and building on open platforms, much like the Databricks LakehouseOur PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\nLearn moreArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\nLearn moredbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\nLearn moreHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.Learn moreThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.Learn moreThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.Learn moreLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.Learn moreMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.Learn morePerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.Learn moreRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.Learn moreTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.Learn moreFAQsWhy partner with Databricks Ventures?\nDepending on the size and stage of the investment, Databricks will provide unique access to product roadmap direction, technical integration support, and go-to-market support; access to Databricks mentors for guidance and best practices; and exposure in Databricks\u2019 global go-to-market programs, including our Data + AI Summit series.What are Databricks Ventures\u2019 investment criteria?\nWe are investing in innovative founders of private companies who share our view of the future for data and AI and are committed to extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.What stages does Databricks invest in?\nWe invest in early through growth-stage private companies within the data, analytics and AI ecosystem.Does Databricks Ventures lead investment rounds?\nNo, we do not lead rounds. Our strategy is to invest alongside a lead institutional investor.What is Databricks Ventures\u2019 typical investment size?\nDatabricks Ventures takes minority positions in rounds led by institutional VCs; typical check size varies based on stage of company and size of funding round.Does Databricks take board seats?No, Databricks does not plan to take board seats in portfolio companies.Build your startup on DatabricksDatabricks for Startups offers free credits, expert advice and go-to-market support.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jaison-dominic\/#","text":"Jaison Dominic - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJaison DominicSenior Manager Information Systems at AmgenBack to speakersJaison Dominic is a Transformational Data & Analytics leader passionate about driving value for patients and businesses through Data Engineering, Advanced Analytics, and Enterprise Data Fabric. He enjoys driving discussions on Data Strategy alignment with business objectives, leading teams, and building effective partnerships within and outside the organization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u3092\u6d3b\u7528\u3057\u305f\u30c7\u30fc\u30bf\u51e6\u7406\u306e\u5168\u5de5\u7a0b\u304c\u30b7\u30f3\u30d7\u30eb\u306bLabelbox\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3067AI\u3084\u30a2\u30ca\u30ea\u30c6\u30a3\u30af\u30b9\u306b\u5fc5\u8981\u306a\u975e\u69cb\u9020\u5316\u30c7\u30fc\u30bf\u3092\u7c21\u5358\u306b\u6e96\u5099\u3067\u304d\u308bProphecy\u30c9\u30e9\u30c3\u30b0\uff06\u30c9\u30ed\u30c3\u30d7\u306e\u8996\u899a\u7684\u306a\u64cd\u4f5c\u3067\u3001Spark\uff0fDelta \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u69cb\u7bc9\u3001\u30c7\u30d7\u30ed\u30a4\u30a2\u30eb\u30b7\u30aa\u30f3CDC\u30d9\u30fc\u30b9\u306e\u5206\u6563\u578b\u30ec\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u3001\u30c7\u30fc\u30bf\u30bd\u30fc\u30b9\u3092\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3064\u306a\u3050\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30d6\u30ed\u30b02023\u5e742\u6708 - \u30d1\u30fc\u30c8\u30ca\u30fc\u30b3\u30cd\u30af\u30c8\u3067\u65b0\u305f\u306a\u30d1\u30fc\u30c8\u30ca\u30fc\u3068\u306e\u9023\u643a\u3092\u767a\u88682022\u5e749\u6708 \u30d1\u30fc\u30c8\u30ca\u30fc\u30b3\u30cd\u30af\u30c8\u3067\u65b0\u305f\u306a\u30d1\u30fc\u30c8\u30ca\u30fc\u3068\u306e\u9023\u643a\u3092\u7d39\u4ecb2022\u5e746\u6708 \u30d1\u30fc\u30c8\u30ca\u30fc\u30b3\u30cd\u30af\u30c8\u3067\u65b0\u305f\u306a\u30d1\u30fc\u30c8\u30ca\u30fc\u9023\u643a\u3092\u767a\u8868\u30d1\u30fc\u30c8\u30ca\u30fc\u30b3\u30cd\u30af\u30c8\u3067Databricks\u3067\u30d3\u30b8\u30cd\u30b9\u3092\u69cb\u7bc9\u3057\u3088\u3046\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8Databricks Partner Connect \u30ac\u30a4\u30c9\u3054\u76f8\u8ac7\u3092\u304a\u5f85\u3061\u3057\u3066\u304a\u308a\u307e\u3059Databricks \u306e\u958b\u767a\u8005\u304a\u3088\u3073\u30d1\u30fc\u30c8\u30ca\u30fc\u5411\u3051\u306e\u30ea\u30bd\u30fc\u30b9\u3068\u3001\u30af\u30e9\u30a6\u30c9\u30d9\u30fc\u30b9\u306e\u30aa\u30fc\u30d7\u30f3\u306a\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3092\u6d3b\u7528\u3057\u3066\u3001\u5171\u306b\u30d3\u30b8\u30cd\u30b9\u3092\u767a\u5c55\u3055\u305b\u307e\u3057\u3087\u3046\uff01\u30d1\u30fc\u30c8\u30ca\u30fc\u306b\u306a\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/research","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rodrigo-beceiro\/#","text":"Rodrigo Beceiro - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRodrigo BeceiroCTO & Cofounder at MarvikBack to speakersRodrigo Beceiro is Marvik co-founder and CTO, a machine learning development startup that specializes in Computer Vision, Predictive Analytics and Natural Language Processing. Rodrigo is an Telecommunications Engineer, Scrum Master, graduated from Udacity\u2019s AI nanodegree and from a Master in technological business management. He has also completed the MIT Deep Tech Bootcamp.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anindita-mahapatra\/#","text":"Anindita Mahapatra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnindita MahapatraLead Solutions Architect at DatabricksBack to speakersAnindita joined Databricks in 2019 and is a lead solutions architect in financial services helping customers gleam value from their data initiatives. She co-created Security Analysis Tool (SAT), specializes in Big Data & Analytics with 20+ years of experience in designing scalable multi-tenant solutions. She teaches a Data Engineering course at the Harvard Extension & has written a book \u2018Simplifying Data Engineering and Analytics with Delta\u2019.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br#yourprivacychoices","text":"P\u00e1gina inicial da Databricks - DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWA melhor solu\u00e7\u00e3o de data warehouse \u00e9 o lakehouseCombine todos os seus dados, an\u00e1lises e IA em uma \u00fanica plataformaComece gratuitamenteSaiba maisReduza custos e acelere a inova\u00e7\u00e3o na Lakehouse PlatformSaiba maisUnificadaUma plataforma para seus dados, consistentemente governada e dispon\u00edvel para todas as suas an\u00e1lises e IAAbertaConstru\u00edda em padr\u00f5es abertos e integrada a todas as nuvens para funcionar perfeitamente em sua pilha de dados modernaEscal\u00e1velEscale de forma eficiente com cada carga de trabalho, de simples pipelines de dados at\u00e9 grandes LLMsOrganiza\u00e7\u00f5es orientadas a dados escolhem o Lakehouse\nVer todos os clientes\nO Lakehouse unifica suas equipes de dadosGerenciamento e engenharia de dadosSimplifique a ingest\u00e3o e o gerenciamento de dadosCom ETL automatizado e confi\u00e1vel, compartilhamento de dados aberto e seguro e desempenho extremamente r\u00e1pido, o Delta Lake transforma seu data lake no destino para todos os seus dados estruturados, semiestruturados e n\u00e3o estruturados.Saiba mais Assista \u00e0 demoData warehousingObtenha novos insights a partir dos dados mais completosCom acesso imediato aos dados mais recentes e abrangentes e o poder do Databricks SQL \u2014 que \u00e9 at\u00e9 12 vezes melhor em rela\u00e7\u00e3o ao pre\u00e7o\/desempenho do que data warehouses em nuvem tradicionais \u2014 analistas e cientistas de dados agora podem obter novos insights rapidamente.Saiba mais Assista \u00e0 demoData science e machine learningAcelerar o ML em todo o ciclo de vidaO lakehouse \u00e9 a base do Databricks Machine Learning \u2014 uma solu\u00e7\u00e3o nativa e colaborativa de dados para todo o ciclo de vida do aprendizado de m\u00e1quina, da prepara\u00e7\u00e3o \u00e0 produ\u00e7\u00e3o. Combinado com pipelines de dados de alta qualidade e desempenho, o lakehouse acelera o machine learning e a produtividade da equipe.Saiba mais Assista \u00e0 demoGovernan\u00e7a e compartilhamento de dadosUnifique a governan\u00e7a e compartilhamento para dados, an\u00e1lises e IACom a Databricks, voc\u00ea tem acesso a um modelo comum de seguran\u00e7a e governan\u00e7a para todos os seus dados, an\u00e1lises e ativos de IA no lakehouse, em qualquer da nuvem. Descubra e compartilhe dados entre plataformas, nuvens ou regi\u00f5es sem replica\u00e7\u00e3o ou v\u00ednculo com um fornecedor. Voc\u00ea pode at\u00e9 distribuir produtos de dados em um mercado aberto.Saiba mais Assista \u00e0 demoO data warehouse \u00e9 hist\u00f3ria. Descubra por que o lakehouse \u00e9 a arquitetura moderna para dados e IA.Descubra o lakehouseCat\u00e1logo de sess\u00f5es j\u00e1 dispon\u00edvelJunte-se a n\u00f3s em S\u00e3o Francisco para explorar o ecossistema do lakehouse e os avan\u00e7os em tecnologias de c\u00f3digo abertoExplorar sess\u00f5esVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivo.Obtenha o relat\u00f3rio600 CIOs. 14 setores. 18 pa\u00edses.Este novo estudo descobriu que a estrat\u00e9gia de dados \u00e9 fundamental para o sucesso da IA. Veja mais perspectivas do CIO.Obtenha o relat\u00f3rioO Livro Completo da Engenharia de DadosFique por dentro das tend\u00eancias mais recentes em engenharia de dados baixando sua c\u00f3pia do Livro Completo da Engenharia de Dados.Obter o e-BookTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/\/acceptable-use-policy","text":"Acceptable Use Policy \u2013 Paid (Including Trial) | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAcceptable Use Policy \u2013 Paid (Including Trial)For the paid (including trial) version of DatabricksThis Databricks acceptable use policy (\u201cAUP\u201d) sets forth certain restrictions relating to the access to, and use of, the Databricks Services by you or someone on your behalf under your agreement with Databricks applicable to the Databricks Services (\u201cAgreement\u201d). The restrictions set forth in this AUP are not exhaustive. Any capitalized terms used but not defined herein shall have the meaning set forth in the Agreement. This AUP may be updated by Databricks from time to time upon reasonable notice, which may be provided through the Databricks Services or by posting an updated version of this AUP. Updates of the AUP become binding, including on existing users, on the later of the date specified in the updated AUP or thirty (30) days after posting. Any modification to the AUP within an update will relate solely to restrictions on use of, and access to, the Databricks Services. Any violation of this AUP may result in the suspension or termination of your access to and use of the Databricks Services.You shall not (and shall not permit your Authorized Users to):attempt to access, search, or create accounts for any of our services by any means other than our publicly supported interfaces or as otherwise authorized by us;create multiple accounts for the purpose of extending your free trial;interfere with or disrupt (or attempt to interfere with or disrupt) the Databricks Services, or gain (or attempt to gain) access to any Systems that connect thereto (except as required to appropriately access and use the Databricks Services);use the Databricks Services to violate the security or integrity of, or otherwise abuse, any System of any party (including without limitation the Platform Services or Support Services), including but not limited to gaining unauthorized access to any System (including attempting to probe, scan, monitor, or test the vulnerability of a System), forging any headers or other parts of any message describing its origin or routing, interfering with the proper functioning of any System (including any deliberate attempt by any means to overload a System), implementing denial-of-service attacks, operating non-permissioned network services (including open proxies, mail relays or recursive domain name servers), using any means to bypass System usage limitations, or storing, transmitting or installing malicious code;use the Databricks Services to distribute or facilitate the sending of unsolicited or unlawful (i) email or other messages, or (ii) promotions of any kind;use the Databricks Services to engage in or promote any other fraudulent, deceptive or illegal activities;use the Databricks Services to process, store or transmit material, including any Customer Data, in violation of any Law or any third party rights, including without limitation privacy rights;provide a custom deployment name for your Workspace that might reasonably be considered inappropriate or that includes the trade name of any third party unless such party has provided you with express writing permission;disclose any benchmarking of the Databricks Services except as set forth in the\u00a0Service Specific Terms; oruse the Databricks Services in any circumstances where failure could lead to death, personal injury or environmental damage, and you further acknowledge that the Databricks Services are not designed or intended for such use.Databricks may modify custom deployment names if they are found to be in violation of this AUP.Inactive Monthly PAYG accounts:If an account for which Databricks is providing Monthly PAYG Services is found to be inactive, the account may be suspended or terminated by Databricks, and any Customer Content relating to such account that is stored within the Subscription Services or other Databricks Systems may be deleted. Databricks will provide at least 30 days\u2019 notice (in accordance with the Agreement) prior to permanently deleting your account, unless we deem it reasonably necessary to suspend or terminate your account without notice. For the avoidance of doubt, if we determine that the email associated with your account is invalid (e.g., because it bounces upon our notification of inactivity), we may terminate your account without further notice.An account may be considered inactive if:No Customer Authorized User has logged into the account for at least six months;No Customer Instructional Input was ever created within or input into the account and at least three months has passed since the account was established; orIf your account is set up to be paid by credit card, you (i) did not provide a valid credit card number or (ii) you failed to update an expired or invalid credit card number and at least three months has passed without a valid credit card number being on file, provided that for the avoidance of doubt this provision does not limit Databricks\u2019 right to terminate your account for non-payment relating to actual usage.\u00a0Last modified: October 1, 2021ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/raghu-jayachandran\/#","text":"Raghu Jayachandran - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRaghu JayachandranSenior Manager Enterprise Data at RaceTrac Inc.Back to speakersRaghu Jayachandran is a Senior Manager of Enterprise Data at RaceTrac Inc, a convenience store retailer. His responsibilities are data platform innovation, technology modernization, and strategizing RaceTrac data. He has been an IT professional for over 20 years and has executed data solutions for manufacturing, financial services, government agencies, and retail sectors. \nHe earned a bachelor\u2019s degree in physics, a master\u2019s degree in computer applications, and is pursuing an Executive MBA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/apache-spark-as-a-service","text":"What is Apache Spark as a Service?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache Spark as a ServiceAll>Apache Spark as a ServiceTry Databricks for freeGet StartedWhat is Apache Spark as a Service?Apache Spark is an open source cluster computing framework for fast real-time large-scale data processing.\u00a0Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently rated as the largest open source communities in big data and it features over 200 contributors from more than 50 organizations. Databricks hosts its optimized version of Apache Spark as Spark-as-a-Service in multiple clouds. It comes with a set of built-in applications that can help you access and analyze data faster.\u00a0It leverages Spark\u2019s numerous capabilities of operating on Big Data like its capability of working with streaming data, performing graph computation, offering SQL on Hadoop as well as its machine learning functionality. Even though most organizations have recognized the opportunities that Spark offers, many still struggling. Why? Because of the challenges organizations are facing when trying to analyze data streams or large amounts of data. \u00a0However, this does not mean that you can\u2019t take advantage of the benefits that Spark brings without the hardware investments and full-scale adoption and implementation. Spark as a Service eliminates the infrastructure challenges and speeds up the process by knocking out most of the costs and effort required. There are already several providers that offer Spark as a Service making this framework easy and fast to deploy. This solution works great for short-term data analytics projects that can be set up quickly with a high return on investment. Spark as a Service makes it easy to process and query data stored in Hive, HDFS, HBase and Amazon S3.\u00a0While Spark as a Service is probably the best choice if you have a temporary analytics project. It also proved to the preferred option for companies looking to see the upsides of using big data and analytics before making large investments in their own big data processing system.Main Advantages of Using Spark as a Service:An easy way to access Spark dataNo specialized coding skills required; as a result, it can be easily used by both technical and business userslower costsAdditional ResourcesAbout Apache SparkLearning Apache Spark 2nd Edition eBook8 Steps for a Developer to Learn Apache Spark with Delta Lake eBookIntroducing Apache Spark 3.0: Now available in Databricks Runtime 7.0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/basak-eskili","text":"Basak Eskili - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBasak EskiliML Engineer at Ahold DelhaizeBack to speakersBasak Eskili is a Machine Learning Engineer at Ahold Delhaize. She is working on creating new tools and infrastructure that enable data scientists to quickly operationalise algorithms. She is bridging the gap between data scientists and platform engineers while improving the way of working in accordance with MLOps principles, and ensuring that the models are reliable, scalable, and secure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/hls_workshop","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/leveraging-alternative-and-third-party-data-in-financial-services","text":"Leveraging Alternative and Third-Party Data in Financial Services | DatabricksLeveraging Alternative and Third-Party Data in Financial ServicesData has become the key competitive advantage for banks, insurers and asset managers. The ability to make sense of the data \u2014 both alternative and traditional data sources \u2014 is key for financial services institutions to create competitive advantage and make data-driven decisions.Download this ebook to gain best practices and actionable guidance on how to analyze and extract insights from diverse datasets, giving you the ability to make superior business decisions.This guide covers:The challenges of leveraging alternative data sources for analyticsThe importance of unifying data engineering, analytics, and data science to fuel innovationAn industry use case, featuring MScience, where alternative data and real-time actionable insights are used to improve investment decisionsDownload the eBook, Leveraging Alternative and Third-Party Data in Financial Services with Apache Spark and Databricks to learn more.Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-media-entertainment-use-cases","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pearl-ubaru","text":"Pearl Ubaru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPearl UbaruSr. Technical Marketing Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/p\/whitepaper\/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025","text":"CIO vision 2025: Bridging the gap between BI and AI \u2013 Databricks (CIO-Vision 2025: Die L\u00fccke zwischen BI und KI schlie\u00dfen \u2013 Databricks)BerichtCIO vision 2025 (CIO-Vision 2025)Bridging the gap between BI and AI (Die L\u00fccke zwischen BI und KI schlie\u00dfen)Weltweite Umfrage unter CIOs zur wertorientierten Einf\u00fchrung von KI im UnternehmenErfahren Sie, wie Top-Unternehmen und Organisationen ihre gr\u00f6\u00dften Datenherausforderungen bew\u00e4ltigen, um KI zu meistern. Im neuen Forschungsbericht von MIT Technology Review erhalten Sie Erkenntnisse von 600 CIOs in 18 L\u00e4ndern und 14 Branchen.Wie priorisieren CIOs die Einf\u00fchrung von KI? Wie investieren sie in Verbesserungen ihrer Datenstrategie?Erhalten Sie Antworten aus ausf\u00fchrlichen Interviews mit C-Level-F\u00fchrungskr\u00e4ften u.\u00a0a. von Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global und Marks & Spencer.Informieren Sie sich \u00fcber die wichtigsten Ergebnisse zu den Perspektiven von CIOs:72\u00a0% geben an, dass Daten die gr\u00f6\u00dfte Herausforderung f\u00fcr KI sind, und 68\u00a0% sagen, dass die Vereinheitlichung ihrer Datenplattform f\u00fcr Analytics und KI entscheidend ist.94\u00a0% geben an, KI bereits in Gesch\u00e4ftsbereichen einzusetzen, und mehr als die H\u00e4lfte geht davon aus, dass KI bis 2025 weit verbreitet sein wird72\u00a0% glauben, dass Multicloud von entscheidender Bedeutung ist, und viele unterst\u00fctzen offene Standards, um strategische Flexibilit\u00e4t zu erhaltenBericht abrufenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/product\/aws?itm_data=menu-item-awsProduct","text":"Databricks on AWS Data Platform - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks on AWSThe simple, unified data platform seamlessly integrated with AWS\n\u00a0Get startedSchedule a demoDatabricks on AWS allows you to store and manage all your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all your analytics and AI workloads.Reliable data engineeringSQL analytics on all your dataCollaborative data scienceProduction machine learningWhy Databricks on AWS?Simple\nDatabricks enables a single, unified data architecture on S3 for SQL analytics, data science and machine learning12x better price\/performance\nGet data warehouse performance at data lake economics through SQL-optimized compute clustersProven\nThousands of customers have implemented Databricks on AWS to provide a game-changing analytics platform that addresses all analytics and AI use casesDollar Shave Club: Personalizing customer experiences with Databricks\nDownload eBookHotels.com: Optimizing the customer experience with machine learning\nDownload case studyHP: From data prep to deep learning \u2014 how HP unifies analytics with Databricks\nWatch on-demand webinarFeatured integrationsAWS GravitonAWS GravitonDatabricks clusters support\u00a0AWS Graviton\u00a0instances. These instances use AWS-designed Graviton processors that are built on top of the Arm64 instruction set architecture. AWS claims that instance types with these processors have the best price\/performance ratio of any instance type on Amazon EC2.\u00a0Read moreAWS SecurityAmazon RedshiftAWS GlueEnterprise RolloutUse CasesPersonalized recommendation engines\nProcess all your data in real time to provide the most relevant product and service recommendations.Genomic sequencing\nModernize your technology stack to improve the experience for patients and physicians with the fastest DNASeq pipeline at scale.Fraud detection and\nprevention\nLeverage complete historical data together with real-time data streams to quickly identify anomalous and suspicious financial transactions.ResourcesWhitepapersMining Your Data Lake for Analytics InsightsUnifying Big Data and AI in the Financial Services IndustryThe Hidden Value of Hadoop MigrationWebinarsModernize Data and Analytics Platforms with Confidence with Databricks and AWSWhy Data-Focused Startups Are Building on the LakehouseHarness the Power of Real-Time Analytics for Rapid Decision-Making at QubyLoyaltyOne Simplifies and Scales Data Analytics Pipelines With Delta LakeUnlock the Potential Inside Your Data LakeBuilding a Data Lakehouse at DoorDash and GrammarlyIndustriesLeveraging AI\/ML to Extract Real-World Insights From Population-Scale Clinical Lab Data at PrognosHow Machine Learning Is Changing Data Analytics in GovernmentReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/session_na21\/drifting-away-testing-ml-models-in-production","text":"AboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLCDatabricks - YouTube"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matt-mckenzie\/#","text":"Matt McKenzie - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatt McKenzieGM, Technology at TabcorpBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/product\/pricing","text":"Databricks \u3054\u5229\u7528\u6599\u91d1 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 PT\n\u3055\u3088\u3046\u306a\u3089\u3001\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3002\u3053\u3093\u306b\u3061\u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3002\n\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u304c\u6700\u65b0\u306e\u30c7\u30fc\u30bf\u30b9\u30bf\u30c3\u30af\u306b\u3069\u306e\u3088\u3046\u306b\u9069\u5408\u3059\u308b\u304b\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u51fa\u5e2d\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\u4eca\u3059\u3050\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c5\u67089\u65e5 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\u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeacons2023\u5e746\u670826\u65e5\uff5e29\u65e5\n\n\u76f4\u63a5\u53c2\u52a0\u3059\u308b\u304b\u3001\u57fa\u8abf\u8b1b\u6f14\u306e\u30e9\u30a4\u30d6\u30b9\u30c8\u30ea\u30fc\u30e0\u306b\u53c2\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3054\u767b\u9332\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks 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NOW\u671f\u9593\u9650\u5b9aSQL\u4fa1\u683c\u30ad\u30e3\u30f3\u30da\u30fc\u30f3 - 40%\u4ee5\u4e0a\u5272\u5f15 Serverless SQL\u3068\u65b0\u3057\u3044 SQL Pro \u306e 15\u304b\u6708\u30d7\u30ed\u30e2\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u304f\u3060\u3055\u3044\u3002\u8a73\u3057\u304f\u898b\u308bDatabricks \u3054\u5229\u7528\u6599\u91d1\u30c7\u30fc\u30bf\u30fb\u5206\u6790\u30fbAI \u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u30b7\u30f3\u30d7\u30eb\u306a 1 \u3064\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u7d71\u5408 \u2015 \u4e3b\u8981\u306a\u30af\u30e9\u30a6\u30c9\u3092\u30b5\u30dd\u30fc\u30c8\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30ebDatabricks \u306e\u6599\u91d1\u8a2d\u5b9a\u5f93\u91cf\u8ab2\u91d1\u5236Databricks 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at $0.07 \/ DBU\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u306e\u5b9f\u884c\u3001\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u306e\u69cb\u7bc9\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u7ba1\u7406\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u30ef\u30fc\u30af\u30d5\u30ed\u30fc\u3068\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0 Delta Live TablesStarting at $0.20 \/ DBU\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306b\u6700\u9069\u306a DLT \u30a8\u30c7\u30a3\u30b7\u30e7\u30f3\u3067\u3001Python \u307e\u305f\u306f SQL \u3092\u4f7f\u7528\u3057\u305f\u9ad8\u54c1\u8cea\u306e\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u307e\u305f\u306f\u30d0\u30c3\u30c1 ETL \u30d1\u30a4\u30d7\u30e9\u30a4\u30f3\u3092\u7c21\u5358\u306b\u69cb\u7bc9\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9Databricks SQLStarting at $0.22 \/ DBUBI 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\u306b\u3064\u3044\u3066\u306f\u3001\u30af\u30e9\u30a6\u30c9\u30d7\u30ed\u30d0\u30a4\u30c0\u306e\u6599\u91d1\u304c\u9069\u0000\u0000\u7528\u3055\u308c\u307e\u3059\u3002\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u671f\u9593\u306e\u7d42\u4e86\u5f8c\u306f\u3069\u3046\u306a\u308a\u307e\u3059\u304b\uff1f\u7121\u6599\u304a\u8a66\u3057\u671f\u9593\u304c\u7d42\u4e86\u3059\u308b\u3068\u3001\u81ea\u52d5\u7684\u306b\u540c\u30d7\u30e9\u30f3\u306e\u6709\u6599\u30b5\u30d6\u30b9\u30af\u30ea\u30d7\u30b7\u30e7\u30f3\u306b\u79fb\u884c\u3057\u307e\u3059\u3002\u305f\u3060\u3057\u3001\u30b5\u30d6\u30b9\u30af\u30ea\u30d7\u30b7\u30e7\u30f3\u306f\u3044\u3064\u3067\u3082\u89e3\u7d04\u3067\u304d\u307e\u3059\u3002\u6599\u91d1\u0000\u0000\u306f\u4f7f\u7528\u91cf\u30fb\u30b9\u30c8\u30ec\u30fc\u30b8\u5bb9\u91cf\u306e\u3069\u3061\u3089\u3067\u8a08\u7b97\u3055\u308c\u307e\u3059\u304b\uff1fDatabricks \u306e\u6599\u91d1\u306f\u3001\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u4f7f\u7528\u91cf\u306b\u57fa\u3065\u3044\u3066\u3044\u307e\u3059\u3002\u30b9\u30c8\u30ec\u30fc\u30b8\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306a\u3069\u306e\u95a2\u9023\u30b3\u30b9\u30c8\u306f\u3001\u304a\u4f7f\u3044\u306b\u306a\u308b\u30b5\u30fc\u30d3\u30b9\u3084\u30af\u30e9\u30a6\u30c9\u30b5\u30fc\u30d3\u30b9\u30d7\u30ed\u30d0\u30a4\u30c0\u306b\u3088\u3063\u3066\u7570\u306a\u308a\u307e\u3059\u3002DBU \u3068\u306f\u4f55\u3092\u610f\u5473\u3057\u307e\u3059\u304b\uff1fDatabricks \u30e6\u30cb\u30c3\u30c8\uff08DBU\uff09\u3068\u306f\u3001Databricks \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u51e6\u7406\u80fd\u529b\u3092\u898f\u683c\u5316\u3057\u305f\u5358\u4f4d\u3067\u3042\u308a\u3001\u6e2c\u5b9a\u3068\u8ab2\u91d1\u306e\u76ee\u7684\u3067\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u304c\u6d88\u8cbb\u3059\u308b DBU \u306e\u6570\u306f\u3001\u4f7f\u7528\u3059\u308b\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u30ea\u30bd\u0000\u0000\u30fc\u30b9\u3084\u51e6\u7406\u3059\u308b\u30c7\u30fc\u30bf\u306e\u91cf\u306a\u3069\u306e\u51e6\u7406\u6307\u6a19\u306b\u3088\u3063\u3066\u6c7a\u307e\u308a\u307e\u3059\u3002 \u5730\u57df\u306b\u3088\u3063\u3066\u6599\u91d1\u304c\u7570\u306a\u308a\u307e\u3059\u304b\uff1fDatabricks \u306e\u6599\u91d1\u3084\u30b9\u30dd\u30c3\u30c8\u5272\u5f15\u306f\u3001\u304a\u4f7f\u3044\u306e\u5730\u57df\u3084\u30af\u30e9\u30a6\u30c9\u30b5\u30fc\u30d3\u30b9\u30d7\u30ed\u30d0\u30a4\u30c0\u306b\u3088\u3063\u3066\u7570\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002\u8a73\u3057\u304f\u306f\u3001\u5404\u88fd\u54c1\u306e Databricks \u306e\u6599\u91d1\u8a2d\u5b9a\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002Databricks \u306f\u3001\u4ed6\u306e\u30af\u30e9\u30a6\u30c9\u30b5\u30fc\u30d3\u30b9\u3084\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3068\u6bd4\u8f03\u3057\u3066\u3001\u9ad8\u4fa1\u683c\u3067\u3059\u304b\uff1fDatabricks \u306e\u88fd\u54c1\u306f\u3001\u304a\u5ba2\u69d8\u306e\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u306e TCO\uff08Total Cost of Ownership\uff09\u3092\u8003\u616e\u3057\u305f\u4fa1\u683c\u8a2d\u5b9a\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002Databricks \u306b\u3088\u308b\u30b3\u30b9\u30c8\u524a\u6e1b\u3092\u898b\u7a4d\u3082\u308b\u969b\u306b\u306f\u3001 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\u79d2\u3042\u305f\u308a\u306e\u4f7f\u7528\u91cf\u306b\u57fa\u3065\u3044\u3066\u8ab2\u91d1\u304c\u767a\u751f\u3057\u3001\u8acb\u6c42\u306f\u6708\u3054\u3068\u306e\u30af\u30ec\u30b8\u30c3\u30c8\u30ab\u30fc\u30c9\u6c7a\u6e08\u3068\u306a\u308a\u307e\u3059\u3002\u3053\u306e\u4ed6\u306b\u3001\u8acb\u6c42\u66f8\u30d9\u30fc\u30b9\u306e\u304a\u652f\u6255\u3044\u3084\u5e74\u9593\u30d7\u30e9\u30f3\u306a\u3069\u306e\u8acb\u6c42\u65b9\u6cd5\u3082\u3054\u7528\u610f\u3057\u3066\u304a\u308a\u307e\u3059\u3002\u8a73\u3057\u304f\u306f\u304a\u554f\u3044\u5408\u308f\u305b\u304f\u3060\u3055\u3044\u3002\u30c6\u30af\u30cb\u30ab\u30eb\u30b5\u30dd\u30fc\u30c8\u306f\u63d0\u4f9b\u3055\u308c\u307e\u3059\u304b\uff1f\u30c6\u30af\u30cb\u30ab\u30eb\u30b5\u30dd\u30fc\u30c8\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u307e\u305f\u3001\u6280\u8853\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306e\u53c2\u7167\u3092\u304a\u85a6\u3081\u3057\u3066\u3044\u307e\u3059\u3002 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/can-elfeoglu\/#","text":"Can Elfeoglu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCan ElfeogluStaff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pieter-noordhuis\/#","text":"Pieter Noordhuis - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPieter NoordhuisSr. Staff Software Engineer at DatabricksBack to speakersSoftware Engineer at Databricks working on developer toolingLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/avanade-risk-management","text":"Avanade Risk Management | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionRisk Management by AvanadeIndustry-specific solution developed by Avanade and powered by the Databricks Lakehouse Platform\u00a0Get startedRapidly deploy data into value-at-risk modelsFinancial institutions face greater regulatory and operational compliance complexity than ever before, requiring an agile and flexible approach to risk modeling.\u00a0Avanade\u2019s Risk Management\u00a0solution, built on Azure Databricks, enables financial institutions to rapidly deploy data into value-at-risk models to keep up with emerging risks and threats. By modernizing models, financial institutions are able to reduce compliance risks.Address risk governance through an agile and flexible approach to risk modelingLeverage modern compute to analyze years of historical data and continuously assess and monitor risk at enterprise scaleStreamline and accelerate model compliance and data transparencyGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/teja-tangeda\/#","text":"Teja Tangeda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTeja TangedaPrincipal Data Engineer at American AirlinesBack to speakersTeja Tangeda is a Principal Data Engineer at American Airlines. He has over a decade of experience as a Data Engineer. His love for aviation, travel, and data led him to American Airlines. Teja enjoys using his skills to solve complex data issues. He is inspired daily by his wife and two kids. In his free time, Teja likes to garden and take long walks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/accelerators","text":"Databricks Solution Accelerators \u2013 Schneller Daten- und KI-Wert bereitstellen \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWBranchenl\u00f6sungenDaten- und KI-gesteuerte Ergebnisse, die am wichtigsten sind, noch schneller liefernJetzt kostenlos testenDatabricks Solution AcceleratorsSparen Sie mit Databricks Solution Accelerators Stunden an Zeitaufwand beim Entdecken, Entwerfen, Entwickeln und Testen. Unsere speziell entwickelten Leitf\u00e4den \u2013 voll funktionsf\u00e4hige Notebooks und Best Practices \u2013 beschleunigen die Ergebnisse in Ihren h\u00e4ufigsten und wirkungsvollsten Anwendungsf\u00e4llen. Gelangen Sie in nur zwei Wochen von der Idee zum Machbarkeitsnachweis.\n\u00a0\nNutzen Sie Solution Accelerators mit Ihrer kostenlosen Databricks-Testversion oder Ihrem bestehenden Konto.\n\u00a0\nNoch heute Ihre kostenlose Testversion startenAccelerators durchsuchensearchHide filtersIndustrySortDatabricksToxizit\u00e4tserkennung in SpielenfeaturedDatabricksDirekte Verf\u00fcgbarkeitfeaturedDatabricksDetaillierte Nachfrageprognosenfeatured\ud83d\udd25DatabricksAutomatisches Entfernen von PatientendatenfeaturednewDatabricksAbsatzprognosen und Werbe-Attribution\ud83d\udd25DatabricksAbstraktion realer Daten f\u00fcr die OnkologieDatabricksAufl\u00f6sung der Kundenentit\u00e4tDatabricksBedrohungserkennung mit DNSDatabricksBestand f\u00fcr SicherheitDatabricksBeweise aus der realen WeltDatabricksBildanalyse in der digitalen PathologieDatabricksComputer Vision FoundationsDatabricksCustomer Lifetime Value\ud83d\udd25SplunkCyberanalyse (Splunk-Konnektor)DatabricksDigitale ZwillingeDatabricksEmpfehlungs-EngineDatabricksErkennung unerw\u00fcnschter ArzneimittelereignissenewDatabricksESG-Leistungs-Analytics\ud83d\udd25DatabricksF&E-Optimierung mit Knowledge GraphsnewDatabricksFHIR-Interoperabilit\u00e4t mit dbigniteDatabricksGeldw\u00e4schebek\u00e4mpfungDatabricksGenomweite AssoziationsstudienDatabricksGeodaten-Analytics zur BetrugserkennungDatabricksGesamteffektivit\u00e4t der Ausr\u00fcstungDatabricksH\u00e4ndlerklassifizierungDatabricksHL7v2-Interoperabilit\u00e4t mit SmolderDatabricksKohortenbildung mit Knowledge GraphsDatabricksKundensegmentierungDatabricksMedicare-RisikoanpassungDatabricksMeldewesenDatabricksModerne AnlageplattformDatabricksMulti-Touch-ZuordnungDatabricksNeigungsbewertungnewDatabricksOptimierte KommissionierungDatabricksOptimierung von Real-Time BiddingDatabricksPoint-of-Sale-Analytics in EchtzeitnewDatabricksPr\u00e4vention von Finanzbetrug in EchtzeitDatabricksPreistransparenznewDatabricksPrognose der AbonnentenabwanderungDatabricksReputationsrisikoDatabricksRisikomanagementDatabricksSkalierbare RoutengenerierungDatabricksSoziale Determinanten von GesundheitDatabricks\u00dcberlebensanalyse und Lifetime ValueDatabricksUnscharfe ArtikelzuordnungDatabricksVerwaltung der KundenbindungDatabricksVideo Quality of ExperienceDatabricksVorausschauende Wartung (IoT)FAQWie viel kosten Solution Accelerators?Solution Accelerators stehen jedem Databricks-Kunden kostenlos zur Verf\u00fcgung.Muss ich Databricks-Kunde sein, um einen Solution Accelerator nutzen zu k\u00f6nnen?Sie k\u00f6nnen Solution Accelerators mit einer kostenlosen Databricks-Testversion oder mit Ihrem bestehenden Databricks-Konto implementieren.Was kann ich von einem Solution Accelerator erwarten?Mit Solution Accelerators sparen Sie Stunden beim Entdecken, Entwerfen, Entwickeln und Testen. Unser Ziel ist es, Ihre Daten- und KI-Anwendungsf\u00e4lle zu beschleunigen, indem wir die richtigen Ressourcen (Notebooks, bew\u00e4hrte Muster und Best Practices) bereitstellen. Sie k\u00f6nnen davon ausgehen, dass Sie in nur zwei Wochen von der Idee zum Machbarkeitsnachweis gelangen.Sehen Sie, wie echte Kunden Databricks verwendenKundenberichte erkundenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=PricingPage-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions#by-industry","text":"Databricks Solution Accelerators - Databricks Use CasesSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for IndustryNo compromise data analytics and AI solutions purpose-built for your industryGet startedSchedule a demoDiscover the Lakehouse for your industryCommunications, Media & EntertainmentEarn more attention, capture more imaginationsLearn howFinancial ServicesBuild more trust, ensure peace of mindLearn howHealthcare and Life SciencesDiscover and deliver better careLearn howRetail and Consumer GoodsLead customers on their journey and champion your brandLearn howBrowse all industriessearchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listIndustry SolutionsFrom idea to proof of concept in as little as two weeksDatabricks Solution Accelerators are purpose-built guides \u2014 fully functional notebooks and best practices \u2014 that speed up results. Databricks customers are saving hours of discovery, design, development and testing, with many going from idea to proof of concept (PoC) in as little as two weeks.Explore AcceleratorsReady to start?Explore what Databricks can do for you by starting of with a free trial.Start your trialProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/built-on-partner-program","text":"Built on Databricks \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWBuilt on Databricks \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Databricks\uc640 \ube44\uc988\ub2c8\uc2a4 \uad6c\ucd95, \ub9c8\ucf00\ud305 \ubc0f \uc131\uc7a5\uc9c0\uae08 \uc2e0\uccad\ud558\uae30Built on Databricks \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\uc5d0\uc11c\ub294 \ucd5c\uc2e0 SaaS \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc758 \uac1c\ubc1c\uc744 \uac00\uc18d\ud654\ud558\uace0 \ube44\uc988\ub2c8\uc2a4\ub97c \uc131\uc7a5\uc2dc\ud0ac \uc218 \uc788\ub294 \uae30\uc220 \ubc0f GTM(go-to-market) \ub9ac\uc18c\uc2a4\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uae30\ubc18\uc73c\ub85c \uad6c\ucd95\ud558\uba74 \ube44\uc6a9 \ud6a8\uc728\uc801\uc778 \ud1b5\ud569 \uacbd\ud5d8\uc744 \uc81c\uacf5\ud558\uc5ec \ub370\uc774\ud130 \uc560\ud50c\ub9ac\ucf00\uc774\uc158, \uc81c\ud488 \ubc0f \uc11c\ube44\uc2a4\ub97c \uac1c\ubc1c\ud558\uace0 \uac1c\ubc29\ud615\uc758 \uae00\ub85c\ubc8c \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc5d0\uc11c \uaddc\ubaa8\uc5d0 \ub9de\uac8c \ub370\uc774\ud130\ub97c \uc6d0\ud65c\ud558\uac8c \uacf5\uc720\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.Built on Databricks\ub97c \ud1b5\ud574 \uaddc\ubaa8\uc5d0 \ub9de\uac8c \ube44\uc988\ub2c8\uc2a4 \uac00\uce58\ub97c \uc2e4\ud604\ud558\uace0 \uc788\ub294 \ud30c\ud2b8\ub108\ube14\ub85c\uadf8\uc9c0\uae08 \uc77d\uae30\uc6e8\ube44\ub098\uc9c0\uae08 \ubcf4\uae30\ube14\ub85c\uadf8\uc9c0\uae08 \uc77d\uae30Built on Databricks \ud30c\ud2b8\ub108 \ud61c\ud0ddDatabricks \uc804\ubb38\uac00\uc640 \uc0c1\ub2f4\nDatabricks \uc81c\ud488, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubc0f \uc9c0\uc6d0\ud300\uc5d0 \ubb38\uc758\ucd5c\uc2e0 \ud50c\ub7ab\ud3fc \uad6c\ucd95\n\uc2dc\uc7a5\uc744 \uc120\ub3c4\ud558\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \ud1b5\ud569\ub41c \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\uc5d0 \ud65c\uc6a9\ub354 \ub9ce\uc740 \uace0\uac1d\uc5d0\uac8c \ub3c4\ub2ec\n\ub2e8 \ud558\ub098\uc758 \uc548\uc804\ud55c \uac1c\ubc29\ud615 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130 \uc18c\ube44\uc790\ub85c \ub3c4\ub2ec \ubc94\uc704 \ud655\uc7a5\ub9c8\ucf00\ud305 \uc9c0\uc6d0\n\ub9c8\ucf00\ud305 \ud22c\uc790\ub97c \ud1b5\ud55c \ub9e4\ucd9c \uc99d\ub300\uc640 \ub3c4\ub2ec \ubc94\uc704 \ud655\ub300\uacf5\ub3d9 \uc601\uc5c5\nDatabricks \uc601\uc5c5\ud300\uacfc\uc758 \ud611\uc5c5 \ubc0f \uc9c0\uc6d0\uc744 \ud1b5\ud574 \ub354 \ub9ce\uc740 \uae30\ud68c \uac1c\ubc1c\uc9c0\uae08 \uc2dc\uc791\ud574 \ubcf4\uc138\uc694!\uc9c0\uae08 \uc2e0\uccad\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/llm","text":"Large Language Models (LLM) - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLarge Language Models (LLM)Register nowDeep dive into all things LLM - from in-person day long trainings, to community sessions focused on LLM tooling and Responsible use, to dedicated sessions on Databricks open-source model Dolly, LLMOps and more.\nSessionsBuilding and Deploying Large Language Models on Databricks | Paid TrainingLarge Language Models like ChatGPT and Dolly have taken the world by storm. Everybody from researchers and engineers to business leaders is rushing to understand how to utilize the latest developments in large language models (LLMs). This course is designed to teach individuals how to leverage LLMs for real-world use cases, including popular topics such as Transformers, BERT, and GPT. Through interactive lectures and exercises, you will learn how to develop, implement, evaluate, and deploy LLMs on Databricks. \nView this session in the catalog\nTesting Generative AI Models: What You Need to KnowGenerative AI shows incredible promise for enterprise applications. The explosion of generative AI can be attributed to the convergence of several factors. Most significant is that the barrier to entry has dropped for AI application developers through customizable prompts (few-shot learning), enabling laypeople to generate high-quality content. The flexibility of models like ChatGPT and DALLE-2 have sparked curiosity and creativity about new applications that they can support. The number of tools will continue to grow in a manner similar to how AWS fueled app development. But excitement must be tampered by concerns about new risks imposed to business and society. Increased capability and adoption also increase risk exposure. As organizations explore creative boundaries of generative models, measures to reduce risk must be put in place. However, the enormous size of the input space and inherent complexity make this task more challenging than traditional ML models.\nIn this session, we summarize the new risks introduced by the new class of generative foundation models through several examples, and compare how these risks relate to the risks of mainstream discriminative models. Steps can be taken to reduce the operational risk, bias and fairness issues, and privacy and security of systems that leverage LLM for automation. We\u2019ll explore model hallucinations, output evaluation, output bias, prompt injection, data leakage, stochasticity, and more. We\u2019ll discuss some of the larger issues common to LLMs and show how to test for them. A comprehensive, test-based approach to generative AI development will help instill model integrity by proactively mitigating failure and the associated business risk.\nYaron Singer, CEO & co-Founder, Robust Intelligence\nView this session in the catalog\nRapidly Scaling Applied AI\/ML with Foundational Models and Applying Them to Modern AI\/ML Use CasesToday many of us are familiar with foundational models such as LLM\/ChatGPTl. However, there are many more enterprise foundational models that can be rapidly deployed, trained and applied to enterprise use cases. This approach dramatically increases the performance of AI\/ML models in production, but also gives AI teams rapid roadmaps for efficiency and delivering value to the business. Databricks provides the ideal toolset to enable this approach. In this session, we will provide a logically overview of foundational models available today, demonstrate a real-world use case, and provide a business framework for data scientists and business leaders to collaborate to rapidly deploy these use cases.\nNick King, Founder & CEO, Data Kinetic\nView this session in the catalog\nHow You Can Audit A Language ModelLanguage models like ChatGPT are incredible research breakthroughs but require auditing & risk management before productization. These systems raise concerns related to toxicity, transparency & reproducibility, intellectual property licensing & ownership, dis- & misinformation, supply chains & significant carbon footprints. How can your org. leverage these new tools without taking on undue or unknown risks?\nRecent public reference work from In-Q-Tel Labs & BNH.AI details an audit of a named entity recognition (NER) application based on the pre-trained language model RoBERTa. If you have a language model use case in mind & want to understand your risks, this presentation will cover:\n\nStudying past incidents using the AI Incident Database and using this information to guide debugging.\nFinding & fixing common data quality issues.\nApplying general public tools & benchmarks as appropriate (e.g., checklist, SuperGLUE, HELM).\nBinarizing specific tasks & debugging them using traditional model assessment and bias testing.\nConstructing adversarial attacks based on a model's most significant risks and analyzing the results in terms of performance, sentiment & toxicity.\nTesting performance, sentiment & toxicity across different & less common languages.\nConducting random attacks: random sequences of attacks, prompts or other tests that may evoke unexpected responses.\nDon't forget about security: auditing code for backdoors & training data for poisoning, ensuring endpoints are protected with authentication & throttling and analyzing third-party dependencies.\nEngaging stakeholders to help find problems system designers & developers cannot see.\n\nIt's now time to figure out how to live with AI, and that means audits, risk management & regulation.\nPatrick Hall, Principal Scientist, BNH.AI\nView this session in the catalog\nExplainable Data Drift for NLPDetecting data drift, although far from solved for Tabular data, has become a common practice as a way to monitor ML models in production. For Natural Language Processing on the other hand the question remains mostly open. In this talk, we will present and compare two approaches. First, we will demonstrate how by extracting a wide range of explainable properties per document such as topics, language, sentiment, named entities, keywords and more we are able to explore potential sources of drift. We will show how these properties can be consistently tracked over time, how they can be used to detect meaningful Data Drift as soon as it occurs and how they can be used to explain and fix the root cause. The second approach we\u2019ll present is to detect drift by using the embeddings of common foundation models (such as OpenAI\u2019s GPT3 model family) and use them to identify areas in the embedding space in which significant drift has occurred. These areas in embedding space should then be characterized in a human-readable way to enable root cause analysis of the detected drift. We\u2019ll then compare the performance and explainability of these two methods, and explore the pros and cons of using each approach.\nNoam Bressler, ML Team Lead, Deepchecks\nView this session in the catalog\nBuilding AI-powered Products with Foundation ModelsFoundation models make for fantastic demos, but in practice, they can be challenging to put into production. These models work well over datasets that match common training distributions (e.g. generating web text or internet images), but may fail on domain-specific tasks or long-tail edge cases\u2014the settings that matter most to organizations building differentiated products! We propose a data-centric development approach that organizations can use to adapt foundation models to their own private\/proprietary datasets. We'll describe several techniques, including supervision \"warmstarts\" and interactive prompting (spoiler alert: no code needed!). To make these techniques come to life, we'll walk through real case studies describing how we've seen data-centric development drive AI-powered products, from \"AI assist\" use cases (e.g. copywriting assistants) to \"fully automated\" solutions (e.g. loan processing engines).\nVincent Chen, Director of Product \/ Founding Engineer, Snorkel AI\nView this session in the catalog\nColossal-AI: Scaling AI Models in Big Model EraThe proliferation of large models based on Transformer has outpaced advances in hardware, resulting in an urgent need for the ability to distribute enormous models across multiple GPUs. Despite this growing demand, best practices for choosing an optimal strategy are still lacking due to the breadth of knowledge required across HPC, DL, and distributed systems. These difficulties have stimulated both AI and HPC developers to explore the key questions:\u00a0\n\nHow can training and inference efficiency of large models be improved to reduce costs?\nHow can larger AI models be accommodated even with limited resources?\u00a0\nWhat can be done to enable more community members to easily access large models and large-scale applications?\u00a0\n\nIn this presentation, we investigated efforts to solve the questions mentioned above. Firstly, diverse parallelization is an important tool to improve the efficiency of large model training and inference. Heterogeneous memory management can help enhance the model accommodation capacity of processors like GPUs. Furthermore, user-friendly DL systems for large models significantly reduce the specialized background knowledge users need, allowing more community members to get started with larger models more efficiently. We will provide participants with a system-level open-source solution, Colossal-AI. More information can be found at https:\/\/github.com\/hpcaitech\/ColossalAI.\nJames Demmel, Dr. Richard Carl Dehmel Distinguished Professor, University of California, Berkeley; Yang You, Presidential Young Professor, National University of Singapore\nView this session in the catalog\nGenerative AI at scale using GAN and Stable DiffusionGenerative AI is under the spotlight and it has diverse applications but there are also many considerations when deploying a generative model at scale. This presentation will make a deep dive into multiple architectures and talk about optimization hacks for the sophisticated data pipelines that generative AI requires.\u00a0\nThe presentation will cover:\n\nHow to create and prepare a dataset for training at scale in single GPU and multi GPU environments\nHow to optimize your data pipeline for training and inference in production considering the complex deep learning models that need to be run.\nTradeoff between higher quality outputs versus training time and resources and processing times.\n\nPaula Martinez, CEO & Cofounder, Marvik; Rodrigo Beceiro, CTO & Cofounder, Marvik\nView this session in the catalog\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/about-us","text":"Chi \u00e8 Databricks, fondata dai creatori originali di Apache Spark\u2122Skip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks \u00e8 l'azienda del lakehouseNata nel mondo accademico e nella comunit\u00e0 open-source, Databricks \u00e8 stata fondata nel 2013 dai creatori originali di Apache Spark\u2122, Delta Lake e MLflow. Prima e unica piattaforma lakehouse in cloud al mondo, Databricks unisce il meglio dei data warehouse e dei data lake per offrire una piattaforma aperta e unificata per dati e AI.\n\u00a0Esplora la Lakehouse PlatformAttualmente, oltre 7.000 organizzazioni in tutto il mondo (fra cui ABN AMRO, Cond\u00e9 Nast, Regeneron e Shell) si affidano a Databricks per gestire attivit\u00e0 su larga scala di data engineering, data science collaborativa, machine learning e analisi lungo tutto il ciclo di vita.\nCon quartier generale a San Francisco, sedi in tutto il mondo e centinaia di partner globali fra cui Microsoft, Amazon, Tableau, Informatica, Cap Gemini e Booz Allen Hamilton, Databricks persegue la missione di semplificare e democratizzare i dati e l'intelligenza artificiale, aiutando i team di gestione dei dati a risolvere i problemi pi\u00f9 complessi.Leggi le storie dei clientiConosci i nostri partnerI nostri clientiVedi tutti i clienti\nI nostri leaderGruppo dirigenteConosci i nostri dirigentiFondatoriConosci i nostri fondatoriConsiglio direttivoConosci i nostri consiglieriI nostri investitoriProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joseph-sarsfield\/#","text":"Joseph Sarsfield - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoseph SarsfieldMachine Learning Engineer at Marks & SpencerBack to speakersJoseph started working for M&S in June 2021 as Senior Machine Learning Engineer. He is interested in building production-ready models at scale that utilize his ML and programming background. Previously he has designed and deployed data quality models for a National Healthcare Service program and worked on human-pose estimation algorithms using depth sensors. He has a Ph.D. in machine learning and enjoys hiking in his spare time.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=seattle%2C%20washington","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hannes-muhleisen\/#","text":"Hannes M\u00fchleisen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHannes M\u00fchleisenCo-Founder and CEO at DuckDB LabsBack to speakersProfessor Dr. Hannes M\u00fchleisen is a creator of the DuckDB database management system and the co-founder and CEO of DuckDB Labs, a consulting company providing services for DuckDB. He is also a senior researcher of the Database Architectures group at the Centrum Wiskunde & Informatica (CWI) in Amsterdam and a Professor of Data Engineering at Radboud University. Hannes\u2019 main interest is analytical data management systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nicholas-woodbrige\/#","text":"Nicholas Woodbrige - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, Technology at GlaxoSmithKlineBack to speakersTechnical Leader on Strategic Solutions \u2014 Data & Analytics, Cloud, AI\/ML \nI have spearheaded complex, large-scale, and business-critical technical programs at Amazon, Adobe, and now GlaxoSmithKline, bringing a combination of technology knowledge, business insight, and team leadership to deliver solutions and results. \nI partner with executive leaders and stakeholders to understand business needs and collaborate closely with engineering, product, and other functional leaders, as well as external vendors, to strategize and execute, achieving outcomes that move the business forward.\nThe consistent success of these programs depends on the caliber of the team, and I am passionate about managing, coaching, and mentoring talent to perform at the highest levels, even in rapidly changing and ambiguous situations. \nSelect skills include: Strategic Planning & Execution, Complex Program & Project Management, Product Development, Executive\/Stakeholder Engagement, Business Analysis\/Requirements Gathering, Vendor Management, Relationship Building, Change Management, Team LeadershipLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alexander-booth\/#","text":"Alexander Booth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlexander BoothAssistant Director of Research & Development at Texas Rangers Baseball Club, LLCBack to speakersAlexander is a data scientist, data engineer, and application developer with extensive experience in using machine learning and artificial intelligence techniques, based on insights from big data, to communicate actionable decisions to management to help generate a competitive advantage. He specializes in Sports Analytics with a particular passion for learning how innovation and new technology can shape the game of baseball.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks \u2013 Regroupez toutes vos charges de travail d'analytique et d'IA | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWAzure DatabricksLe service de donn\u00e9es et d'IA de Databricks disponible via Microsoft Azure pour stocker toutes vos donn\u00e9es sur un lakehouse ouvert et simple et regrouper toutes vos charges de travail d'analytique et d'IA.D\u00e9marrerPlanifier une d\u00e9moAzure Databricks est optimis\u00e9 pour Azure et \u00e9troitement int\u00e9gr\u00e9 \u00e0 Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI et d'autres services Azure afin de stocker toutes vos donn\u00e9es sur un lakehouse simple et ouvert, tout en regroupant l'ensemble de vos charges de travail d'analytique et d'IA.Simple\nUnifiez vos donn\u00e9es, l'analytique et l'IA\nsur une plateforme commune couvrant tous vos cas d'usage de donn\u00e9esOuvert\nUnifiez votre \u00e9cosyst\u00e8me de donn\u00e9es\ngr\u00e2ce \u00e0 l'open source, aux standards et aux formatsCollaborative\nUnifiez vos \u00e9quipes data\npour qu'elles collaborent sur l'ensemble des workflows de donn\u00e9es et d'IAPourquoi choisir Azure Databricks\u00a0?Des charges de travail Apache Spark\u2122 50 fois plus performantes\nD\u00e9ployez des clusters de calcul dont la mise \u00e0 l'\u00e9chelle est automatique avec Spark hautement optimis\u00e9 et qui fonctionnent jusqu'\u00e0 50 fois plus rapidement.En savoir plusDes millions d'heures serveur chaque jour\nAzure Databricks est utilis\u00e9 par des milliers de clients qui ex\u00e9cutent chaque jour des millions d'heures serveur dans plus de 34\u00a0r\u00e9gions Azure.En savoir plusSimplicit\u00e9 d'utilisation\nCommencez avec un seul clic dans le portail Azure, int\u00e9grez en mode natif les data services et services de s\u00e9curit\u00e9 Azure, et augmentez votre productivit\u00e9 de 25 % gr\u00e2ce \u00e0 la data science et au data engineering collaboratifs.En savoir plusCas d'usage du secteurServices financiersSwiss ReA unifi\u00e9 l'analytique de donn\u00e9es pour le data engineering, la data science et les analystes.HSBC\nA cr\u00e9\u00e9 une plateforme de paiement num\u00e9rique \u00e0 l'aide d'Azure Databricks.ABN AMROA am\u00e9lior\u00e9 ses workflows d'analytique en facilitant la collaboration et la production d'insights d'IA, gr\u00e2ce \u00e0 des fonctionnalit\u00e9s de machine learning avanc\u00e9es et automatis\u00e9es.En savoir plusVente au d\u00e9tailSant\u00e9 et sciences du vivantAssistez \u00e0 un \u00e9v\u00e9nement Azure DatabricksDatabricks, Microsoft et nos partenaires ont le plaisir d'organiser ces \u00e9v\u00e9nements d\u00e9di\u00e9s \u00e0 Azure Databricks. N'h\u00e9sitez pas \u00e0 nous rendre visite lors d'un \u00e9v\u00e9nement pr\u00e8s de chez vous pour en savoir plus sur le service de donn\u00e9es et d'IA \u00e0 la croissance la plus rapide sur Azure\u00a0! L'ordre du jour et le format vont varier d'une fois \u00e0 l'autre. Veuillez donc consulter la page de l'\u00e9v\u00e9nement sp\u00e9cifique pour plus de d\u00e9tails.\u00a0En savoir plusOptimis\u00e9 pour AzureUne int\u00e9gration transparente aux data stores et services de donn\u00e9es Azure gr\u00e2ce \u00e0 des connecteurs sp\u00e9cialis\u00e9s pour un acc\u00e8s rapide aux donn\u00e9es et une gestion simplifi\u00e9e au sein de votre environnement. Facilite la configuration des contr\u00f4les de s\u00e9curit\u00e9, la gestion des environnements et le traitement de toutes vos donn\u00e9es Azure.En savoir plusInt\u00e9grations pharesAzure Active DirectoryL'Authentification unique avec Azure Active Directory est la meilleure fa\u00e7on de se connecter \u00e0 Azure Databricks. Azure Databricks prend \u00e9galement en charge le provisionnement automatis\u00e9 des utilisateurs avec Azure\u00a0AD pour cr\u00e9er de nouveaux utilisateurs, leur offrir le bon niveau d'acc\u00e8s et d\u00e9sactiver les acc\u00e8s des utilisateurs supprim\u00e9s.Azure Data Lake StoreAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultRessourcesLIVRES BLANCSAzure Databricks pour le data engineeringAzure Databricks\u00a0: la meilleure plateforme pour le ML et l'IATrois cas pratiques sur Azure DatabricksD\u00e9marrer avec Apache Spark sur Azure DatabricksVID\u00c9OSAli Ghodsi et Rohan Kumar (CVP, Microsoft) en toute intimit\u00e9 au Keynote Data + AI Summit NA 2021D\u00e9mo Int\u00e9gration cloud d'Azure DatabricksIng\u00e9rez des donn\u00e9es dans Delta Lake sur Azure DatabricksExplorez vos donn\u00e9es \u00e0 l'aide de Databricks SQLEbooksMagic Quadrant Gartner 2021 pour les plateformes de data science et de machine learningIntroduction \u00e0 la plateforme de donn\u00e9es cloud moderneHuit \u00e9tapes pour que les d\u00e9veloppeurs apprennent \u00e0 utiliser Apache Spark\u2122 avec Delta LakeTout savoir sur Apache Spark\u2122\u00a0: prendre un bon d\u00e9part avec l'architecture centrale et les concepts de basePr\u00eat \u00e0 vous lancer\u00a0?D\u00e9marrerPlanifier une d\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andrew-blance\/#","text":"Andrew Blance - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndrew BlanceInnovation Consultant at WaterstonsBack to speakersAndrew is an innovation consultant at Waterstons, an IT consultancy. His role involves working with clients and research partners to carry out projects with emerging technologies. He co-hosts a podcast called Brains on the Outside, where he pitches ridiculous business ideas. Once, Durham University deemed him sensible enough to make him a Doctor of particle physics. He can run 5km pretty fast and thinks modern Star Trek isn't as bad as people make it out to be.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/larry-feinsmith\/#","text":"Larry Feinsmith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLarry FeinsmithHead of Global Tech Strategy, Innovation and Partnerships at JP Morgan Chase & Co.Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u0000\u0000\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/de\/company\/leadership-team","text":"F\u00fchrungsteam | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWF\u00fchrungUnser F\u00fchrungsteam verfolgt eine langfristige Vision und nutzt dabei unsere jahrzehntelange Erfahrung, um einen neuen Kurs f\u00fcr Daten und KI zu entwickeln.Unser TeamLeitungsteamGr\u00fcnderVorstandAli GhodsiMitbegr\u00fcnder und Chief Executive OfficerAndy KofoidPresident, Global Field OperationsDavid ConteChief Financial OfficerAmy ReichanadterChief People OfficerTr\u00e2m PhiSVP und General CounselRon GabriskoChief Revenue OfficerRick SchultzChief Marketing OfficerHatim ShafiqueChief Operating OfficerFerm\u00edn SernaChief Security OfficerNaveen ZutshiChief Information OfficerVinod MarurSVP of EngineeringDavid MeyerSVP of ProductsAdam ConwaySVP of ProductsArsalan Tavakoli-ShirajiMitgr\u00fcnder und SVP of Field EngineeringProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/industries\/retail-industry-solutions","text":"\ub9ac\ud14c\uc77c \ubc0f CPG\ub97c \uc704\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc194\ub8e8\uc158 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, 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\uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\ud1b5\ud569 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \ud50c\ub7ab\ud3fc \uc18c\ub9e4\uc5c5\uccb4\ub294 \uace0\uac1d \uc5ec\uc815\uc758 \ubaa8\ub4e0 \ub2e8\uacc4\uc5d0\uc11c \ub354 \ub9ce\uc740 \uc131\uacfc \uc2e4\ud604\uac00\uc785\ud558\uae30\ubb38\uc758\uc131\ub2a5 \ud5a5\uc0c1, \uaddc\ubaa8 \ud655\uc7a5, TCO \uc808\uac10\ub9ac\ud14c\uc77c\uc6a9\n\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uae30\ubcf8 \ub0b4\uc7a5\ub41c \uacf5\uc720 \uae30\ub2a5\uacfc \uac70\ubc84\ub10c\uc2a4\ub85c \ub370\uc774\ud130 \ubc0f AI \uc6cc\ud06c\ub85c\ub4dc\ub97c \ud1b5\ud569\ud558\uc5ec \ub0b4\ubd80 \ubc0f \uc678\ubd80 \ud300\uc774 \ud544\uc694\ud55c \ub370\uc774\ud130\ub97c \uc801\uc2dc\uc5d0 \ud65c\uc6a9\ud558\ub3c4\ub85d \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc804\uccb4 \uac00\uce58 \uc0ac\uc2ac\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5\uace0\uac1d \ucc38\uc5ec\ubaa8\ub4e0 \uc811\uc810\uc758 \uad00\ub828\uc131 \ud5a5\uc0c1 \ubc0f \uace0\ub3c4\uc758 \ub9de\ucda4 \uc124\uc815\uace0\uac1d\uc5d0 \ub300\ud55c \uc815\ud655\ud558\uace0 \uc804\uccb4\uc801\uc778 \uc2dc\uc57c\ub97c \uc2e4\uc2dc\uac04\uc73c\ub85c \ud655\ubcf4\ud568\uc73c\ub85c\uc368 \uc18c\ub9e4\uc5c5\uccb4\ub294 \ucc44\ub110 \uc804\ubc18\uc758 \uac10\uc815 \ud30c\uc545, \uad8c\uc7a5 \uc0ac\ud56d \uac1c\uc778\ud654 \ub4f1 \uace0\uac1d \ub9de\ucda4\ud615 \uad00\uacc4\ub97c \ud615\uc131\ud558\ub294 \ub370 \ud544\uc694\ud55c \ubaa8\ub4e0 \uac83\uc744 \uac16\ucd94\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uadf8 \uacb0\uacfc \uc218\uc775\uc131\uacfc \ucda9\uc131\ub3c4\uac00 \ub192\uc544\uc84c\uc2b5\ub2c8\ub2e4.\uc6b4\uc601 \ud6a8\uc728\uc131\uc9c1\uc6d0 \uc0dd\uc0b0\uc131\uc81c\ud488 \uc131\ub2a5\ub9ac\ud14c\uc77c \uc194\ub8e8\uc158 \ubc0f \ud30c\ud2b8\ub108\uac01 \uc5c5\uc885\uc5d0 \ub9de\ub294 \ucd5c\uace0\uc758 \ub370\uc774\ud130 \ubd84\uc11d \ubc0f AI \uc194\ub8e8\uc158 \uc81c\uacf5Databricks \uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ub294 \ubaa8\ub4e0 \uae30\ub2a5\uc744 \uac16\ucd98 \ub178\ud2b8\ubd81\uacfc \ubaa8\ubc94 \uc0ac\ub840\ub97c \ud3ec\ud568\ud55c \uc804\uc6a9 \uac00\uc774\ub4dc\ub97c \ud1b5\ud574 \ub9ac\ud14c\uc77c \ubd80\ubb38\uc758 \uc131\uacfc \uc2e4\ud604\uc744 \uac00\uc18d\ud654\ud569\ub2c8\ub2e4. \uc131\ud5a5 \ud3c9\uac00, \uace0\uac1d \uc0dd\uc560 \uac00\uce58 \uac00\uce58, \ucd5c\uc801\ud654\ub41c \uc624\ub354 \ud53c\ud0b9 \ub4f1\uc758 \uc0ac\uc6a9 \uc0ac\ub840\uc5d0\uc11c \ubc1c\uacac, \uc124\uacc4, \uac1c\ubc1c, \ud14c\uc2a4\ud2b8 \uc2dc\uac04\uc744 \ub2e8\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc138\ubd84\ud654\ub41c \uc608\uce21\ub354 \ube60\ub974\uac8c \ub300\uaddc\ubaa8\uc758 \uc608\uce21 \uc0dd\uc131\nDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\u0000\u0000\ub7ab\ud3fc\uc758 \ubd84\uc0b0 \ucef4\ud4e8\ud305 \uc131\ub2a5\uc744 \ud65c\uc6a9\ud558\uc5ec \ub9e4\uc7a5\uc758 \ubcf4\uc720 \ud488\ubaa9 \uc218\uc900\uc5d0\uc11c \ubcf4\ub2e4 \ud6a8\uc728\uc801\uc778 \ubc29\uc2dd\uc73c\ub85c \uc138\ubd84\ud654\ub41c \uc608\uce21\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\uace0\uac1d \uc138\ubd84\ud654\uace0\uac1d \uc138\ubd84\ud654\ub85c \ud0c0\uac8c\ud305 \uac1c\uc120\n\ud310\ub9e4 \ub370\uc774\ud130, \ucea0\ud398\uc778, \ud504\ub85c\ubaa8\uc158 \uc2dc\uc2a4\ud15c \ub4f1\uc744 \uc0ac\uc6a9\ud55c \uace0\uae09 \uace0\uac1d \uc138\ubd84\ud654\ub97c \ud1b5\ud574 \ud589\ub3d9\uc5d0 \uae30\ubc18\ud55c \uad6c\ub9e4 \uc608\uce21\uc744 \ubcf4\ub2e4 \uc815\ud655\ud558\uac8c \uc774\ub04c\uc5b4\ub0c5\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\uc2e4\uc2dc\uac04 POS \ubd84\uc11d\uc5ec\ub7ec \ub9e4\uc7a5 \uc704\uce58\uc5d0\uc11c \uc2e4\uc2dc\uac04 \uc7ac\uace0\ub97c \uacc4\uc0b0\ud558\uc5ec \ub9ac\ud14c\uc77c \ub9c8\uc9c4 \uac1c\uc120\n\ubaa8\ub4e0 POS(Point-of-sale) \ub370\uc774\ud130 \uc18c\uc2a4 \ubc0f \uc720\ud615\uc744 \ub300\uaddc\ubaa8\ub85c \uc2e0\uc18d\ud558\uac8c \uc218\uc9d1\ud558\uc5ec \ub9e4\uc7a5\uc758 \uc2dc\uae09\ud55c \uc815\ubcf4 \uc694\uad6c\ub97c \ud574\uacb0\ud558\ub294 \uc2e4\uc2dc\uac04 \uc778\uc0ac\uc774\ud2b8\ub97c \ub3c4\ucd9c\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\ub9ac\ud14c\uc77c \uc561\uc140\ub7ec\ub808\uc774\ud130 \ub458\ub7ec\ubcf4\uae30Databricks\ub294 \uc8fc\uc694 \ucee8\uc124\ud305 \uae30\uc5c5\uacfc \ud611\ub825\ud558\uc5ec \ud601\uc2e0\uc801\uc778 \uc5c5\uc885\ubcc4 \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud588\uc2b5\ub2c8\ub2e4. Databricks Brickbuilder Solutions\ub294 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uace0 \ub370\uc774\ud130\uc5d0\uc11c \ub354 \ub9ce\uc740 \uac00\uce58\ub97c \ucc3d\ucd9c\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc90d\ub2c8\ub2e4. \uc218\uc2ed \ub144 \uac04 \ucd95\uc801\ub41c \uc5c5\uacc4 \uacbd\ud5d8\uc744 \ub178\ud558\uc6b0 \uc0bc\uc544 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uae30\ubc18\uc73c\u0000\u0000\ub85c \uac1c\ubc1c\ud55c Brickbuilder Solutions\ub294 \uace0\uac1d\uc758 \uc694\uad6c \uc0ac\ud56d\uc744 \uc815\ud655\ud788 \ud574\uacb0\ud574\uc90d\ub2c8\ub2e4.\ud1b5\ud569 \uc218\uc694 \uc804\ub9dd\ub2e8\uc77c \uc815\ubcf4 \ucd9c\ucc98 \uc218\uc694 \uacc4\ud68d\uc73c\ub85c \uc815\ud655\ub3c4, \uc138\ubd84\ud654 \uc218\uc900, \uc2dc\uae30 \uc801\uc808\uc131\uc744 \uadf9\ub300\ud654\ud558\uc138\uc694.\uc790\uc138\ud788\uc218\uc775 \uc131\uc7a5 \uad00\ub9ac\uc778\ubcf4\uc774\uc2a4 \ub370\uc774\ud130, \uc678\ubd80 \uc2dc\uc7a5 \ub370\uc774\ud130, \ub274\uc2a4 \ubc0f \uc6f9 \uc2a4\ud06c\ub798\ud551 \ub370\uc774\ud130\ub97c \uc2e0\uc18d\ud558\uac8c \ubd84\uc11d\ud558\uc5ec \ub9ac\ud14c\uc77c \ud328\ud134\uc744 \ud0d0\uc0c9\ud558\uc138\uc694.\uc790\uc138\ud788Trellis\uc218\uc694 \uc608\uce21, \ubcf4\ucda9, \uc870\ub2ec, \uac00\uaca9 \ucc45\uc815 \ubc0f \ud504\ub85c\ubaa8\uc158 \uc11c\ube44\uc2a4\uc640 \uad00\ub828\ub41c \ubb38\uc81c\ub97c \ud574\uacb0\ud574 \ubcf4\uc138\uc694.\uc790\uc138\ud788\ube0c\ub9ad\ube4c\ub354 \uc194\ub8e8\uc158 \ub458\ub7ec\ubcf4\uae30\"\uc774\uc81c \uace0\uac1d \uc218\uc900\uc5d0\uc11c \uc774\uc804\uc5d0\ub294 \uc5b4\ub835\uace0 \ubd80\ub2f4\uc2a4\ub7ec\uc6b4 \uc791\uc5c5\uc774\uc5c8\ub358 \uc628\ub77c\uc778 \ubc0f \uc624\ud504\ub77c\uc778 \uad6c\ub9e4 \uc815\ubcf4\ub97c \uacb0\ud569\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uace0, \uc774 \uc634\ub2c8\ucc44\ub110 \ubdf0\ub97c \ud1b5\ud574 \uc628\ub77c\uc778\uc5d0\uc11c \ubcf4\ub2e4 \ud3ec\uad04\uc801\uc778 \ucd94\ucc9c \uc5d4\uc9c4\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uac8c \ub418\uc5b4 \uc5c4\uccad\ub09c \ucc38\uc5ec\ub97c \uc774\ub04c \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4.\"\n\u2014 Wendell Kuling, Jumbo\uc758 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubc0f \ubd84\uc11d \ubd80\ubb38 \ucc45\uc784\uc790\n\"Databricks \ub355\ubd84\uc5d0 \ubaa8\ub4e0 \uc2dc\uc7a5\uc5d0\uc11c \ub3d9\uae09 \ucd5c\uace0\ub97c \ub2a5\uac00\ud558\ub294 \uace0\uac1d \uacbd\ud5d8\uc744 \uc81c\uacf5\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uae30\ubc18\uc73c\ub85c \ub2f9\uc0ac\uc758 \uc774\ud574 \uad00\uacc4\uc790\uc640 \uac1c\ubc1c\uc790\ub4e4\uc774 \ud611\uc5c5\uc744 \uc99d\uc9c4\ud558\uace0, 1\uc5b5 8\ucc9c\ub9cc \uba85\uc758 \uace0\uac1d\uc5d0\uac8c \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud558\ub294 \ub370 \ud544\uc694\ud55c \uc911\uc694\ud55c \ud2b8\ub80c\ub4dc\uc640 \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\"\n\u2014 Sergiy Tkachuk, Reckitt\uc758 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubd80\ubb38 \ucc45\uc784\uc790\n\"\uc608\uc804\uc5d0\ub294 \ubd88\uac00\ub2a5\ud588\ub358 \uc140\ud504 \uc11c\ube44\uc2a4 \ubc29\uc2dd\uc73c\ub85c \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\ub294 \uc0ac\uc5c5\ubd80\uac00 \uc810\uc810 \ub298\uc5b4\ub0ac\uc2b5\ub2c8\ub2e4. Databricks\uac00 Columbia\uc5d0 \uc77c\uc73c\ud0a8 \uae0d\uc815\uc801 \uc601\ud5a5\uc740 \uc785\uc774 \ub2f3\ub3c4\ub85d \ub9d0\ud574\ub3c4 \ubaa8\uc790\ub78d\ub2c8\ub2e4.\"\n\u2014 Columbia Sportswear \uc120\uc784 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uad00\ub9ac\uc790 Lara Minor\n\ub9ac\uc18c\uc2a4\uc140\ud504 \uac00\uc774\ub4dc \ud22c\uc5b4\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \ub458\ub7ec\ubcf4\ub294 \ub370 \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uc6e8\ube44\ub098\ub9ac\ud14c\uc77c\uc758 \uc2e4\uc2dc\uac04 \uc758\uc0ac \uacb0\uc815 \uac00\uc18deBook\ub9ac\ud14c\uc77c \uc0ac\uc6a9 \uc0ac\ub840 Big Book\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/jp\/product\/open-source","text":"\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 PT\n\u3055\u3088\u3046\u306a\u3089\u3001\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3002\u3053\u3093\u306b\u3061\u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3002\n\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u304c\u6700\u65b0\u306e\u30c7\u30fc\u30bf\u30b9\u30bf\u30c3\u30af\u306b\u3069\u306e\u3088\u3046\u306b\u9069\u5408\u3059\u308b\u304b\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u51fa\u5e2d\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\u4eca\u3059\u3050\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c5\u67089\u65e5 |\u5348\u524d8\u6642(\u592a\u5e73\u6d0b\u6a19\u6e96\u6642)\n\u00a0\n\u88fd\u9020\u696d\u306e\u305f\u3081\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u767a\u898b\u3059\u308b\n\u30b3\u30fc\u30cb\u30f3\u30b0\u304c\u3001\u624b\u4f5c\u696d\u306b\u3088\u308b\u691c\u67fb\u3092\u6700\u5c0f\u9650\u306b\u6291\u3048\u3001\u8f38\u9001\u30b3\u30b9\u30c8\u3092\u524a\u6e1b\u3057\u3001\u9867\u5ba2\u6e80\u8db3\u5ea6\u3092\u9ad8\u3081\u308b\u91cd\u8981\u306a\u610f\u601d\u6c7a\u5b9a\u3092\u3069\u306e\u3088\u3046\u306b\u884c\u3063\u3066\u3044\u308b\u304b\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u4eca\u3059\u3050\u767b\u9332\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeacons2023\u5e746\u670826\u65e5\uff5e29\u65e5\n\n\u76f4\u63a5\u53c2\u52a0\u3059\u308b\u304b\u3001\u57fa\u8abf\u8b1b\u6f14\u306e\u30e9\u30a4\u30d6\u30b9\u30c8\u30ea\u30fc\u30e0\u306b\u53c2\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3054\u767b\u9332\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29REGISTER NOW\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9Databricks \u306e\u30a8\u30f3\u30b8\u30cb\u30a2\u306f\u3001\u4e3b\u8981\u306a\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c7\u30fc\u30bf\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u306e\u30aa\u30ea\u30b8\u30ca\u30eb\u30af\u30ea\u30a8\u30fc\u30bf\u30fc\u3067\u3059\u30df\u30fc\u30c8\u30a2\u30c3\u30d7\u306b\u53c2\u52a0Databricks \u306e\u4e3b\u8981\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30d7\u30ed\u30b8\u30a7\u30af\u30c8Apache Spark\u2122Apache Spark \u306f\u3001\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u3001\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u3001\u6a5f\u68b0\u5b66\u7fd2\u30ef\u30fc\u30af\u30ed\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b\u305f\u3081\u306e\u7d71\u5408\u30a8\u30f3\u30b8\u30f3\u3067\u3059\u3002\nApache Spark \u3068\u306f\nSpark \u3068 Databricks \u306e\u6bd4\u8f03\nspark.apache.org \u306e\u30b5\u30a4\u30c8\u3078\nDelta LakeDelta Lake \u3067\u306f\u3001AWS S3\u3001ADLS\u3001GCS\u3001HDFS \u306a\u3069\u306e\u30b9\u30c8\u30ec\u30fc\u30b8\u30b7\u30b9\u30c6\u30e0\u306e\u4e0a\u306b\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u69cb\u7bc9\u3067\u304d\u307e\u3059\u3002\nDelta Lake \u3092\u8a73\u3057\u304f\u898b\u308b\nDelta.io \u306e\u30b5\u30a4\u30c8\u3078\n\u30c6\u30c3\u30af\u30c8\u30fc\u30af\uff1aDelta Lake \u5165\u9580\nMLflowMLflow \u306f\u3001\u5b9f\u9a13\u3001\u518d\u73fe\u6027\u3001\u30c7\u30d7\u30ed\u30a4\u30e1\u30f3\u30c8\u3001\u4e2d\u592e\u30e2\u30c7\u30eb\u30ec\u30b8\u30b9\u30c8\u30ea\u306a\u3069\u3001\u6a5f\u68b0\u5b66\u7fd2\u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u3092\u7ba1\u7406\u3057\u307e\u3059\u3002\nDatabricks \u306e\u30de\u30cd\u30fc\u30b8\u30c9\u578b MLflow\nmlflow.org \u306e\u30b5\u30a4\u30c8\u3078\n\u30c6\u30c3\u30af\u30c8\u30fc\u30af\uff1aMLflow \u306b\u3088\u308b ML \u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u7ba1\u7406\nRedashRedash \u3067\u306f\u3001\u3042\u3089\u3086\u308b\u30e6\u30fc\u30b6\u30fc\u304c SQL \u3092\u6d3b\u7528\u3057\u3066\u3001\u30c7\u30fc\u30bf\u30bd\u30fc\u30b9\u30b5\u30a4\u30ba\u306e\u898f\u6a21\u3092\u554f\u308f\u305a\u3001\u30c7\u30fc\u30bf\u3092\u63a2\u7d22\u3001\u30af\u30a8\u30ea\u3001\u8996\u899a\u5316\u3001\u5171\u6709\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\nGitHub \u306e Redash \u306e\u30b5\u30a4\u30c8\u3078\nDelta SharingDelta Sharing \u306f\u3001\u30bb\u30ad\u30e5\u30a2\u306a\u30c7\u30fc\u30bf\u5171\u6709\u306e\u305f\u3081\u306e\u65b0\u305f\u306a\u30aa\u30fc\u30d7\u30f3\u30d7\u30ed\u30c8\u30b3\u30eb\u3067\u3001\u7d44\u7e54\u5185\u5916\u3067\u306e\u30c7\u30fc\u30bf\u5171\u6709\u3092\u5bb9\u6613\u306b\u3057\u307e\u3059\u3002\nDelta Sharing \u306e\u30b5\u30a4\u30c8\u3078\nDatabricks \u306f\u3001\u6b21\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u3082\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059TensorFlowDatabricks \u306f\u3001\u30af\u30e9\u30b9\u30bf\u4e0a\u306e\u6df1\u5c64\u5b66\u7fd2\u3068\u6c4e\u7528\u7684\u306a\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u306e\u305f\u3081\u306e\u30e9\u30a4\u30d6\u30e9\u30ea TensorFlow \u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002\nTensorFlow on Databricks\nPyTorch\u2122PyTorch \u306e\u30af\u30ea\u30a8\u30a4\u30bf\u30fc\u3067\u3042\u308b Facebook \u3068\u306e\u9023\u643a\u306b\u3088\u308a PyTorch \u3092\u7d71\u5408\u3057\u3066\u3044\u307e\u3059\u3002\nPyTorch on Databricks\nKeras\u2122Keras \u306f\u3001TensorFlow\u4e0a\u3067\u5b9f\u884c\u3055\u308c\u308b Python \u3067\u8a18\u8ff0\u3055\u308c\u305f\u6df1\u5c64\u5b66\u7fd2 API\u3067\u3059\u3002\u6a5f\u68b0\u5b66\u7fd2\u306e\u305f\u3081\u306e Databricks \u30e9\u30f3\u30bf\u30a4\u30e0\u306e\u4e00\u90e8\u3068\u3057\u3066\u63d0\u4f9b\u3055\u308c\u307e\u3059\u3002\nKeras on Databricks\nRStudioR \u3092\u4f7f\u7528\u3057\u305f\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u578b\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u305f\u3081\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30c4\u30fc\u30eb\u7fa4\u3092 Databricks \u306b\u7d71\u5408\u3067\u304d\u307e\u3059\u3002\nR \u0000\u0000\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u306b\u3088\u308b\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u5206\u6790\nscikit-learnNumPy\u3001SciPy\u3001Matplotlib \u4e0a\u306b\u69cb\u7bc9\u3055\u308c\u305f\u6a5f\u68b0\u5b66\u7fd2\u306b\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b Python \u30d1\u30c3\u30b1\u30fc\u30b8\u3092 Databricks \u4e0a\u3067\u5229\u7528\u3067\u304d\u307e\u3059\u3002\nScikit-learn on Databricks\nXGBoostPython\u3001R\u3001C++ \u306a\u3069\u306e\u8a00\u8a9e\u306b\u5bfe\u5fdc\u3057\u305f\u5206\u6563\u578b\u52fe\u914d\u30d6\u30fc\u30b9\u30c6\u30a3\u30f3\u30b0\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u63d0\u4f9b\u3055\u308c\u307e\u3059\u3002XGBoost on DatabricksTerraformHashiCorp Terraform \u306f\u3001\u8907\u6570\u306e\u30af\u30e9\u30a6\u30c9\u30d7\u30ed\u30d0\u30a4\u30c0\u306b\u308f\u305f\u3063\u3066\u30bb\u30ad\u30e5\u30a2\u304b\u3064\u4e88\u6e2c\u53ef\u80fd\u306a\u30af\u30e9\u30a6\u30c9\u30a4\u30f3\u30d5\u30e9\u3092\u69cb\u7bc9\u3059\u308b\u305f\u3081\u306e\u4e00\u822c\u7684\u306a\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c4\u30fc\u30eb\u3067\u3059\u3002Databricks Terraform \u30d7\u30ed\u30d0\u30a4\u30c0\u306b\u3088\u308a\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u67d4\u8edf\u3067\u5805\u7262\u306a\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u3001Databricks \u30ef\u30fc\u30af\u30b9\u30da\u30fc\u30b9\u5168\u4f53\u3092\u4ed6\u306e\u30a4\u30f3\u30d5\u30e9\u3068\u4e00\u7dd2\u306b\u7ba1\u7406\u3067\u304d\u307e\u3059\u3002\u307e\u305f\u3001Terraform \u3092\u5229\u7528\u3059\u308b\u3053\u3068\u3067\u3001IaC \uff08\u30b3\u30fc\u30c9\u3068\u3057\u3066\u306e\u30a4\u30f3\u30d5\u30e9\uff09\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u63a1\u7528\u3067\u304d\u307e\u3059\u3002Terraform on Databricks\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u0000\u0000\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u0000\u0000\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/kr\/glossary","text":"\uc6a9\uc5b4\uc9d1 \uc544\uce74\uc774\ube0c - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWGlossaryA-Zsearch DNA \uc11c\uc5f4 DNA \uc11c\uc5f4\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nDNA \uc11c\uc5f4\uc740 DNA(deoxyribonucleic acid, \ub514\uc625\uc2dc\ub9ac\ubcf4 \ud575\uc0b0)\uc758 \ub274\ud074\ub808\uc624\ud0c0\uc774\ub4dc(nucleotides)\uc758 \uc815\ud655\ud55c \uc21c\uc11c\ub97c \ud310\ubcc4\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. &nbsp;DNA \uc11c\uc5f4\uc740 \ub124 \uac00\uc9c0 \ud654\ud559\uc801 \uae30\ubcf8 \uc694\uc18c\uc778 \uc544\ub370\ub2cc, \uad6c\uc544\ub2cc, \uc0ac\uc774\ud1a0\uc2e0, \ud0c0\uc774\ubbfc \ub4f1 DNA \ubd84\uc790 \ub0b4\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ud654\ud559 \ubb3c\uc9c8\uc758 \uc21c\uc11c\ub97c \ub9d0\ud569\ub2c8\ub2e4. \uc774\uac83\uc744 '\uc5fc\uae30'\ub77c\uace0\ub3c4 \ud569\ub2c8\ub2e4. DNA \uc11c\uc5f4\uc744 \uc815\ud558\ub294 \uccab \ubc88\uc9f8 \ubc29\uc2dd\uc740 1970\ub144\ub300 \uc911\ubc18 Fred Sange{...} Hive \ub0a0\uc9dc \ud568\uc218 Hive \ub0a0\uc9dc \ud568\uc218\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nHive\ub294 \uc218\ub9ce\uc740 \uae30\ubcf8 \ub0b4\uc7a5 \ud568\uc218\ub97c \uc81c\uacf5\ud558\uc5ec \ub370\uc774\ud130 \ucc98\ub9ac\uc640 \ucffc\ub9ac\uc5d0 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4. \uc774\ub7f0 \ud568\uc218\uac00 \uc81c\uacf5\ud558\ub294 \uae30\ub2a5 \uc911\uc5d0\ub294 \ubb38\uc790\uc5f4 \uc870\uc791, \ub0a0\uc9dc \uc870\uc791, \ud0c0\uc785 \ubcc0\ud658, \uc870\uac74 \uc5f0\uc0b0\uc790, \uc218\ud559\uc801 \ud568\uc218 \ub4f1\uc774 \uc788\uc73c\uba70 \uc774\uc678\uc5d0\ub3c4 \uc5ec\ub7ec \uac00\uc9c0\uac00 \uc788\uc2b5\ub2c8\ub2e4.\nHIVE \uae30\ubcf8 \ub0b4\uc7a5 \ud568\uc218\uc758 \uc720\ud615\n\ub0a0\uc9dc \ud568\uc218\n\uc8fc\ub85c \ub0a0\uc9dc\uc5d0 \uc77c\uc218\ub97c \ub354\ud558\ub294 \ub4f1 \uc774\uc640 \ube44\uc2b7\ud55c \uc5f0\uc0b0\uc758 \ub0a0\uc9dc \ub370\uc774\ud130 \ud0c0\uc785\uc744 \ub300\uc0c1\uc73c\ub85c \ud55c \uc5f0\uc0b0\uc744 \uc218\ud589\ud558\ub294 \ub370 \uc4f0\uc785\ub2c8\ub2e4.\n\uc218\ud559{...} Lambda \uc544\ud0a4\ud14d\ucc98 Lambda \uc544\ud0a4\ud14d\ucc98\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nLambda \uc544\ud0a4\ud14d\ucc98\ub294 \uc5c4\uccad\ub09c \ub300\ub7c9\uc758 \ub370\uc774\ud130(\uc989 \u201c\ube45\ub370\uc774\ud130\u201d)\ub97c \ucc98\ub9ac\ud558\ub294 \ubc29\uc2dd\uc758 \uc77c\uc885\uc73c\ub85c, \ud558\uc774\ube0c\ub9ac\ub4dc \ubc29\uc2dd\uc73c\ub85c \uc77c\uad04 \ucc98\ub9ac\ub098 \uc2a4\ud2b8\ub9bc \ucc98\ub9ac \ubc29\uc2dd\uc744 \uc774\uc6a9\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4. Lambda \uc544\ud0a4\ud14d\ucc98\ub294 \uc784\uc758 \ud568\uc218 \uc5f0\uc0b0 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \uc4f0\uc785\ub2c8\ub2e4. Lambda \uc544\ud0a4\ud14d\ucc98 \uc790\uccb4\ub294 3\uac1c\uc758 \uacc4\uce35\uc73c\ub85c \uc774\ub8e8\uc5b4\uc838 \uc788\uc2b5\ub2c8\ub2e4.\n\ubc30\uce58 \uacc4\uce35\n\uc0c8\ub85c\uc6b4 \ub370\uc774\ud130\ub294 \ub370\uc774\ud130 \uc2dc\uc2a4\ud15c\uc5d0 \uc77c\uc885\uc758 \ud53c\ub4dc \ud615\ud0dc\ub85c \ub04a\uc784\uc5c6\uc774 \uc720\uc785\ub429\ub2c8\ub2e4. \uc774\uac83\uc744 {...} Medallion \uc544\ud0a4\ud14d\ucc98 Medallion \uc544\ud0a4\ud14d\ucc98\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uba54\ub2ec\ub9ac\uc628 \uc544\ud0a4\ud14d\ucc98\ub294&nbsp;\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \ub17c\ub9ac\uc801\uc73c\ub85c \ub370\uc774\ud130\ub97c \uc815\ub9ac\ud558\ub294 \ub370 \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \uc124\uacc4 \ud328\ud134\uc785\ub2c8\ub2e4. \uc774 \uc544\ud0a4\ud14d\ucc98\uc758 \ubaa9\ud45c\ub294 \ub370\uc774\ud130\uac00 \uc544\ud0a4\ud14d\ucc98\uc758 \uac01 \ub808\uc774\uc5b4\ub97c \ud1b5\uacfc\ud558\ub294 \ub3d9\uc548(\ube0c\ub860\uc988 \u21d2 \uc2e4\ubc84 \u21d2 \uace8\ub4dc \ub808\uc774\uc5b4 \ud14c\uc774\ube14) \ub370\uc774\ud130\uc758 \uad6c\uc870\uc640 \ud488\uc9c8\uc744 \uc99d\ubd84\uc801, \uc810\uc9c4\uc801\uc73c\ub85c \uac1c\uc120\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uba54\ub2ec\ub9ac\uc628 \uc544\ud0a4\ud14d\ucc98\ub294 \"\uba40\ud2f0 \ud649\" \uc544\ud0a4\ud14d\ucc98\ub77c\uace0 \ubd80\ub974\uae30\ub3c4 \ud569\ub2c8\ub2e4.\n&nbsp;\n\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\uc758 \uc7a5\uc810{...} Unified AI \ud504\ub808\uc784\uc6cc\ud06c Unified Artificial Intelligence, \uc989 UAI\ub294 Facebook\uc5d0\uc11c \uc62c\ud574 F8 \uc911\uc5d0 \ubc1c\ud45c\ud55c \uac1c\ub150\uc785\ub2c8\ub2e4. \uc774 \uac1c\ub150\uc740 Facebook\uc774 \uc81c\uc791\ud558\uace0 \uc544\uc6c3\uc18c\uc2f1\ud55c 2\uac00\uc9c0 \ub525\ub7ec\ub2dd \ud504\ub808\uc784\uc6cc\ud06c\ub97c \ud569\uce5c \uac83\uc785\ub2c8\ub2e4. \ud558\ub098\ub294 \ub300\uaddc\ubaa8 \ucef4\ud4e8\ud305 \ub9ac\uc18c\uc2a4\uc5d0 \uc561\uc138\uc2a4\ub97c \ubcf4\uc720\ud55c \ub9ac\uc11c\uce58 \uc911\uc810\uc801 PyTorch\uc774\uace0, \ub2e4\ub978 \ud558\ub098\ub294 Android\uc640 Raspberry Pi \ub514\ubc14\uc774\uc2a4\uc5d0\uc11c\uc758 \ubaa8\ub378 \ubc30\ud3ec\uc5d0 \uc8fc\ub825\ud558\ub294 Caffe\uc785\ub2c8\ub2e4. Facebook\uc758 Unified AI\ub294 \ubc94\uc704{...} \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub294 \uc5ec\ub7ec \uc18c\uc2a4\uc758 \ud604\uc7ac \ubc0f \uacfc\uac70 \ub370\uc774\ud130\ub97c \ube44\uc988\ub2c8\uc2a4\uc5d0\uc11c \uc27d\uac8c \uc778\uc0ac\uc774\ud2b8\uc640 \ubcf4\uace0\uc11c\ub97c \uc5bb\uc744 \uc218 \uc788\ub3c4\ub85d \uc800\uc7a5\ud558\ub294 \ub370\uc774\ud130 \uad00\ub9ac \uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub294 \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4(BI), \ubcf4\uace0 \ubc0f \ub370\uc774\ud130 \ubd84\uc11d\uc5d0 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.\n\ub370\uc774\ud130 \uc6e8\u0000\u0000\uc5b4\ud558\uc6b0\uc2a4\ub97c \uc0ac\uc6a9\ud558\uba74 \uc6b4\uc601 \uc2dc\uc2a4\ud15c(\uc608: POS \uc2dc\uc2a4\ud15c, \uc7ac\uace0 \uad00\ub9ac \uc2dc\uc2a4\ud15c, \ub9c8\ucf00\ud305\/\uc601\uc5c5 \ub370\uc774\ud130\ubca0\uc774\uc2a4)\uc5d0\uc11c \uc5c5\ub85c\ub4dc\ub41c \ube44\uc988\ub2c8\uc2a4 \ub370\uc774\ud130\ub97c \ube60\ub974\uace0 \uc27d\uac8c \ubd84\uc11d\ud560 \uc218 \uc788{...} \ub525\ub7ec\ub2dd \ub525\ub7ec\ub2dd\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub525\ub7ec\ub2dd\uc740 \uba38\uc2e0 \ub7ec\ub2dd\uc758 \ud558\uc704 \uc9d1\ud569\uc73c\ub85c, \ud2b9\ud788 \uc0ac\ub78c\uc758 \ub1cc \uad6c\uc870\uc640 \uae30\ub2a5\uc5d0\uc11c \uc601\uac10\uc744 \uc5bb\uc740, \uc54c\uace0\ub9ac\uc998\uc744 \ud3ec\ud568\ud55c \ub300\ub7c9\uc758 \ub370\uc774\ud130\ub97c \ub2e4\ub8f9\ub2c8\ub2e4. \uadf8\ub798\uc11c \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uc885\uc885 \uc2ec\uce35 \uc2e0\uacbd\ub9dd\uc774\ub77c\uace0 \ubd80\ub974\ub294 \uac83\uc785\ub2c8\ub2e4. \uc774\ub294 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\ubcc4 \uc54c\uace0\ub9ac\uc998\uc774 \uc544\ub2c8\ub77c \ud559\uc2b5 \ub370\uc774\ud130 \ud45c\ud604\uc744 \uae30\ubc18\uc73c\ub85c \ud55c \ub113\uc740 \uc758\ubbf8\uc758 \uba38\uc2e0 \ub7ec\ub2dd \ubc29\uc2dd\uc5d0 \uc18d\ud569\ub2c8\ub2e4.\n\ub525\ub7ec\ub2dd\uc758 \uc791\uc6a9 \uc6d0\ub9ac\ub294 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub525\ub7ec\ub2dd\uc5d0\uc11c\ub294 \ucef4\ud4e8\ud130 \ubaa8\ub378\uc774 \uc774\ubbf8\uc9c0, \ud14d\uc2a4\ud2b8\ub098 \uc18c\ub9ac\uc5d0\uc11c \uc9c1\uc811 \ubd84\ub958 \uc791\uc5c5\uc744{...} \uc608\uce21 \ubd84\uc11d \uc608\uce21 \ubd84\uc11d\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc608\uce21 \ubd84\uc11d(Predictive analytics)\uc740 \uc9c0\ub2a5\ud615 \ubd84\uc11d\uc758 \ud55c \uac00\uc9c0 \ud615\ud0dc\uc785\ub2c8\ub2e4. \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130\uc640 \uacfc\uac70 \ub370\uc774\ud130\ub97c \ub458 \ub2e4 \uc0ac\uc6a9\ud558\uc5ec \ud328\ud134\uc744 \ud30c\uc545\ud558\uace0 \ud5a5\ud6c4 \uacb0\uacfc\uc640 \ucd94\uc138\ub97c \uc608\u0000\uce21\ud569\ub2c8\ub2e4.\n\uc608\uce21 \ubd84\uc11d\uc740 \uc5b4\ub5bb\uac8c \ub3d9\uc791\ud569\ub2c8\uae4c?\n\uc608\uce21 \ubd84\uc11d\uc740 \ud1b5\uacc4 \ubd84\uc11d \uae30\ubc95, \ubd84\uc11d \ucffc\ub9ac, \ub370\uc774\ud130 \ub9c8\uc774\ub2dd, \uc608\uce21 \ubaa8\ub378\ub9c1\uacfc \uc790\ub3d9 \uba38\uc2e0 \ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uacfc \uac19\uc740 \ub2e4\uc591\ud55c \uae30\ubc95\uc744 \ud65c\uc6a9\ud574 Dataset\uac00 \uc608\uce21\ud615 \ubaa8\ub378\uc744 \ub9cc\ub4e4\uac8c \ud55c \ub2e4\uc74c \ud2b9\uc815 \uc774\ubca4\ud2b8\uc758 \ubc1c{...} \uc778\uacf5 \uc2e0\uacbd\ub9dd(ANN) \uc778\uacf5 \uc2e0\uacbd\ub9dd\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc778\uacf5 \uc2e0\uacbd\ub9dd(Artificial Neural Network, ANN)\uc740 \uc0ac\ub78c\uc758 \ub1cc \uc18d \ub274\ub7f0\uc758 \uc791\uc6a9\uc744 \ubcf8\ub5a0 \ud328\ud134\uc744 \uad6c\uc131\ud55c \ucef4\ud4e8\ud305 \uc2dc\uc2a4\ud15c\uc758 \uc77c\uc885\uc785\ub2c8\ub2e4.\n\uc778\uacf5 \uc2e0\uacbd\ub9dd\uc740 \uc5b4\ub5bb\uac8c \uc791\ub3d9\ud569\ub2c8\uae4c?\n\uc778\uacf5 \uc2e0\uacbd\ub9dd(ANN)\uc740 \uac00\uc911\uce58\ub97c \uc801\uc6a9\ud55c \ubc29\ud5a5\uc131 \uadf8\ub798\ud504\ub77c\uace0 \ubcf4\uba74 \uac00\uc7a5 \uc801\ub2f9\ud569\ub2c8\ub2e4. \uc774\ub97c \ubcf4\ud1b5 \uc5ec\ub7ec \uacc4\uce35\uc73c\ub85c \uad6c\uc870\ud654\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uacc4\uce35\uc5d0\ub294 \uc0ac\ub78c\uc758 \ub1cc \uc18d\uc5d0 \uc788\ub294 \uc0dd\ubb3c\ud559\uc801 \ub274\ub7f0\uc744 \ubaa8\ubc29\ud55c \uc218\ub9ce\uc740 \ub178\ub4dc\uac00 \uc788\uace0, \uc774\ub4e4\uc774 \uc11c\ub85c \uc5f0\uacb0\ub418{...} \uc9c0\uc18d\ud615 \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uc9c0\uc18d\ud615 \uc560\ud50c\ub9ac\ucf00\uc774\uc158(Continuous Application)\uc740 \uc2e4\uc2dc\uac04\uc73c\ub85c \ub370\uc774\ud130\uc5d0 \ubc18\uc751\ud558\ub294 \uc885\ub2e8\uac04(E2E) \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc785\ub2c8\ub2e4. \ud2b9\ud788 \uac1c\ubc1c\uc790\uc758 \uacbd\uc6b0 \ubcc4\ub3c4\uc758 \uc2dc\uc2a4\ud15c\uc5d0\uc11c \ud604\uc7ac \ucc98\ub9ac \uc911\uc778 \uc9c0\uc18d\ud615 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc758 \uc5ec\ub7ec \uce21\uba74(\uc608\ub97c \ub4e4\uc5b4 \ucffc\ub9ac \uc81c\uacf5, \ubc30\uce58 \uc791\uc5c5\uacfc\uc758 \uc0c1\ud638\uc791\uc6a9 \ub4f1)\uc744 \uc9c0\uc6d0\ud558\uae30 \uc704\ud574 \ub2e8 \ud55c \uac00\uc9c0 \ud504\ub85c\uadf8\ub798\ubc0d \uc778\ud130\ud398\uc774\uc2a4\ub97c \uc0ac\uc6a9\ud558\uace0\uc790 \ud569\ub2c8\ub2e4. \uc544\ub798\uc5d0 \ub2e4\uc74c\uacfc \uac19\uc740 \uc0ac\uc6a9 \uc0ac\ub840\ub97c \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \uc9c0\uc18d\ud615 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc758 \uc608\ub97c \uc18c\uac1c\ud558\uc600\uc2b5\ub2c8\ub2e4.\n\uc2e4\uc2dc\uac04\uc73c{...} \ud558\ub461 \ud074\ub7ec\uc2a4\ud130 \ud558\ub461 \ud074\ub7ec\uc2a4\ud130\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache&nbsp;Hadoop\uc740 \uc624\ud508 \uc18c\uc2a4, Java \uae30\ubc18 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \ud504\ub808\uc784\uc6cc\ud06c\uc774\uc790 \ubcd1\ub82c\uc2dd \ub370\uc774\ud130 \ucc98\ub9ac \uc5d4\uc9c4\uc785\ub2c8\ub2e4. \ud558\ub461\uc744 \uc774\uc6a9\ud558\uba74 \ube45\ub370\uc774\ud130 \ubd84\uc11d \ucc98\ub9ac \uc791\uc5c5\uc744 \uc791\uc740 \ud06c\uae30\uc758 \uc791\uc5c5\uc73c\ub85c \ubd84\ud574\ud558\uc5ec \uc54c\uace0\ub9ac\uc998(\uc608\ub97c \ub4e4\uc5b4&nbsp;MapReduce&nbsp;\uc54c\uace0\ub9ac\uc998 \uac19\uc740)\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubcd1\ub82c\uc2dd\uc73c\ub85c \uc218\ud589\ud560 \uc218 \uc788\uace0, \uadf8\ub7f0 \ub2e4\uc74c \ud558\ub461 \ud074\ub7ec\uc2a4\ud130\uc5d0 \ubc30\ud3ec\ud558\uba74 \ub429\ub2c8\ub2e4. \ud558\ub461 \ud074\ub7ec\uc2a4\ud130\ub780 \ub124\ud2b8\uc6cc\ud06c\ub85c \uc11c\ub85c \uc5f0\uacb0\ub41c \uc77c\ub828\uc758 \ucef4\ud4e8\ud130('\ub178\ub4dc'\ub77c\uace0{...} \ud574\uc2dc \ubc84\ud0b7 \ucef4\ud4e8\ud305\uc5d0\uc11c \ud574\u0000\u0000\uc2dc \ud14c\uc774\ube14 [\ud574\uc2dc \ub9f5]\uc740 \ud0a4 [\uace0\uc720\ud55c \ubb38\uc790\uc5f4\uc774\ub098 \uc815\uc218]\ub97c \uae30\ubc18\uc73c\ub85c \uac1c\uccb4\uc5d0 \uc0ac\uc2e4\uc0c1 \uc9c1\uc811\uc801\uc778 \uc561\uc138\uc2a4\ub97c \uc81c\uacf5\ud558\ub294 \ub370\uc774\ud130 \uad6c\uc870\ub97c \ub9d0\ud569\ub2c8\ub2e4. \ud574\uc2dc \ud14c\uc774\ube14\uc740 \ud574\uc2dc \ud568\uc218\ub97c \uc0ac\uc6a9\ud574 \uc778\ub371\uc2a4\ub97c \ubc84\ud0b7\uc774\ub098 \uc2ac\ub86f \uc5b4\ub808\uc774\ub85c \uc5f0\uc0b0\ud558\ub294\ub370, \uc5ec\uae30\uc5d0\uc11c \uc6d0\ud558\ub294 \uac12\uc744 \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc5d0 \uc0ac\uc6a9\ub418\ub294 \ud0a4\uc758 \uc8fc\ub41c \ud2b9\uc9d5\uc744 \uc18c\uac1c\ud569\ub2c8\ub2e4.\n\uc0ac\uc6a9\ub418\ub294 \ud0a4\ub294 SSN, \uc804\ud654\ubc88\ud638, \uacc4\uc88c \ubc88\ud638 \ub4f1 \ubb34\uc5c7\uc774\ub4e0 \uac00\ub2a5\n\ubc18\ub4dc\uc2dc \uace0\uc720\ud55c \ud0a4\uac00 \uc788\uc5b4\uc57c \ud568\n\uac01\uac01\uc758 \ud0a4\uac00 \uac12\uacfc \uc5f0\uacb0\ub428({...}ACID \ud2b8\ub79c\uc7ad\uc158 \ud2b8\ub79c\uc7ad\uc158\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640 \ub370\uc774\ud130 \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c\uc774\ub77c\ub294 \ub9e5\ub77d\uc5d0\uc11c&nbsp;\ud2b8\ub79c\uc7ad\uc158\uc774\ub780 \ud55c \ub2e8\uc704\uc758 \uc791\uc5c5\uc73c\ub85c \ucde8\uae09\ub418\ub294 \ubaa8\ub4e0 \uc791\uc5c5\uc744 \ub9d0\ud569\ub2c8\ub2e4. \ud2b8\ub79c\uc7ad\uc158\uc740 \uc644\uc804\ud788 \uc644\ub8cc\ub418\uae30\ub3c4 \ud558\uace0 \uc804\ud600 \uc644\ub8cc\ub418\uc9c0 \uc54a\uc744 \uc218\ub3c4 \uc788\uc73c\uba70, \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c\uc744 \ud55c\uacb0\uac19\uc740 \uc0c1\ud0dc\ub85c \ub461\ub2c8\ub2e4. \ud2b8\ub79c\uc7ad\uc158\uc758 \uc804\ud615\uc801\uc778 \uc608\ub294 \uc740\ud589 \uacc4\uc88c\uc5d0\uc11c \ud604\uae08\uc744 \uc778\ucd9c\ud560 \ub54c \uc77c\uc5b4\ub098\ub294 \uc77c\uc785\ub2c8\ub2e4. \ud604\uae08\uc774 \uacc4\uc88c\uc5d0\uc11c \uc778\ucd9c\ub418\uac70\ub098, \uc778\ucd9c\ub418\uc9c0 \uc54a\uac70\ub098 \ub458 \uc911\uc758 \ud558\ub098\uc77c \ubfd0 \uadf8 \uc911\uac04 \uc5b4\ub518\uac00\uc758 \uc0c1\ud0dc\ub780 \uc5c6\uc2b5\ub2c8\ub2e4.&nb{...}AdaGrad \uc6a9\uc5b4\uc9d1\uc73c\ub85c \ub3cc\uc544\uac00\uae30\uacbd\uc0ac\ud558\uac15\ubc95(Gradient descent)\uc740 \uba38\uc2e0 \ub7ec\ub2dd\uacfc \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc5d0\uc11c \uac00\uc7a5 \ubcf4\ud3b8\uc801\uc73c\ub85c \uc4f0\uc774\ub294 \ucd5c\uc801\ud654 \ubc29\uc2dd\uc785\ub2c8\ub2e4. \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc744 \ud2b8\ub808\uc774\ub2dd\ud558\ub294 \ub370 \uc4f0\uc785\ub2c8\ub2e4.\n\uacbd\uc0ac\ud558\uac15\ubc95\uc758 \uc720\ud615\n\ucd5c\uc2e0 \uba38\uc2e0 \ub7ec\ub2dd \ubc0f \ub525\ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc5d0 \uc4f0\uc774\ub294 \uacbd\uc0ac\ud558\uac15\ubc95\uc740 \ud06c\uac8c \uc138 \uac00\uc9c0 \uc720\ud615\uc73c\ub85c \ub098\ub20c \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\ubc30\uce58 \uacbd\uc0ac\ud558\uac15\ubc95\n\ubc30\uce58 \uacbd\uc0ac\ud558\uac15\ubc95(Batch Gradient Descent)\uc774 \uadf8\uc911 \uac00\uc7a5 \uac04\ub2e8\ud55c \uc720\ud615\uc785\ub2c8\ub2e4.{...}Apache Hive Apache Hive\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Hive\ub294 \uad11\ubc94\uc704\ud55c&nbsp;Hadoop \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc5d0 \uc18d\ud558\ub294 Apache Hadoop Distributed File System(HDFS)\uc5d0\uc11c \ucd94\ucd9c\ud55c \ub300\uc6a9\ub7c9 \ub370\uc774\ud130\uc138\ud2b8\ub97c \uc77d\uace0, \uc4f0\uace0, \uad00\ub9ac\ud558\ub3c4\ub85d \uc124\uacc4\ub41c \uc624\ud508 \uc18c\uc2a4 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4 \uc18c\ud504\ud2b8\uc6e8\uc5b4\uc785\ub2c8\ub2e4.\nApache Hive\ub294 \uad11\ubc94\uc704\ud55c Apache Hive \ubb38\uc11c \ubc0f \uc9c0\uc18d\uc801 \uc5c5\ub370\uc774\ud2b8\ub97c \ud1b5\ud574 \uc27d\uac8c \uc561\uc138\uc2a4\ud560 \uc218 \uc788\ub294 \ubc29\uc2dd\uc73c\ub85c \uacc4\uc18d\ud574\uc11c \ub370\uc774\ud130{...}Apache Kudu Apache Kudu\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Kudu\ub294 Apache&nbsp;Hadoop\uc6a9\uc73c\ub85c \uac1c\ubc1c\ud55c \ubb34\ub8cc, \uc624\ud508 \uc18c\uc2a4 \uceec\ub7fc \uae30\ubc18 \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4.&nbsp;\uac01\uac01\uc758 \ud589\uc5d0 \ub0ae\uc740 \ub808\uc774\ud134\uc2dc(low-latency) \ub79c\ub364 \uc561\uc138\uc2a4, \ubc00\ub9ac\ucd08 \uae09\uc758 \uc561\uc138\uc2a4\ub97c \uc9c0\uc6d0\ud558\uba70 \uc6b0\uc218\ud55c \ubd84\uc11d \uc561\uc138\uc2a4 \ud328\ud134\uc744 \uc81c\uacf5\ud558\ub294 \uad6c\uc870\uc801 \ub370\uc774\ud130\uc6a9 \uc5d4\uc9c4\uc774\uba70, \ub110\ub9ac \ubcf4\uae09\ub41c Hadoop Distributed File System [HDFS] \ubc0f HBase NoSQL Databas{...}Apache Kylin Apache Kylin\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Kylin\uc740 \uc778\ud130\ub799\ud2f0\ube0c \ubd84\uc11d \ube45 \ub370\uc774\ud130\uc5d0 \uc801\ud569\ud55c \ubd84\uc0b0\ud615 \uc624\ud508 \uc18c\uc2a4 \uc628\ub77c\uc778 \ubd84\uc11d \ucc98\ub9ac(Online Analytics Processing, OLAP) \uc5d4\uc9c4\uc785\ub2c8\ub2e4. Apache Kylin\uc740&nbsp;\ud558\ub461\/Spark\uc5d0\uc11c SQL \uc778\ud130\ud398\uc774\uc2a4\uc640 \ub2e4\ucc28\uc6d0 \ubd84\uc11d(OLAP)\uc744 \uc81c\uacf5\ud558\uae30 \uc704\ud574 \uace0\uc548\ub418\uc5c8\uc2b5\ub2c8\ub2e4. \ub610\ud55c ODBC \ub4dc\ub77c\uc774\ubc84, JDBC \ub4dc\ub77c\uc774\ubc84 \ubc0f REST API\ub97c \uc0ac\uc6a9\ud574 BI \ud234\uacfc \uc190\uc27d\uac8c \ud1b5\ud569\ud560 \uc218\ub3c4 {...}Apache Spark Apache Spark\ub780 ?\nApache Spark\ub294 \ube45\ub370\uc774\ud130 \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \uc4f0\uc774\ub294 \uc624\ud508 \uc18c\uc2a4 \ubd84\uc11d \uc5d4\uc9c4\uc785\ub2c8\ub2e4. \ubc30\uce58\ub294 \ubb3c\ub860 \uc2e4\u0000\uc2dc\uac04 \ubd84\uc11d\uacfc \ub370\uc774\ud130 \ucc98\ub9ac \uc6cc\ud06c\ub85c\ub4dc\ub3c4 \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.&nbsp;Apache Spark\ub294 2009\ub144 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ub300\ud559\uad50 \ubc84\ud074\ub9ac \ucea0\ud37c\uc2a4\uc5d0\uc11c \uc5f0\uad6c \ud504\ub85c\uc81d\ud2b8\ub85c \uc2dc\uc791\ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc5f0\uad6c\uc9c4\uc740&nbsp;\ud558\ub461&nbsp;\uc2dc\uc2a4\ud15c\uc5d0\uc11c \ucc98\ub9ac \uc791\uc5c5\uc758 \uc18d\ub3c4\ub97c \ub192\uc77c \ubc29\ubc95\uc744 \uac15\uad6c\ud558\uace0 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. \uc774 \uc5d4\uc9c4\uc740 \ud558\ub461&nbsp;MapReduce&nbsp;{...}Apache Spark as a Service Apache Spark as a Service\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Spark\ub294 \uace0\uc18d \uc2e4\uc2dc\uac04 \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \ucc98\ub9ac\ub97c \uc704\ud55c \uc624\ud508 \uc18c\uc2a4 \ud074\ub7ec\uc2a4\ud130 \ucef4\ud4e8\ud305 \ud504\ub808\uc784\uc6cc\ud06c\uc785\ub2c8\ub2e4.Spark\ub294 2009\ub144 UC \ubc84\ud074\ub9ac AMPLab\uc5d0\uc11c \ud0c4\uc0dd\ud55c \uc774\ub798 \ud070 \uc131\uc7a5\uc744 \uc774\ub8e8\uc5c8\uc2b5\ub2c8\ub2e4. \uc9c0\uae08\uc740 \ube45\ub370\uc774\ud130 \ubd80\ubb38\uc5d0\uc11c \uac00\uc7a5 \ud070 \uc624\ud508 \uc18c\uc2a4 \ucee4\ubba4\ub2c8\ud2f0\ub85c \ud3c9\uac00\ub418\uba70 50\uc5ec \uac1c \uc870\uc9c1\uacfc \ub2e8\uccb4\uc5d0\uc11c 200\uc5ec \uba85\uc774 \uae30\uc5ec\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. Databricks\ub294 \uc790\uc0ac Apache Spark \ucd5c\uc801\ud654 \ubc84{...}Catalyst Optimizer Spark SQL\uc758 \ud575\uc2ec\uc740 Catalyst Optimizer\uc785\ub2c8\ub2e4. \uc774\uac83\uc740 \uc9c0\ub2a5\ud615 \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4 \uae30\ub2a5(\uc608: Scala\uc758 \ud328\ud134 \ub9e4\uce6d\uacfc quasi quote \ub4f1)\uc744 \ucc38\uc2e0\ud55c \ubc29\uc2dd\uc73c\ub85c \ud65c\uc6a9\ud574 \ud655\uc7a5\ud560 \uc218 \uc788\ub294 \ucffc\ub9ac \ucd5c\uc801\ud654 \ud504\ub85c\uadf8\ub7a8\uc744 \uad6c\ucd95\ud569\ub2c8\ub2e4. Catalyst\ub294 Scala\ub85c \uc4f4 \uae30\ub2a5\uc131 \ud504\ub85c\uadf8\ub798\ubc0d \uad6c\uc870\ub97c \uae30\ubc18\uc73c\ub85c \ud558\uba70 \ub2e4\uc74c\uacfc \uac19\uc740 \ub450 \uac00\uc9c0 \uc6a9\ub3c4\ub97c \uc5fc\ub450\uc5d0 \ub450\uace0 \uace0\uc548\ud558\uc600\uc2b5\ub2c8\ub2e4.\nSpark SQL\uc5d0 \uc0c8\ub85c\uc6b4 \ucd5c\uc801\ud654 \uae30\ubc95\uacfc \ud2b9\uc9d5\uc744 \uc190\uc27d\uac8c \ucd94\uac00\n\ucd5c\uc801{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Databricks Runtime Databricks Runtime\uc740 Databricks\uc5d0\uc11c \uad00\ub9ac\ud558\ub294 \uba38\uc2e0 \ud074\ub7ec\uc2a4\ud130\uc5d0\uc11c \uc2e4\ud589\ub418\ub294 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc544\ud2f0\ud329\ud2b8 \uc138\ud2b8\uc785\ub2c8\ub2e4. \uc5ec\uae30\uc5d0\ub294 Spark\ub3c4 \ud3ec\ud568\ud558\uc9c0\ub9cc \uc774\uc678\uc5d0\ub3c4 \uc5ec\ub7ec \uad6c\uc131\uc694\uc18c\uc640 \uc5c5\ub370\uc774\ud2b8\ub97c \ucd94\uac00\ud558\uc5ec \ube45\ub370\uc774\ud130 \ubd84\uc11d\uc758 \uc0ac\uc6a9\uc131, \uc131\ub2a5\uacfc \ubcf4\uc548\uc744 \ub300\ud3ed \uac1c\uc120\ud574\uc90d\ub2c8\ub2e4. \uc8fc\ub41c \ucc28\ubcc4\uc810\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.\nDBIO\ub85c \uc131\ub2a5 \uac1c\uc120:&nbsp;Databricks I\/O \ubaa8\ub4c8, \uc989 DBIO\ub294 \uc218\uc9c1\uc73c\u0000\ub85c \ud1b5\ud569\ub41c \uc2a4\ud0dd\uc744 \ud65c\uc6a9\ud574 \ud074\ub77c\uc6b0\ub4dc \ub0b4 Spark\uc758 \uc131\ub2a5\uc744{...}DataFrames DataFrame\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nDataFrame\uc774\ub780 \ub370\uc774\ud130\ub97c \ud589\uacfc \uc5f4\ub85c \uad6c\uc131\ub41c 2\ucc28\uc6d0 \ud45c(\uc2a4\ud504\ub808\ub4dc\uc2dc\ud2b8\uc640 \ube44\uc2b7)\ub85c \uc815\ub9ac\ud558\ub294 \ub370\uc774\ud130 \uad6c\uc870\uc785\ub2c8\ub2e4. DataFrame\uc740 \ucd5c\uc2e0 \ub370\uc774\ud130 \ubd84\uc11d\uc5d0\uc11c \uac00\uc7a5 \ubcf4\ud3b8\uc801\uc73c\ub85c \uc4f0\uc774\ub294 \ub370\uc774\ud130 \uad6c\uc870 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4. \uc720\uc5f0\ud558\uace0 \uc9c1\uad00\uc801\uc778 \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130\ub97c \uc800\uc7a5\ud558\uace0 \uc791\uc5c5\uc774 \uac00\ub2a5\ud558\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4.\n\uac01 DataFrame\uc5d0\ub294&nbsp;\uc2a4\ud0a4\ub9c8\ub77c\uace0 \ud558\ub294 \ube14\ub8e8\ud504\ub9b0\ud2b8\uac00 \uc788\uc5b4\uc11c, \uac01 \uc5f4\uc758 \uc774\ub984\uacfc \ub370\uc774\ud130 \uc720\ud615\uc744 \uc815\uc758\ud569\ub2c8\ub2e4. Spark {...}Datasets Dataset\ub294 Spark\uc758 Java \ubc0f Scala\uc6a9 \uad6c\uc870\uc801 API\uc758 type-safe \ubc84\uc804\uc785\ub2c8\ub2e4. \uc774 API\ub294 Python\uacfc R\uc5d0\uc11c\ub294 \uc774\uc6a9\ud560 \uc218 \uc5c6\ub294\ub370, \uc774 \ub458\uc740 \ub3d9\uc801 \ud0c0\uc774\ud551(dynamically typed) \uc5b8\uc5b4\uc774\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4. \ud558\uc9c0\ub9cc Scala\uc640 Java\uc5d0\uc11c \ub300\ud615 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc4f0\ub294 \ub370\uc5d0\ub294 \uc544\uc8fc \uac15\ub825\ud55c \ud234\uc785\ub2c8\ub2e4. DataFrame\uc774 \uc720\ud615 Row \uac1c\uccb4\ub85c \uad6c\uc131\ub41c \ubd84\uc0b0\ud615 \uceec\ub809\uc158\uc774\ub77c\uace0 \uc5b8\uae09\ud55c \uc801\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\u0000\u0000\uae30\uc5d0 \ub2e4\uc591\ud55c \uc720\ud615\uc758 \ud14c\uc774\ube14 \ud615\uc2dd \ub370\uc774{...}Genomics \uc720\uc804\uccb4\ud559(Genomics)\uc740 \uc720\uae30\uccb4\uc758 \uc720\uc804\uccb4(\uac8c\ub188) \uc11c\uc5f4, \ubd84\uc11d\uacfc \uad00\ub828\ub41c \uc720\uc804\ud559\uc758 \ud55c \ubd84\uc57c\uc785\ub2c8\ub2e4. \uc774 \ud559\ubb38\uc758 \uc8fc\ub41c \ubaa9\uc801\uc740 DNA\uc758 \uc804\uccb4 \uc11c\uc5f4, DNA\ub97c \uad6c\uc131\ud558\ub294 \uc6d0\uc790\uc758 \uad6c\uc131\uc774\ub098 \uc5ec\ub7ec DNA \uc6d0\uc790 \uc0ac\uc774\uc758 \ud654\ud559\uc801 \uacb0\ud569 \ud615\ud0dc\ub97c \uc54c\uc544\ub0b4\ub294 \ub370 \uc788\uc2b5\ub2c8\ub2e4. \uc720\uc804\uccb4\ud559\uc740 \uc720\uc804\uccb4\ub97c \ud558\ub098\uc758 \uc644\uc804\ud55c \uad6c\uc870\ub85c \ubcf4\ub294 \ud559\ubb38\uc785\ub2c8\ub2e4. \ub530\ub77c\uc11c \uc5b4\ub5a4 \uc720\uae30\uccb4\uc758 \uc804\uccb4\uc801\uc778 \uc720\uc804 \ud615\uc9c8\uc744 \uc5f0\uad6c\ud558\ub294 \ud559\ubb38\uc774\ub77c\uace0 \uc815\uc758\ud560 \uc218 \uc788\uaca0\uc2b5\ub2c8\ub2e4. DNA\ub97c \uc0ac\uc0c1 \ucd5c\ucd08\ub85c \ubd84\ub9ac\ud55c \uac83\uc740 1869\ub144\uc758 \uc77c\uc774\uc9c0\ub9cc, {...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hosted Spark Hosted Spark\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Spark\ub294 \uc18d\ub3c4, \uc0ac\uc6a9 \ud3b8\uc774\uc131\uacfc \uace0\uae09 \ubd84\uc11d\uc744 \uc911\uc2ec\uc73c\ub85c \uad6c\ucd95\ub41c \ube45\ub370\uc774\ud130\uc6a9 \uace0\uc18d, \uc77c\ubc18 \ud074\ub7ec\uc2a4\ud130 \ucef4\ud4e8\ud305 \uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4. 2009\ub144\uc5d0 UC \ubc84\ud074\ub9ac\uc5d0\uc11c \ucc98\uc74c \uad6c\ucd95\ub418\uc5c8\uc2b5\ub2c8\ub2e4. Scala, Java, Python\uacfc R\uc5d0\uc11c \uace0\uc218\uc900 API\ub97c \uc81c\uacf5\ud558\uba70 \ub370\uc774\ud130 \ubd84\uc11d\uc5d0 \uc801\ud569\ud55c \ubc94\uc6a9 \uc5f0\uc0b0 \uadf8\ub798\ud504\ub97c \uc9c0\uc6d0\ud558\ub294 \ucd5c\uc801\ud654 \uc5d4\uc9c4\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \uc774\uc678\uc5d0\ub3c4 SQL\uacfc DataFrame\uc6a9 Spark SQL, \uba38\uc2e0 \ub7ec\ub2dd\uc6a9 MLlib,{...}Jupyter Notebook Jupyter Notebook\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nJupyter Notebook\uc740 \uc624\ud508 \uc18c\uc2a4 \uc6f9 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc73c\ub85c, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\uac00 \ub77c\uc774\ube0c \ucf54\ub4dc, \uc2dd, \uae30\ud0c0 \uba40\ud2f0\ubbf8\ub514\uc5b4 \ub9ac\uc18c\uc2a4\ub97c \ud3ec\ud568\ud558\uc5ec \ubb38\uc11c\ub97c \uc0dd\uc131 \ubc0f \uacf5\uc720\ud558\ub294 \ub370 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\nJupyter Notebook\uc740 \uc5b4\ub5a4 \uc6a9\ub3c4\ub85c \uc0ac\uc6a9\ud558\ub098\uc694?\nJupyter Notebook\uc740 \ud0d0\uc0c9\uc801 \ub370\uc774\ud130 \ubd84\uc11d(EDA), \ub370\uc774\ud130 \uc815\ub9ac \ubc0f \ubcc0\ud658, \ub370\uc774\ud130 \uc2dc\uac01\ud654, \ud1b5\uacc4\uc801 \ubaa8\ub378\ub9c1, \uba38\uc2e0 \ub7ec\ub2dd, {...}Keras \ubaa8\ub378 Keras \ubaa8\ub378\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nKeras\ub294 Theano\uc640&nbsp;Tensorflow&nbsp;\uae30\ubc18\uc758 \ub525\ub7ec\ub2dd\uc6a9 \uace0\ucc28\uc6d0 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. Python \uc5b8\uc5b4\ub85c \uc4f0\uc5ec \uad11\ubc94\uc704\ud55c \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uae54\ub054\ud558\uace0 \ud3b8\ub9ac\ud558\uac8c \uc81c\uc791\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.&nbsp;Keras\ub294 \uc2e0\uacbd\ub9dd \uac1c\ubc1c, \ud14c\uc2a4\ud2b8\uc5d0 \uad00\ud55c \ud55c \uac00\uc7a5 \uc560\uc6a9\ub418\ub294 \uace0\uc218\uc900 \uc2e0\uacbd\ub9dd API \uc911 \ud558\ub098\ub85c \uc790\ub9ac \uc7a1\uc558\uc2b5\ub2c8\ub2e4. Keras \uace0\uc218\uc900 API \ub355\ubd84\uc5d0 \uc694\uc998\uc740 \uc2e0\uacbd\ub9dd \uacc4\uce35\uc744 \uc0dd\uc131\ud558\uace0 \ubcf5\uc7a1\ud55c \uc544\ud0a4\ud14d\ucc98\ub97c \uc124\uc815\ud558\ub294 \uac83\ucbe4\uc740 \uac04{...}Managed Spark Managed Spark\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nManaged Spark \uc11c\ube44\uc2a4\ub97c \uc774\uc6a9\ud558\uba74 \uc77c\uad04 \ucc98\ub9ac, \ucffc\ub9ac, \uc2a4\ud2b8\ub9ac\ubc0d\uacfc \uba38\uc2e0 \ub7ec\ub2dd \ub4f1\uc744 \uc704\ud55c \uc624\ud508 \uc18c\uc2a4 \ub370\uc774\ud130 \ud234\uc744 \uc720\ub9ac\ud558\uac8c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uc790\ub3d9\ud654 \uae30\ub2a5\uc744 \uc774\uc6a9\ud558\uba74 \ud544\uc694\uc5d0 \ub530\ub77c \uc2e0\uc18d\ud558\uac8c \ud074\ub7ec\uc2a4\ud130\ub97c \ub9cc\ub4e4\uc5b4 \uac04\ud3b8\ud558\uac8c \uad00\ub9ac\ud558\uace0, \uc791\uc5c5\uc774 \uc644\ub8cc\ub418\uba74 \ub04c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c \uc6cc\ud06c\ub85c\ub4dc, \uc131\ub2a5 \uc694\uad6c\uc0ac\ud56d\uc5d0 \ub530\ub77c\uc11c\ub098 \uae30\uc874 \ub9ac\uc18c\uc2a4\ub97c \ubc14\ud0d5\uc73c\ub85c \ud074\ub7ec\uc2a4\ud130 \ud06c\uae30\ub97c \uc870\uc815\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \ubfd0\ub9cc \uc544\ub2c8\ub77c \uc644\uc804\ud55c Mana{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}ML \ud30c\uc774\ud504\ub77c\uc778 \uc77c\ubc18\uc801\uc73c\ub85c \uba38\uc2e0 \ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uc744 \uc2e4\ud589\ud560 \ub54c\ub294 \uc804\ucc98\ub9ac, \uae30\ub2a5 \ucd94\ucd9c, \uc801\ud569\ud55c \ubaa8\ub378 \ucc3e\uae30(model fitting) \uacfc \uac80\uc99d \ub2e8\uacc4\ub85c \uad6c\uc131\ub41c \uc2dc\ud000\uc2a4\ub97c \uac70\uccd0\uc57c \ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \ud14d\uc2a4\ud2b8 \ubb38\uc11c\ub97c \ubd84\ub958\ud558\ub294 \uacbd\uc6b0, \ud14d\uc2a4\ud2b8 \uc870\uac01\ud654\uc640 \uc815\ub9ac, \ud2b9\uc9d5 \ucd94\ucd9c, \uad50\ucc28 \uac80\uc99d\uc744 \ud1b5\ud55c \ubd84\ub958 \ubaa8\ub378 \uad50\uc721 \ub4f1\uc758 \uc791\uc5c5\uc744 \uac70\uce58\uac8c \ub429\ub2c8\ub2e4. \uac01 \ub2e8\uacc4\uc5d0 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ub9ce\uc9c0\ub9cc, \ub2e8\ud3b8\uc801\uc778 \uc815\ubcf4\ub97c \uc5f0\uacb0\ud574 \uacb0\ub860\uc744 \ub0b4\uae30\ub780 \ubcf4\uae30\ubcf4\ub2e4 \uc5b4\ub824\uc6b8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \ub300\uaddc\ubaa8 Dataset\uc778 \uacbd\uc6b0{...}MLOps MLOps\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nMLOps\ub294 \uba38\uc2e0 \ub7ec\ub2dd \uc791\uc5c5(Machine Learning Operations)\uc744 \ub73b\ud569\ub2c8\ub2e4. MLOps\ub294 \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc744 \ud504\ub85c\ub355\uc158\uc73c\ub85c \uc804\ud658\ud558\ub294 \ud504\ub85c\uc138\uc2a4\ub97c \uac04\uc18c\ud654\ud558\uace0, \ub4a4\uc774\uc5b4 \uc774\ub97c \uc720\uc9c0\uad00\ub9ac\ud558\uace0 \ubaa8\ub2c8\ud130\ub9c1\ud558\ub294 \ub370 \uc8fc\uc548\uc810\uc744 \ub454 \uba38\uc2e0 \ub7ec\ub2dd \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc758 \ud575\uc2ec \uae30\ub2a5\uc785\ub2c8\ub2e4. MLOps\ub294 \ud611\uc5c5 \uae30\ub2a5\uc774\uba70, \uc8fc\ub85c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8, DevOps \uc5d4\uc9c0\ub2c8\uc5b4, IT\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.\nMLOps\uc758 \uc6a9\ub3c4\ub294 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nMLO{...}Pandas Dataframe \n\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubd84\uc57c\uc5d0\uc11c pandas DataFrame\uc73c\ub85c \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc758 \ubaa8\ub4e0 \uc7a0\uc7ac\ub825\uc744 \uc774\ub04c\uc5b4 \ub0b8\ub2e4\uba74 \uae30\uc5c5\uc758 \uc5c5\ubb34 \ubc29\uc2dd\uc744 \ud601\uc2e0\ud560 \uc218 \uc788\ub2e4\ub294 \ub9d0\uc740 \uacfc\uc7a5\uc774 \uc544\ub2d9\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574\uc11c\ub294 \uc801\ud569\ud55c \ub370\uc774\ud130 \uad6c\uc870\uac00 \ud544\uc694\ud558\uba70 \uc801\ud569\ud55c \ub370\uc774\ud130 \uad6c\uc870\ub97c \uc0ac\uc6a9\ud558\uba74 \ub370\uc774\ud130\ub97c \uc870\uc791\ud558\uace0 \ubd84\uc11d\ud558\uba74\uc11c \ud6a8\uc728\uc131\uc744 \uadf9\ub300\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc774\ub7ec\ud55c \ubaa9\uc801\uc744 \uc704\ud574 \uc0ac\uc6a9 \uac00\ub2a5\ud55c \uac00\uc7a5 \uc720\uc6a9\ud55c \ub370\uc774\ud130 \uad6c\uc870 \uc911 \ud558\ub098\uac00 pandas DataFrame\uc785\ub2c8\ub2e4.\npandas\ub294 Pyth{...}Parquet Parquet\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Parquet\ub294 \ud6a8\uc728\uc801\uc778 \ub370\uc774\ud130 \uc2a4\ud1a0\ub9ac\uc9c0\uc640 \uac80\uc0c9\uc744 \uc9c0\uc6d0\ud558\ub3c4\ub85d \uc124\uacc4\ub418\uc5c8\uc73c\uba70, \uceec\ub7fc \uc911\uc2ec\uc758 \uc624\ud508 \uc18c\uc2a4 \ub370\uc774\ud130 \ud30c\uc77c \ud615\uc2dd\uc785\ub2c8\ub2e4. \ubcf5\uc7a1\ud55c \ub370\uc774\ud130\ub97c \uc77c\uad04\uc801\uc73c\ub85c \ucc98\ub9ac\ud558\ub294 \uae30\ub2a5\uc744 \ub354\uc6b1 \ud5a5\uc0c1\ud558\uc5ec \ud6a8\uc728\uc801\uc778 \ub370\uc774\ud130 \uc555\ucd95 \ubc0f \uc778\ucf54\ub529 \ubc29\uc2dd\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. Apache Parquet\ub294 \ubc30\uce58 \ubc0f \uc778\ud130\ub799\ud2f0\ube0c \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \uacf5\ud1b5\uc801\uc778 \uc0c1\ud638 \uad50\ud658 \ud615\uc2dd\uc744 \uc81c\uacf5\ud558\ub3c4\ub85d \uc124\uacc4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.&nbsp;\ud558\ub461\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \ub2e4\ub978 \uceec\ub7fc\ud615 \uc2a4\ud1a0\ub9ac\uc9c0 \ud30c\uc77c \ud615{...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}PyCharm PyCharm\uc740 \ucef4\ud4e8\ud130 \ud504\ub85c\uadf8\ub798\ubc0d\uc5d0 \uc4f0\uc774\ub294 \ud1b5\ud569\ud615 \uac1c\ubc1c \ud658\uacbd(Integrated Development Environment, IDE)\uc73c\ub85c Python \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\uc5d0 \ub9de\uac8c \uc81c\uc791\ub418\uc5c8\uc2b5\ub2c8\ub2e4. Databricks\uc5d0\uc11c PyCharm\uc744 \uc0ac\uc6a9\ud558\ub294 \uacbd\uc6b0, PyCharm\uc774 \uae30\ubcf8\uc801\uc73c\ub85c Python \uac00\uc7a5 \ud658\uacbd\uc744 \ub9cc\ub4e4\uc9c0\ub9cc \uc0ac\uc6a9\uc790\uac00 \uad6c\uc131\uc744 \ud1b5\ud574 Conda \ud658\uacbd\uc744 \ub9cc\ub4e4\ub3c4\ub85d \ud560 \uc218\ub3c4 \uc788\uace0 \uae30\uc874 \ud658\uacbd\uc744 \uc0ac\uc6a9\ud574\ub3c4 \ub429\ub2c8\ub2e4.\n{...}PySpark PySpark\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Spark\ub294 Scala \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\ub85c \uc791\uc131\ub418\uc5c8\uc2b5\ub2c8\ub2e4 PySpark\ub294 Apache Spark\uc640 Python\uc758 \uacf5\ub3d9 \uc791\uc5c5\uc744 \uc9c0\uc6d0\ud558\uae30 \uc704\ud574 \ub9b4\ub9ac\uc2a4\ub418\uc5c8\uc73c\uba70, \uc0ac\uc2e4\uc0c1 Spark\uc6a9 Python API\uc758 \uc77c\uc885\uc785\ub2c8\ub2e4. \ub610\ud55c PySpark\ub97c \uc0ac\uc6a9\ud558\uba74 Apache Spark\uc640 Python \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\ub85c RDD(Resilient Distributed Datasets)\uc5d0 \uc811\uc18d\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 P{...}Resilient Distributed Dataset (RDD) RDD\ub294 \ucc98\uc74c \uc0dd\uacbc\uc744 \ub54c\ubd80\ud130 Spar\uc758 \uae30\ubcf8 \uc0ac\uc6a9\uc790 \ub300\uc0c1(user-facing) API\uc600\uc2b5\ub2c8\ub2e4. RDD\ub294 \ubcf8\uc9c8\uc801\uc73c\ub85c \ub370\uc774\ud130\uc758 \uc5ec\ub7ec \uc694\uc18c\ub97c \ubaa8\uc740 \ubcc0\uacbd \ubd88\uac00\ub2a5\ud55c(immutable) \ubd84\uc0b0\ud615 \uceec\ub809\uc158\uc785\ub2c8\ub2e4. \ud074\ub7ec\uc2a4\ud130 \ub0b4 \uc5ec\ub7ec \ub178\ub4dc\uc5d0 \uac78\uccd0 \ubd84\ud560\ub41c \ud615\ud0dc\ub85c \ubcc0\ud658\uc774\ub098 \uc791\uc5c5\uc744 \uc81c\uacf5\ud558\ub294 \uc800\uc218\uc900 API\uc640 \ub3d9\uc2dc\uc5d0 \uc791\uc5c5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\nRDD\ub97c \uc0ac\uc6a9\ud574\uc57c \ud560 \ub54c\ub97c \uacb0\uc815\uc9d3\ub294 5\uac00\uc9c0 \uc774\uc720\nDataset\uc5d0\uc11c \uc800\uc218\u0000\uc900 \ubcc0\ud658, \uc791\uc5c5\uacfc \uc81c\uc5b4\ub97c \uc6d0\ud558\ub294 \uacbd\uc6b0.\n\ub370\uc774\ud130{...}Spark API Spark\ub97c \ub2e4\ub8e8\ub2e4 \ubcf4\uba74 \ub2e4\uc74c\uacfc \uac19\uc740 \uc138 \uac00\uc9c0 API\ub97c \uc811\ud558\uac8c \ub429\ub2c8\ub2e4. DataFrame, Dataset \uadf8\ub9ac\uace0 RDD\uc758 \uc138 \uac00\uc9c0\uc785\ub2c8\ub2e4.\nRDD\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nRDD, \uc989 Resilient Distributed Datasets\ub780 \ubd84\uc0b0\ud615 \ucef4\ud4e8\ud305\uc744 \ud3ec\ud568\ud55c \ub808\ucf54\ub4dc \uceec\ub809\uc158\uc73c\ub85c \ubcf8\uc9c8\uc801\uc73c\ub85c \ub0b4\uacb0\ud568\uc131\uc774 \uc788\uace0 \ubcc0\uacbd \ubd88\uac00\ub2a5\ud569\ub2c8\ub2e4. \uc800\uc218\uc900 API\uc640 \ubcd1\ub825 \ubc29\uc2dd\uc73c\ub85c \uc6b4\uc601\ud560 \uc218 \uc788\ub294\ub370, \uc774 \uacbd\uc6b0 \uc9c0\uc5f0 \uae30\ub2a5 \ub54c\ubb38\uc5d0 Spark \uc791\uc5c5\uc774 \ube60\ub978 \uc18d\ub3c4\ub85c \uc218\ud589\ub429\ub2c8\ub2e4. {...}Spark Elasticsearch Spark Elasticsearch\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nSpark Elasticsearch\ub294 NoSQL \ubd84\uc0b0\ud615 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc758 \uc77c\uc885\uc73c\ub85c \ubb38\uc11c \uc911\uc2ec\uc801 \ubc18\uc815\ud615 \ub370\uc774\ud130\ub97c \uc800\uc7a5\ud558\uace0 \uac80\uc0c9\ud558\uace0 \uad00\ub9ac\ud569\ub2c8\ub2e4. \uc774 \ub370\uc774\ud130\ubca0\uc774\uc2a4\ub294 Apache Lucene \uae30\ubc18 GitHub \uc624\ud508 \uc18c\uc2a4 RESTful \uac80\uc0c9 \uc5d4\uc9c4\uc774\uba70 Apache License \uc57d\uad00\uc5d0 \ub530\ub77c \ub9b4\ub9ac\uc2a4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.Elasticsearch\ub294 Java \uae30\ubc18\uc774\uae30 \ub54c\ubb38\uc5d0 \uc5ec\ub7ec \uac00\uc9c0 \ub2e4\uc591\ud55c \ud615\uc2dd\uc73c\ub85c \ubb38\uc11c \ud30c\uc77c\uc744 \uac80\uc0c9 {...}Spark SQL \ub300\ub2e4\uc218\uc758 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8, \uc560\ub110\ub9ac\uc2a4\ud2b8, \uc77c\ubc18 \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4 \uc0ac\uc6a9\uc790\ub294 \ub370\uc774\ud130\ub97c \ud0d0\uc0c9\ud560 \ub54c \uc778\ud130\ub799\ud2f0\ube0c SQL \ucffc\ub9ac\uc5d0 \uc758\uc874\ud569\ub2c8\ub2e4. Spark SQL\uc740 \uad6c\uc870\uc801 \ub370\uc774\ud130 \ucc98\ub9ac\ub97c \uc704\ud55c&nbsp;Spark&nbsp;\ubaa8\ub4c8\uc785\ub2c8\ub2e4. \uc774 \ubaa8\ub4c8\uc740 \uc77c\uba85 DataFrames\ub77c\ub294 \ud504\ub85c\uadf8\ub798\ubc0d \ucd94\uc0c1\ud654\ub97c \uc81c\uacf5\ud558\uba70 \ubd84\uc0b0\ud615 SQL \ucffc\ub9ac \uc5d4\uc9c4 \uc5ed\ud560\ub3c4 \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\uac83\uc744 \uc774\uc6a9\ud558\uba74 \uc218\uc815\ub418\uc9c0 \uc54a\uc740&nbsp;\ud558\ub461&nbsp;Hive \ucffc\ub9ac\ub97c \uae30\uc874 \ubc30\ud3ec\uc640 \ub370\uc774\ud130\uc5d0\uc11c \ucd5c\ub300 100\ubc30 {...}Spark Streaming Apache Spark Streaming\uc740 Apache Spark \uc2a4\ud2b8\ub9ac\ubc0d \uc5d4\uc9c4\uc758 \uc774\uc804 \uc138\ub300\uc785\ub2c8\ub2e4. Spark Streaming\uc740 \ub354 \uc774\uc0c1 \uc5c5\ub370\uc774\ud2b8\ub418\uc9c0 \uc54a\ub294 \ub808\uac70\uc2dc \ud504\ub85c\uc81d\ud2b8\uc785\ub2c8\ub2e4. Apache Spark\uc5d0\ub294 Structured Streaming\uc774\ub77c\ub294 \uc0c8\ub86d\uace0 \uac04\ud3b8\ud55c \uc2a4\ud2b8\ub9ac\ubc0d \uc5d4\uc9c4\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uacfc \ud30c\uc774\ud504\ub77c\uc778 \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \uc704\ud574\uc11c\ub294 Spark Structured Streaming\uc744 \uc0ac\uc6a9\ud574\uc57c \ud569\ub2c8\ub2e4. Structured Streaming\uc744 \ucc38\uc870{...}Spark \uc560\ud50c\ub9ac\ucf00\uc774\uc158 Spark \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc740&nbsp;driver&nbsp;\ud504\ub85c\uc138\uc2a4 \ud558\ub098\uc640 \uc77c\ub828\uc758&nbsp;executor&nbsp;\ud504\ub85c\uc138\uc2a4\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4. driver \ud504\ub85c\uc138\uc2a4\ub294 main() \ud568\uc218\ub97c \uc2e4\ud589\ud558\uace0 \ud074\ub7ec\uc2a4\ud130 \ub0b4 \ub178\ub4dc\uc5d0 \uc704\uce58\ud558\uba70 \uc138 \uac00\uc9c0 \uc791\uc5c5\uc744 \ub2f4\ub2f9\ud569\ub2c8\ub2e4. \ud558\ub098\ub294 Spark \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uad00\ub828 \uc815\ubcf4\ub97c \uc720\uc9c0\ud558\ub294 \uac83, \uc0ac\uc6a9\uc790\uc758 \ud504\ub85c\uadf8\ub7a8\uc774\ub098 \uc785\ub825\uc5d0 \ub300\uc751\ud558\ub294 \uac83, \uadf8\ub9ac\uace0 \ub098\uba38\uc9c0 \ud558\ub098\ub294 executor(\uc7a0\uc2dc \ud6c4 \uc815\uc758\ud568) \uc791\uc5c5\uc744 \ubd84\uc11d, \ubc30\ud3ec, \uc608\uc57d\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. dri{...}Spark \ud29c\ub2dd Spark \uc131\ub2a5 \ud29c\ub2dd\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nSpark \uc131\ub2a5 \ud29c\ub2dd\uc740 \uc2dc\uc2a4\ud15c\uc774 \uc0ac\uc6a9\ud558\ub294 \uba54\ubaa8\ub9ac, \ucf54\uc5b4\uc640 \uc778\uc2a4\ud134\uc2a4\ub97c \ub300\uc0c1\uc73c\ub85c \uae30\ub85d\ud560 \uc124\uc815\uc744 \uc870\uc815\ud558\ub294 \ud504\ub85c\uc138\uc2a4\ub97c \uac00\ub9ac\ud0b5\ub2c8\ub2e4. \uc774 \ud504\ub85c\uc138\uc2a4\ub97c \uac70\uce58\uba74 Spark\uc5d0\uc11c \ud760\uc7a1\uc744 \ub370 \uc5c6\ub294 \uc131\ub2a5\uc744 \ubcf4\uc7a5\ud560 \uc218 \uc788\uc73c\uba70, Spark\uc5d0\uc11c \ub9ac\uc18c\uc2a4 \ubcd1\ubaa9 \ud604\uc0c1\uc744 \uc608\ubc29\ud558\ub294 \ud6a8\uacfc\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.\n\ub370\uc774\ud130 \uc9c1\ub82c\ud654\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uba54\ubaa8\ub9ac \uc0ac\uc6a9\ub7c9\uc744 \uc904\uc774\uae30 \uc704\ud574 Spark RDD\ub97c \uc9c1\ub82c\ud654 \ud615\uc2dd\uc73c\ub85c \uc800\uc7a5\ud574\uc57c \ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \uc9c1{...}Sparklyr Sparklyr\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nSparklyr\uc740 R\uacfc Apache Spark \uc0ac\uc774\uc5d0\uc11c \uc778\ud130\ud398\uc774\uc2a4\ub97c \uc81c\uacf5\ud558\ub294 \uc624\ud508 \uc18c\uc2a4 \ud328\ud0a4\uc9c0\uc785\ub2c8\ub2e4. \uc774\uc81c Spark \uae30\ub2a5\uc744 \ucd5c\uc2e0 R \ud658\uacbd\uc5d0\uc11c\ub3c4 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Spark\ub294 \ubd84\uc0b0\ub41c \ub370\uc774\ud130\uc640 \uc0c1\ud638\uc791\uc6a9\ud560 \uc218 \uc788\uc73c\uba74\uc11c\ub3c4 \ub808\uc774\ud134\uc2dc\uac00 \uc9e7\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4. Sparklyr\uc740 \uc778\ud130\ub799\ud2f0\ube0c \ud658\uacbd\uc5d0\uc11c \ub300\uaddc\ubaa8 Dataset\uc640 \uc0c1\ud638\uc791\uc6a9\uc744 \uc8fc\uace0\ubc1b\ub294 \ub370 \ud6a8\uacfc\uc801\uc778 \ud234\uc785\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74 R\uc758 \uce5c\uc219\ud55c \ud234\uc744 \uc774\uc6a9\ud574 Spark \ub370\uc774\ud130\ub97c {...}SparkR SparkR\uc740 Spark\uc5d0\uc11c R\uc744 \uc2e4\ud589\ud558\ub294 \ub370 \uc4f0\ub294 \ud234\uc785\ub2c8\ub2e4. \uc774\uac83\ub3c4 Spark\uc758 \ub2e4\ub978 \ubaa8\ub4e0 \uc5b8\uc5b4 \ubc14\uc778\ub529\uacfc \ub9c8\ucc2c\uac00\uc9c0\ub85c \uac19\uc740 \uc6d0\uce59\uc744 \ub530\ub985\ub2c8\ub2e4. SparkR\uc744 \uc0ac\uc6a9\ud558\ub824\uba74 \ud658\uacbd\uc5d0 \uac00\uc838\uc640 \ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uae30\ub9cc \ud558\uba74 \ub429\ub2c8\ub2e4. \uc804\ubc18\uc801\uc73c\ub85c Python API\uc640 \uc544\uc8fc \ube44\uc2b7\ud55c\ub370, Python\uc774 \uc544\ub2c8\ub77c R\uc758 \uad6c\ubb38\uc744 \ub530\ub978\ub2e4\ub294 \uc810\ub9cc \ub2e4\ub985\ub2c8\ub2e4. \ub300\uccb4\ub85c Python\uc5d0\uc11c \uc774\uc6a9 \uac00\ub2a5\ud55c \uac83\uc740 \uac70\uc758 \ubaa8\ub450 SparkR\uc5d0\uc11c\ub3c4 \uc774\uc6a9\ud560 \uc218 \uc788\ub2e4\uace0 \ubcf4\uba74 \ub429\ub2c8\ub2e4.\n{...}Sparse Tensor Python\uc740 \uc77c\uba85 numpy\ub77c\ub294 \uae30\ubcf8 \ub0b4\uc7a5 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc81c\uacf5\ud558\uc5ec \ub2e4\ucc28\uc6d0 \ubc30\uc5f4\uc744 \uc870\uc791\ud569\ub2c8\ub2e4. pytensor \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uac1c\ubc1c\ud558\ub824\uba74 \uae30\ubcf8\uc801\uc73c\ub85c \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ubd80\ud130 \uad6c\uc131\ud558\uace0 \uc0ac\uc6a9\ud574\uc57c \ud569\ub2c8\ub2e4.&nbsp;Sptensor\ub294 \ud76c\uc18c \ud150\uc11c\ub97c \ub098\ud0c0\ub0b4\ub294 \ud074\ub798\uc2a4\uc785\ub2c8\ub2e4. \ud76c\uc18c \ud150\uc11c\ub780 \ub300\ubd80\ubd84\uc758 \uc785\ub825 \ud56d\ubaa9\uc774 0\uc778 Dataset\uc785\ub2c8\ub2e4. \ub300\ud615 \ub300\uac01\uc120 \ud589\ub82c(diagonal matrix)\uc774 \ub300\ud45c\uc801\uc778 \uc608\uc785\ub2c8\ub2e4. (\uac12\uc774 0\uc778 \uc6d0\uc18c\uac00 \ub9ce\uc74c). \uc774\uac83\uc740 \ud150\uc11c \uac1c\uccb4\uc758 \uc804\uccb4 \uac12\uc744 \uc800\uc7a5\ud558\uc9c0{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming\uc740 \uc2a4\ud2b8\ub9bc \ucc98\ub9ac\uc6a9 \uace0\ucc28\uc6d0 API\uc758 \uc77c\uc885\uc73c\ub85c, Spark 2.2\uc5d0\uc11c\ub294 \ubc14\ub85c \ud504\ub85c\ub355\uc158\uc5d0 \uc801\uc6a9\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. Structured Streaming\uc744 \uc0ac\uc6a9\ud558\uba74 Spark\uc758 \uad6c\uc870\uc801 API\ub97c \uc0ac\uc6a9\ud574 \ubc30\uce58 \ubaa8\ub4dc\ub85c \uc218\ud589\ud558\ub294 \uac83\uacfc \uac19\uc740 \uc5f0\uc0b0\uc744 \uc2a4\ud2b8\ub9ac\ubc0d \ubc29\uc2dd\uc73c\ub85c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74 \ub808\uc774\ud134\uc2dc\ub97c \uc904\uc774\uace0 \uc99d\ubd84\uc2dd\uc73c\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4. Structured Streaming\uc758 \uac00\uc7a5 \uc88b\uc740 \uc810\uc740 \ucf54\ub4dc\ub97c \uc0ac\uc2e4\uc0c1 {...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API Tensorflow Estimator API\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nEstimator\ub294 \uc644\uc804\ud55c \ubaa8\ub378\uc774\uc9c0\ub9cc \uc801\uc740 \uc0ac\uc6a9\uc790\uc5d0\uac8c\ub294 \ucda9\ubd84\ud788 \uc9c1\uad00\uc801\uc73c\ub85c \ubcf4\uc785\ub2c8\ub2e4. Estimator API\ub97c \uc0ac\uc6a9\ud558\uba74 \ubaa8\ub378\uc744 \uad50\uc721\ud560 \ubc29\uc2dd, \ubaa8\ub378\uc758 \uc815\ud655\ub3c4\ub97c \ud310\ub2e8\ud560 \ubc29\uc2dd, \uc608\uce21\uc744 \uc0dd\uc131\ud560 \ubc29\uc2dd\uc744 \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.&nbsp;TensorFlow\ub294 \uc544\ub798 \uc774\ubbf8\uc9c0\uc640 \uac19\uc774 \uc5ec\ub7ec \uac1c\uc758 API \uacc4\uce35\uc73c\ub85c \uad6c\uc131\ub41c \ud504\ub85c\uadf8\ub798\ubc0d \uc2a4\ud0dd\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.&nbsp;estimator\ub294 \ub450 \uac00\uc9c0 \uc720\ud615\uc774 \uc788\uc5b4 \uc0ac\uc804\uc5d0{...}Tungsten Tungsten Project\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nTungsten\uc740 Apache Spark\uc758 \uc2e4\ud589 \uc5d4\uc9c4\uc5d0 \ubcc0\uacbd \uc0ac\ud56d\uc744 \uc801\uc6a9\ud558\uc5ec \uba54\ubaa8\ub9ac \ubc0f CPU\ub97c Spark \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \uc801\ud569\ud558\uac8c \ud6a8\uc728\uc131\uc744 \uac1c\uc120\ud558\ub294 \ub370 \uc911\uc810\uc744 \ub450\uc5b4 \uc131\ub2a5\uc744 \ucd5c\uc2e0 \ud558\ub4dc\uc6e8\uc5b4 \ud55c\ub3c4\uc5d0 \ub354 \uac00\uae5d\uac8c \ubc00\uc5b4\ubd99\uc774\uace0\uc790 \ucd94\uc9c4\ud55c \uc5c4\ube0c\ub810\ub77c \ud504\ub85c\uc81d\ud2b8\uc758 \ucf54\ub4dc\uba85\uc785\ub2c8\ub2e4.\nTungsten Project\uc758 \uc774\ub2c8\uc154\ud2f0\ube0c:\n\uba54\ubaa8\ub9ac \uad00\ub9ac\uc640 \uc774\uc9c4\uc218 \ucc98\ub9ac:&nbsp;\uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uc758\u0000\u0000\ubbf8 \uccb4\uacc4\ub97c \ud65c\uc6a9\ud558\uc5ec \uba54\ubaa8\ub9ac\ub97c{...}Unified Data Analytics Unified Data Analytics\ub294 \uc0c8\ub85c\uc6b4 \uc194\ub8e8\uc158 \uce74\ud14c\uace0\ub9ac\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \ucc98\ub9ac\ub97c AI \uae30\uc220\uacfc \ud1b5\ud569\ud558\uc5ec \uae30\uc5c5\uc5d0\uc11c AI\ub97c \ud55c\uacb0 \uc27d\uac8c \uc644\uc131\ud560 \uc218 \uc788\uac8c \uc9c0\uc6d0\ud558\uc5ec \uac01\uc790\uc758 AI \uc774\ub2c8\uc154\ud2f0\ube0c \uc9c4\ud589 \uc18d\ub3c4\ub97c \ube60\ub974\uac8c \ud574\uc90d\ub2c8\ub2e4. Unified Data Analytics\ub294 \uae30\uc5c5\uc5d0\uc11c \ub2e4\uc591\ud55c \uc0ac\uc77c\ub85c\ud615 \ub370\uc774\ud130 \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c\uc744 \uc544\uc6b0\ub974\ub294 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub418\uba70 \ubaa8\ub378 \uad6c\ucd95\uc744 \uc704\ud574 \ub808\uc774\ube14\uc774 \uc9c0\uc815\ub41c Dataset\ub97c \uc900\ube44\ud558\ub294 \ub370 \uc720\uc775\ud569\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74{...}Unified Data Analytics Platform Databricks\uc758&nbsp;Unified Data Analytics Platform\uc744 \uc774\uc6a9\ud558\uba74&nbsp;\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\ub97c \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ube44\uc988\ub2c8\uc2a4\uc640 \ud1b5\ud569\ud558\uc5ec \ud601\uc2e0\uc758 \uc18d\ub3c4\ub97c \ub192\uc5ec\uc90d\ub2c8\ub2e4. Databricks\ub97c Unified Data Analytics Platform\uc73c\ub85c \ud65c\uc6a9\ud558\uba74 \uc544\ubb34\ub7f0 \ud55c\uacc4 \uc5c6\uc774 \uc5c4\uccad\ub09c \uaddc\ubaa8\ub85c \ub370\uc774\ud130\ub97c \uc2e0\uc18d\ud558\uac8c \uc900\ube44\ud558\uace0 \uc815\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c \uc774 \ud50c\ub7ab\ud3fc\uc744 \uc774\uc6a9\ud558\uba74 \uac01\uc885 \uc778\uacf5\uc9c0\ub2a5 \uc560\u0000\u0000\ud50c\ub9ac\ucf00\uc774\uc158 \uc804\uccb4\uc5d0 ML \ubaa8\ub378\uc744 \uc9c0\uc18d\ud574\uc11c \uad50\uc721\ud558\uace0 {...}Unified Data Warehouse Unified Data Warehouse\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uae30\uc5c5\uc758 \ud1b5\ud569 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc778 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\ub294 \ud55c \uae30\uc5c5 \uc870\uc9c1\uc758 \uac01\uc885 \ube44\uc988\ub2c8\uc2a4 \uc815\ubcf4\uac00 \ubaa8\ub450 \ubcf4\uad00\ub418\uc5b4 \uc788\uc5b4 \ud68c\uc0ac \uc804\uccb4\uc5d0\uc11c \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4. \uc624\ub298\ub0a0 \ub300\ubd80\ubd84 \uae30\uc5c5\uc5d0\uc11c\ub294 \ub370\uc774\ud130\ub97c \uc11c\ub85c \uaca9\ub9ac\ub41c \uc0ac\uc77c\ub85c\uc5d0\uc11c \uad00\ub9ac\ud558\uace0, \ub3d9\uc2dc\uc5d0 \uac19\uc740 \uc870\uc9c1\uc5d0 \uc18c\uc18d\ub41c \uc5ec\ub7ec \ud300\uc5d0\uc11c\ub3c4 \ub2e4\uc591\ud55c \ub370\uc774\ud130 \uad00\ub9ac \ud234\uc744 \uc0ac\uc6a9\ud574 \uc5ec\ub7ec \uac00\uc9c0 \uc720\ud615\uc758 \ub370\uc774\ud130\ub97c \uad00\ub9ac\ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \ub370\uc774\ud130 \ud488\uc9c8, \ub370\uc774\ud130 \ud1b5\ud569, \ub370\uc774\ud130{...}\uad6c\uccb4\ud654 \ubdf0 Databricks Delta\uc758 Delta \ud30c\uc774\ud504\ub77c\uc778\/\uad6c\uccb4\ud654 \ubdf0\nIntro\nDelta \ud30c\uc774\ud504\ub77c\uc778\uc740 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778 \uc218\uba85 \uc8fc\uae30\ub97c \uad00\ub9ac\ud560 \uc218 \uc788\ub3c4\ub85d \uc77c\ub828\uc758 API\uc640 UI\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774\uac83\uc740 \uc624\ud508 \uc18c\uc2a4 \ud504\ub808\uc784\uc6cc\ud06c\ub85c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ud300\uc5d0\uc11c ETL \uac1c\ubc1c\uc744 \uac04\uc18c\ud654\ud558\uace0 \ub370\uc774\ud130 \uc548\uc815\uc131\uc744 \uac1c\uc120\ud558\uba70 \uc6b4\uc601\uc744 \ud655\uc7a5\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4.&nbsp;\ub370\uc774\ud130 \ubcc0\ud658\uc744 \uc704\ud574 \ucf54\ub529\ud558\uace0 \uc791\uc5c5\uc744 \uc608\uc57d\ud558\ub294 \ubc29\uc2dd\uc774 \uc544\ub2c8\ub77c, \uc120\uc5b8\uc801 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc5ec \uc5ec\ub7ec\ubd84\uc774 \uc6d0\ud558\ub294{...}\ub300\uccb4 \ub370\uc774\ud130 \ub300\uccb4 \ub370\uc774\ud130\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub300\uccb4 \ub370\uc774\ud130(Alternative data)\ub294 \ub0a8\ub4e4\uc774 \uc0ac\uc6a9\ud558\uc9c0 \uc54a\ub294, \ube44\uc77c\ubc18\uc801\uc778 \uc815\ubcf4 \ucd9c\ucc98\ub97c \uac00\ub9ac\ud0a4\ub294 \ub300\uc548\uc801(alternative) \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \uc0ac\uc6a9\ud574 \uc218\uc9d1\ud55c \uc815\ubcf4\uc785\ub2c8\ub2e4. \ub300\uccb4 \ub370\uc774\ud130\ub97c \ubd84\uc11d\ud558\uba74 \uc5c5\uacc4\uc758 \ud3c9\ubc94\ud55c \ub370\uc774\ud130 \uc18c\uc2a4\uac00 \uc81c\uacf5\ud560 \uc218 \uc788\ub294 \ubc94\uc704\ub97c \ubc97\uc5b4\ub09c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\ub9cc \uc815\ud655\ud788 \ubb34\uc5c7\uc744 \ub300\uccb4 \ub370\uc774\ud130\ub85c \uac04\uc8fc\ud574\uc57c \ud558\ub294\uc9c0\ub294 \uc5c5\uc885\ub9c8\ub2e4 \ub2e4\ub985\ub2c8\ub2e4. \uc774 \uac1c\ub150\uc758 \uc815\uc758\ub294 \uc6b0\ub9ac \ud68c\uc0ac\ub098 \uacbd\uc7c1\uc0ac\uac00 \uc774\ubbf8 \uc0ac\uc6a9 \uc911\uc778 \uae30{...}\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub780 \ubb34\uc5c7\uc778\uac00\uc694?\n\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub294&nbsp;\ub370\uc774\ud130\uac00 \uac00\uce58\ub97c \ucc3d\ucd9c\ud558\ub294\uc9c0 \ud655\uc778\ud558\ub294&nbsp;\uac10\ub3c5 \ud589\uc704\uc774\uba70,&nbsp;\ube44\uc988\ub2c8\uc2a4 \uc804\ub7b5\uc744 \uc9c0\uc6d0\ud558\ub294 \ud65c\ub3d9\uc785\ub2c8\ub2e4.&nbsp;\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub294 \ub2e8\uc21c\ud55c \ub3c4\uad6c\ub098 \ud504\ub85c\u0000\u0000\uc138\uc2a4\uac00 \uc544\ub2d9\ub2c8\ub2e4. \uc0ac\ub78c, \ud504\ub85c\uc138\uc2a4, \uae30\uc220, \ub370\uc774\ud130\uc640 \uad00\ub828\ud558\uc5ec \ube44\uc988\ub2c8\uc2a4 \ubaa9\ud45c\uc640 \ubaa9\uc801\uc744 \uc9c0\uc6d0\ud558\ub294 \ubb38\ud654\uc5d0 \ucd08\uc810\uc744 \ub9de\ucd94\uace0, \ud504\ub808\uc784\uc6cc\ud06c\ub97c \ud1b5\ud574 \ube44\uc988\ub2c8\uc2a4 \uc804\ub7b5\uc5d0 \ub370\uc774\ud130 \uad00\ub828 \uc694\uad6c \uc0ac\ud56d\uc744 \uc77c\uce58\uc2dc\ud0b5\ub2c8\ub2e4.\n\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub294 \ube44\uc988\ub2c8\uc2a4\uc5d0 \uc5b4\ub5a4 \uc7a5\uc810{...}\ub370\uc774\ud130 \uacf5\uc720 \ub370\uc774\ud130 \uacf5\uc720\ub780 \ubb34\uc5c7\uc778\uac00\uc694?\nData sharing\uc740 \ud558\ub098 \ub610\ub294 \uc5ec\ub7ec \uba85\uc758 \uace0\uac1d\uc5d0\uac8c \uac19\uc740 \ub370\uc774\ud130\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\ub294 \uae30\ub2a5\uc785\ub2c8\ub2e4. \uc694\uc998 \ub4e4\uc5b4\uc11c\ub294 \uc5b4\ub290 \ud68c\uc0ac\uc5d0\uc11c\ub098 \uc9c0\uc18d\uc801\uc73c\ub85c \ub298\uc5b4\ub098\ub294 \ubc29\ub300\ud55c \ub370\uc774\ud130 \uc790\uccb4\uac00 \uc804\ub7b5\uc801 \uc790\uc0b0\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc870\uc9c1 \uc548\ud30e\uc73c\ub85c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud558\ub294 \uac83\uc740 \uc0c8\ub85c\uc6b4 \uc0ac\uc5c5 \uae30\ud68c\ub97c \ubc1c\uacac\ud560 \uc218 \uc788\ub3c4\ub85d&nbsp;\ub3c4\uc640\uc8fc\ub294 \uae30\uc220\uc774\uae30\ub3c4 \ud569\ub2c8\ub2e4. \uc678\ubd80 \uc18c\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc740 \ubb3c\ub860\uc774\uace0, \ub370\uc774\ud130\ub97c \uacf5\uc720\ud558\uba74 \u200b\u200b\ud30c\ud2b8\ub108\uc640 \ud611\uc5c5\ud560 \uc218 \uc788\uc73c\uba70, \uc0c8\ub85c\uc6b4 {...}\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294&nbsp;\ub370\uc774\ud130 \ub808\uc774\ud06c\uac00 \uac00\uc9c0\uace0 \uc788\ub294 \uc720\uc5f0\uc131, \ube44\uc6a9 \ud6a8\uc728\uc131, \uadf8\ub9ac\uace0 \ub300\uc6a9\ub7c9 \uc9c0\uc6d0 \uae30\ub2a5\uc5d0 \ub354\ud574, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \ub370\uc774\ud130 \uad00\ub9ac \uae30\ub2a5\uacfc ACID \ud2b8\ub79c\uc7ad\uc158\uc744 \ud1b5\ud569\ud55c \uc0c8\ub85c\uc6b4 \ud615\ud0dc\uc758 \uc624\ud508 \ub370\uc774\ud130 \uad00\ub9ac \uc544\ud0a4\ud14d\ucc98\ub85c, \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \ub300\uc0c1\uc73c\ub85c \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4(BI)\uc640 \uba38\uc2e0 \ub7ec\ub2dd(ML)\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4: \ub2e8\uc21c\ud568, \uc720\uc5f0\ud568 \uadf8\ub9ac\uace0 \uc800\ub834\ud55c \ube44\uc6a9\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 \uc0c8\ub85c\uc6b4 {...}\ub370\uc774\ud130 \ubcfc\ud2b8 \ub370\uc774\ud130 \ubcfc\ud2b8\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub370\uc774\ud130 \ubcfc\ud2b8\ub294 \uc5d4\ud130\ud504\ub77c\uc774\uc988\uae09 \ubd84\uc11d\uc744 \uc704\ud55c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ub97c \uad6c\ucd95\ud558\ub294 \ub370 \uc0ac\uc6a9\ub418\ub294 \ub370\uc774\ud130 \ubaa8\ub378\ub9c1 \uc124\uacc4 \ud328\ud134\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \ubcfc\ud2b8\ub294 \ud5c8\ube0c, \ub9c1\ud06c, \uc704\uc131, \uc774\ub807\uac8c \uc138 \uac00\uc9c0 \uc720\ud615\uc758 \uc5d4\ud130\ud2f0\uac00 \uc788\uc2b5\ub2c8\ub2e4.\n\ud5c8\ube0c\ub294 \ud575\uc2ec \ube44\uc988\ub2c8\uc2a4 \uac1c\ub150\uc744 \ub300\ud45c\ud558\uba70, \ub9c1\ud06c\ub294 \ud5c8\ube0c \uac04\uc758 \uad00\uacc4\ub97c \ub300\ud45c\ud558\uace0, \uc704\uc131\uc740 \ud5c8\ube0c\uc640 \ud5c8\ube0c \uac04 \uad00\uacc4\uc5d0 \ub300\ud55c \uc815\ubcf4\ub97c \uc800\uc7a5\ud569\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ubcfc\ud2b8\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud328\ub7ec\ub2e4\uc784\uc744 \ucc44\ud0dd\ud558\uace0 \uc788\ub294 \uc870\uc9c1\uc5d0\uac8c \ub9e4\uc6b0 \uc801\ud569\ud55c \ub370\uc774\ud130 {...}\ub370\uc774\ud130 \ubd84\uc11d \ud50c\ub7ab\ud3fc \ub370\uc774\ud130 \ubd84\uc11d \ud50c\ub7ab\ud3fc\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ub370\uc774\ud130 \ubd84\uc11d \ud50c\ub7ab\ud3fc\uc740 \uc6a9\ub7c9\uc774 \ud06c\uace0 \ubcf5\uc7a1\ud55c \ub3d9\uc801 \ub370\uc774\ud130\ub97c \ub300\uc0c1\uc73c\ub85c \ubd84\uc11d\uc744 \uc218\ud589\ud574\uc57c \ud558\ub294 \uc11c\ube44\uc2a4\uc640 \uae30\uc220\ub85c \uad6c\uc131\ub41c \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc785\ub2c8\ub2e4. \uc774\uac83\uc744 \ud1b5\ud574 \ud68c\uc0ac\uc5d0 \uc18d\ud55c \ub2e4\uc591\ud55c \ucd9c\ucc98\ub85c\ubd80\ud130 \uc5bb\uc740 \ub370\uc774\ud130\ub97c \uac80\uc0c9, \uc870\ud569, \ub370\uc774\ud130\uc640 \uc0c1\ud638\uc791\uc6a9\uc744 \uc8fc\uace0\ubc1b\uae30\ub3c4 \ud558\uace0 \ud0d0\uc0c9, \ud45c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc885\ud569\uc801\uc778 \ub370\uc774\ud130 \ubd84\uc11d \ud50c\ub7ab\ud3fc\uc5d0\ub294 \ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \ub0b4\uc7a5\ud55c \uc5ec\ub7ec \uac00\uc9c0 \ud234\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4. \uc608\uce21 \ubd84\uc11d\uacfc \ub370\uc774\ud130 \uc2dc\uac01\ud654\ubd80\ud130 \ub85c\ucf00\uc774\uc158 \uc778\ud154\ub9ac\uc804\uc2a4(Lo{...}\ub514\uc9c0\ud138 \ud2b8\uc708 \ub514\uc9c0\ud138 \ud2b8\uc708\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uae30\uc874\uc5d0\ub294 \ub514\uc9c0\ud138 \ud2b8\uc708\uc744 \"\"\ubb3c\ub9ac\uc801 \uac1c\uccb4\ub97c \uc815\ud655\ud788 \ubc18\uc601\ud558\ub3c4\ub85d \uc124\uacc4\ub41c \uac00\uc0c1 \ubaa8\ub378\"\"\ub85c \uc815\uc758\ud588\uc2b5\ub2c8\ub2e4. \u2013 IBM[KVK4] \ub514\uc9c0\ud138 \ud2b8\uc708\uc740 \ubd84\ub9ac \ub610\ub294 \uc9c0\uc18d\uc801\uc778 \uc81c\uc870 \ud504\ub85c\uc138\uc2a4\ub97c \uc704\ud574 \ub2e4\uc591\ud55c IoT \uc13c\uc11c\ub97c \ud1b5\ud574 \uc2dc\uc2a4\ud15c \ubc0f \ud504\ub85c\uc138\uc2a4 \uc0c1\ud0dc \ub370\uc774\ud130(\uc6b4\uc601 \uae30\uc220 \ub370\uc774\ud130(OT))\ub97c \uc218\uc9d1\ud558\uace0, \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130(\uc815\ubcf4 \uae30\uc220(IT))\ub97c \uc218\uc9d1\ud558\uc5ec \uac00\uc0c1 \ubaa8\ub378\uc744 \ud615\uc131\ud569\ub2c8\ub2e4. \uc774 \uac00\uc0c1 \ubaa8\ub378\uc740 \uadf8 \ub2e4\uc74c \uc2dc\ubbac\ub808\uc774\uc158\uc744 \uc2e4\ud589\ud558\uace0 \uc131\ub2a5 \ubb38\uc81c\ub97c \uc870\uc0ac\ud558\uc5ec{...}\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub780 \ubb34\uc5c7\uc778\uac00\uc694?\n\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc740 Databricks\uc5d0\uc11c \uccab \ubc88\uc9f8\ub85c \ucd9c\uc2dc\ud55c \uc5c5\uc885\ubcc4 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4. \uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130, \ub370\uc774\ud130 \uacf5\uc720 \uae30\ub2a5\uacfc \ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud1b5\ud574 \uc18c\ub9e4\uc5c5\uccb4\uac00 \ube68\ub9ac \uc6b4\uc601\uc744 \uc815\uc0c1\ud654\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\n\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 \uae30\uc220, \ud30c\ud2b8\ub108, \ub3c4\uad6c, \uc0b0\uc5c5 \uc774\ub2c8\uc154\ud2f0\ube0c\uc758 \uc815\uc810\uc73c\ub85c\uc11c&nbsp;\ub370\uc774\ud130 + AI\ub97c \uc911\uc2ec\uc73c\ub85c \ud611\uc5c5\uc744 \uac15\ud654\ud569\ub2c8\ub2e4. \ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 4\uac00\uc9c0\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.\n\ud1b5\ud569 \ub370{...}\uba38\uc2e0 \ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac(MLlib) Apache Spark\uc758 \uba38\uc2e0 \ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac(Machine Learning Library, MLlib)\ub294 \ub2e8\uc21c\uc131, \ud655\uc7a5\uc131, \ub2e4\ub978 \ud234\uacfc\uc758 \ud1b5\ud569\uc744 \uc5fc\ub450\uc5d0 \ub450\uace0 \uace0\uc548\ud558\uc600\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\ub294 Spark\uc758 \ud655\uc7a5\uc131, \uc5b8\uc5b4 \ud638\ud658\uc131\uacfc \uc18d\ub3c4\ub97c \ud65c\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \ubb38\uc81c\uc810\uacfc \ubaa8\ub378\uc5d0\ub9cc \uc9d1\uc911\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc989 \ubd84\uc0b0\ud615 \ub370\uc774\ud130\ub97c \ub458\ub7ec\uc2fc \ubcf5\uc7a1\ud55c \ubb38\uc81c(\uc778\ud504\ub77c, \uad6c\uc131 \ub4f1)\ub97c \ud574\uacb0\ud558\ub294 \ub370 \uc2dc\uac04\uc744 \ube8f\uae30\uc9c0 \uc54a\uc544\ub3c4 \ub429\ub2c8\ub2e4. MLlib\uc740 Spark \uae30\ubc18\uc73c\ub85c \uad6c\ucd95\ub41c \ud655\uc7a5\ud560 \uc218 {...}\uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378 \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc774\ub780 \uc774\uc804\uc5d0 \uc811\ud55c \uc801 \uc5c6\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0\uc11c \ud328\ud134\uc744 \ucc3e\uac70\ub098 \uc774\ub97c \uadfc\uac70\ub85c \uacb0\uc815\uc744 \ub0b4\ub9b4 \uc218 \uc788\ub294 \ud504\ub85c\uadf8\ub7a8\uc785\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \uc790\uc5f0\uc5b4 \ucc98\ub9ac\uc758 \uacbd\uc6b0, \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc740 \ud30c\uc2f1\uc744 \ud1b5\ud574 \uc774\uc804\uc5d0 \uc811\ud55c \uc801 \uc5c6\ub294 \ubb38\uc7a5\uc774\ub098 \ub2e8\uc5b4 \uc870\ud569\uc758 \ubc30\ud6c4 \uc758\ub3c4\ub97c \uc62c\ubc14\ub85c \uc778\uc2dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uacbd\uc6b0, \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc774 \uc790\ub3d9\ucc28\ub098 \uac1c \ub4f1 \uc0ac\ubb3c\uc744 \uc778\uc2dd\ud558\ub3c4\ub85d \uad50\uc721\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378\uc740 \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \uc138\ud2b8\ub85c '\uad50\uc721'{...}\ubaa8\ub378 \ub9ac\uc2a4\ud06c \uad00\ub9ac \ubaa8\ub378 \ub9ac\uc2a4\ud06c \uad00\ub9ac\ub780 \uc798\ubabb\ub41c \ubaa8\ub378\uc774\ub098 \uc798\ubabb \uc0ac\uc6a9\ub41c \ubaa8\ub378\uc744 \uadfc\uac70\ub85c \ud55c \uc758\uc0ac \uacb0\uc815\uc73c\ub85c \uc778\ud55c \uc7a0\uc7ac\uc801\uc778 \ub098\uc05c \uacb0\uacfc\uc5d0\uc11c \ubc1c\uc0dd\ud558\ub294 \ub9ac\uc2a4\ud06c\ub97c \uac10\ub3c5 \uad00\ub9ac\ud558\ub294 \uac83\uc744 \ub9d0\ud569\ub2c8\ub2e4. \ubaa8\ub378 \ub9ac\uc2a4\ud06c \uad00\ub9ac\uc758 \ubaa9\ud45c\ub294 \ubaa8\ub378 \ub9ac\uc2a4\ud06c\ub97c \ud30c\uc545, \uacc4\uce21\ud558\uc5ec \uc644\ud654\ud560 \uae30\ubc95\uacfc \uad00\ud589\uc744 \ub3d9\uc6d0\ud558\ub294 \ub370 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \ubaa8\ub378 \uc624\ub958\ub098 \uc798\ubabb\ub41c \ubaa8\ub378 \uc0ac\uc6a9 \uac00\ub2a5\uc131\uc744 \uc54c\uc544\ub0b4\ub294 \uac83\uc785\ub2c8\ub2e4. \uae08\uc735 \uc11c\ube44\uc2a4\uc758 \uacbd\uc6b0, \ubaa8\ub378 \ub9ac\uc2a4\ud06c\ub294 \uc815\ud655\ub3c4\uac00 \ucda9\ubd84\ud558\uc9c0 \uc54a\uc740 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud574 \uc758\uc0ac \uacb0\uc815\uc744 \ub0b4\ub824 \ubc1c\uc0dd\ud558\ub294 \uc190\uc2e4 \uc704\u0000\ud5d8\uc785\ub2c8\ub2e4. {...}\ubc00\uc9d1 \ud150\uc11c \ubc00\uc9d1 \ud150\uc11c\ub294 \uc778\uc811\ud55c \uc21c\ucc28\uc801 \uba54\ubaa8\ub9ac \ube14\ub85d\uc5d0 \uac12\uc744 \uc800\uc7a5\ud558\ub294\ub370, \uc774\uacf3\uc5d0 \ubaa8\ub4e0 \uac12\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4. \ud150\uc11c, \uc989 \ub2e4\ucc28\uc6d0 \uc5b4\ub808\uc774\ub294 \ub9e4\uc6b0 \ub2e4\uc591\ud55c \ub2e4\ucc28\uc6d0 \ub370\uc774\ud130 \ubd84\uc11d \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0\uc11c \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ud150\uc11c \uc5f0\uc0b0\uc744 \uc218\ud589\ud560 \uc904 \uc544\ub294 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc81c\ud488\uc740 \ub9ce\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 MATLAB \uc2a4\uc704\ud2b8\uc758 \uacbd\uc6b0, \ub2e4\uc591\ud55c \uc624\ud508 \uc18c\uc2a4 \ud0c0\uc0ac \ud234\ubc15\uc2a4\ub85c \ubcf4\uac15\ub418\uae30\uae4c\uc9c0 \ud588\uc2b5\ub2c8\ub2e4. MATLAB \ub2e8\ub3c5\uc73c\ub85c \ub2e4\uc591\ud55c \uc694\uc18c \uad00\ub828 \uc774\uc9c4\uc218 \ubc00\uc9d1 \ud150\uc11c \uc5f0\uc0b0\uc744 \uc9c0\uc6d0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. dense \uacc4\uce35\uc740 \uc644\uc804\ud788 \uc5f0\uacb0\ub41c {...}\ubca0\uc774\uc9c0\uc548 \uc2e0\uacbd\ub9dd \ubca0\uc774\uc9c0\uc548 \uc2e0\uacbd\ub9dd\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ubca0\uc774\uc9c0\uc548 \uc2e0\uacbd\ub9dd(Bayesian Neural Networks, BNN)\uc740 \uacfc\uc801\ud569(overfitting)\uc744 \uc81c\uc5b4\ud558\uae30 \uc704\ud574 \uc0ac\ud6c4 \ucd94\ub860\uc744 \uc0ac\uc6a9\ud574 \ud45c\uc900 \ub124\ud2b8\uc6cc\ud06c\ub97c \uc5f0\uc7a5\ud55c \uac83\uc744 \uac00\ub9ac\ud0b5\ub2c8\ub2e4. \ub113\uc740 \uc758\ubbf8\uc5d0\uc11c \ubcf4\uba74 \ubca0\uc774\uc9c0\uc548 \ubc29\uc2dd\uc740 \ud1b5\uacc4\uc801\uc778 \ubc29\ubc95\ub860\uc744 \uc0ac\uc6a9\ud574 \ubaa8\ub378 \ub9e4\uac1c\ubcc0\uc218(\uc2e0\uacbd\ub9dd\uc758 \uac00\uc911\uce58\uc640 \ud3b8\ud5a5)\ub97c \ube44\ub86f\ud55c \ubaa8\ub4e0 \uac83\uc5d0 \ud655\ub960 \ubd84\ud3ec\uac00 \uc218\ubc18\ub41c\ub2e4\uace0 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\uc5d0\uc11c \ud2b9\uc815 \uac12\uc744 \ucde8\ud560 \uc218 \uc788\ub294 \ubcc0\uc218\ub294 \ud574\ub2f9 \ubcc0\uc218\uc5d0 \uc561\uc138{...}\ubcc0\ud658 \ubcc0\ud658\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nSpark\uc5d0\uc11c \ucf54\uc5b4 \ub370\uc774\ud130 \uad6c\uc870\uac00&nbsp;\ubcc0\uacbd \ubd88\uac00\ub2a5(immutable)\ud558\ub2e4\ub294 \uac83\uc740 \uc77c\ub2e8 \uc0dd\uc131\ud558\uba74 \ubcc0\uacbd\ud560 \uc218 \uc5c6\ub2e4\ub294 \ub73b\uc785\ub2c8\ub2e4. \uc774\uac83\uc740 \ucc98\uc74c\uc5d0\ub294 \uc870\uae08 \uae30\uc774\ud55c \uac1c\ub150\uc73c\ub85c \uc5ec\uaca8\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcc0\uacbd\ud560 \uc218 \uc5c6\ub2e4\uba74 \uc5b4\ub5bb\uac8c \uc0ac\uc6a9\ud569\ub2c8\uae4c? DataFrame\uc744 \"\ubcc0\uacbd\"\ud558\ub824\uba74 Spark\uc5d0 \uc9c0\uae08 \uac00\uc9c0\uace0 \uc788\ub294 DataFrame\uc744 \uc6d0\ud558\ub294 \ubc84\uc804\uc73c\ub85c \uc218\uc815\ud560 \ubc29\ubc95\uc744 \uc9c0\uc2dc\ud574\uc57c \ud569\ub2c8\ub2e4. \uc774\ub7f0 \uc9c0\uce68\uc744&nbsp;\ubcc0\ud658(transformations)\uc774\ub77c\uace0 {...}\ubcf5\ud569 \uc774\ubca4\ud2b8 \ucc98\ub9ac \ubcf5\ud569 \uc774\ubca4\ud2b8 \ucc98\ub9ac(CEP)\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\ubcf5\ud569 \uc774\ubca4\ud2b8 \ucc98\ub9ac(Complex event processing [CEP])\ub294 \ub2e4\ub978 \ub9d0\ub85c \uc774\ubca4\ud2b8, \uc2a4\ud2b8\ub9bc \ub610\ub294 \uc774\ubca4\ud2b8 \uc2a4\ud2b8\ub9bc \ucc98\ub9ac\ub77c \ud558\uba70 \uae30\uc220\uc744 \uc0ac\uc6a9\ud574 \ub370\uc774\ud130\ub97c \ucffc\ub9ac\ud55c \ub2e4\uc74c \ub370\uc774\ud130\ubca0\uc774\uc2a4 \ub0b4\uc5d0 \uc800\uc7a5\ud558\uac70\ub098, \uacbd\uc6b0\uc5d0 \ub530\ub77c\uc11c\ub294 \uc560\ucd08\uc5d0 \uc804\ud600 \uc800\uc7a5\ud558\uc9c0 \uc54a\uace0 \ucffc\ub9ac\ud558\ub294 \uac83\uc744 \ub9d0\ud569\ub2c8\ub2e4. \ubcf5\u0000\ud569 \uc774\ubca4\ud2b8 \ucc98\ub9ac\ub294 \uad6c\uc131 \ud234\uc758 \uc77c\uc885\uc73c\ub85c, \ub300\ub7c9\uc758 \uc11c\ub85c \ub2e4\ub978 \uc815\ubcf4\ub97c \uc9d1\uacc4\ud558\uba70 \uc2e4\uc2dc\uac04\uc73c\ub85c \uc5ec\ub7ec \uc774\ubca4\ud2b8 \uc0ac\uc774\uc758 \uc778\uacfc \uad00\uacc4\ub97c \uc2dd\ubcc4 \ubc0f \ubd84\uc11d{...}\ube45\ub370\uc774\ud130 \ubd84\uc11d \ub370\uc774\ud130 \ubd84\uc11d\uacfc \ube45\ub370\uc774\ud130 \ubd84\uc11d\uc758 \ucc28\uc774\n\ud558\ub461\uc774 \ubc1c\uba85\ub418\uae30 \uc804\uc5d0\ub294 \ud604\ub300\uc2dd \uc2a4\ud1a0\ub9ac\uc9c0\uc640 \ucef4\ud4e8\ud305 \uc2dc\uc2a4\ud15c\uc758 \uae30\uc800\ub97c \uc774\ub8e8\ub294 \uae30\uc220\uc774 \ube44\uad50\uc801 \uae30\ubcf8\uc801\uc774\uc5b4\uc11c, \uae30\uc5c5\uc5d0\uc11c\ub294 \ub300\ubd80\ubd84 \"\uc2a4\ubab0 \ub370\uc774\ud130\" \ubd84\uc11d\ub9cc \uac00\ub2a5\ud55c \ud55c\uacc4\uac00 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. \ub2e4\ub9cc \uc774\ub807\uac8c \ube44\uad50\uc801 \uae30\ubcf8\uc801\uc778 \ud615\ud0dc\uc758 \ubd84\uc11d\ub3c4 \uc5b4\ub824\uc6b8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130 \uc18c\uc2a4\ub97c \ud1b5\ud569\ud558\ub294 \uacbd\uc6b0 \ubd84\uc11d\uc774 \uc27d\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4. \uae30\uc874 \ub370\uc774\ud130 \ubd84\uc11d\uc758 \uacbd\uc6b0, \uc8fc\ub85c \uad00\uacc4\ud615 \ub370\uc774\ud130\ubca0\uc774\uc2a4(\uc608: SQL \ub370\uc774\ud130\ubca0\uc774\uc2a4)\ub97c \uc0ac\uc6a9\ud558\uace0 \uad6c\uc870\uc801 \ub370\uc774\ud130 \ud14c\uc774\ube14{...}\uc0dd\ubb3c\uc815\ubcf4\ud559 \uc0dd\ubb3c\uc815\ubcf4\ud559(Bioinformatics)\uc774\ub780 \uc0dd\ubb3c\ud559 \ub370\uc774\ud130\ub97c \ubaa8\uc740 \ub300\uaddc\ubaa8 \uceec\ub809\uc158\uc5d0\uc11c \uc5f0\uc0b0\uc744 \ud1b5\ud574 \uc9c0\uc2dd\uc744 \ucd94\ucd9c\ud558\ub294 \ud559\ubb38 \ubd84\uc57c\ub97c \ub9d0\ud569\ub2c8\ub2e4.\n\uc0dd\ubb3c\uc815\ubcf4\ud559\uc740 \uc0dd\ubb3c\ud559\uc801 \ub370\uc774\ud130\ub97c \uc800\uc7a5, \uac80\uc0c9, \uad6c\uc131\u0000\ud558\uace0 \ubd84\uc11d\ud558\ub294 \ub370 \uc0dd\ubb3c\uacf5\ud559 IT\ub97c \uc0ac\uc6a9\ud558\ub294 \ubd84\uc57c\ub97c \uc77c\uceeb\uc2b5\ub2c8\ub2e4. \uc720\uc804\uccb4 \uc11c\uc5f4(genome sequencing) \ud504\ub85c\uc81d\ud2b8\ub098 \uc5ec\ud0c0 \uc5f0\uad6c\uc5d0\uc11c \uc5c4\uccad\ub09c \uc591\uc758 \ub370\uc774\ud130\uac00 \uc0dd\uc131\ub418\uc5c8\ub294\ub370, \uc774 \ub370\uc774\ud130 \uc6e8\uc774\ube0c\uc758 \uacb0\uacfc \uc0dd\ubb3c\ud559 \ubd84\uc57c\uc758 \ub09c\uc81c\ub294 \ub300\ubd80\ubd84 \ucef4\ud4e8\ud305 \ucabd \ubb38\uc81c\ub85c \ubc14\ub00c\uac8c \ub418\uc5c8{...}\uc124\ube44 \uc885\ud569 \ud6a8\uc728 \uc124\ube44 \uc885\ud569 \ud6a8\uc728\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc124\ube44 \uc885\ud569 \ud6a8\uc728(Overall Equipment Effectiveness, OEE)\uc740 \uc81c\uc870 \uc791\uc5c5\uc7a5\uc774 \uc6b4\uc601\ub418\ub3c4\ub85d \uc608\uc57d\ub41c \uae30\uac04 \ub3d9\uc548 \ucd5c\ub300 \uc7a0\uc7ac\ub825 \ub300\ube44 \uc5bc\ub9c8\ub098 \ud65c\uc6a9\ub418\ub294\uc9c0(\uc2dc\uc124, \uc2dc\uac04 \ubc0f \uc790\uc7ac)\ub97c \uce21\uc815\ud55c \uac83\uc785\ub2c8\ub2e4. OEE\ub294 \uc2e4\uc81c \uc0dd\uc0b0\uc801\uc778 \uc81c\uc870 \uc2dc\uac04\uc758 \ubc31\ubd84\uc728\uc744 \ud30c\uc545\ud569\ub2c8\ub2e4. OEE\ub294 \ubd84\ub9ac\ub418\uac70\ub098 \uc5f0\uc18d\uc801\uc778 \ud504\ub85c\uc138\uc2a4\uc758 \uc804\uccb4 \uc131\uacfc\ub97c \ubcf4\uc5ec \uc8fc\ub294 \ub300\uc2dc\ubcf4\ub4dc\uc785\ub2c8\ub2e4. OEE\uc758 \ucd5c\ub300\uac12\uc740 100%\uc774\uba70, 100%\uc758 OEE\ub294 \ucd5c\ub300 \uc18d\ub3c4(10{...}\uc218\uc694 \uc804\ub9dd \uc218\uc694 \uc608\uce21\uc774\ub780 \ubb34\uc5c7\uc778\uac00\uc694?\n\uc218\uc694 \uc608\uce21\uc740 \uc18c\ube44\uc790 \uc218\uc694(=\ubbf8\ub798\uc758 \uc218\uc775)\ub97c \uc608\uce21\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4. \ud2b9\ud788, \uc1fc\ud551\uac1d\uc774 \uad6c\ub9e4\ud560 \uc81c\ud488\uad70\uc744 \uc815\ub7c9\u0000\uc801 \ub370\uc774\ud130\uc640 \uc815\uc131\uc801 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc608\uce21\ud569\ub2c8\ub2e4.\n\uc18c\ub9e4\uc5c5\uccb4\ub294 \uc18c\ube44\uc790\uac00 \uc6d0\ud558\ub294 \uc2dc\uc810\uc5d0 \uc81c\ud488\uc744 \uc81c\uacf5\ud558\uc9c0 \ubabb\ud574 1\uc870 \ub2ec\ub7ec \uaddc\ubaa8\uc5d0 \uc774\ub974\ub294 \uc218\uc775\uc744 \ub193\uce58\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc218\uc694 \uc608\uce21\uc5d0 \uc2e4\ud328\ud55c \uae30\uc5c5\uc740 \ub9e4\uc7a5\uc5d0 \uc798\ubabb\ub41c \uc81c\ud488\uc744 \uacf5\uae09\ud558\uac70\ub098 \uc2ec\uc9c0\uc5b4\ub294 \uc7ac\uace0\uac00 \ub3d9\uc774 \ub098\uae30\ub3c4 \ud569\ub2c8\ub2e4.\n\ub9ac\ud14c\uc77c\uc6a9 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub294 \uc218\uc694 \uc608\uce21\uc744 \uc5b4\ub5bb\uac8c \uc9c0{...}\uc2a4\ub178\uc6b0\ud50c\ub808\uc774\ud06c \uc2a4\ud0a4\ub9c8 \uc2a4\ub178\uc6b0\ud50c\ub808\uc774\ud06c \uc2a4\ud0a4\ub9c8\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc2a4\ub178\uc6b0\ud50c\ub808\uc774\ud06c \uc2a4\ud0a4\ub9c8\ub294 \uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub97c \ud655\uc7a5\ud55c \ub2e4\ucc28\uc6d0\uc801 \ub370\uc774\ud130 \ubaa8\ub378\ub85c, \ucc28\uc6d0 \ud14c\uc774\ube14\uc744 \ud558\uc704 \ucc28\uc6d0\uc73c\ub85c \ub098\ub215\ub2c8\ub2e4. \uc2a4\ub178\uc6b0\ud50c\ub808\uc774\ud06c \uc2a4\ud0a4\ub9c8\ub294 OLAP \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0 \ub300\ud55c \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4 \ubc0f \ubcf4\uace0, \ub370\uc774\ud130 \ub9c8\ud2b8, \uad00\uacc4\ud615 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0 \ud754\ud788 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.\n\uc2a4\ub178\uc6b0\ud50c\ub808\uc774\ud06c \uc2a4\ud0a4\ub9c8\uc5d0\uc11c \uc5d4\uc9c0\ub2c8\uc5b4\ub294 \uac1c\ubcc4 \ucc28\uc6d0 \ud14c\uc774\ube14\uc744 \ub17c\ub9ac\uc801 \ud558\uc704 \ucc28\uc6d0\uc73c\ub85c \ub098\ub215\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74 \ub370\uc774\ud130 \ubaa8\ub378\uc774 \ub354 \ubcf5\uc7a1\ud574\uc9c0\ub9cc, \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 \uc791\uc5c5\ud558\uae30\ub294 \ub354 {...}\uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8 \uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub294 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc815\ub9ac\ud558\ub294 \ub370 \uc0ac\uc6a9\ud558\ub294 \ub2e4\ucc28\uc6d0\uc801 \ub370\uc774\ud130 \ubaa8\ub378\ub85c, \uc27d\uac8c \uc774\ud574\ud558\uace0 \ubd84\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub294 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4, \ub370\uc774\ud130\ubca0\uc774\uc2a4, \ub370\uc774\ud130 \ub9c8\ud2b8 \ub4f1\uc758 \ud234\uc5d0 \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub294 \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud55c \ucffc\ub9ac\ub97c \ucd5c\uc801\ud654\ud558\ub3c4\ub85d \uc124\uacc4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.\nRalph Kimball\uc774 1990\ub144\ub300\uc5d0 \ub3c4\uc785\ud55c \uc2a4\ud0c0 \uc2a4\ud0a4\ub9c8\ub294 \ubc18\ubcf5\uc801 \ube44\uc988\ub2c8\uc2a4 \uc815\uc758\uc758 \ubcf5\uc81c\ub97c \uc904\uc5ec \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc5d0\uc11c{...}\uc2e0\uacbd\ub9dd \uc2e0\uacbd\ub9dd\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc2e0\uacbd\ub9dd\uc774\ub780 \ub1cc \uc18d \ub274\ub7f0\uc758 \ub9dd\ud615 \uad6c\uc870\ub97c \ub2ee\uc740 \ub2e4\uce35\ud615 \uad6c\uc870\uc758 \ucef4\ud4e8\ud305 \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc5ec\uae30\uc5d0\ub294 \uc11c\ub85c \uc5f0\uacb0\ub41c \ucc98\ub9ac \uc18c\uc790, \uc77c\uba85 '\ub274\ub7f0'\uc774\ub77c\ub294 \uac83\uc774 \uc788\uc73c\uba70 \uc774\ub4e4\uc774 \uc11c\ub85c \ud611\ub825\ud558\uc5ec \ucd9c\ub825 \ud568\uc218\ub97c \ub3c4\ucd9c\ud569\ub2c8\ub2e4. \uc2e0\uacbd\ub9dd\uc740 \uc785\ub825 \ubc0f \ucd9c\ub825 \uacc4\uce35\/\ucc28\uc6d0\uc73c\ub85c \uad6c\uc131\ub418\uba70 \ub300\ubd80\ubd84\uc740 \uc228\uaca8\uc9c4 \uacc4\uce35\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \uc228\uaca8\uc9c4 \uacc4\uce35\uc740 \uc785\ub825\uc744 \ucd9c\ub825 \uacc4\uce35\uc5d0\uc11c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubb34\uc5b8\uac00\ub85c \ubcc0\ud658\ud574\uc8fc\ub294 \ub2e8\uc704\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4.\n\uc2e0\uacbd\ub9dd \uc544\ud0a4\ud14d\ucc98\uc758 \uc720\ud615:\n\uc2e0\uacbd\ub9dd, \ub2e4\ub978 \ub9d0\ub85c \uc778{...}\uc2e4\uc2dc\uac04 \ub9ac\ud14c\uc77c \uc18c\ub9e4\uc5c5\uc5d0\uc11c \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\ub294 \ubb34\uc5c7\uc778\uac00\uc694?\n\uc2e4\uc2dc\uac04 \ub9ac\ud14c\uc77c(Real-time retail)\uc774\ub780 \ub370\uc774\ud130\uc5d0 \uc2e4\uc2dc\uac04 \uc561\uc138\uc2a4\ud558\ub294 \uac83\uc744 \ub9d0\ud569\ub2c8\ub2e4.&nbsp;\ubc30\uce58 \uc911\uc2ec \uc561\uc138\uc2a4, \ubd84\uc11d, \ucef4\ud4e8\ud305\uc5d0\uc11c \ubc97\uc5b4\ub098\uba74 \ub370\uc774\ud130\ub97c \"\uc5b8\uc81c\ub4e0\" \uc0ac\uc6a9\ud560 \uc218 \uc788\uc5b4 \uc815\ud655\ud558\uace0 \uc2dc\uae30\uc801\uc808\ud558\uac8c \uc758\uc0ac\uacb0\uc815\uc744 \ub0b4\ub9ac\uace0 \ube44\uc988\ub2c8\uc2a4 \uc778\ud154\ub9ac\uc804\uc2a4\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc218\uc694 \uc608\uce21, \uac1c\uc778\ud654, \uc9c4\uc5f4 \uc0c1\ud488 \uac00\uc6a9\uc131, \ub3c4\ucc29 \uc2dc\uac04 \uc608\uce21, \uc8fc\ubb38 \uc218\ub839\uacfc \ud1b5\ud569 \ub4f1\uc758 \uc2e4\uc2dc\uac04 \uc0ac\uc6a9 \uc0ac\ub840\ub294 \uacf5\uae09\ub9dd \ubbfc\ucca9\uc131\uc744 \uac1c\uc120\ud558\uace0 \uc11c\ube44\uc2a4{...}\uc608\uce21\uc801 \uc720\uc9c0\uad00\ub9ac \uc608\uce21\uc801 \uc720\uc9c0\uad00\ub9ac\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc694\ucee8\ub300, \uc608\uce21\uc801 \uc720\uc9c0 \uad00\ub9ac\ub294 \uac00\ub3d9 \uc2dc\uac04\uacfc \uc0dd\uc0b0\uc131\uc744 \uadf9\ub300\ud654\ud558\uae30 \uc704\ud574 \uace0\uc815\ub41c \uc77c\uc815\uc744 \ub530\ub974\ub294 \ub300\uc2e0 \uc790\uc0b0\uc758 \uc2e4\uc81c \uc0c1\ud0dc\ub97c \uae30\ubc18\uc73c\ub85c \uc790\uc0b0\uc758 \uc720\uc9c0 \uad00\ub9ac\uac00 \ud544\uc694\ud55c \uc2dc\uae30\uc640 \uc218\ud589\ud574\uc57c \ud558\ub294 \ud2b9\uc815 \uc720\uc9c0 \uad00\ub9ac \ud65c\ub3d9\uc744 \uc54c\uc544\ub0b4\ub294 \uac83\uc785\ub2c8\ub2e4. \uc774\ub294 \ub9ce\uc740 \ube44\uc6a9\uc744 \ucd08\ub798\ud558\ub294 \uc7a5\ube44 \ub2e4\uc6b4\ud0c0\uc784\uc744 \uc904\uc774\uae30 \uc704\ud574 \uc7a5\uc560\ub97c \uc608\uce21 \ubc0f \uc608\ubc29\ud558\uace0 \uc801\uc808\ud55c \uc720\uc9c0 \uad00\ub9ac \ub8e8\ud2f4\uc744 \uc218\ud589\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.\n\uc7a5\ube44\ub85c\ubd80\ud130 IoT \ubc0f \uc13c\uc11c \ub370\uc774\ud130\uac00 \uc2a4\ud2b8\ub9ac\ubc0d\ub418\ubbc0\ub85c \uc608\uce21\uc801 \uc720\uc9c0 \uad00\ub9ac\ub97c{...}\uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc740 \uc5ec\ub7ec \uac1c\uc758 \ucef4\ud4e8\ud130 \uc2dc\uc2a4\ud15c, \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \ubc0f\/\ub610\ub294 \uc11c\ube44\uc2a4\ub97c \uc870\uc728\ud558\uace0 \uad00\ub9ac\ud558\ub294 \uac83\uc73c\ub85c, \uc5ec\ub7ec \uac1c\uc758 \uc791\uc5c5\uc744 \ud568\uaed8 \uc5f0\uacb0\ud558\uc5ec \ud06c\uae30\uac00 \ud070 \uc6cc\ud06c\ud50c\ub85c\ub098 \ud504\ub85c\uc138\uc2a4\ub97c \uc2e4\ud589\ud558\ub294 \ubc29\uc2dd\uc744 \ucde8\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud504\ub85c\uc138\uc2a4\ub294 \uc5ec\ub7ec \uac1c\uc758 \uc790\ub3d9\ud654\ub41c \uc791\uc5c5\uc73c\ub85c \uad6c\uc131\ub420 \uc218 \uc788\uc73c\uba70 \uad00\ub828\ub418\ub294 \uc2dc\uc2a4\ud15c\ub3c4 \uc5ec\ub7ec \uac1c\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158\uc758 \ubaa9\ud45c\ub294 \ube48\ub3c4\uac00 \ub192\uace0 \ubc18\ubcf5\ud560 \uc218 \uc788\ub294 \ud504\ub85c\uc138\uc2a4\uc758 \uc2e4\ud589\uc744 \uac04\uc18c\ud654 \ubc0f \ucd5c\uc801\ud654\ud558\uc5ec \ub370\uc774\ud130 \ud300\uc774 \ubcf5\uc7a1{...}\uc624\ud508 \ubc45\ud0b9 \uc624\ud508 \ubc45\ud0b9\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc624\ud508 \ubc45\ud0b9\uc740 \uc18c\ube44\uc790\uc758 \uae08\uc735 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \uc548\uc804\ud558\uac8c \uc81c\uacf5\ud558\ub294 \uc218\ub2e8\uc774\uba70, \ubaa8\ub4e0 \uac83\uc5d0 \uace0\uac1d\uc758 \ub3d9\uc758\uac00 \ud544\uc694\ud569\ub2c8\ub2e4.\u00b2 \uaddc\uc81c, \uae30\uc220 \ubc0f \ub3d9\uc801 \uacbd\uc7c1 \ud658\uacbd\uc774\ub77c\ub294 \uc694\uc778 \ub54c\ubb38\uc5d0 \uc624\ud508 \ubc45\ud0b9\uc740 \uc740\ud589\uc774 \uc544\ub2cc \ud0c0\uc0ac, \uc18c\ube44\uc790 \ub4f1\uc5d0 \uace0\uac1d \ub370\uc774\ud130\ub97c \ubbfc\uc8fc\ud654\ud560 \uac83\uc744 \uc694\uad6c\ud569\ub2c8\ub2e4. \ud601\uc2e0\uc740 \uad00\ub828\uc131\uc774 \ub9e4\uc6b0 \ub192\uc740 \ud50c\ub7ab\ud3fc \uae30\ubc18 \ubc30\ud3ec\ub97c \ubaa9\ud45c\ub85c \uc0b0\uc5c5\uc744 \uc9c4\ud654\uc2dc\ud0a4\uba74\uc11c \uc740\ud589\uc5d0\ub294 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uacfc \uc2e0\uaddc \uc2dc\uc7a5 \uc9c4\ucd9c \ubc94\uc704\ub97c \ud655\uc7a5\ud560 \uc218 \uc788\ub294 \ub2e4\uc591\ud55c \uae30\ud68c\ub97c \uc81c\uacf5\ud569\ub2c8{...}\uc774\uc0c1\uce58 \ud0d0\uc9c0 \uc774\uc0c1\uce58 \ud0d0\uc9c0(Anomaly Detection)\uc740 \ub098\uba38\uc9c0 \uad00\uce21 \uacb0\uacfc\uc640\ub294 \ud1b5\uacc4\uc801\uc73c\ub85c \ub2ec\ub77c \uc758\uc2ec\uc744 \uc720\ubc1c\ud560 \uc218 \uc788\ub294 \ub4dc\ubb38 \uc774\ubca4\ud2b8\ub098 \uad00\uce21 \uacb0\uacfc\ub97c \uc54c\uc544\ubcf4\ub294 \uae30\ubc95\uc785\ub2c8\ub2e4. \uadf8\ub7ec\ud55c \u201c\ubcc0\uce59\u201d \ud589\ub3d9\uc740 \ubcf4\ud1b5 \uc2e0\uc6a9\uce74\ub4dc \uc0ac\uae30 \ud589\uc704, \uc2dc\uc2a4\ud15c \uc624\ub958\ub098 \uc0ac\uc774\ubc84 \uacf5\uaca9 \ub4f1 \uc77c\uc885\uc758 \ubb38\uc81c\uc810\uc73c\ub85c \ud574\uc11d\ub420 \ub54c\uac00 \ub9ce\uc2b5\ub2c8\ub2e4. \uae08\uc735\uacc4\uc758 \uacbd\uc6b0, \uac10\uc2dc\ud574\uc57c \ud560 \ud2b8\ub79c\uc7ad\uc158\uc774 \uc218\ucc9c \uac74\uc5d0\uc11c \uc218\ubc31\ub9cc \uac74\uc5d0 \ub2ec\ud558\ubbc0\ub85c \ubcc0\uce59 \uac80\uc0c9\uc744 \uc774\uc6a9\ud558\uba74 \uc624\ub958\uac00 \ubc1c\uc0dd\ud558\ub294 \uc704\uce58\ub97c \uc9da\uc5b4\ub0b4\uc5b4 \uadfc\ubcf8 \uc6d0\uc778 \ubd84\uc11d\uc744 \uac15\ud654\ud558\uace0, \ubb38\uc81c\uc5d0 \uc2e0\uc18d\ud788{...}\uc790\ub3d9\ud654 \ud3b8\ud5a5 \uc790\ub3d9\ud654 \ud3b8\ud5a5\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uc790\ub3d9\ud654 \ud3b8\ud5a5(Automation bias)\uc740 \uc790\ub3d9 \ubcf4\uc870 \ub3c4\uad6c\ub098 \uc758\uc0ac \uacb0\uc815 \uc9c0\uc6d0 \uc2dc\uc2a4\ud15c\uc5d0 \uc9c0\ub098\uce58\uac8c \uc758\uc874\ud558\ub294 \uac83\uc744 \ub9d0\ud569\ub2c8\ub2e4. \uc790\ub3d9 \uc758\uc0ac \uacb0\uc815 \ubcf4\uc870 \ub3c4\uad6c\uac00 \ub110\ub9ac \ubcf4\uae09\ub418\uba74\uc11c \uc911\ud658\uc790\uc2e4\uc774\ub098 \ud56d\uacf5\uae30 \uc870\uc885\uc11d\uacfc \uac19\uc774 \uc911\ub300\ud55c \uc758\uc0ac \uacb0\uc815\uc744 \ub0b4\ub824\uc57c \ud558\ub294 \uc0c1\ud669\uc5d0\uc11c \uc774\ub7f0 \ub3c4\uad6c\ub97c \uc774\uc6a9\ud558\ub294 \uc0ac\ub840\uac00 \uc810\uc810 \ud754\ud574\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc0ac\ub78c\uc740 \uc778\uc9c0\uc801\uc778 \ub178\ub825\uc774 \uac00\uc7a5 \uc801\uac8c \ud544\uc694\ud55c \uae38\uc744 \ud0dd\ud558\uc5ec \"\uc790\ub3d9\ud654 \ud3b8\ud5a5\"\uc73c\ub85c \uae30\uc6b0\ub294 \uacbd\ud5a5\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uac19\uc740 \uac1c\ub150\uc744 AI\uc640 {...}\ucd94\ucd9c, \ubcc0\ud658, \ub85c\ub4dc(ETL) \nDelta Live \ud14c\uc774\ube14\nDelta Live Table(DLT)\uc744 \uc0ac\uc6a9\ud558\uba74 Delta Lake\uc5d0\uc11c \uace0\ud488\uc9c8 \ub370\uc774\ud130\ub97c \uc81c\uacf5\ud558\ub294 \uc548\uc815\uc801\uc778 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc190\uc27d\uac8c \uad6c\ucd95\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n&nbsp;\nDatabricks\uc758 ETL\n\uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30\n&nbsp;\nETL\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\uae30\uc5c5\uc5d0\uc11c \ub2e4\ub8e8\ub294 \ub370\uc774\ud130, \ub370\uc774\ud130 \uc18c\uc2a4\uc640 \ub370\uc774\ud130 \uc720\ud615\uc758 \uc591\uc774 \ub298\uc5b4\ub098\uba74\uc11c \ubd84\uc11d, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 \uba38\uc2e0 \ub7ec\ub2dd{...}\ucee8\ubcfc\ub8e8\uc154\ub110 \ub808\uc774\uc5b4 \ub525\ub7ec\ub2dd\uc5d0\uc11c \ucee8\ubcfc\ub8e8\uc154\ub110 \uc2e0\uacbd\ub9dd(Convolutional Neural Network, CNN \ub610\ub294 ConvNet)\uc774\ub780 \uc2ec\uce35 \uc2e0\uacbd\ub9dd\uc758 \ud55c \ub4f1\uae09\uc73c\ub85c, \ubcf4\ud1b5 \uc774\ubbf8\uc9c0 \uc18d\uc5d0 \uc874\uc7ac\ud558\ub294 \ud328\ud134\uc744 \uc778\uc9c0\ud558\ub294 \ub370 \uc4f0\uc774\uc9c0\ub9cc \uc774\uc678\uc5d0 \uacf5\uac04 \ub370\uc774\ud130 \ubd84\uc11d, \ucef4\ud4e8\ud130 \ube44\uc804, \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \uc2e0\ud638 \ucc98\ub9ac \ubc0f \uc5ec\ud0c0 \ub2e4\uc591\ud55c \uc6a9\ub3c4\uc5d0\ub3c4 \uc4f0\uc785\ub2c8\ub2e4. \ucee8\ubcfc\ub8e8\uc154\ub110 \uc2e0\uacbd\ub9dd\uc758 \uad6c\uc870\ub294 \uc0ac\ub78c\uc758 \ub1cc \uc18d \ub274\ub7f0\uc758 \uc5f0\uacb0 \ud328\ud134\uacfc \u0000\ub2ee\uc740 \ud615\ud0dc\ub97c \ucde8\ud558\uba70 \uc2dc\uac01 \ud53c\uc9c8(Visual Cortex) \uc870\uc9c1\uc5d0\uc11c \uc601\uac10\uc744 \uc5bb\uc5c8\uc2b5\ub2c8\ub2e4. {...}\ud53c\ucc98 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uba38\uc2e0 \ub7ec\ub2dd\uc744 \uc704\ud55c \ud53c\ucc98 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1(Feature engineering)\n\ub370\uc774\ud130 \ucc98\ub9ac\ub77c\uace0\ub3c4 \ubd88\ub9ac\ub294 \ud53c\ucc98 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc740 \uac00\uacf5\ub418\uc9c0 \uc54a\uc740 \ub370\uc774\ud130\ub97c \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378 \uac1c\ubc1c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \uae30\ub2a5\uc73c\ub85c \uc804\ud658\ud558\ub294 \ud504\ub85c\uc138\uc2a4\uc785\ub2c8\ub2e4. \uc774 \ud56d\ubaa9\uc5d0\uc11c\ub294 \ud53c\ucc98 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc758 \uc8fc\uc694 \uac1c\ub150\uacfc \ud53c\ucc98 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc774 ML \uc218\uba85 \uc8fc\uae30 \uad00\ub9ac\uc5d0\uc11c \uc218\ud589\ud558\ub294 \uc5ed\ud560\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\n\uba38\uc2e0 \ub7ec\ub2dd\uc5d0\uc11c \ud2b9\uc131\uc740 \ubaa8\ub378 \ud2b8\ub808\uc774\ub2dd\uc5d0 \uc0ac\uc6a9\ub418\ub294 \uc785\ub825 \ub370\uc774\ud130\uc785\ub2c8\ub2e4. \ud2b9\uc131\uc740 \ubaa8\ub378\uc774 \ud559\uc2b5\ud560 \uc5b4\ub5a4 \uc5d4\ud130\ud2f0\uc758 \uc18d\uc131\uc785\ub2c8\ub2e4{...}\ud558\ub461 \ud558\ub461\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\n\"\ud558\ub461\"\uc774\ub780 \ubb34\uc5c7\uc744 \uc758\ubbf8\ud560\uae4c\uc694? \ub354 \uc911\uc694\ud55c \uac83\uc740, \"\ud558\ub461\"\uc740 \ubb34\uc5c7\uc758 \uc57d\uc790\uc77c\uae4c\uc694? \uc0ac\uc2e4, \uace0\uac00\uc6a9\uc131 \ubd84\uc0b0\ud615 \uac1d\uccb4 \uc9c0\ud5a5\uc801 \ud50c\ub7ab\ud3fc(High Availability Distributed Object Oriented Platform)\uc744 \ub73b\ud569\ub2c8\ub2e4. \ud558\ub461 \uae30\uc220\uc740 \ubc14\ub85c \uc774\ub7f0 \uc7a5\uc810\uc744 \uac1c\ubc1c\uc790\uc5d0\uac8c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc989, \uac1d\u0000\u0000\uccb4 \uc9c0\ud5a5\uc801 \uc791\uc5c5\uc744 \ubcd1\ub82c \ubd84\uc0b0\ud558\uc5ec \uace0\uac00\uc6a9\uc131\uc744 \ud655\ubcf4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\nApache Hadoop\uc740 \uc624\ud508 \uc18c\uc2a4, Java \uae30\ubc18 {...}\ud558\ub461 \uc5d0\ucf54\uc2dc\uc2a4\ud15c \ud558\ub461&nbsp;\uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc774\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\nApache Hadoop \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc774\ub780 Apache Hadoop \uc18c\ud504\ud2b8\uc6e8\uc5b4 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc774\ub8e8\ub294 \ub2e4\uc591\ud55c \uad6c\uc131 \uc694\uc18c\ub97c \ub9d0\ud569\ub2c8\ub2e4. \uc624\ud508 \uc18c\uc2a4 \ud504\ub85c\uc81d\ud2b8\ub294 \ubb3c\ub860 \uad11\ubc94\uc704\ud55c \ubcf4\uc870 \ud234\uc774 \ub9ce\uc2b5\ub2c8\ub2e4. \ud558\ub461 \uc5d0\ucf54\uc2dc\uc2a4\ud15c \uc911\uc5d0\uc11c \uac00\uc7a5 \uc798 \uc54c\ub824\uc9c4 \ud234\uc744 \uba87 \uac00\uc9c0\ub9cc \uc608\ub85c \ub4e4\uba74&nbsp;HDFS, Hive, Pig, YARN,&nbsp;MapReduce, Spark, HBase , Oozie, Sqoop, Zookeeper&nb{...}\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/fr\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Clients Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLes clients DatabricksD\u00e9couvrez comment des entreprises innovantes de tous les secteurs mettent la plateforme Lakehouse de Databricks au service de leur succ\u00e8sHistoires \u00e0 la une\n\n\nT\u00e9moignage de client\n\nComment l\u2019IA change la d\u00e9couverte de m\u00e9dicaments\nAstraZeneca d\u00e9couvre, d\u00e9veloppe et commercialise des m\u00e9dicaments r\u00e9volutionnaires pour lutter contre des maladies comptant parmi les plus graves au monde.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nCaptiver le regard avec une mode audacieuse\nBurberry voit une am\u00e9lioration de 70 % des gains de temps pour la g\u00e9n\u00e9ration d'informations sur les images avec Databricks Lakehouse\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nPromouvoir l\u2019efficacit\u00e9 organisationnelle par l\u2019unification des donn\u00e9es\nAlors que l\u2019ing\u00e9nierie et la construction durables prennent de plus en plus d\u2019importance, le groupe Colas s\u2019est donn\u00e9 pour mission d\u2019imaginer, de construire et d\u2019entretenir des infrastructures de transport qui minimisent l\u2019impact environnemental tout en maximisant la valeur pour leurs clients.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nModerniser les services financiers gr\u00e2ce aux donn\u00e9es et \u00e0 l'IA\n\u00ab\u00a0Malgr\u00e9 l'adoption croissante du big data et de l'IA, la plupart des entreprises de services financiers est toujours confront\u00e9e \u00e0 d'importants d\u00e9fis, que cela concerne la vari\u00e9t\u00e9 des types de donn\u00e9es, leur \u00e9volutivit\u00e9 ou encore la protection de la vie priv\u00e9e.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nDes insights plus rapidement gr\u00e2ce \u00e0 la gouvernance des donn\u00e9es unifi\u00e9e\nGreenFlex est un leader europ\u00e9en dans le domaine de la gestion environnementale, de l'efficacit\u00e9 \u00e9nerg\u00e9tique et de la gestion de l'impact environnemental.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nUn avenir durable \u00e0 grande vitesse pour les transports\nLa mission de la SNCF est d'assurer le transport fluide et durable des passagers et des marchandises, tout en r\u00e9duisant les \u00e9missions carbone et en mettant les \u00e9nergies renouvelables au service de l'avenir de la mobilit\u00e9.\u00a0\n\nEn savoir plusD\u00e9couvrir tous les clientsThe Data Team EffectLes \u00e9quipes data repr\u00e9sentent une force unie pour r\u00e9soudre les probl\u00e8mes mondiaux les plus complexes.Voyez comment \u2192Et si c'\u00e9tait vous, la prochaine success story\u00a0?Nous contacterRessourcesT\u00e9moignage de clientD\u00e9couvrez comment Databricks permet \u00e0 Cond\u00e9 Nast de proposer des contenus personnalis\u00e9s \u00e0 ses clients.En savoir plusWebinaireD\u00e9couvrez comment Apple et Disney+ ont r\u00e9uni l'analytique et l'IA pour r\u00e9ussirRegarderPodcastSlawek Kierner, SVP, Chief Data et Analytics Officer chez Humana, nous parle du r\u00f4le des donn\u00e9es et de l'IA dans l'\u00e9quit\u00e9 des soins m\u00e9dicauxRegarderPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yali-sassoon\/#","text":"Yali Sassoon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYali SassoonCPO at SnowplowBack to speakersYali is passionate about the transformative impact of data. Yali Sassoon co-founded Snowplow to help companies realize the possibilities the behavioral data creates to build deep understanding of individuals in real-time. Prior to Snowplow Yali spent his career in data, as a consultant (operational and strategic) and in house at OpenX. Yali has an MPhil in History and Philosophy of Science and a BA in Natural Sciences, both from the University of Cambridge.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pravin-darbare\/#","text":"Pravin Darbare - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPravin DarbareVice President of Data Analytics at WorkdayBack to speakersComing soonLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sean-owen","text":"Sean Owen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSean OwenPrincipal Product Specialist at DatabricksBack to speakersSean is a Principal Product Specialist for Data Science and Machine Learning at Databricks. He is an Apache Spark committer and PMC member, and co-author Advanced Analytics with Spark. Previously, he was director of Data Science at Cloudera and an engineer at Google, and worked in early-stage technology venture investing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/machine-learning","text":"Production Machine Learning | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSimplify the Machine Learning LifecycleShift from organizational and technological silos to an open and unified platform for the full data and ML lifecycleGet startedBuilding ML models is hard. Moving them into production is harder. Maintaining data quality and model accuracy over time are just a few of the challenges. Databricks uniquely streamlines ML development, from data preparation to model training and deployment, at scale.The ChallengeThe sheer amount of diversity of ML frameworks makes it hard to manage ML environmentsDifficult handoffs between teams due to disparate tools and processes, from data prep, to experimentation, and productionHard to track experiments, models, dependencies and artifacts makes it hard to reproduce resultsSecurity & compliance risksThe SolutionOne-click access to ready-to-use, optimized and scalable ML environments across the lifecycleOne platform for data ingest, featurization, model building, tuning, and productionization simplifies handoffsAutomatically track experiments, code, results and artifacts and manage models in one central hubMeet compliance needs with fine-grained access control, data lineage, and versioning.Databricks for Machine LearningSee how Databricks helps collaboratively prep data, build, deploy, and manage state of the art ML models, from experimentation to production, at unprecedented scale.WorkspaceWorkspaceOne central place to store and share notebooks, experiments, and projects backed with role-based access control.Collaborative NotebooksAutoMLExperiments TrackingModel RegistryFrom experimentation to production ML at unmatched scaleBest in class developer environmentEverything you need to get the job done is one click away in the Workspace: data sets, ML environments, notebooks, files, experiments, models, are all securely available in one place.Collaborative notebooks with multi-language support (Python, R, Scala, SQL) make it easier to work as a team while co-authoring, Git integration, versioning, role-based access control, and more, help you stay in control. Or simply use familiar tools like Jupyter Lab, PyCharm, IntelliJ, RStudio with Databricks to benefit from limitless data storage and compute.Learn moreFrom raw data to high-quality feature storeMachine learning practitioners train models on a large variety of data forms and formats: small or large data sets, DataFrames, text, images, batch or streaming. All require specific pipelines and transformations\nDatabricks lets you ingest raw data from virtually any source, merge batch and streaming data, schedule transformations, version tables, and perform quality checks to make sure data is pristine and ready for analytics for the rest of the organization. So now you can seamlessly and reliably work on any data, CSV files or massive data lake ingests, based on your needs.Learn moreThe best place to run scikit-learn, TensorFlow, PyTorch, and more\u2026ML frameworks are evolving at a frenetic pace making it challenging to maintain ML environments. The Databricks ML Runtime provides ready to use and optimized ML environments including the most popular ML frameworks (scikit-learn, TensorFlow, etc\u2026) and Conda support.\nBuilt-in AutoML like hyperparameter tuning help get to results faster, and simplified scaling helps you go from small to big data effortlessly so you don\u2019t have to be limited by how much compute is available to you anymore. For example, train deep learning models faster by distributing compute across your clusters with HorovodRunner and squeeze more performance out of each GPU in your cluster by running the CUDA-optimized version of TensorFlow.Learn moreTrack experiments and artifacts to reproduce runs laterML algorithms have dozens of configurable parameters, and whether working alone or as a team, it is difficult to track which parameters, code, and data went into each experiment to produce a model.MLflow automatically keeps track of your experiments along with artifacts like data, code, parameters and results for each training run from within notebooks. So you can quickly see at a glance previous runs, compare results, and revert to a previous version of your code as needed. Once you have identified the best version of a model for production, register it in a central repository to submit it for deployment and simplify handoffs.Learn moreConfidently move from prototyping to productionOnce trained models are registered, you can collaboratively manage them through their lifecycle with the MLflow model registry.Models can be versioned and moved through various stages, like experimentation, staging, production and archived. Stakeholders can comment and submit requests to change stage. All of the lifecycle management integrates with approval and governance workflows and role-based access controls.Deploy models anywhereQuickly deploy production models for batch inference on Apache Spark\u2122, or as REST APIs using built-in integration with Docker containers, Azure ML, and Amazon SageMaker.Operationalize production models using jobs scheduler and auto-managed clusters to scale as needed based on business needs.Quickly push the latest versions of your models to production and monitor model drift with Delta Lake and MLflow.Learn moreHow it worksEnabling the Complete Machine Learning Lifecycle on DatabricksLearn more\nCustomer Story \n\nSaving Energy in Homes with a Unified Approach to Data and AI\nWith Databricks, Quby has been able to deliver on their mission: leverage machine learning to improve the comfort and lives of their customers while helping reduce energy consumption.\nLearn more\nSee more customer storiesResourcesReportGartner\u00ae Names Databricks a LeadereBookStandardizing the ML LifecycleeBookThe Big Book of Machine LearningReady to get started?Try Databricks freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/model-serving","text":"Model Serving | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWModel ServingSimplified Production MLTry for freeSchedule a demo\nML Virtual Event\nEnabling Production ML at Scale With LakehouseMarch 14, 9 AM PDT \/ 4 PM GMT\nRegister nowIntroductionModel Serving\u00a0is built within the Databricks Lakehouse Platform and integrates with your lakehouse data, offering automatic lineage, governance and monitoring across data, features and model lifecycle. Simplify model deployment, reduce infrastructure overheads and accelerate time to production. With built-in auto-scaling capability, you can scale from zero all the way up to your most critical needs while paying only for the compute you use.Customer QuotesUnified with lakehouse dataDeep integration with the lakehouse provides automatic lineage, governance and monitoring across data, features and model lifecycleSimplified deploymentAutomated infrastructure configuration and maintenance to reduce overheads and accelerate your ML deploymentsReal-timeQuickly scale from zero all the way up to your most critical needs, and down as your needs change, while paying only for the compute you useGet started with these resourcesBlogAnnouncing General Availability of Databricks Model ServingDocumentationModel serving on the lakehouseeBookThe Big Book of Machine Learning Use CasesReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/julien-le-dem","text":"Julien Le Dem - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJulien Le DemChief Architect at AstronomerBack to speakersJulien Le Dem is the Chief Architect of Astronomer and Co-Founder of Datakin. He co-created Apache Parquet and is involved in several open source projects including OpenLineage, Marquez (LFAI&Data), Apache Arrow, Apache Iceberg and a few others. Previously, he held senior roles at Wework, Dremio, Twitter where he also obtained a two-character Twitter handle (@J_) and Yahoo, where he received his Hadoop initiation. His French accent makes his talks particularly attractive.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Databricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30 | DatabricksDatabricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30AWS, Microsoft Azure \ub610\ub294 Google Cloud \uc911 \uc6d0\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4\uc5d0\uc11c 14\uc77c \ub3d9\uc548 Databricks \ud50c\ub7ab\ud3fc \uc804\uccb4\ub97c \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud574 \ubcf4\uc138\uc694.\ub370\uc774\ud130 \uc218\uc9d1 \ub2e8\uc21c\ud654 \ubc0f ETL \uc790\ub3d9\ud654\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uc218\ubc31 \uac1c\uc758 \uc18c\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574 \ubcf4\uc138\uc694. \uac04\ub2e8\ud55c \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \uc5b8\uc5b4\ub85c \ud611\uc5c5\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uacf5\ub3d9 \uc800\uc791, \uc790\ub3d9 \ubc84\uc804 \uad00\ub9ac, Git \ud1b5\ud569, RBAC\ub97c \ud65c\uc6a9\ud558\uc5ec Python, R, Scala \ubc0f SQL\ub85c \ucf54\ub529\ud558\uc138\uc694.\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 12\ubc30 \ub354 \uc6b0\uc218\ud55c \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc804 \uc138\uacc4 7,000\uac1c \uace0\uac1d\uc0ac\uac00 BI\ubd80\ud130 AI\uc5d0 \uc774\ub974\ub294 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc704\ud574\uc11c Databricks \ub97c \uc120\ud0dd\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.Databricks \uacc4\uc815 \uc0dd\uc131\ud558\uae301\/2\uc774\ub984\uc131\ud68c\uc0ac \uc774\uba54\uc77c\ud68c\uc0ac\uc9c1\ud568\uc804\ud654\ubc88\ud638(\uc120\ud0dd\uc0ac\ud56d)\ubcf4\uae30 \uc911\uc5d0\uc11c \uc120\ud0dd\ud558\uc138\uc694\uad6d\uac00\uacc4\uc18d\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0(\uc5c5\ub370\uc774\ud2b8\ub428)\uc774\uc6a9\uc57d\uad00\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/discoverlakehouse","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marcel-kramer","text":"Marcel Kramer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarcel KramerHead of Data Engineering at ABN AMRO Bank N.VBack to speakersAccountable for ~50 DevOps teams with 500+ IT engineers delivering all bank wide data capabilities (DQ monitoring, data distribution, data privacy and security, data governance, advanced analytics, process mining and MLE platforms). Broad tech stack ranging from traditional to latest cutting edge technologies. Defined together with CDO rigorous data strategy, to make ABN AMRO a data driven company. Actively involved with AA ventures in data technology investments.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/migrating-from-a-data-warehouse-to-a-data-lakehouse","text":"Migrating from a Data Warehouse to a Data Lakehouse | DatabrickseBookMigrating From a Data Warehouse to a Data Lakehouse for DummiesAnalyze All Your Data in One PlaceEnterprise data warehouses offer features essential to running a business, but they limit your benefits by creating complexity, introducing data management issues and hindering innovation. With a modern data architecture, you no longer need to operate two competing data architectures \u2014 data warehouses and data lakes. You can run your SQL and BI workloads where all your data already resides \u2014 your data lake.That\u2019s why you should migrate to the Databricks Lakehouse, a simple, open and multicloud platform that offers better price\/performance and fine-grained governance for your data warehouse workloads \u2014 as well as scalable AI \u2014 all while helping you optimize your total cost of ownership by simplifying your data architecture.In this eBook, you\u2019ll learn how to:Assess your company\u2019s data maturityPrioritize your data and AI strategyManage all your unique data types in one placeEvaluate top considerations for your data warehouse migrationMaximize your benefits from enterprise dataGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/sparse-tensor","text":"What is Sparse Tensor?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSparse TensorAll>Sparse TensorTry Databricks for freeGet StartedPython offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library.  Sptensor is a class that represents the sparse tensor. A sparse tensor is a dataset in which most of the entries are zero, one such example would be a large diagonal matrix. (which has many zero elements). It does not store the whole values of the tensor object but stores the non-zero values and the corresponding coordinates of them. Sparse tensor storage formats allow us to only store non-zero values thereby reducing storage requirements and eliminating unnecessary silent computations involving zero values. Here are its main attributes:vals (numpy.ndarray) A 1-dimensional array of non-zero values of the sparse tensor.subs (numpy.ndarray) A 2-dimensional array of coordinates of the values in vals.shape(tuple)The shape of the sparse tensor.func(binary operator) This function is used to construct the sparse tensor as an accumulator.On top of that, its main functions are:__init__(self, subs, vals, shape = None, func=sum.__call__) Consturctor for the sptensor class. subs and vals (numpy.ndarray) or (list) are coordinates and values of the sptensor.tondarray(self) This function returns a numpy. ndarray object that has the same values with the sptensor.permute(self, order) By applying this function it will return the sptensor object that is permuted by the given order (list).ipermute(self, order) Returns the sptensor object that is permuted by the inverse of the given order (list).copy(self) Returns the copied sptensor object of the sptensor.totensor(self) Returns the tensor object that has the same values with the sptensor.nnz(self) Returns the number of non-zero elements in the sptensor.ndims(self) Returns the number of dimensions of the tensor.dimsize(self, ind)Returns the size of the specified dimension. Same as shape[ind].Additional ResourcesDeep Learning with Apache Spark and TensorFlowHow (Not) To Scale Deep Learning in 6 Easy StepsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=dataengineering-promocard-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/modern-cloud-data-platform-for-dummies","text":"The Modern Cloud Data Platform for Dummies | DatabrickseBookData has a new destination. Here\u2019s your guide.How to get the best of data warehouses and data lakesYou might\u2019ve heard that the lakehouse is opening up a new era of data and AI.But before you can run a data lakehouse, you need to walk through this guide.\u00a0The Modern Cloud Data Platform for Dummies\u00a0is the introduction every data professional needs to start simplifying \u2014 and future-proofing \u2014 their data management strategy.In this eBook, you\u2019ll take a deep dive into:Why traditional data management solutions are failingLakehouse vs. other data management solutions \u2014 a head-to-head comparisonThe business and technical benefits of unifying all analytics workloads in one platformDownload the eBook now and see how the lakehouse can help your data teams simplify and move faster \u2014 and still bring down costs. This is the guide you\u2019ll want to share with your team members and other stakeholders.Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Experimente o Databricks | DatabricksExperimente o Databricks gratuitamente Experimente a plataforma Databricks completa gratuitamente por 14 dias em sua nuvem AWS, Microsoft Azure ou Google Cloud.Simplique a ingest\u00e3o de dados e automatize processos de ETLImporte dados de centenas de fontes. Utilize uma abordagem asseverativa e simples para construir pipelines de dados.Colabore em sua linguagem preferidaCode em Python, R, Scala e SQL com colabora\u00e7\u00e3o, versionamento autom\u00e1tico, integra\u00e7\u00f5es com Git e controles de acesso (RBAC) Pre\u00e7o\/Performance at\u00e9 12x superior a data warehouses em nuvemDescubra porque mais de 7000 clientes de todo mundo confiam na Databricks para todos os seus workloads de Dados, de BI a AI.Crie sua conta Databricks1\/2Primeiro NomeSegundo NomeEmailEmpresaT\u00edtuloTelefone (Opcional)SelecionarPa\u00edsContinuarAviso de privacidade (atualizado)Termos de UsoSuas op\u00e7\u00f5es de privacidadeSeus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=home-promotile-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dan-smith","text":"Dan Smith - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDan SmithHead of Technology Data & Analytics at Perenti GroupBack to speakersDan Smith is currently the Head of Technology Data & Analytics at Perenti Group, a global leading mining services company. He leads the data team providing information to 9000+ people in the business. Dan lead Perenti's digital transformation change of an on-prem migration to a Cloud based Lakehouse architecture, and expanding on all the capabilities that it brings. He previously had roles with Systems Integrators, Consultancies and Product development companies. Recently Dan has worked closely with key cloud providers to implement fit for purpose, future proofed data architectures for Perenti. His goal is to uncover insights and drive business value in the short term, while setting up success and flexibility for future capabilities in the medium and long term.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/audience\/digital-native","text":"Aziende e applicazioni native digitali | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWIl Lakehouse per le aziende nate nel cloudCostruisci e adatta pi\u00f9 velocemente dati, analisi e funzionalit\u00e0 di AI su un'unica piattaforma dati ad alte prestazioni\nCominciaGuarda le demoPi\u00f9 la crescita \u00e8 rapida, pi\u00f9 i dati diventano complessi. Innovare pi\u00f9 velocemente con la piattaforma Databricks Lakehouse Platform - un approccio semplice e conveniente a dati, analisi e AI che rende pi\u00f9 produttive migliaia di aziende e startup native digitali.Innovare grazie alla flessibilit\u00e0 dell'open-source\nUsa i tuoi dati ovunque e in qualunque momento, senza dipendere dai fornitori. Gli sviluppatori di Apache Spark\u2122 hanno creato il Lakehouse con formati e API aperti.\nGuarda i progetti open-sourceCostruisci carichi di lavoro di dati scalabili\nGarantisci prestazioni affidabili e veloci sui carichi di lavoro ETL per l'invio dei dati in streaming e in batch, mentre Databricks gestisce automaticamente la tua infrastruttura.\nVedi il data engineeringAccedi pi\u00f9 velocemente alle informazioni sui dati\nInserisci, trasforma e interroga tutti i tuoi dati da un unico punto d'accesso. Smetti di gestire i server ed espanditi quando ne hai bisogno con il sistema serverless. Un rapporto prezzo\/performance fino a 12 volte migliore.\nVedi Databricks SQLSviluppa app di nuova generazione grazie al ML\nAccelera il ciclo di vita del ML dalla sperimentazione alla produzione. Dai slancio alla produttivit\u00e0 con strumenti come notebook collaborativi, MLflow e MLOps.\nVedi le funzionalit\u00e0 del MLPrimi passi con DatabricksProva Databricks\nInizia la prova gratuita di 14 giorni con Databricks su AWS in pochi e semplici passaggi. Trova le risorse adatte a te e al tuo team di dati.\nInizia gratisCostruisci le tue competenze\nAccedi a corsi di formazione e certificazione su misura per le tue esigenze, tra cui analisi dei dati, data engineering, data science e machine learning.\nAccedi alla formazioneOttimizza i costi\nRiduci i costi dell'infrastruttura del 40% e aumenta la produttivit\u00e0 con un servizio gestito. Dai un'occhiata ai nostri piani di fatturazione con pagamento a consumo e sconti.\nGuarda i prezziAssistenza tecnica\nTrova pi\u00f9 rapidamente le risposte grazie all'aiuto degli esperti di Databricks. In pi\u00f9, potrai sviluppare velocemente la tua soluzione per i dati grazie ai nostri notebook self-service.\nGuarda i notebookProgrammi integratiCostruite le vostre applicazioni data-driven sulla lakehouse e accelerate la crescita del vostro business con DatabricksDatabricks per le startupIniziare rapidamente con il programma di avvio. Scopri come ottenere crediti gratuiti, consulenza di esperti e supporto per il lancio sul mercato.Maggiori informazioniPartner costruiti\u00a0Diventate un partner integrato per accedere a vantaggi tecnici, di go-to-market e di co-marketing che vi aiuteranno ad ampliare la vostra portata e a far crescere il vostro business.Maggiori informazioniLa nuova generazione di aziende costruite su DatabricksArchitetture di soluzioni per le imprese native digitaliPipeline ETL scalabili ad alte prestazioniCostruisci una piattaforma end-to-end di data engineering ed ETL che ti permetta di concentrarti sull'offerta di informazioni significative su qualsiasi cloud. Non sar\u00e0 pi\u00f9 necessario costruire e mantenere le pipeline n\u00e9 eseguire carichi di lavoro ETL.Sfrutta gli strumenti pronti per la produzione, tra cui Delta Live Tables, Unity Catalog e Workflows.Sfrutta la solida integrazione Git, l'orchestrazione e i controlli della qualit\u00e0 dei dati.Unifica le operazioni in batch e in streaming su un'architettura semplificata e velocizza lo sviluppo e i test delle pipeline di dati.Qualit\u00e0 dei dati garantita e data skipping migliorato con Delta Lake, un protocollo file open-source utilizzabile da Apache Spark, Trino, Presto, Flink e altri ancora.CominciaAnalisi SQL e data warehousingInserisci, trasforma e interroga tutti i tuoi dati da un unico punto d'accesso per offrire pi\u00f9 velocemente informazioni approfondite all'azienda.Esegui tutte le tue applicazioni SQL e di BI su larga scala con un rapporto prezzo\/prestazioni fino a 12 volte migliore. Assicura governance dei dati e sicurezza.Gestisci un'elevata concorrenza con un bilanciamento del carico interamente gestito e la scalabilit\u00e0 delle risorse di calcolo.Sfrutta i formati aperti e le API, oltre a ingestione, trasformazione e strumenti di BI di tua scelta con i connettori personalizzati.Riduci i costi generali di gestione delle risorse grazie al calcolo serverless.CominciaMachine learning innovativaAccelera la ML e data science migliorando produttivit\u00e0 e collaborazione sul lakehouse.Sfrutta gli strumenti di collaborazione e le opzioni per un AutoML trasparente.Prepara, elabora e gestisci dati e funzionalit\u00e0 in modalit\u00e0 self-service, oltre a modelli di gestione, il tutto con un negozio di funzionalit\u00e0 in hosting.Standardizza il ciclo di vita del ML dalla sperimentazione alla produzione grazie a MLflow per tracciare parametri, metriche e iterazioni del modello nel corso del tempo.Implementa modelli in batch o con endpoint REST serverless in tempo reale.CominciaPartner tecnologici\nScopri e integra i tuoi dati e i tuoi strumenti e servizi di AI preferiti direttamente dalla piattaforma Databricks\nEsplora Partner ConnectSoluzioni per settori specificiLa nuova generazione di leader di settore sta costruendo le soluzioni di analisi dei dati e AI con DatabricksEsplora le soluzioni per settore industrialeRetail e largo consumo\nPrendi decisioni in tempo reale e offri esperienze migliori ai clienti.\nMaggiori informazioniServizi finanziari\nPotenzia i tuoi servizi finanziari guidati dai dati e dall'AI per il futuro.\nMaggiori informazioniVideogame\nSfrutta la potenza dei dati e dell'AI per sbloccare esperienze di gioco di livello superiore.\nMaggiori informazioniComunicazioni, media e intrattenimento\u00a0\nCrea media guidati dai dati e dall'AI per un'esperienza dei clienti di livello superiore.\nMaggiori informazioniTecnologia e software\nSviluppa soluzioni di nuova generazione grazie alle capacit\u00e0 avanzate di dati e ML.\nMaggiori informazioniTecnologia sanitaria\nOffrire esiti risultati ai pazienti con la potenza dei dati e dell'AI.\nMaggiori informazioniGuida tecnicaRisolvere i problemi comuni dei datiPer le startup e le imprese native digitaliScoprite come supportare i casi d'uso dei dati in fase di scalata, aumentando l'efficienza dei costi e la produttivit\u00e0. Potrete usufruire di diagrammi di architettura, soluzioni passo-passo e guide rapide. Troverete anche casi d'uso reali di aziende leader come Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable e Zipline.Richiedi la copiaRisorseeBookChe cos'\u00e8 una lakehouse?The Big Book of Data EngineeringIl grande libro dei casi d'uso del machine learningGuida definitiva a Delta LakeDelta Lake: la tecnologia alla base del LakehouseThe Big Book of MLOpsThe Data Team\u2019s Guide to the Databricks Lakehouse PlatformGuide introduttiveEseguire carichi di lavoro ETLPipeline di dati con Delta Live TablesGuida SQL: query e dashboardGuida rapida alla data scienceGuida rapida al machine learningBlogAnnunciOpen sourceApprofondimenti di settoreSoluzioniPronto per cominciare?Comincia la prova gratuitaProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/kr","text":"\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98 \ubc0f AI \uae30\uc5c5 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 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\ub370\ubaa8 \ubcf4\uae30\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc2dc\ub300\ub294 \uac14\uc2b5\ub2c8\ub2e4.\n\uc65c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ub370\uc774\ud130\uc640 AI\ub97c \uc704\ud55c\n\ucd5c\uc2e0 \uc544\ud0a4\ud14d\ucc98\uc778\uc9c0 \uadf8 \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc54c\uc544\ubcf4\uae30\uc138\uc158 \uce74\ud0c8\ub85c\uadf8 \uacf5\uac1c\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uacfc \uc624\ud508 \uc18c\uc2a4 \uae30\uc220\uc758 \ubc1c\uc804\uc744 \ub9cc\ub098\ubcfc \uc218 \uc788\ub294 \uc0cc\ud504\ub780\uc2dc\uc2a4\ucf54\ub85c \uc5ec\ub7ec\ubd84\uc744 \ucd08\ub300\ud569\ub2c8\ub2e4.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.\ubcf4\uace0\uc11c \ubc1b\uae30600\uba85\uc758 CIO. 14\uac1c \uc0b0\uc5c5. 18\uac1c \uad6d\uac00.\uc774 \uc0c8\ub85c\uc6b4 \uc870\uc0ac\uc5d0\uc11c \ub370\uc774\ud130 \uc804\ub7b5\uc774 AI\uc758 \uc131\uacf5\uc5d0 \uc911\uc694\ud558\ub2e4\ub294 \uac83\uc744 \uc54c\uc558\uc2b5\ub2c8\ub2e4. \ub354 \ub9ce\uc740 CIO\uc758 \uacac\ud574\ub97c \ud655\uc778\ud558\uc138\uc694.\ubcf4\uace0\uc11c \ubc1b\uae30\ubcf4\ub2e4 \ud6a8\uacfc\uc801\uc778 MLOps \ubc29\ubc95\uc744 \ucc3e\ub294 ML \uc5d4\uc9c0\ub2c8\uc5b4\uc640 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\uac00 \uc77d\uc5b4\uc57c \ud560 \uc790\ub8cceBook \ub2e4\uc6b4\ub85c\ub4dc\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\u0000\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/taylor-hosbach","text":"Taylor Hosbach - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTaylor HosbachData Scientist at DIRECTVBack to speakersTaylor Hosbach is a Data Scientist at DIRECTV. He joins DIRECTV from Hopper and Epic where he utilized machine learning and advanced analytics to deliver actionable insights that improve business operations. He also has experience managing teams and working cross-functionally with the business to drive impact and opportunities for implementing Data Science solutions. Taylor holds an M.S. in Data Science from The University of Texas at Austin and a B.S. from Lehigh University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gavita-regunath\/#","text":"Gavita Regunath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGavita RegunathPrincipal Data Scientist at Advancing AnalyticsBack to speakersGavita Regunath is a passionate data scientist with Advancing Analytics, a mother, wife, mentor, and addicted to learning new things. In her spare time, she loves spending time with her family and enjoys fulfilling her STEM role, where she delivers AI and machine learning lessons to primary school children.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/saad-ansari","text":"Saad Ansari - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSaad AnsariSenior Staff Product Manager at DatabricksBack to speakersSaad is a product manager at Databricks working on the Developer Ecosystem. Prior to this he was CTO and co-founder at Connecterra using Artificial Intelligence to improve sustainability, productivity and animal welfare in the Dairy Industry (think Fitbit for cows!). Saad has also worked as a PM and Developer at Microsoft. He holds a masters in computer science from Stanford.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/apache-hive","text":"What is Apache Hive Used For?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache HiveAll>Apache HiveTry Databricks for freeGet StartedWhat is Apache Hive?Apache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.With extensive Apache Hive documentation and continuous updates, Apache Hive continues to innovate data processing in an ease-of-access way.The History of Apache HiveApache Hive is an open source project that was conceived of by co-creators Joydeep Sen Sarma and Ashish Thusoo during their time at Facebook. Hive started as a subproject of Apache Hadoop, but has graduated to become a top-level project of its own. With the growing limitations of Hadoop and Map Reduce jobs and the increasing size of data from 10s of GB a day in 2006 to 1TB\/day and to 15TB\/day within a few years. The engineers at Facebook were unable to run the complex jobs with ease, giving way to the creation of Hive.Apache Hive was created to achieve two goals - an SQL-based declarative language that also allowed engineers to be able to plug in their own scripts and programs when SQL did not suffice, which also enabled most of engineering world (SQL Skills based) to use Hive with minimal disruption or retraining compared to others.Second, it provided a centralized metadata store (Hadoop based) of all the datasets in the organization. While initially developed in the walls of Facebook, Apache Hive is used and developed by other companies such as Netflix. Amazon maintains a software fork of Apache Hive included in Amazon Elastic MapReduce on Amazon Web Services.What are some features of Hive?Apache Hive supports the analysis of large datasets stored in Hadoop's HDFS and compatible file systems such as Amazon S3, Azure Blob Storage, Azure Data Lake Storage, Google Cloud Storage, and Alluxio.It provides a SQL-like query language called HiveQL with schema-on-read and transparently converts queries to Apache Spark, MapReduce, and Apache Tez jobs. Other features of Hive include:Hive Data Functions help processing and querying big datasets. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditional operators, mathematical functions, and othersMetadata storage in a relational database management systemDifferent storage types such as Parquet, plain text, RCFile, HBase, ORC, and othersOperating on compressed data stored into the Hadoop ecosystem using algorithmsBuilt-in user-defined functions (UDFs) to manipulate dates, strings, and other data-mining tools. Hive supports extending the UDF set to handle use-cases not supported by built-in functionsSQL-like queries (HiveQL), which are implicitly converted into MapReduce or Tez, or Spark jobsApache Hive architecture and key Apache Hive componentsThe key components of the Apache Hive architecture are the Hive Server 2, Hive Query Language (HQL), the External Apache Hive Metastore, and the Hive Beeline Shell.Hive Server 2The Hive Server 2 accepts incoming requests from users and applications and creates an execution plan and auto generates a YARN job to process SQL queries. The server also supports the Hive optimizer and Hive compiler to streamline data extraction and processing.Hive Query LanguageBy enabling the implementation of SQL-reminiscent code, the Apache Hive negates the need for long-winded JavaScript codes to sort through unstructured data and allows users to make queries using built-in HQL statements (HQL). These statements can be used to navigate large datasets, refine results, and share data in a cost-effective and time-efficient manner.The Hive MetastoreThe central repository of the Apache Hive infrastructure, the metastore is where all of the Hive\u2019s metadata is stored. In the metastore, metadata can also be formatted into Hive tables and partitions to compare data across relational databases. This includes table names, column names, data types, partition information, and data location on HDFS.Hive Beeline ShellIn line with other database management systems (DBMS), Hive has its own built-in command-line interface where users can run HQL statements. Also, the Hive shell also runs Hive JDBC and ODBC drivers and so can conduct queries from an Open Database Connectivity or Java Database Connectivity application.How does Apache Hive software work?The Hive Server 2 accepts incoming requests from users and applications before creating an execution plan and automatically generates a YARN job to process SQL queries. The YARN job may be generated as a MapReduce, Tez, or Spark workload.This task then works as a distributed application in Hadoop. Once the SQL query has been processed, the results will either be returned to the end-user or application, or transmitted back to the HDFS.The Hive Metastore will then leverage a relational database such as Postgres or MySQL to persist this metadata, with the Hive Server 2 retrieving table structure as part of its query planning. In some cases, applications may also interrogate the metastore as part of their underlying processing.Hive workloads are then executed in YARN, the Hadoop resource manager, to provide a processing environment capable of executing Hadoop jobs. This processing environment consists of allocated memory and CPU from the various worker nodes in the Hadoop cluster.YARN will attempt to leverage HDFS metadata information to ensure processing is deployed where the needed data resides, with MapReduce, Tez, Spark, or Hive can auto-generate code for SQL queries as MapReduce, Tez, or Spark jobs.Despite Hive only recently leveraging MapReduce, most Cloudera Hadoop deployments will have Hive configured to use MapReduce, or sometimes Spark. Hortonworks (HDP) deployments normally have Tez set up as the execution engine.What are the five different data types used by Apache Hive?Through its use of batch processing, Apache Hive is able to efficiently extract and analyze petabytes of data at rapid speeds - making it ideal for not only processing the data but also running ad hoc queries.The Apache Hive data types consist of five categories: Numeric, Date\/Time, String, Complex, and Misc.Numeric Data TypesAs the name suggests, these data types are integer-based data types. Examples of these data types are \u2018TINYINT,\u2019 \u2018SMALLINT,\u2019 \u2018INT,\u2019 and \u2018BIGINT\u2019.Date\/Time Data TypesThese data types allow users to input a time and a date, with \u2018TIMESTAMP,\u2019 \u2018DATE,\u2019 and \u2018INTERVAL,\u2019 all being accepted inputs.String Data TypesAgain this type of data is very straightforward and allows for written text, or \u2018strings,\u2019 to be implemented as data for processing. String data types include \u2018STRING,\u2019 \u2018VARCHAR,\u2019 and \u2018CHAR.\u2019Complex Data TypesOne of the more advanced data types, complex types record more elaborate data and consist of types like \u2018STRUCT\u2019, \u2018MAP,\u2019 \u2018ARRAY,\u2019 and \u2018UNION.\u2019Misc. TypesData types that don\u2019t fit into any of the other four categories are known as miscellaneous data types and can take inputs such as \u2018BOOLEAN\u2019 or \u2018BINARY.\u2019How Map Join works in Hive ApacheIn Apache Hive, Map Join is a feature employed to increase the speed and efficiency of a query by combining, or rather 'joining,' data from two tables whilst bypassing the Map-Reduce stages of the process.What is a Relational Database Management System (RDBMS) and how does Apache Hive use it?A Relational Database Management System (RDBMS) is a database model which operates by storing metadata in a row- or column-based table structure and allows for the connection and comparison of different datasets.By using an RDBMS, Apache Hive can ensure that all the data is stored and processed safely, reliably, and accurately because integrated features such as role-based security and encrypted communications ensure that only the correct people are given access to the information extracted.What\u2019s the difference between Apache Hive and a traditional RDBMS?There are a few key differences between Apache Hive and an RDBMS:RDBMS functions work on read and write many times whereas Hive works on write once, read many times.Hive follows the schema-on-read rule, only meaning there is no data validation, checking or parsing, just copying\/moving files. In traditional databases, a schema is applied to a table that enforces a schema on a write rule.Because Hive is built on top of Hadoop, it has to comply with the same restrictions of Hadoop and MapReduce which other RDBMS may not need to.Apache Hive vs. Apache SparkAn analytics framework designed to process high volumes of data across various datasets, Apache Spark provides a powerful user interface capable of supporting various languages from R to Python.Hive provides an abstraction layer that represents the data as tables with rows, columns, and data types to query and analyze using an SQL interface called HiveQL. Apache Hive supports ACID transactions with Hive LLAP. Transactions guarantee consistent views of the data in an environment in which multiple users\/processes are accessing the data at the same time for Create, Read, Update and Delete (CRUD) operations.Databricks offers Delta Lake, which is similar to Hive LLAP in that it provides ACID transactional guarantees, but it offers several other benefits to help with performance and reliability when accessing the data. Spark SQL is Apache Spark\u2019s module for interacting with structured data represented as tables with rows, columns, and data types.Spark SQL is SQL 2003 compliant and uses Apache Spark as the distributed engine to process the data. In addition to the Spark SQL interface, a DataFrames API can be used to interact with the data using Java, Scala, Python, and R. Spark SQL is similar to HiveQL.Both use ANSI SQL syntax, and the majority of Hive functions will run on Databricks. This includes Hive functions for date\/time conversions and parsing, collections, string manipulation, mathematical operations, and conditional functions.There are some functions specific to Hive that would need to be converted to the Spark SQL equivalent or that don\u2019t exist in Spark SQL on Databricks. You can expect all HiveQL ANSI SQL syntax to work with Spark SQL on Databricks.This includes ANSI SQL aggregate and analytical functions. Hive is optimized for the Optimized Row Columnar (ORC) file format and also supports Parquet. Databricks is optimized for Parquet and Delta but also supports ORC. We always recommend using Delta, which uses open-source Parquet as the file format.Apache Hive vs. PrestoA project originally established at Facebook, PrestoDB, more commonly known as Presto, is a distributed SQL query engine that allows users to process and analyze petabytes of data at a rapid speed. Presto\u2019s infrastructure supports the integration of both relational databases and non-relational databases from MySQL and Teradata to MongoDB and Cassandra.Additional ResourcesHadoop to Lakehouse migration guideMigration hubCloud Modernization Ebook: A business guide into the hidden value of migration from HadoopOn-demand quick demo's of the Databricks Lakehouse PlatformBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/big-book-of-retail-consumer-goods-use-cases","text":"Big Book of Retail & Consumer Goods Use Cases | DatabrickseBookReimagine the future of retail with the LakehouseMake smarter real-time decisionsYour customers want the right product or service at the right time and with a seamless shopping experience. Learn how to tackle your most critical use cases with the Databricks Lakehouse for Retail so you can modernize your data and AI capabilities and drive real-time decisions in order to lead customers on a journey that champions your brand. Get the details in this new eBook.You\u2019ll learn how to:Build a foundation for innovation with all your data types, sources and workloads in a single architectureDevelop a resilient and predictive supply chain with scalable, fine-grained forecastsCombine all customer data so you can offer personalized experiences that help increase market shareGet record-setting performance at a market-leading cost of ownershipAct faster with the LakehouseProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/product\/aws?itm_data=menu-item-awsProduct","text":"Piattaforma di dati Databricks su AWS - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks su AWSPiattaforma di gestione dei dati semplice e unificata, integrata con AWS\n\u00a0CominciaProgramma una demoDatabricks su AWS consente di conservare e gestire tutti i dati su una semplice piattaforma lakehouse aperta che unisce il meglio di data warehouse e data lake per unificare tutti i carichi di lavoro di analisi e AI.Data engineering affidabileAnalisi SQL su tutti i datiCollaborative Data ScienceMachine learning in produzionePerch\u00e9 Databricks su AWS?Semplice\nDatabricks supporta un'architettura singola unificata per la gestione dei dati su S3 per analisi SQL, data science e machine learningRapporto prezzo\/prestazioni 12 volte migliore\nOttieni le prestazioni del data warehouse al prezzo del data lake con cluster di calcolo ottimizzati per SQLCollaudata\nMigliaia di clienti hanno implementato Databricks su AWS per fornire una piattaforma di analisi rivoluzionaria per tutti i casi d'uso di analisi e AIDollar Shave Club: personalizzare le esperienze dei clienti con Databricks\nScarica l'eBookHotels.com: ottimizzare l'esperienza del cliente con il machine learning\nScarica la storia di successoHP: dalla preparazione dei dati al deep learning, HP unifica l'analisi con Databricks\nGuarda il webinar on-demandIntegrazioni disponibiliAWS GravitonAWS GravitonI cluster di Databricks supportano istanze AWS Graviton. Queste istanze usano processori Graviton progettati da AWS e basati sull'architettura del set di istruzioni Arm64. Secondo AWS, le istanze con questi processori offrono il miglior rapporto prezzo\/prestazioni fra tutti i tipi di istanze su Amazon EC2.\u00a0Maggiori informazioniSicurezza AWSAmazon RedshiftAWS GlueImplementazione in tutta l'aziendaCasi d'usoMotori di raccomandazione personalizzati\nElabora tutti i dati in tempo reale per fornire le raccomandazioni pi\u00f9 rilevanti per prodotti e servizi.Sequenziamento del genoma\nCome rinnovare la dotazione tecnologica per migliorare l'esperienza di pazienti e medici con la pipeline DNASeq pi\u00f9 veloce su larga scala.Individuazione e prevenzione delle frodi\nSfrutta tutti i dati storici insieme ai flussi di dati in tempo reale per individuare velocemente transazioni finanziarie anomale o sospette.RisorseWhitepaperScavare nel data lake per un'analisi approfondita dei datiUnificare Big Data e AI nel settore dei servizi finanziariIl valore nascosto della migrazione da HadoopWebinarModernizzare le piattaforme di gestione e analisi dei dati in tutta sicurezza usando Databricks e AWSPerch\u00e9 le startup focalizzate sui dati stanno puntando sul lakehouseQuby sfrutta la potenza dell'analisi in tempo reale per prendere decisioni rapideLoyaltyOne semplifica e potenzia le pipeline di dati con Delta LakeSfrutta il potenziale del tuo data lakeCostruzione di un data lakehouse in DoorDash e GrammarlySettori industrialiPrognos sfrutta AI\/ML per estrarre informazioni concrete da dati di laboratorio clinici riferiti a tutta la popolazioneCome il machine learning sta cambiando l'analisi dei dati nella pubblica amministrazionePronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/legal\/privacynotice#dbinformationwecollectaboutyou","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/customers","text":"Clients Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLes clients DatabricksD\u00e9couvrez comment des entreprises innovantes de tous les secteurs mettent la plateforme Lakehouse de Databricks au service de leur succ\u00e8sHistoires \u00e0 la une\n\n\nT\u00e9moignage de client\n\nComment l\u2019IA change la d\u00e9couverte de m\u00e9dicaments\nAstraZeneca d\u00e9couvre, d\u00e9veloppe et commercialise des m\u00e9dicaments r\u00e9volutionnaires pour lutter contre des maladies comptant parmi les plus graves au monde.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nCaptiver le regard avec une mode audacieuse\nBurberry voit une am\u00e9lioration de 70 % des gains de temps pour la g\u00e9n\u00e9ration d'informations sur les images avec Databricks Lakehouse\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nPromouvoir l\u2019efficacit\u00e9 organisationnelle par l\u2019unification des donn\u00e9es\nAlors que l\u2019ing\u00e9nierie et la construction durables prennent de plus en plus d\u2019importance, le groupe Colas s\u2019est donn\u00e9 pour mission d\u2019imaginer, de construire et d\u2019entretenir des infrastructures de transport qui minimisent l\u2019impact environnemental tout en maximisant la valeur pour leurs clients.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nModerniser les services financiers gr\u00e2ce aux donn\u00e9es et \u00e0 l'IA\n\u00ab\u00a0Malgr\u00e9 l'adoption croissante du big data et de l'IA, la plupart des entreprises de services financiers est toujours confront\u00e9e \u00e0 d'importants d\u00e9fis, que cela concerne la vari\u00e9t\u00e9 des types de donn\u00e9es, leur \u00e9volutivit\u00e9 ou encore la protection de la vie priv\u00e9e.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nDes insights plus rapidement gr\u00e2ce \u00e0 la gouvernance des donn\u00e9es unifi\u00e9e\nGreenFlex est un leader europ\u00e9en dans le domaine de la gestion environnementale, de l'efficacit\u00e9 \u00e9nerg\u00e9tique et de la gestion de l'impact environnemental.\n\nEn savoir plus\n\n\nT\u00e9moignage de client\n\nUn avenir durable \u00e0 grande vitesse pour les transports\nLa mission de la SNCF est d'assurer le transport fluide et durable des passagers et des marchandises, tout en r\u00e9duisant les \u00e9missions carbone et en mettant les \u00e9nergies renouvelables au service de l'avenir de la mobilit\u00e9.\u00a0\n\nEn savoir plusD\u00e9couvrir tous les clientsThe Data Team EffectLes \u00e9quipes data repr\u00e9sentent une force unie pour r\u00e9soudre les probl\u00e8mes mondiaux les plus complexes.Voyez comment \u2192Et si c'\u00e9tait vous, la prochaine success story\u00a0?Nous contacterRessourcesT\u00e9moignage de clientD\u00e9couvrez comment Databricks permet \u00e0 Cond\u00e9 Nast de proposer des contenus personnalis\u00e9s \u00e0 ses clients.En savoir plusWebinaireD\u00e9couvrez comment Apple et Disney+ ont r\u00e9uni l'analytique et l'IA pour r\u00e9ussirRegarderPodcastSlawek Kierner, SVP, Chief Data et Analytics Officer chez Humana, nous parle du r\u00f4le des donn\u00e9es et de l'IA dans l'\u00e9quit\u00e9 des soins m\u00e9dicauxRegarderPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/product\/data-science","text":"Data Science | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWData ScienceLa Data Science collaborative \u00e0 l'\u00e9chelleEssai gratuitPlanifier une d\u00e9moPlongez plus profond\u00e9ment dans la science des donn\u00e9es sur DatabricksDatabricks NotebooksIDE IntegrationReposMachine LearningRationalisez le workflow Data Science de bout en bout \u2013 de la pr\u00e9paration des donn\u00e9es au partage des informations, en passant par la mod\u00e9lisation \u2013 gr\u00e2ce \u00e0 un environnement unifi\u00e9 et collaboratif reposant sur une fondation ouverte de lakehouse. B\u00e9n\u00e9ficiez d'un acc\u00e8s rapide \u00e0 des donn\u00e9es fiables, de ressources de calcul pr\u00e9configur\u00e9es, d'un IDE int\u00e9gr\u00e9, d'une prise en charge multilingue et d'outils int\u00e9gr\u00e9s de visualisation avanc\u00e9e, pour donner un maximum de flexibilit\u00e9 \u00e0 vos \u00e9quipes d'analytique.Collaboration dans l'ensemble du workflow de Data Science\u00c9crivez du code en Python, R, Scala et SQL, explorez les donn\u00e9es gr\u00e2ce \u00e0 des visualisations interactives et d\u00e9couvrez de nouveaux insights avec les notebooks de Databricks. Partagez du code en toute confiance et en toute s\u00e9curit\u00e9 gr\u00e2ce \u00e0 la co-cr\u00e9ation, aux commentaires, \u00e0 la gestion de versions automatique, aux int\u00e9grations Git et aux contr\u00f4les d'acc\u00e8s bas\u00e9s sur les r\u00f4les.Concentrez-vous sur la Data Science, pas sur l'infrastructureVous n'\u00eates plus limit\u00e9 par la capacit\u00e9 de stockage de votre ordinateur portable, ni par la puissance de calcul dont vous disposez. Migrez rapidement votre environnement local vers le cloud et connectez des notebooks \u00e0 vos ressources de calcul personnelles et vos clusters autog\u00e9r\u00e9s.Utilisez votre IDE local pr\u00e9f\u00e9r\u00e9 avec un calcul \u00e9volutif.Le choix d'un IDE est tr\u00e8s personnel et impacte consid\u00e9rablement la productivit\u00e9.Connectez votre IDE pr\u00e9f\u00e9r\u00e9 \u00e0 Databricks afin de pouvoir continuer \u00e0 b\u00e9n\u00e9ficier d'un stockage de donn\u00e9es et d'un calcul sans limite. Ou utilisez simplement RStudio ou JupyterLab directement depuis Databricks pour une exp\u00e9rience fluide.Soyez pr\u00eat pour la data scienceNettoyez et cataloguez toutes vos donn\u00e9es - en batch, en streaming, structur\u00e9es ou non structur\u00e9es - en un seul endroit avec Delta Lake et rendez-les accessibles \u00e0 toute votre organisation via un magasin de donn\u00e9es centralis\u00e9. Quand les donn\u00e9es arrivent, des contr\u00f4les de qualit\u00e9 automatiques garantissent qu'elles r\u00e9pondent aux attentes et qu'elles sont pr\u00eates pour l'analytique. Au fur et \u00e0 mesure que les donn\u00e9es sont aliment\u00e9es par de nouvelles entr\u00e9es et qu'elles sont transform\u00e9es, la gestion de versions vous permet de r\u00e9pondre aux besoins de conformit\u00e9.Des outils visuels avec peu de code pour explorer les donn\u00e9esUtilisez des outils visuels natifs dans les notebooks Databricks pour pr\u00e9parer, transformer et analyser vos donn\u00e9es. Donnez aux \u00e9quipes, quel que soit leur niveau d'expertise, les moyens de travailler avec les donn\u00e9es. Une fois vos transformations de donn\u00e9es et vos visualisations termin\u00e9es, vous pouvez g\u00e9n\u00e9rer le code qui s\u2019ex\u00e9cute en arri\u00e8re-plan. Comme vous n'avez plus besoin d'\u00e9crire le code de base, vous pouvez consacrer davantage de temps \u00e0 des t\u00e2ches plus productives.D\u00e9couvrez et partagez de nouveaux insightsPartagez et exportez facilement vos r\u00e9sultats en transformant rapidement votre analyse en tableau de bord dynamique. Constamment \u00e0 jour, ces derniers peuvent \u00e9galement ex\u00e9cuter des requ\u00eates interactives. Les cellules, les visualisations ou les notebooks peuvent \u00eatre partag\u00e9s avec un contr\u00f4le d'acc\u00e8s bas\u00e9 sur les r\u00f4les et export\u00e9s dans plusieurs formats, notamment HTML et IPython Notebook.Migrer vers DatabricksVous en avez assez des silos de donn\u00e9es, de la lenteur des performances et des co\u00fbts \u00e9lev\u00e9s associ\u00e9s aux anciens syst\u00e8mes comme Hadoop et aux entrep\u00f4ts de donn\u00e9es d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de donn\u00e9es, d'analyses et d'IA.Migrer vers DatabricksRessources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez la biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur la data science et le machine learning.\nExplorer les ressourcesRapports et ebooksLe Grand Livre de la Data ScienceL'art de la data science collaborative \u00e0 grande \u00e9chelleModern Cloud Data PlatformMLflow \u2013 une plateforme de machine learning open sourceD\u00e9couvrez la nouvelle solution de Delta SharingDatabricks nomm\u00e9 leader dans le Magic Quadrant\u2122 Gartner\u00ae 2021 dans les cat\u00e9gories SGBD et DSMLGuide de migration : Hadoop vers DatabricksBlogsCinq \u00e9tapes cl\u00e9s pour r\u00e9ussir la migration de Hadoop vers l'architecture Lakehouse\u00c9v\u00e8nements virtuelsGuide \u00e9tape par \u00e9tape de la migration HadoopPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/broadcast-streaming","text":"Databricks for Broadcast and Streaming - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for Broadcast and StreamingThe next-generation data platform that helps you drive smarter consumer and advertiser outcomes with tools to know, grow and retain engaged viewersGet startedSchedule a demoMeet Data Lakehouse: The best of both worlds in one platformA data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It\u2019s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all your data and cloud platforms.Learn moreWhy Databricks for broadcast and streaming?Get more value from all your data\nUnlock insights from both structured and unstructured video\/image\/NLP media assets to create new content monetization opportunities.Drive stronger business outcomes through collaboration\nData teams can innovate and deploy solutions faster, thanks to the collaborative workspace of the Databricks Lakehouse Platform.Operate at the speed of business\nWith optimized streaming ingest, pre-built offerings with top solution providers, and real-time model serving with MLflow, accelerate consumer and advertiser outcomes for your business.Leverage pre-built models for ML and AI\nDatabricks has a collaborative notebook environment with managed runtime for machine learning models, as well as Solution Accelerators for common use cases including customer lifetime value and churn prediction.Databricks for broadcast and streaming use casesDatabricks empowers teams to build more effective personalized experiences at scale, improve advertising performance, and derive more value across your entire content portfolio.Audience experience\nCreate a personalized, frictionless journey to move consumers from anonymous to advocate\nPersonalization engines\nGDPR\/CCPA compliance\nChurn management\nForum moderation\nStreaming quality of service\nAdvertising performance and optimization\nGive sales and operations teams the right insights to increase advertising performance and targeting\nAttribution\nInventory and yield management\nAudience segmentation and targeting\nCampaign performance\nAd verification\nContent lifecycle\nAdvanced insights on content pricing, crew scheduling, content metadata extraction and more\nProduct development lifecycle\nContent pricing and analytics\nCrew\/resource optimization\nImage\/profanity recognition\nSlate management and monetization\nTransforming broadcast and streaming with Lakehouse\n\u201cWith the Databricks Lakehouse Platform on AWS, Warner Bros. Discovery is powering the future of content discovery and audience experiences. By leveraging data to better predict consumer behavior and provide personalized content recommendations in real time, we are able to customize the viewer experience and improve overall engagement for our customers.\u201d\u2014 Martin Ma, GVP, Engineering at Warner Bros. DiscoveryPartners and solutionsGet started with a variety of data and analytics solutions and templates specific to broadcast and streamingMulti-touch attributionMeasure ad effectiveness and optimize marketing spend with better channel attributionGet started Survival analysis\/LTVPredict which consumers are at risk of churning and what factors extend to the consumer lifecycleGet started Propensity to churnEffectively manage retention, understand lifecycle and reduce your churn rateGet started Behavioral segmentationCreate advanced segments to drive better purchasing predictions based on behaviorsGet startedSales forecasting and attributionIncrease advertising outcomes by optimizing and focusing on the best-performing channelsGet startedRecommendationsIncrease conversions and engagement with personalized omnichannel recommendationsGet startedComputer vision\/LabelboxAnnotate images and videos to help drive contextual ad targeting in the Lakehouse\n\u00a0\nComing soon\nVideo quality of experienceAnalyze batch and streaming data to ensure a performant streaming content experienceGet startedReal-time biddingLearn how to predict ad viewability in real time to enhance your RTB strategyGet startedSee all solutionsDatabricks for broadcast and streaming in actionResourceseBooks and downloadsThe Big Book of Media & Entertainment Use CasesData-Driven Innovation in Media & EntertainmentLakehouse for Media & Entertainment Solution SheetWebinarsPushing Boundaries: Advanced M&E Case StudiesIntro to Databricks Solution Accelerators for M&ECustomer Lifetime ValuePredicting Churn to Improve Customer RetentionBlogsThe Emergence of the Composable Customer Data PlatformDominate Your Daily Wordle With LakehouseHow DPG Delivers High-Quality and Marketable Segments to Advertisers100 Years of Horror Films: An Analysis Using Databricks SQLReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matt-mckenzie","text":"Matt McKenzie - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatt McKenzieGM, Technology at TabcorpBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/legal\/privacynotice","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-media-entertainment-use-cases?itm_data=mesols-promo-EB-bbme","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/robinson-creighton","text":"Robinson Creighton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRobinson CreightonPrincipal Analyst, Enterprise Data Ops at Comcast AdvertisingBack to speakersRobinson \"Robs\" Creighton is Sr. DataOps Lead, Advanced Analytics, for Comcast Effectv, responsible for their data stack architecture and lakehouse migration. Previously, she worked as a data analyst at Northwestern Mutual. She is a graduate of the University of Pennsylvania.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thomas-roach\/#","text":"Thomas Roach - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThomas RoachSr. Solutions Architect at DatabricksBack to speakersI am a Sr Solutions Architect at Databricks where I help our customers leverage our technology to solve strategic problems and maximize the value of their data assets. I have been working with Data for over two decades. The first 15 working with RDBMS technologies and the last eight working with Big Data technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/special-events","text":"Special Events - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpecial EventsYour pass will give you free access to a host of special events across four days in San Francisco. Attend parties and get-togethers, networking opportunities, meetups and specialist panels, such as the Women in Data discussion.MeetupsWomen in Data + AIPartiesMeetupsJoin like-minded professionals at our Data + AI Summit meetups to discuss the latest news, innovations and trends across the data, analytics and AI ecosystem.\nCome to a meetup!Eat, socialize and network with fellow data prosLearn new tips and tricks for your favorite technologiesSee what new features are in the pipelineWomen in Data and AIAttend our popular Women in Data and AI panel discussion and explore the array of activities and opportunities for women in data to connect. Join us for a special luncheon, a meetup at our after-party and much, much more throughout Summit.\nAs an attendee, you can: Hear from women who are making an impact and revolutionizing the world of data, analytics and AI \u2014 during a lunch and learn sessionJoin us at a dedicated meetup and offsite party for Data + AI Summit womenNetwork throughout the event with inspirational women who work in data, analytics and AIPartiesEnjoy exclusive parties \u2014 celebrate the world of data, analytics and AI with your fellow data professionals throughout four days in San Francisco.\nJoin us for a variety of social gatherings including an offsite party featuring live entertainment and more fun activities! Details coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-thompson","text":"Justin Thompson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin ThompsonDirector, IT Data and Analytics at JetBlueBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mani-kandasamy\/#","text":"Mani Kandasamy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMani KandasamyTech Fellow at Deloitte Consulting LLPBack to speakersMani is a technology executive with Deloitte Consulting LLP and leads @Scale cloud data modernization and analytics solutions for a global portfolio of Deloitte's clients. \nHe is a highly sought and trusted technical advisor, conference speaker, and passionate about helping the clients transform continually leveraging emerging and niche technologies to achieve greater business benefits.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/morgan-hsu","text":"Morgan Hsu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMorgan HsuDirector, Data and ML Engineering at FanDuelBack to speakersMorgan manages the Insights and ML platform teams at FanDuel. His teams provide ML infrastructure and services used to support use cases including responsible gaming, fraud detection, and marketing optimization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nitu-nivedita","text":"Nitu Nivedita - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNitu NiveditaManaging Director at AccentureBack to speakersNitu Nivedita is a Managing Director within Accenture\u2019s Applied Intelligence group specializing in Artificial Intelligence, Machine Learning and Cloud Computing for scaling AI. Nitu is also the product and engineering lead for Human.AI (which is portfolio of many AI assets and engineering teams focused on building AI solutions for the Future of Work). In this role, Nitu provides technical leadership for accelerating large-scale digital transformation journeys in client organizations, building enterprise-wide AI solutions that deliver game-changing results and creating sustainable value. Nitu is passionate about technology, business and innovation. She leads a 50+ global solution team of software engineers, data scientists, ML engineers, architects, and product managers to help clients scale AI faster, innovate with cutting-edge multi-cloud technologies and thereby create 360-degree value for our communities \nNitu has a Bachelor\u2019s of Technology (B.Tech) degree in Computer Science Engineering from National Institute of Technology, India. She has an MBA from Cornell University, New York and SDA Bocconi, Italy. She received the \u2018Award of Excellence\u2019 for achieving highest academic excellence during Computer Science Engineering, top of Dean\u2019s list during MBA, and she was the Director of \u2018Girls in Tech\u2019 - a global organization which helps young female professionals and school-aged girls to become interested in technology, coding, and more \nNitu has been a founding member of Accenture's \u201cWomen in AI\u201d forum. She has been awarded and\/or nominated as a finalist for multiple Global AI & Technology Leadership Awards by various global organizations (VentureBeat, Women in AI etc), 2021Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/healthcare-and-life-sciences","text":"Lakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicasOfere\u00e7a melhores resultados a pacientes com dados e IAComece agoraAgendar uma demonstra\u00e7\u00e3oQuatro desafios de dados no setor de sa\u00fade e ci\u00eancias biol\u00f3gicasFragmenta\u00e7\u00e3o de dados do paciente\nOs silos de dados e o suporte limitado a dados n\u00e3o estruturados impedem que as empresas entendam a jornada do paciente.Dados de sa\u00fade em r\u00e1pido crescimento\nAs arquiteturas de dados legadas on-premise s\u00e3o complexas de gerenciar e caras para dimensionar e atender aos enormes volumes atuais de dados de sa\u00fade, impulsionados principalmente pelo crescimento de imagens e gen\u00f4mica.Cuidados e opera\u00e7\u00f5es em tempo real\nData warehouses e ferramentas desarticuladas impedem a entrega em tempo real de insights necess\u00e1rios para tomar decis\u00f5es cr\u00edticas de sa\u00fade e produzir e administrar importantes produtos terap\u00eauticos com seguran\u00e7a.Complexidade na an\u00e1lise avan\u00e7ada de sa\u00fade\nOs recursos simplistas de ML impedem que as organiza\u00e7\u00f5es abordem um amplo espectro, desde modelos de atendimento ao paciente de \u00faltima gera\u00e7\u00e3o at\u00e9 an\u00e1lises preditivas para P&D de medicamentos.Lakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicasPlataforma unificada de dados e IA\nUma plataforma \u00fanica que re\u00fane todas as suas cargas de trabalho de dados e an\u00e1lises para permitir inova\u00e7\u00f5es profundas para atendimento aos pacientes e P&D de medicamentos.\nSolu\u00e7\u00f5es para parceiros\nOs principais provedores de solu\u00e7\u00f5es globais para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas, como Deloitte, Accenture e ZS Associates, desenvolvem o lakehouse. Aproveite as ofertas predefinidas que aceleram a transforma\u00e7\u00e3o orientada por dados em P&D de medicamentos e atendimento aos pacientes.\nFerramentas para acelerar\nA Databricks e seus parceiros desenvolveram uma s\u00e9rie de aceleradores de solu\u00e7\u00f5es que facilitam a ingest\u00e3o de dados de sa\u00fade, como mensagens HL7, e a realiza\u00e7\u00e3o de casos de uso como a an\u00e1lise de textos m\u00e9dicos e o monitoramento da seguran\u00e7a de medicamentos.\nColabora\u00e7\u00e3o no setor\nPermita o compartilhamento seguro e aberto de dados e a colabora\u00e7\u00e3o com organiza\u00e7\u00f5es em todo o ecossistema de sa\u00fade para acelerar a pesquisa para salvar vidas e melhorar a presta\u00e7\u00e3o de cuidados.\nCuidando do futuro com lakehouse\n\u00a0\n\u201cO Databricks Lakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas oferece \u00e0 GE Healthcare uma plataforma moderna, aberta e colaborativa para criar insights sobre os pacientes durante toda sua jornada de atendimento. Com esses recursos, reduzimos os custosos silos de dados legados e equipamos nossas equipes com insights oportunos e precisos.\u201d\u2014 Joji George, CTO, LCS Digital, GE HealthcarePor que Lakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas?\nAcelere a pesquisa e melhore os resultados dos pacientes em uma plataforma aberta e colaborativa para dados e IAVis\u00e3o 360\u00ba do paciente\nRe\u00fana todos os seus dados estruturados e n\u00e3o estruturados (pacientes, P&D e opera\u00e7\u00f5es) em uma \u00fanica plataforma dedicada a an\u00e1lises e IA. Com uma vis\u00e3o hol\u00edstica da jornada do paciente, as organiza\u00e7\u00f5es podem oferecer tratamentos mais personalizados.Escalabilidade infinita para estudos em n\u00edvel populacional\nAnalise dados de milh\u00f5es de pacientes de forma r\u00e1pida e confi\u00e1vel com uma plataforma escal\u00e1vel baseada em nuvem. Com esses insights em n\u00edvel populacional, as organiza\u00e7\u00f5es obt\u00eam uma vis\u00e3o mais completa das tend\u00eancias de sa\u00fade e, por sua vez, podem desenvolver terapias mais eficazes.An\u00e1lises em tempo real, opera\u00e7\u00f5es em tempo real\nIngira e processe rapidamente dados de streaming onde quer que estejam para potencializar as an\u00e1lises em tempo real, com aplica\u00e7\u00f5es que v\u00e3o desde o gerenciamento da capacidade de leitos hospitalares at\u00e9 a otimiza\u00e7\u00e3o da fabrica\u00e7\u00e3o e distribui\u00e7\u00e3o de produtos farmac\u00eauticos.Descoberta de medicamentos e atendimento ao paciente utilizando ML\nLibere o potencial do machine learning para entender melhor as doen\u00e7as e prever as necessidades de sa\u00fade. Todos os seus dados est\u00e3o perfeitamente conectados com um conjunto completo de ferramentas colaborativas para an\u00e1lises avan\u00e7adas.Baixar e-bookParceiros e solu\u00e7\u00f5esComece com uma variedade de solu\u00e7\u00f5es e modelos de an\u00e1lise e dados espec\u00edficos para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicasSa\u00fade conectadaMelhore a experi\u00eancia dos pacientes e os resultados de sa\u00fade personalizando o percurso de atendimento e o acesso aos servi\u00e7os.Introdu\u00e7\u00e3oPrecisionView\u2122Expanda os recursos, aumente as capacidades e enrique\u00e7a a colabora\u00e7\u00e3o interna no setor de sa\u00fade e ci\u00eancias biol\u00f3gicas.Introdu\u00e7\u00e3oInteroperabilidade de dados de sa\u00fadeAutomatize a ingest\u00e3o de pacotes FHIR em streaming no lakehouse para analisar os dados downstream de pacientes em grande escala.Introdu\u00e7\u00e3oIntrodu\u00e7\u00e3oGerenciamento inteligente de dados para pesquisa biom\u00e9dicaTransforme os dados cient\u00edficos em ativos para seus neg\u00f3cios criando uma cadeia de valor de ponta a ponta.Introdu\u00e7\u00e3oVer todas as solu\u00e7\u00f5es de parceirosModelos de dados e configura\u00e7\u00e3o de coortes: correspond\u00eancia OMOP e escore de propens\u00e3oIngira e padronize facilmente dados do mundo real em seu lakehouse para an\u00e1lise observacional em escalaIntrodu\u00e7\u00e3oInteroperabilidade: ingerir mensagens HL7V2Automatize a ingest\u00e3o de mensagens HL7V2 em streaming no lakehouse para an\u00e1lises em tempo realIntrodu\u00e7\u00e3oInteroperabilidade: ingerir pacotes FHIRAutomatize a ingest\u00e3o de pacotes FHIR em streaming no lakehouse para analisar os dados downstream de pacientesIntrodu\u00e7\u00e3oImagem: classifica\u00e7\u00e3o de patologia digitalAumente os fluxos de trabalho de diagn\u00f3stico com deep learning, detectando met\u00e1stases em l\u00e2minas de patologia digitalIntrodu\u00e7\u00e3oP&D: identifica\u00e7\u00e3o de alvos de medicamentosAnalise associa\u00e7\u00f5es gen\u00e9ticas em grande escala para ajudar as equipes de P&D a identificar novos alvos de medicamentosIntrodu\u00e7\u00e3oSa\u00fade da popula\u00e7\u00e3o: previs\u00e3o de risco de doen\u00e7asCrie modelos preditivos de risco de doen\u00e7as para melhorar os programas de gerenciamento de cuidadosIntrodu\u00e7\u00e3oNLP: detecte efeitos adversosMelhore o monitoramento da seguran\u00e7a de medicamentos com a detec\u00e7\u00e3o de afeitos adversos com nossa solu\u00e7\u00e3o de NLP desenvolvida em conjunto com John Snow LabsIntrodu\u00e7\u00e3oNLP: extraia dados oncol\u00f3gicos reaisTransforme notas de oncologia n\u00e3o estruturadas em insights sem precedentes de pacientes usando nossa solu\u00e7\u00e3o de NLP em conjunto com John Snow LabsIntrodu\u00e7\u00e3oNLP: automatize a remo\u00e7\u00e3o de PHIAutomatize a remo\u00e7\u00e3o de informa\u00e7\u00f5es confidenciais de pacientes dos dados textuais usando nossa solu\u00e7\u00e3o de NLP em conjunto com John Snow LabsIntrodu\u00e7\u00e3oVer todas as solu\u00e7\u00f5esLakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas na pr\u00e1ticaQuer saber mais?Cuidados de sa\u00fade\nOfere\u00e7a atendimento centrado no paciente com o poder dos dados e da IACi\u00eancias biol\u00f3gicas\nTrazendo novos tratamentos para pacientes que precisam por meio de an\u00e1lise de dados e IAMelhore os resultados de sa\u00fade com dados e IABaixar e-book \u2192Recursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre dados e IA para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicas.\nExplorar recursose-booksImproving Outcomes With the Lakehouse for Healthcare and Life SciencesDescubra novos insights de pacientes com processamento de linguagem natural em grande escalaLakehouse: perceba o potencial dos dados reaisVis\u00e3o geral de solu\u00e7\u00f5es: Lakehouse para o setor de sa\u00fade e ci\u00eancias da vidaWebinarsWorkshop: FHIR e an\u00e1lise de pacientes em tempo real com um lakehouseWebinar: Chesapeake Regional Information System impulsionando inova\u00e7\u00f5es na \u00e1rea da sa\u00fade para pacientesWorkshop: Padroniza\u00e7\u00e3o de dados com OMOP e previs\u00e3o de riscos de doen\u00e7as com MLWorkshop: Extraia dados reais com NLPWorkshop: Acelerando a P&D com dados reais + IABlogsAmgen acelera o desenvolvimento e a entrega de medicamentos com o lakehouse dedicado a cuidados com a sa\u00fade e as ci\u00eancias biol\u00f3gicasLakehouse para o setor de sa\u00fade e ci\u00eancias biol\u00f3gicasMelhoria da seguran\u00e7a dos medicamentos por meio da detec\u00e7\u00e3o de efeitos adversos via NLPO kit de ferramentas de gen\u00f4mica de c\u00f3digo aberto da Databricks supera as principais ferramentasExtra\u00e7\u00e3o de insights oncol\u00f3gicos de dados cl\u00ednicos reais com NLPTudo pronto para come\u00e7ar?Adorar\u00edamos saber seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteAgendar uma demonstra\u00e7\u00e3oProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/daniel-tenedorio","text":"Daniel Tenedorio - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDaniel TenedorioSr. Staff Software Engineer at DatabricksBack to speakersDaniel Tenedorio is a software engineer at Databricks, working on Spark Core and Spark SQL. He interacts with the Apache Spark\u2122 open-source community to develop and review query processing features. Daniel has a breadth of experience in database management systems development from building and launching features underpinning multiple major production services over time.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/avanade-intelligent-manufacturing","text":"Avanade Intelligent Manufacturing | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionIntelligent ManufacturingIndustry-specific solution developed by Avanade and powered by Databricks Lakehouse PlatformGet startedAI is the solution for manufacturingLacking an awareness of the physical asset state carries a cost that is too large to ignore for manufacturers. Every year, businesses lose millions of dollars due to equipment failure, unscheduled downtime and lack of control in maintenance scheduling.\u200b Along with lost dollars, businesses will experience lower employee morale when stations are in and out of service. To solve for this, Avanade\u2019s Intelligent Manufacturing solution supports connected production facilities and assets, workers, products and consumers to create value through enhanced insights and improved outcomes. With the solution, you can:Realize value across the business: Improve outcomes across production (e.g., uptime, quantity\/yield), worker experience and customer insights.Operationalize team coordination and productivity: Enhance care team productivity with continuous and coordinated care team collaboration.Utilize data: Harness your data, drive interoperability and provide enhanced insights at scale using analytics and AI.Get startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/r-programming","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jon-osborn","text":"Jon Osborn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJon OsbornField CTO at Ascend.ioBack to speakersJon Osborn is an experienced technology executive (CDAO, VP) with deep management & development experience using cloud native solutions for agile data delivery. He is passionate about building high performance teams & zero impedance paths to production for both data & apps. With his background and track record of success, he excels at defining the combinations of business justification, executive support, mindset shift, & cultural changes required to drive a winning data modernization strategy.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/compliance-ethics","text":"Legal Compliance & Ethics | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesLegal Compliance & EthicsAt Databricks, we do business the right way. We think about why we do what we do, and act intentionally using first principles thinking based on the risks and consequences of our actions.Behaviorally, we play by the rules, act with integrity, and speak up if we see someone violating our policies or the law. Our Global Code of Conduct supports these behaviors by explaining our policies and guidelines for conducting business with the highest standards of ethics.Databricks is committed to an environment where open, honest communications are the expectation, not the exception. We want all our employees and everyone we work with to understand this commitment and feel not only valued, but comfortable in raising issues to us.\u00a0\u00a0Access our Code of Conduct\u00a0>Databricks also holds third parties, including business partners and vendors, to the same high standards we hold for ourselves. We place a high degree of trust in our third parties and expect them to demonstrate the same ethical behaviors we expect of our own employees.Access our Third Party Code of Conduct >Databricks respects global human rights and expects internationally recognized standards to be the guide for everyone in our global network.Access our Modern Slavery Statement\u00a0>Databricks France is committed to diversity and gender equality. Databricks France demonstrates this commitment and its compliance with Gender Equality requirements by calculating and publishing its Gender Equality Index on an annual basis.Access Our France Gender Equity Index>\u00a0ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/miao-wang","text":"Miao Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMiao WangSenior Engineering Manager at AdobeBack to speakersMiao is a Senior Engineering Manager at Adobe, where he works with a great team on platform engineering with Spark and other open-source technologies. He was an active Spark contributor before changing to his manager role. His interests span high-speed networks, data center infrastructure, data processing, and machine learning. Prior to joining Adobe, he worked at A10 Networks, IBM, and Alibaba in various engineering roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/thomas-la-piana","text":"Thomas La Piana - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingThomas La PianaSenior Software Engineer at EthycaBack to speakersThomas La Piana is a data engineer turned product engineer with experience building out modern data stacks across multiple startups. Thomas joined Ethyca in 2021 to help create data privacy tools that engineers might actually want to use and shift the consideration of data privacy left.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/heiko-udluft","text":"Heiko Udluft - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHeiko UdluftChief Technology Officer at Divirod, Inc.Back to speakersHeiko Udluft is proud to be part of the team that is building a data platform for the world\u2019s most valuable asset: WATER. As CTO of Divirod he is building our digital services with a team of developers in close collaboration with Market and Business Development team members. Previously he worked as Product Owner, Tech-Team Lead, and Data Scientist for Airbus Defense and Space GmbH in a business incubator. His background is in Aerospace Engineering with a specialization in Air Transport and Operations. He completed PhD-level research on decentralized control at Delft University of Technology. In this research, he applied Artificial Intelligence methods, specifically Agent-Based Modelling and Simulation, to increase the resiliency of critical infrastructure. Previously, he worked and studied at the Massachusetts Institute of Technology with a focus on improving the capacity and efficiency of a large-scale infrastructure system. His passion is in exploring technology and knowledge that can be implemented on a global scale to sustainably better human lives.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/discover\/demos","text":"Centre de d\u00e9mo produits et partenaires Databricks \u2013 D\u00e9mo de l'Acc\u00e9l\u00e9rateur de solutions \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWCentre de d\u00e9mosGr\u00e2ce \u00e0 ces vid\u00e9os simples \u00e0 la demande, vous obtiendrez un premier aper\u00e7u de Databricks du point de vue des professionnels. Chaque d\u00e9mo ci-dessous est accompagn\u00e9e d'\u00e9l\u00e9ments connexes \u2014 notamment des notebooks, des vid\u00e9os et des eBooks \u2014 afin que vous puissiez vous-m\u00eame tester Databricks.Essayer gratuitementD\u00e9mos ProduitsPlateforme DatabricksDans cette d\u00e9mo, vous aurez un aper\u00e7u g\u00e9n\u00e9ral de la plateforme Databricks Lakehouse, avec notamment une discussion sur l'int\u00e9gration des projets open source, tels qu'Apache Spark\u2122, Delta Lake, MLflow et Koalas, dans l'\u00e9cosyst\u00e8me Databricks.En savoir plusDatabricks SQLDatabricks WorkflowsUnity CatalogData Science et Machine LearningDelta SharingDelta LakeDelta\u00a0Live\u00a0tablesInt\u00e9gration des donn\u00e9es de Delta Lake (Auto Loader et COPY INTO)D\u00e9mo PartenairesInt\u00e9gration cloud d'Azure DatabricksLa plateforme Lakehouse d'Azure Databricks vous offre le meilleur des data lakes et des data warehouses sur une plateforme simple, ouverte et collaborative qui s'int\u00e8gre en toute s\u00e9curit\u00e9 \u00e0 vos services Azure existants. Dans cette d\u00e9mo, vous verrez les int\u00e9grations d'Azure Databricks les plus courantes, telles qu'Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics ou bien encore Power BI.En savoir plusInt\u00e9gration cloud de Databricks sur AWSD\u00e9ploiement de Databricks sur Google CloudContact partenairesSolutions pour l'industrieDe l\u2019id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulementLes acc\u00e9l\u00e9rateurs de solutions Databricks sont des guides sp\u00e9cialis\u00e9s con\u00e7us pour acc\u00e9l\u00e9rer les r\u00e9sultats \u00e0 l'aide de notebooks enti\u00e8rement fonctionnels et de bonnes pratiques. Les clients Databricks gagnent du temps dans leurs op\u00e9rations de d\u00e9couverte, de conception, de d\u00e9veloppement et de test. Beaucoup d'entre eux passent de l'id\u00e9e \u00e0 la preuve de concept (PoC) en deux semaines seulement.Explorez les Acc\u00e9l\u00e9rateursCr\u00e9ez votre compte Databricks1\/2Pr\u00e9nomNomE-mail professionnelEntrepriseIntitul\u00e9 de posteNum\u00e9ro de t\u00e9l\u00e9phone (facultatif)Veuillez s\u00e9lectionnerPaysD\u00e9marrerProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/glossary\/snowflake-schema","text":"What is a Snowflake Schema?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSnowflake SchemaAll>Snowflake SchemaTry Databricks for freeGet StartedWhat is a snowflake schema?A snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and reporting in OLAP data warehouses, data marts, and relational databases.In a snowflake schema, engineers break down individual dimension tables into logical subdimensions. This makes the data model more complex, but it can be easier for analysts to work with, especially for certain data types.It's called a snowflake schema because its entity-relationship diagram (ERD) looks like a snowflake, as seen below.Snowflake schemas vs. star schemasLike star schemas, snowflake schemas have a central fact table which is connected to multiple dimension tables via foreign keys. However, the main difference is that they are more normalized than star schemas.Snowflake schemas offer more storage efficiency, due to their tighter adherence to high normalization standards, but query performance is not as good as with more denormalized data models. Denormalized data models like star schemas have more data redundancy (duplication of data), which makes query performance faster at the cost of duplicated data.Benefits of snowflake schemasFast data retrievalEnforces data qualitySimple, common data model for data warehousingDrawbacks of snowflake schemasLots of overhead upon initial setupRigid data modelHigh maintenance costsResourcesDatabricks SQL product pageDatabricks Glossary \u2014 Star Schema\u00a0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/blog","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/lovelytics-snowflake-migration","text":"Snowflake-to-Databricks Migration by Lovelytics | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionSnowflake-to-Databricks Migration by LovelyticsMigration solution developed by Lovelytics and powered by the Databricks Lakehouse Platform\nGet startedEnsure a rapid and sound migration processMigrating data platforms doesn\u2019t have to be a scary undertaking. In partnership with Databricks, Lovelytics has developed a migration solution strategy and specialty tools to ensure a rapid, sound migration process that leverages Databricks to unlock more value from data and AI. This five-step migration accelerator helps customers confidently move from Snowflake to Databricks. Unlock the value of Databricks best-in-class SQL performance, native ML capabilities and ML lifecycle management, including real streaming data use cases. With the Lovelytics migration accelerator, you can realize:2.7x average faster performance than Snowflake, according to third-party reports12x more cost efficiency than Snowflake, according to third-party reportsGet startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vicky-andonova","text":"Vicky Andonova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVicky AndonovaManager, Applied Machine Learning at AnomaloBack to speakersVicky is a founding team member and the manager of the Applied Machine Learning team at Anomalo. Her team is responsible for building Anomalo\u2019s machine-learning models and translating them into actionable insights for customers. Before Anomalo, Vicky worked at Instacart as a senior data scientist. There, she built Instacart\u2019s experimentation platform and was the lead data scientist on a company initiative to improve grocery delivery quality. Vicky graduated with a BSEE from Columbia University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paula-martinez\/#","text":"Paula Martinez - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaula MartinezCEO & Cofounder at MarvikBack to speakersPaula Mart\u00ednez cofounded Marvik, a machine learning consulting and development company that specializes in Computer Vision, Predictive Analytics and Natural Language Processing. Paula is an Electrical Engineer and holds a Master in technological business management. She was selected as a Google Developer Expert in machine learning and co-organizes machine learning meetups. She has also completed programs at MIT and Berkeley among others.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yaron-singer","text":"Yaron Singer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYaron SingerCEO & Co-Founder at Robust IntelligenceBack to speakersYaron Singer is the CEO & co-founder of Robust Intelligence, and the Gordon McKay Professor of Computer Science and Applied Mathematics at Harvard. Before Harvard he was a researcher at Google and obtained his PhD from UC Berkeley. He's the recipient of the NSF CAREER award, the Sloan fellowship, Facebook faculty award, Google faculty award, 2012 Best Student Paper Award at the ACM conference on Web Search & Data Mining, 2010 Facebook Graduate Fellowship, and 2009 Microsoft Research PhD Fellowship.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/built-on-partner-program","text":"Partnerprogramm \u201eBuilt on Databricks\u201c | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWPartnerprogramm \u201eBuilt on Databricks\u201cIhr Unternehmen mit Databricks aufbauen, vermarkten und erweiternJetzt bewerbenDas Partnerprogramm \u201eBuilt on Databricks\u201c bietet Zugriff auf technische Ressourcen und Markteinf\u00fchrungsressourcen, um die Entwicklung Ihrer modernen SaaS-Anwendung zu beschleunigen und Ihr Gesch\u00e4ft auszubauen. Grundlage bildet die Databricks Lakehouse-Plattform: ein kosteng\u00fcnstiges, globales offenes \u00d6kosystem zur Entwicklung von Datenanwendungen, Produkten und Services sowie zur nahtlosen gemeinsamen Nutzung von Daten in gro\u00dfem Ma\u00dfstab.\u201eBuilt on Databricks\u201c-Unternehmen generieren Gesch\u00e4ftswert in gro\u00dfem Ma\u00dfstabBlogJetzt lesenWebinarJETZT ANSEHENBlogJetzt lesenVorteile des Partnerprogramms \u201eBuilt on Databricks\u201cZugang zu Databricks-Experten\nZugang zu Produkt-, Technik- und Supportmitarbeitern von DatabricksAuf einer modernen Plattform entwickeln\nNutzung der marktf\u00fchrenden Lakehouse-Plattform f\u00fcr einheitliche Daten, Data Analytics und KIMehr Kunden erreichen\nGr\u00f6\u00dfere Reichweite f\u00fcr jeden Datenkunden \u00fcber eine offene und sichere PlattformMarketingunterst\u00fctzung\nZugriff auf Marketinginvestitionen zur Erh\u00f6hung der Pr\u00e4senz und Vergr\u00f6\u00dferung Ihrer ReichweiteZusammenarbeit beim Vertrieb\nMehr M\u00f6glichkeiten dank Enablement und Zusammenarbeit mit dem Databricks-VertriebWarum noch warten?Jetzt bewerbenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
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{"source":"https:\/\/www.databricks.com\/glossary\/machine-learning-models","text":"What are Machine Learning Models?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMachine Learning ModelsAll>Machine Learning ModelsWhat is a machine learning Model?A machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recognize the intent behind previously unheard sentences or combinations of words. In image recognition, a machine learning model can be taught to recognize objects - such as cars or dogs. A machine learning model can perform such tasks by having it 'trained' with a large dataset. During training, the machine learning algorithm is optimized to find certain patterns or outputs from the dataset, depending on the task. The output of this process - often a computer program with specific rules and data structures - is called a machine learning model.What is a machine learning Algorithm?A machine learning algorithm is a mathematical method to find patterns in a set of data. Machine Learning algorithms are often drawn from statistics, calculus, and linear algebra. Some popular examples of machine learning algorithms include linear regression, decision trees, random forest, and XGBoost.What is Model Training in machine learning?The process of running a machine learning algorithm on a dataset (called training data) and optimizing the algorithm to find certain patterns or outputs is called model training. The resulting function with rules and data structures is called the trained machine learning model.What are the different types of Machine Learning?In general, most machine learning techniques can be classified into supervised learning, unsupervised learning, and reinforcement learning.What is Supervised Machine Learning?In supervised machine learning, the algorithm is provided an input dataset, and is rewarded or optimized to meet a set of specific outputs. For example, supervised machine learning is widely deployed in image recognition, utilizing a technique called classification. Supervised machine learning is also used in predicting demographics such as population growth or health metrics, utilizing a technique called regression.What is Unsupervised Machine Learning?In unsupervised machine learning, the algorithm is provided an input dataset, but not rewarded or optimized to specific outputs, and instead trained to group objects by common characteristics. For example, recommendation engines on online stores rely on unsupervised machine learning, specifically a technique called clustering.What is Reinforcement Learning?In reinforcement learning, the algorithm is made to train itself using many trial and error experiments. Reinforcement learning happens when the algorithm interacts continually with the environment, rather than relying on training data. One of the most popular examples of reinforcement learning is autonomous driving.What are the different machine learning models?There are many machine learning models, and almost all of them are based on certain machine learning algorithms. Popular classification and regression algorithms fall under supervised machine learning, and clustering algorithms are generally deployed in unsupervised machine learning scenarios.Supervised Machine LearningLogistic Regression: Logistic Regression is used to determine if an input belongs to a certain group or notSVM: SVM, or Support Vector Machines create coordinates for each object in an n-dimensional space and uses a hyperplane to group objects by common featuresNaive Bayes: Naive Bayes is an algorithm that assumes independence among variables and uses probability to classify objects based on featuresDecision Trees: Decision trees are also classifiers that are used to determine what category an input falls into by traversing the leaf's and nodes of a treeLinear Regression: Linear regression is used to identify relationships between the variable of interest and the inputs, and predict its values based on the values of the input variables.kNN: The k Nearest Neighbors technique involves grouping the closest objects in a dataset and finding the most frequent or average characteristics among the objects.Random Forest: Random forest is a collection of many decision trees from random subsets of the data, resulting in a combination of trees that may be more accurate in prediction than a single decision tree.Boosting algorithms: Boosting algorithms, such as Gradient Boosting Machine, XGBoost, and LightGBM, use ensemble learning. They combine the predictions from multiple algorithms (such as decision trees) while taking into account the error from the previous algorithm.Unsupervised Machine LearningK-Means: The K-Means algorithm finds similarities between objects and groups them into K different clusters.Hierarchical Clustering: Hierarchical clustering builds a tree of nested clusters without having to specify the number of clusters.What is a Decision Tree in Machine Learning (ML)?A Decision Tree is a predictive approach in ML to determine what class an object belongs to. As the name suggests, a decision tree is a tree-like flow chart where the class of an object is determined step-by-step using certain known conditions.  A decision tree visualized in the Databricks Lakehouse. Source: https:\/\/www.databricks.com\/blog\/2019\/05\/02\/detecting-financial-fraud-at-scale-with-decision-trees-and-mlflow-on-databricks.htmlWhat is Regression in Machine Learning?Regression in data science and machine learning is a statistical method that enables predicting outcomes based on a set of input variables. The outcome is often a variable that depends on a combination of the input variables.  A linear regression model performed on the Databricks Lakehouse. Source: https:\/\/www.databricks.com\/blog\/2015\/06\/04\/simplify-machine-learning-on-spark-with-databricks.htmlWhat is a Classifier in Machine Learning?A classifier is a machine learning algorithm that assigns an object as a member of a category or group. For example, classifiers are used to detect if an email is spam, or if a transaction is fraudulent.How many models are there in machine learning?Many! Machine learning is an evolving field and there are always more machine learning models being developed.What is the best model for machine learning?The machine learning model most suited for a specific situation depends on the desired outcome. For example, to predict the number of vehicle purchases in a city from historical data, a supervised learning technique such as linear regression might be most useful. On the other hand, to identify if a potential customer in that city would purchase a vehicle, given their income and commuting history, a decision tree might work best.What is model deployment in Machine Learning (ML)?Model deployment is the process of making a machine learning model available for use on a target environment\u2014for testing or production. The model is usually integrated with other applications in the environment (such as databases and UI) through APIs. Deployment is the stage after which an organization can actually make a return on the heavy investment made in model development.  A full machine learning model lifecycle on the Databricks Lakehouse. Source: https:\/\/www.databricks.com\/blog\/2019\/09\/18\/productionizing-machine-learning-from-deployment-to-drift-detection.htmlWhat are Deep Learning Models?Deep learning models are a class of ML models that imitate the way humans process information. The model consists of several layers of processing (hence the term 'deep') to extract high-level features from the data provided. Each processing layer passes on a more abstract representation of the data to the next layer, with the final layer providing a more human-like insight. Unlike traditional ML models which require data to be labeled, deep learning models can ingest large amounts of unstructured data. They are used to perform more human-like functions such as facial recognition and natural language processing.  A simplified representation of deep learning. Source: https:\/\/www.databricks.com\/discover\/pages\/the-democratization-of-artificial-intelligence-and-deep-learning What is Time Series Machine Learning?A time-series machine learning model is one in which one of the independent variables is a successive length of time minutes, days, years etc.), and has a bearing on the dependent or predicted variable. Time series machine learning models are used to predict time-bound events, for example - the weather in a future week, expected number of customers in a future month, revenue guidance for a future year, and so on.Where can I learn more about machine learning?Check out this free eBook to discover the many fascinating machine learning use-cases being deployed by enterprises globally.To get a deeper understanding of machine learning from the experts, check out the Databricks Machine Learning blog.Additional ResourcesThe Big Book of MLOpsMachine Learning Engineering for the Real World Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/de\/solutions\/migration","text":"Zu Databricks migrieren | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWZu Databricks migrierenModernisieren Sie Ihre Datenplattform durch einen Umstieg auf Databricks Lakehouse\nDatabricks kostenlos testenDatabricks kontaktierenKosten senken, Innovation beschleunigen und Ihre Datenplattform vereinfachen \u2013 das geht ganz unkompliziert durch Migration von Ihrem Enterprise Data Warehouse oder \u00e4lteren Data Lake zu Databricks Lakehouse. Danach f\u00fchren Sie alle Daten-, Analytics- und KI-Workloads auf einer modernen, einheitlichen Plattform aus, die auf offenen Standards basiert und durch einen gemeinsamen Governance-Ansatz abgesichert ist.Warum zu Databricks migrieren?Ihre Datenplattform vereinfachenHolen Sie sich eine moderne zentralisierte Plattform f\u00fcr alle Daten-, Analytics- und KI-Anwendungsf\u00e4lle. Damit vereinheitlichen Sie Governance und Nutzungserlebnis cloud- und datenteam\u00fcbergreifend.\nKosteng\u00fcnstig skalierenSchluss mit dem Verwalten von Servern: Ab jetzt skalieren Sie bedarfsgerecht per Serverless. Betreiben Sie Data Warehousing im gro\u00dfen Stil mit einem bis zu 12-mal besseren Preis-Leistungs-Verh\u00e4ltnis.\nInnovationen beschleunigenErstellen Sie KI-, ML- und Echtzeit-Analytics-Funktionen schneller mit kollaborativen Selfservice-Tools und Open-Source-Technologien wie MLflow und Apache Spark\u2122.\nMigrieren von Hadoop\nMehr InformationenMigrieren von einem Data Warehouse\nMehr InformationenUnbesorgt migrierenWir haben Hunderte von Kunden bei der Migration von Legacy-Datenplattformen unterst\u00fctzt. Der Einsatz eines gestaffelten End-to-End-Migrationsprozesses stellt ein kalkulierbares Modell bereit, das die Kosten sowohl w\u00e4hrend als auch nach der Migration nachvollziehbar macht. Au\u00dferdem stellt der Lakehouse-First-Ansatz beim Migrieren aller Workloads die Unterst\u00fctzung f\u00fcr bestehende wie auch neue Anwendungsf\u00e4lle sicher. Das Ergebnis: geringere Risiken, eine beschleunigte Time-to-Value und ein h\u00f6herer ROI.Die 5 Phasen der DatenmigrationPhase 1:\nEntdeckung\nAutomatisieren Sie die Erkennung mit Profilern. So erhalten Sie Einblicke in die Workloads auf Ihrer Legacy-Plattform und k\u00f6nnen die Nutzungskosten der Databricks-Plattform einsch\u00e4tzen.\nPhase 2:\nBewertung\nF\u00fchren Sie mithilfe von Analyzern eine detaillierte Bewertung der Codekomplexit\u00e4t durch und veranschlagen Sie die Kosten f\u00fcr das Migrationsprojekt.\nPhase 3:\nStrategie\nErledigen Sie das Technologie-Mapping und entwickeln Sie unter fachkundiger Anleitung von Databricks optimale Migrationsverfahren f\u00fcr alle betroffenen Quellplattformen.\nPhase 4:\nPilotprojekt in der Produktion\nF\u00fchren Sie ein Pilotprojekt mit Ihren Anwendungsf\u00e4llen durch, und verwenden Sie gegebenenfalls Codekonverter, um Legacy-Code in Databricks-kompatiblen Code zu transkompilieren. Entwickeln Sie einen Implementierungsplan und eine Roadmap f\u00fcr die Migration.\nPhase 5:\nImplementierung\nWiederholen Sie diese Schritte f\u00fcr alle Workloads. Erhalten Sie Hilfe bei der Migrationsausf\u00fchrung und beim Support durch zertifizierte Partner oder Databricks Professional Services.\nKunden, die erfolgreich zu Databricks migriert sindKundenberichtPersonalisierung der Apothekenversorgung zur Verbesserung der Behandlungsergebnisse\nWeiterlesenKunden-BlogOn-Premise-Anwendungen vollst\u00e4ndig au\u00dfer Betrieb nehmen und so Kosten einsparen und schneller zum Erfolg kommen\nWeiterlesenKundenberichtDer Umstieg in die Cloud l\u00e4utet eine neue \u00c4ra des datengesteuerten Einzelhandels ein\nWeiterlesenBrickbuilder SolutionsNutzen Sie Brickbuilder Solutions f\u00fchrender Beratungspartner \u2013 gezielt entwickelt f\u00fcr die Migration zu Databricks LakehouseCloud Data Migration von AccentureWeniger R\u00e4tselraten, h\u00f6herer Mehrwert\nErste SchritteLegacy System Migration von AvanadeDurch Verlagerung das gesamte Potenzial Ihrer Daten erschlie\u00dfen\nErste SchritteMigrate to Cloud and Databricks von CapgeminiDatenmigration zur Databricks Lakehouse-Plattform optimieren\nErste SchritteMigrate to Databricks von Celebal TechnologiesSchnellere Migration von On-Premises zu geringeren Kosten\nErste SchritteMigrationsl\u00f6sung LeapLogic von ImpetusETL-, Data Warehouse-, Analytics- und Hadoop-Workloads automatisch in Databricks transformieren\nErste SchritteData Wizard for Hadoop\/EDW Migrations von InfosysDaten unbesorgt zu Databricks verschieben\nErste SchritteSnowflake-to-Databricks Migration von LovelyticsEinen schnellen und soliden Migrationsprozess sicherstellen\nErste SchritteSAS Migration Accelerator von Tensile AIVon Tensile AI entwickelte Migrationsl\u00f6sung \u2013 Powered by Databricks Lakehouse PlatformErste SchritteData Intelligence Suite von WiproUnbesorgt zu Databricks migrieren\nErste SchritteWechsel zu einer Data Lakehouse-Strategie\u00a0\u2013 eine weise EntscheidungWie Ihnen ein Data Lakehouse-Ansatz dabei helfen kann, die \u00fcblichen Einschr\u00e4nkungen von Data Warehouses und Data Lakes zu \u00fcberwindenJETZT HERUNTERLADENRessourcenE-BooksMigration von Hadoop zu Data Lakehouse f\u00fcr Anf\u00e4ngerMigrieren von einem Data Warehouse zu einem Data Lakehouse f\u00fcr DummiesVeranstaltungenAusf\u00fchrlicher Leitfaden zur Hadoop-MigrationIhr Data Warehouse modernisierenBlogs5 wichtige Schritte f\u00fcr eine erfolgreiche Migration von Hadoop zur Lakehouse-Architektur7 Gr\u00fcnde f\u00fcr die Migration von Ihrem cloudbasierten Hadoop zur Databricks Lakehouse-PlattformErste SchritteEine Migration muss Ihnen heutzutage kein Kopfzerbrechen mehr bereiten. Fragen Sie uns einfach: Wir zeigen Ihnen, wie das bei Ihnen ablaufen k\u00f6nnte.Databricks kostenlos testenDatabricks kontaktierenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/patrick-hall","text":"Patrick Hall - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPatrick HallPrincipal Scientist | Visiting Faculty at BNH.AI | GWUBack to speakersPatrick is principal scientist at BNH.AI, where he advises clients on AI risk management and supports NIST's AI Risk Management Framework. He also serves as visiting faculty in the Department of Decision Sciences at The George Washington School of Business, teaching classes on data ethics and business analytics. Patrick's technical work has been profiled in Fortune, Wired, InfoWorld, and TechCrunch, and he is the lead author of the book Machine Learning for High Risk Applications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jules-damji\/#","text":"Jules Damji - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJules DamjiLead Developer Advocate at AnyscaleBack to speakersJules S. Damji is a lead developer advocate at Anyscale Inc, an MLflow contributor, and co-author of Learning Spark, 2nd Edition. He is a hands-on developer with over 25 years of experience and has worked at leading companies, such as Sun Microsystems, Netscape, @Home, Opsware\/LoudCloud, VeriSign, ProQuest, Hortonworks, and Databricks, building large-scale distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/complex-event-processing","text":"What is Complex Event Processing?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWComplex Event ProcessingAll>Complex Event ProcessingTry Databricks for freeGet StartedWhat is Complex Event Processing [CEP]?Complex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being stored. Complex event processing is an organizational tool that helps to aggregate a lot of different information and that identifies and analyzes cause-and-effect relationships among events in real time. CEP matches continuously incoming events against a pattern and provides insight into what is happening. and allows you to proactively take effective actions.Complex events are commonly related to important business events [such as opportunities or threats] with the implication that they will be responded to in real-time or at least in something approaching to real-time.Major Application Areas for Complex Event Processing [CEP]:Business Activity Monitoring aims at identifying problems and opportunities in early stages by monitoring business processes and other critical resources.Sensor Networks that are used for monitoring of industrial facilities. These are usually derived from raw numerical measurements [e.g., temperature, smoke].Market data such as stock or commodity prices; they need to be derived from several events and their relationships through CEP.The Most Common Tools Used for Complex Event Processing Are:Apache Spark Streaming used by DatabricksApache Flink used by data ArtisansApache Samza used by LinkedInApache Storm used by TwitterHadoop\/MapReduce.Amazon Kinesis AnalyticsMicrosoft Azure Stream Analytics, Stream InsightFujitsu Software Interstage Big Data Complex Event Processing ServerIBM Streams, Operational Decision Manager [ODM]Oracle Stream Analytics and Stream ExploreComplex Event Processing is mainly used to address the following requirements: Latency has to be low. It is usually expected to be less than a few milliseconds, but sometimes we can have as little as less than one millisecond, between the time that an event arrives and the moment it is processed. The volume of input events per second is quite high. We can typically expect to have hundreds or even a few thousand events per second. Event patterns to be detected are complex: such as patterns based on temporal or spatial relationships.Additional ResourcesDesigning a Horizontally Scalable Event-Driven Big Data Architecture with Apache SparkBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks SQL Price Promotion \u2014 Save 40%+Take advantage of our 15-month promotion on SQL Serverless and the brand-new SQL ProLearn moreDatabricks SQLThe best data warehouse is a lakehouseGet startedWatch demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks SQL (DB SQL) is a serverless data warehouse on the Databricks Lakehouse Platform that lets you run all your SQL and BI applications at scale with up to 12x better price\/performance, a unified governance model, open formats and APIs, and your tools of choice \u2013 no lock-in.Best price \/ performanceLower costs, get best price\/performance, and eliminate the need to manage, configure or scale cloud infrastructure with serverless.Built-in governanceEstablish one single copy for all your data using open standards, and one unified governance layer across all data teams using standard SQL.Rich ecosystemUse SQL and any tool like Fivetran, dbt, Power BI or Tableau along with Databricks to ingest, transform and query all your data in-place.Break down silosEmpower every analyst to access the latest data faster for downstream real-time analytics, and go effortlessly from BI to ML.How does it work?Seamless integrations with the ecosystem\u00a0Ease of use\u00a0Real-world performance\u00a0Centralized governance\u00a0Open and reliable data lake as the foundationEasily ingest, transform and orchestrate data from anywhereWork with your data, no matter where it is. Turnkey capabilities allow analysts and analytic engineers to easily ingest data from anything like cloud storage to enterprise applications such as Salesforce, Google Analytics, or Marketo using Fivetran. It\u2019s just one click away. Then, simply manage dependencies and transform data in-place with built-in ETL capabilities on the Lakehouse, or using your favorite tools like dbt on Databricks SQL for best-in-class performance.\u00a0\u201cThe combination of Databricks and Fivetran has enabled us to build a robust and modern data pipeline in a very short amount of time. Fivetran had all the right connectors and integrations we needed.\u201d\u2014 Justin Wille, Director of Insights and Analytics, Kreg ToolLearn moreModern analytics and BI with your tools of choiceWork seamlessly with the most popular BI tools like\u00a0Tableau,\u00a0Power BI\u00a0and Looker. Now analysts can use their favorite tools to discover new business insights on the most complete and freshest data. Databricks SQL also empowers every analyst to collaboratively query, find and share insights with the built-in SQL editor, visualizations and dashboards.\u00a0\u201cWith data at our fingertips, we are much more confident knowing that we are using the most recent and complete data to feed our Power BI dashboards and reports.\u201d\u2014 Jake Stone, Senior Manager, Business Analytics, ButcherBoxLearn moreEliminate resource management with serverless computeDatabricks SQL serverless removes the need to manage, configure or scale cloud infrastructure on the Lakehouse, freeing up your data team for what they do best. Databricks SQL warehouses provide instant, elastic SQL compute \u2014 decoupled from storage \u2014 and will automatically scale to provide unlimited concurrency without disruption, for high concurrency use cases.\u00a0\u201cDatabricks SQL Serverless allows us to use the power of Databricks SQL while being much more efficient with our infrastructure.\u201d\u2014 R. Tyler Croy, Director of Platform Engineering, ScribdLearn moreBuilt from the ground up for best-in-class performanceDatabricks SQL is packed with thousands of optimizations to provide you with the best performance for all your tools, query types and real-world applications. This includes the next-generation vectorized query engine\u00a0Photon, which together with SQL warehouses, provides up to 12x better price\/performance than other cloud data warehouses.\u00a0\u201cThe Databricks Lakehouse Platform has enabled us to run analytics that reduce the time it takes to derive insights from audience behaviors from weeks to minutes.\u201d\u2014 Stephane Caron, Sr. Director of Business Intelligence, CBC\/Radio-CanadaLearn moreCentrally store and govern all your data with standard SQLEstablish one single copy of all your data using open format Delta Lake to avoid data lock-in, and perform in-place analytics and ETL\/ELT on your Lakehouse \u2014 no more data movements and copies in disjointed systems. Then, easily discover, secure and manage all your data with fine-grained governance, data lineage, and standard SQL across clouds with Databricks Unity Catalog.\u00a0\u201cDatabricks is core to our business because its lakehouse architecture provides us a unified way to access, store and share actionable data.\u201d\u2014 Jagan Mangalampalli, Director of Big Data, PunchhLearn moreBuilt on a common data foundation, powered by the Lakehouse PlatformThe Databricks Lakehouse Platform provides the most complete end-to-end data warehousing solution for all your modern analytics needs, and more. Get world-class performance at a fraction of the cost of cloud data warehouses. Speed up time from raw to actionable data at scale \u2014 and unify batch and streaming. Additionally, the Lakehouse lets data teams go from descriptive to predictive analytics effortlessly to uncover new insights.\u00a0\u201cDatabricks has provided one platform for our data and analytics teams to access and share data across ABN AMRO, delivering ML-based solutions that drive automation and insight throughout the company.\u201d\u2014 Stefan Groot, Head of Analytics Engineering, ABN AMROLearn moreMigrate to DatabricksTired of the data silos, slow performance and high costs associated with legacy systems like Hadoop and enterprise data warehouses? Migrate to the Databricks Lakehouse: the modern platform for all your data, analytics and AI use cases.Migrate to DatabricksIntegrationsSeamless integrations with the ecosystem means maximum flexibility for your data teams. Ingest business-critical data with Fivetran, transform it in-place with dbt, and find new insights with Power BI, Tableau or Looker, all without moving your data into a legacy data warehouse.Data Ingestion and ETLData GovernanceBI and Dashboards+ Any other Apache Spark\u2122\ufe0f compatible client\u201cNow more than ever, organizations need a data strategy that enables speed and agility to be adaptable. As organizations are rapidly moving their data to the cloud, we\u2019re seeing growing interest in doing analytics on the data lake. Databricks SQL delivers an entirely new experience for customers to tap into insights from massive volumes of data with the performance, reliability and scale they need. We\u2019re proud to partner with Databricks to bring that opportunity to life.\u201d\u2014 Francois Ajenstat, Chief Product Officer, TableauCustomer storiesDiscover moreDelta LakePartner ConnectUnity CatalogDelta Live TablesRelated content\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of a lakehouse.\nExplore resourceseBooksRise of the Data Lakehouse by Bill Inmon, father of the data warehouseWhy the Lakehouse Is Your Next Data WarehouseData, Analytics and AI governanceThe Big Book of Data EngineeringMigrating from a Data Warehouse to a Data Lakehouse for DummiesEventsInner Workings of the Lakehouse From Data + AI World TourWebinar on Performance-Tuning Best Practices on the Lakehouse \u2014 Inside the Life of a QueryDatabricks SQL Free Training \u2013 On DemandThe Best Data Warehouse Is a LakehouseBlogsDatabricks Sets Official Data Warehousing Performance RecordAnnouncing General Availability of Databricks SQLEvolution of the SQL Language at Databricks: ANSI Standard by Default and Easier Migrations From Data WarehousesDeploying dbt on Databricks Just Got Even SimplerData Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse PlatformHow to Build a Marketing Analytics Solution Using Fivetran and dbt on the Databricks LakehouseReady to get started?Try for freeJoin the communityProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/data-partner-program","text":"\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 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\uc778\ud154\ub9ac\uc804\uc2a4\ubd84\uc11d\uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uacf5\uae09\uc5c5\uccb4\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uc9c0\uae08 \uc2e0\uccad\ud558\uae30\ud30c\ud2b8\ub108 \ucc3e\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \u0000\uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=demos-try-workflows-trial#account","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-spark-streaming","text":"What is Spark Streaming?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark StreamingAll>Spark StreamingTry Databricks for freeGet StartedApache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Streaming. You should use Spark Structured Streaming for your streaming applications and pipelines. See Structured Streaming.What is Spark Streaming?Apache Spark Streaming is a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads. Spark Streaming is an extension of the core Spark API that allows data engineers and data scientists to process real-time data from various sources including (but not limited to) Kafka, Flume, and Amazon Kinesis. This processed data can be pushed out to file systems, databases, and live dashboards. Its key abstraction is a Discretized Stream or, in short, a DStream, which represents a stream of data divided into small batches. DStreams are built on RDDs, Spark\u2019s core data abstraction. This allows Spark Streaming to seamlessly integrate with any other Spark components like MLlib and Spark SQL. Spark Streaming is different from other systems that either have a processing engine designed only for streaming, or have similar batch and streaming APIs but compile internally to different engines. Spark\u2019s single execution engine and unified programming model for batch and streaming lead to some unique benefits over other traditional streaming systems.Four Major Aspects of Spark StreamingFast recovery from failures and stragglersBetter load balancing and resource usageCombining of streaming data with static datasets and interactive queriesNative integration with advanced processing libraries (SQL, machine learning, graph processing)This unification of disparate data processing capabilities is the key reason behind Spark Streaming\u2019s rapid adoption. It makes it very easy for developers to use a single framework to satisfy all their processing needs.Additional ResourcesThe Data Scientist\u2019s Guide to Apache Spark\u2122 eBookStructured Streaming DocumentationSimplify CDC Pipeline with Spark Streaming SQL and Delta LakeIntroducing Apache Spark 3.0: Now available in Databricks Runtime 7.0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marius-panga\/#","text":"Marius Panga - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarius PangaSolutions Architect at DatabricksBack to speakersSolutions Architect at Databricks with considerable experience in business intelligence, data warehousing, and data engineering. Deeply committed to exploring the potential of data and technology to tackle real-world issues.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Tables\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\n\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u4e00\u89a7\n\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306b\u304a\u3051\u308b Databricks \u6d3b\u7528\u306e\u30e1\u30ea\u30c3\u30c8\u3068\u306f\uff1feBook \u3084\u52d5\u753b\u306a\u3069\u306e\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u304c\u898b\u3064\u304b\u308a\u307e\u3059\u3002\n\u8a73\u3057\u304f\u898b\u308beBook\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u69cb\u7bc9\uff08\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u63d0\u5531\u8005 Bill Inmon \u8457\uff09\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u304c\u6b21\u306e\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3068\u306a\u308b\u7406\u7531\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u306e<br \/>\u30d3\u30c3\u30b0\u30d6\u30c3\u30af\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u304b\u3089\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3078\u306e\u79fb\u884c \u2015 \"For Dummies\" \u30b7\u30ea\u30fc\u30ba\u30a4\u30d9\u30f3\u30c8\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u3082\u3063\u3068\u8a73\u3057\u304f \u2013 Data+AI \u30ef\u30fc\u30eb\u30c9\u30c4\u30a2\u30fcWeb \u30bb\u30df\u30ca\u30fc\uff1a\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u304a\u3051\u308b\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u30c1\u30e5\u30fc\u30cb\u30f3\u30b0\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9 \u2013 Databricks SQL \u3067\u306e\u30af\u30a8\u30eaDatabricks SQL \u306e\u7121\u6599\u30aa\u30f3\u30e9\u30a4\u30f3\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e\u6c7a\u5b9a\u7248\u300c\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u300d\u30d6\u30ed\u30b0Databricks \u304c DWH \u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306e\u516c\u5f0f\u8a18\u9332\u3092\u66f4\u65b0Databricks SQL \u4e00\u822c\u63d0\u4f9b\u3092\u958b\u59cbDatabricks \u306b\u304a\u3051\u308b SQL \u8a00\u8a9e\u306e\u9032\u5316\uff1aANSI \u306e\u30c7\u30d5\u30a9\u30eb\u30c8\u5316\u3068\u5bb9\u6613\u306a\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u304b\u3089\u306e\u0000\u0000\u79fb\u884cdbt \u306e Databricks \u3078\u306e\u30c7\u30d7\u30ed\u30a4\u304c\u3055\u3089\u306b\u5bb9\u6613\u306b\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u306e\u30e2\u30c7\u30ea\u30f3\u30b0\u624b\u6cd5\u3068\u305d\u306eDatabricks Lakehouse\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3078\u306e\u5b9f\u88c5Databricks Lakehouse\u306b\u304a\u3051\u308bFivetran\u3068dbt\u3092\u7528\u3044\u305f\u30de\u30fc\u30b1\u30c6\u30a3\u30f3\u30b0\u5206\u6790\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u306e\u69cb\u7bc9\u65b9\u6cd5\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u307e\u3059\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u306b\u53c2\u52a0\u3059\u308b\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marianna-cervino","text":"Marianna Cervino - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarianna CervinoGlobal Data Scientist at GucciBack to speakersMarianna holds a Master Degree in Physics from University of Bari. She is a Data Scientist experienced in Time Series Forecasting methodologies and has worked on business problems of diverse industries in the past years. She joined Gucci in 2021, where she works in collaboration with the Media Department.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/roie-schwaber-cohen","text":"Roie Schwaber-Cohen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRoie Schwaber-CohenStaff Developer Advocate at PineconeBack to speakersRoie Schwaber-Cohen is a staff developer advocate at Pinecone. He has 15 years of software engineering experience and has worked in a variety of startups across industries. Roie is a musician, playing piano and flute. He lives in Seattle with my wife and daughter, along with our two dogs and cat.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions","text":"Databricks Solution Accelerators - Databricks Use CasesSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks for IndustrySoluzioni di analisi dei dati e AI senza compromessi per settori specificiCominciaProgramma una demoScopri il Lakehouse per il tuo settoreComunicazioni, media e intrattenimentoOttieni maggiore attenzione, cattura pi\u00f9 ideeScopri comeServizi finanziariAumenta la fiducia, assicura tranquillit\u00e0Scopri comeSanit\u00e0 e bioscienzeScopri e offri un'assistenza miglioreScopri comeRetail e largo consumoAccompagna i clienti nel loro viaggio e promuovi il brandScopri comeScorri l'elenco di tutti i settorisearchHide filtersIndustry\ud83e\udd14No results available. Try adjusting the filters or start a new search.reset the listSoluzioni per settori specificiDall'idea al progetto concettuale (Proof of Concept) in sole due settimaneGli Acceleratori Databricks sono guide specifiche \u2014 notebook con funzionalit\u00e0 complete e best practice \u2014 che velocizzano l'ottenimento di risultati. I clienti di Databricks risparmiano molte ore nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo, e molti di loro vanno dall'idea al \"proof of concept\" in sole due settimane.Scopri gli AcceleratoriCominciamo?Scopri che cosa puoi fare con Databricks attivando una prova gratuita.Comincia la provaProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-stevens","text":"Chris Stevens - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris StevensSenior Staff Software Engineer at DatabricksBack to speakersChris Stevens is a Senior Staff Software Engineer and manager at Databricks. His work focuses on the intersection of the control and data planes, ranging from workload execution protocols and query routing to warehouse auto-scaling and cache management. His background is in operating systems where he worked on Windows NT and co-created Minoca OS.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/customers\/reckitt","text":"Customer Story: Reckitt | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYResponding to global demand shifts with ease25%reduction in computing costs7,000+users across the organizationWatch now INDUSTRY: Retail and consumer goods SOLUTIONS: Consumer retention,recommendation engines TECHNICAL USE CASES: Lakehouse,Delta Lake,data science,machine learning,Databricks SQL,ETL CLOUD: Azure,Google Cloud\u201cDatabricks enables us to outperform and deliver best-in-class customer experiences in every market. With its Lakehouse platform, our stakeholders and developers can work more collaboratively and unlock critical trends and insights needed to serve our 180 million customers.\u201d\n\u2014 Sergiy Tkachuk, Head of Data Science at ReckittReckitt is the company behind some of the world\u2019s most recognizable and trusted consumer brands in hygiene, health and nutrition, including Air Wick, Clearasil, Lysol, Mucinex, Woolite and more. Prior to implementing Databricks Lakehouse, Reckitt was missing opportunities to collect comprehensive customer data insights or observe market trends because of their Hadoop data warehouse environment, which created data silos and hindered collaboration across data users and teams. Today, Reckitt leverages Databricks Lakehouse on Azure to meet the needs of billions of consumers worldwide by surfacing real-time, highly accurate, deep customer data insights, leading to a better understanding of international market trends and demand across the multiple product lines they support. With Databricks Lakehouse, Reckitt now has a single source of truth for all their data \u2014 leading to improved supply chain operations, consumer experiences, and faster, more flexible business growth.Adapting legacy architecture for digital-first commerceEvery day, more than 20 million Reckitt products are bought globally. Reckitt seeks to always put consumers and people first, seek out new opportunities, strive for excellence in all that they do, and build shared success with all partners.With billions of customers to serve across thousands of retailers, real-time insights play a critical role in the accurate understanding and predictability of market trends, consumer behaviors and inventory management across diverse industries.\u201cBy leveraging data and analytics, we can address challenges related to changes happening in various markets as they take place,\u201d said Sergiy Tkachuk, Head of Data Science at Reckitt. \u201cIt\u2019s the only way to deliver best-in-class experiences at scale, helping our partners to retain more customers and positively impact revenue streams.\u201dAlthough Reckitt\u2019s initial Hadoop data warehouse environment provided the company with a good understanding of tabular data formats and relationships, data silos and the on-demand scaling challenges impacted their ability to acquire unified views into the customer and market. It also influenced critical data needs, such as surfacing repeat-customer information or order details to assess behaviors and trends over time.In the legacy Hadoop environment, business analysts were limited to accessing data from function-specific data systems and had to work in spreadsheets, which were intensive, time-consuming and unable to scale. The data science team was pulling data from multiple warehouses, using various tools to process information and get results on their machines. Analysts were leveraging different tools for querying, dragging down efficiency and introducing data locality issues.\u201cThings got even more complex when the data started rolling in more rapidly,\u201d said Tkachuk. \u201cFollowing the surge in e-commerce adoption, the need for more collaborative data and engineering environments emerged. It was challenging to track customer behavioral purchases or loyalty patterns, as the data residing in silos takes a long time even to perform simple descriptive analytics. Time to market for analytics products suffered from increasing complexity and more users onboarding very quickly.\u201dReckitt\u2019s business analysts and data scientists were in major need of a collaborative environment to work on joint projects and easily share large data sets, with better flexibility across tools and the ability to scale as data volumes rose and platform usage went up.Democratizing all data with LakehouseMany considerations went into selecting the foundation for their data vision, with a critical consideration revolving around the ability to provide analytics tools and knowledge to their business users, and enable them to build their own data-driven solutions. This shared approach to data was a core reason Reckitt turned to Databricks Lakehouse Platform, but it certainly wasn\u2019t the only one. Reckitt\u2019s data scientists, analysts and engineers needed to create a standardized data model to comprise all cross-functional data, in a normalized form that could be picked up by any function and scaled as volumes rose. Delta Lake provides Reckitt\u2019s data team with a common data layer to build scalable and reliable data pipelines for both analytics and machine learning workloads. With all their data ready for analytics, their analytics team could now power high-performing BI and analytics, and would improve creation time-to-value.Today, the data science team has implemented several ETL pipelines for 50+ structured and unstructured data sources, and groups throughout the business \u2014 many outside of the data lake core development team \u2014 use Databricks Lakehouse to derive deeper market insights, better understand customer patterns and build KPIs around consumer purchase behavior. Data scientists use the new platform to enhance feature engineering and integrate with different beta dimensions for model building, as well as operationalize those models using MLflow.These new capabilities powered another major initiative that Reckitt was able to undertake: building an internal data platform to serve as the home of all consumer data. With Databricks Lakehouse as the underlying technology, teams across the business are now able to unlock the value of consumer data and draw insights without an assist from data science or engineering. Even nontechnical users can activate segments and do advanced modeling within the platform.\u201cThe goal of this initiative was to enable teams worldwide to outperform their goals, and deliver best-in-class customer experiences from the ground up,\u201d said Tkachuk. \u201cWith the Databricks Lakehouse Platform, our stakeholders and developers can work collaboratively, delivering global recommendations systems, brand sales performance tracking, and other key enhancements for health, hygiene and nutrition businesses \u2014 in 73 countries for more than 180 million customers.\u201dThanks to the streamlined processes and flexible automation capabilities made possible by Databricks, Reckitt saves on administrative efforts and costs, allowing them to spend more time on value-adding activities.\u201cWe\u2019re democratizing data consumption across the entire organization,\u201d said Tkachuk. \u201cWe\u2019re enabling not only engineers and data scientists to make better use of data, but also business analysts and stakeholders with nontechnical backgrounds \u2014 that\u2019s approximately 7,000 users in total.\u201dUnlocking data perspectives and market predictabilitySince implementing Databricks Lakehouse, Reckitt has optimized its global data strategy and continues to save significant hours on computation, subsequently reducing total computing spend by about one-fourth.\u201cThe biggest impact we achieved with this is that we now have a single source of truth for all data,\u201d said Tkachuk. \u201cDiscoveries are being leveraged and used at the organizational level, giving consistent insights across teams. The unified platform has helped our stakeholders, data engineers, data scientists, business analysts and reporting experts get more actionable, accurate insights by connecting the different dots of data points, helping us make smarter business decisions.\u201dReckitt continues to pursue innovation and evolution when it comes to its Lakehouse foundation. They plan to adopt new features and integrations on the Databricks platform in order to advance their architecture and add further scalability and flexibility for users. The roadmap includes extending their adoption of other powerful components of the Lakehouse Platform \u2014 such as Delta Sharing for an even more effortless data sharing experience across the organization, Unity Catalog to allow them to ensure better data and AI governance, and integrations to leverage the power of graph-based algorithms. Finally, Reckitt plans to leverage the Koalas implementation on PySpark for quicker Python user onboarding, increasing coverage and further ensuring data consistency and visibility.\u201cWith data centralized and available on demand, we now have an unmatched ability to unlock value-adding BI and ML use cases,\u201d said Tkachuk. \u201cFrom data scientist to executive, Databricks Lakehouse has been game-changing for Reckitt and all of our partners.\u201dLearn more about\u00a0Reckitt\u00a0and its global brands.Related ContentVideoData + AI World Tour | Reckitt KeynoteReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/sales-forecasting","text":"Solution Accelerator - How to: Measure Advertising Effectiveness with Sales Forecasting & Attribution | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorMeasure ad effectiveness with sales forecasting and attributionIncrease ad revenue by focusing on the best-performing channels\n\u00a0\nConnect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.\nRead the full write-up\nDownload notebooksBenefits and business valueLeverage fine-grained insightsForecast ad impressions to sales for daily-level or even segment-level insights via real-time dashboards to pinpoint the right channels\nBoost marketing ROIAllocate budgets effectively to get the most out of marketing dollars\nOptimize your media mixEasily understand which ads and programs resonate most with customer segments\nReference ArchitectureData usedSales data. Batch and streaming ad metrics like impressions, clicks, etc.ResourcesCase studyLearn moreWebinarLearn moreBlogLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-powell","text":"Michael Powell - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious Diseases at California Department of Public Health (CDPH)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/ebook\/support-your-data-workloads-scale","text":"Support your data workloads at scale | DatabricksTechnical GuideSupport your data workloads at scaleWhile boosting cost efficiency and productivityHow to increase productivity and efficiently support your data, analytics and AI workloads at scaleDownload this technical guide to learn how startups and digital native businesses are solving some of their common data challenges. You\u2019ll benefit from architecture diagrams, step-by-step solutions and quickstart guides. Learn how to support data use cases as you scale while boosting cost efficiency and productivity. You\u2019ll also find real-life use cases from leading companies such as Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable and Zipline.Read the entire guide or dive straight into any of these specific challenges:Consolidating on an open, unified data platform like the lakehouseScaling capacity and increasing performance and usability of data solutionsBuilding effective machine learning operationsGet the technical guideProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/himanshu-arora","text":"Himanshu Arora - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHimanshu AroraResident Solutions Architect at DatabricksBack to speakersHimanshu is a Resident Solutions Architect at Databricks. He has been using Spark, Big Data, and Reactive systems for a few years now in production to help enterprises in their data and digital transformation journey. Prior to that, he was a Java\/Scala developer. Himanshu joined Databricks in 2020 and since then he has been helping Databricks customers on numerous projects around Data Architecture & Design, Optimization & Best Practices, Lakehouse implementation, Migration to Databricks, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-big-book-of-data-engineering","text":"The Big Book of Data Engineering | DatabrickseBookTranslate raw data into actionable dataLearn from real-world use casesGet the latest data engineering best practicesKeep up with the latest trends in data engineering by downloading your new and improved copy of The Big Book of Data Engineering. You\u2019ll benefit from data sets, code samples and best practices as you translate raw data into actionable data. You\u2019ll also see real-life end-to-end use cases from leading companies such as J.B. Hunt, ABN AMRO and Atlassian.Download now to learn how to:Build and maintain pipelines and run ETL workloads directly on a data lakeEnable real-time point-of-sale analyticsBuild a cybersecurity lakehouseUnlock the power of health dataRun your data lifecycle on the Databricks Lakehouse PlatformGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chang-she\/#","text":"Chang She - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChang SheCEO at LanceDBBack to speakersChang She is the CEO and cofounder of LanceDB, the developer-friendly, serverless vector database for AI applications. Previously Chang was VP of Eng at Tubi TV where he led all data and ML efforts. In a past life Chang was one of the original co-authors of the Pandas library.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/fhir","text":"FHIR Interoperability With dbignite | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorFHIR Interoperability With dbignitePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedUnlock FHIR bundles for real-time analyticsHolistic patient-centric care requires a 360-view into the patient's health. With FHIR becoming the standard protocol for health data exchange, the opportunity to bring together siloed patient data into a longitudinal record is now a reality. But challenges still persist in being able to analyze and extract insights from FHIR bundles. With the Databricks Lakehouse for Healthcare and Life Sciences, healthcare data teams can:Automate the ingestion of FHIR bundlesAddress incremental data updates seamlesslyFlatten FHIR bundles to enable interactive queryingPrepare dynamic patient data for analytics and AI at scaleDownload FHIR notebookResourceseBookRead nowOn-demand webinarWatch nowBlogRead nowDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr","text":"Architecture de data lakehouse et IA \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLe meilleur data warehouse est un lakehouseUnifiez vos donn\u00e9es, votre analytique\net votre IA sur une seule plateformeEssayer gratuitementEn savoir plusR\u00e9duisez les co\u0000\u00fbts et acc\u00e9l\u00e9rez l'innovation avec la plateforme lakehouseEn savoir plusUnifi\u00e9eUne seule plateforme pour toutes vos donn\u00e9es, r\u00e9gies par une gouvernance coh\u00e9rente et disponibles pour toutes vos t\u00e2ches d'analyse et d'IAOuvertB\u00e2tie sur des standards ouvertes, int\u00e9gr\u00e9e \u00e0 tous les clouds pour une harmonie parfaite avec votre pile de donn\u00e9es moderne\u00c9volutiveUne \u00e9volutivit\u00e9 efficace pour toutes les charges de travail, des simples pipelines de donn\u00e9es aux LLM de grande envergure.Les organisations data-driven choisissent Lakehouse\nVoir tous les clients\nLe lakehouse unifie vos \u00e9quipes dataGestion des donn\u00e9es et Data EngineeringRationalisez l'ingestion et la gestion de vos donn\u00e9esAvec un ETL automatis\u00e9 et fiable, un partage de donn\u00e9es ouvert et s\u00e9curis\u00e9 et des performances rapides comme l'\u00e9clair, Delta Lake envoie toutes vos donn\u00e9es structur\u00e9es, semi-structur\u00e9es et non structur\u00e9es vers votre datalake.En savoir plus Regarder la d\u00e9moEntreposage des donn\u00e9esObtenez de nouveaux insights \u00e0 partir des donn\u00e9es les plus compl\u00e8tesGr\u00e2ce \u00e0 l'acc\u00e8s imm\u00e9diat aux donn\u00e9es les plus r\u00e9centes et compl\u00e8tes et \u00e0 la puissance de Databricks SQL \u2014\u00a0dont le rapport prix \/ performance est jusqu'\u00e0 douze fois sup\u00e9rieur \u00e0 celui des data warehouses Cloud traditionnels\u00a0\u2014 les analystes et data scientists peuvent d\u00e9sormais b\u00e9n\u00e9ficier rapidement de nouveaux insights.En savoir plus Regarder la d\u00e9moData Science et Machine LearningAcc\u00e9l\u00e9rer le ML sur l'ensemble du cycle de vieLe lakehouse constitue la base de Databricks Machine Learning, une solution collaborative et native en mati\u00e8re de donn\u00e9es pour l'ensemble du cycle de vie du Machine Learning, de la mise en forme \u00e0 la production. Combin\u00e9 \u00e0 des pipelines de donn\u00e9es de haute qualit\u00e9 et hautement performants, le lakehouse acc\u00e9l\u00e8re le Machine Learning et la productivit\u00e9 des \u00e9quipes.En savoir plus Regarder la d\u00e9moGouvernance et partage des donn\u00e9esDonn\u00e9es, analytique et IA\u00a0: conjuguez gouvernance et partageAvec Databricks, vous b\u00e9n\u00e9ficiez d'un mod\u00e8le commun de s\u00e9curit\u00e9 et de gouvernance pour l'ensemble de vos assets de donn\u00e9es, d'analytique et d'IA au sein de votre lakehouse, quel que soit le cloud. D\u00e9couvrez et partagez les donn\u00e9es de l'ensemble de vos plateformes, cloud ou r\u00e9gions, sans les r\u00e9pliquer ni \u00eatre tributaire d'un fournisseur. Vous pouvez m\u00eame distribuer des produits de donn\u00e9es sur une marketplace ouverte.En savoir plus Regarder la d\u00e9moLe data warehouse est de l'histoire ancienne. D\u00e9couvrez pourquoi le lakehouse constitue l'architecture moderne pour les donn\u00e9es et l'IA.Discover LakehouseLe catalogue de sessions est disponibleRejoignez-nous \u00e0 San Francisco pour explorer l'\u00e9cosyst\u00e8me du lakehouse et d\u00e9couvrir les nouvelles avanc\u00e9es des technologies open sourceParcourez les sessionsD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutive.Obtenir le rapport600 DSI. 14 secteurs. 18 pays.Une nouvelle \u00e9tude r\u00e9v\u00e8le que la strat\u00e9gie de donn\u00e9es joue un r\u00f4le crucial dans le succ\u00e8s de l'IA. D\u00e9couvrez les perspectives d'autres DSI.Obtenir le rapportUne lecture incontournable pour les ing\u00e9nieurs ML et les data scientists qui veulent optimiser leur pratique MLOpsObtenir l'e-bookPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected]om and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rafael-barcelos","text":"Rafael Barcelos - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRafael BarcelosSoftware Architect at Microsoft CorporationBack to speakers15+ years of experience as Full Stack Software Engineer working in several areas from user facing features, to backend services and platform features to support other engineers' goals.\nSince 2017, working as Architect driving the vision for a Data Mesh based platform that is being built by 100+ engineers distributed across the globe to support Data engineering and Data Science efforts on Office 365.\nEnjoy to mentor junior\/senior engineers in their technical careers and to work in fast paced teams focused on delivering solutions for hard problems, especially large-scale related ones.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/test-beckner\/#","text":"TEST Beckner - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTEST BecknerTEST at TESTBack to speakersTESTLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/board-of-directors","text":"Consiglio direttivo di Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLeadershipCon una visione di lungo termine, il nostro gruppo dirigente sfrutta decenni di esperienza per tracciare nuove rotte nel mondo dei dati e dell'intelligenza artificialeConosci il nostro teamGruppo dirigenteFondatoriConsiglio direttivoIon StoicaCofondatore ed Executive ChairBen HorowitzCofondatore di Andreessen HorowitzElena DonioMembro del Consiglio di AmministrazioneAli GhodsiCofondatore e Chief Executive OfficerPete SonsiniGeneral Partner di New Enterprise AssociatesJonathan ChadwickMembro del Consiglio di AmministrazioneMatei ZahariaCofondatore e direttore tecnologicoScott ShenkerProfessore di Informatica all'Universit\u00e0 di BerkeleyProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/glossary\/medallion-architecture","text":"What is a Medallion Architecture?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMedallion ArchitectureAll>Medallion ArchitectureTry Databricks for freeGet StartedWhat is a medallion architecture?A medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through each layer of the architecture (from Bronze \u21d2 Silver \u21d2 Gold layer tables). Medallion architectures are sometimes also referred to as \"multi-hop\" architectures.Benefits of a lakehouse architectureSimple data modelEasy to understand and implementEnables incremental ETLCan recreate your tables from raw data at any timeACID transactions, time travelA quick primer on lakehousesA lakehouse is a new data platform architecture paradigm that combines the best features of data lakes and data warehouses. A modern lakehouse is a highly scalable and performant data platform hosting both raw and prepared data sets for quick business consumption and to drive advanced business insights and decisions. It breaks data silos and allows seamless, secure data access to authorized users across the enterprise on one platform.Bronze layer (raw data)The Bronze layer is where we land all the data from external source systems. The table structures in this layer correspond to the source system table structures \"as-is,\" along with any additional metadata columns that capture the load date\/time, process ID, etc. The focus in this layer is quick Change Data Capture and the ability to provide an historical archive of source (cold storage), data lineage, auditability, reprocessing if needed without rereading the data from the source system.Silver layer (cleansed and conformed data)In the Silver layer of the lakehouse, the data from the Bronze layer is matched, merged, conformed and cleansed (\"just-enough\") so that the Silver layer can provide an \"Enterprise view\" of all its key business entities, concepts and transactions. (e.g. master customers, stores, non-duplicated transactions and cross-reference tables).The Silver layer brings the data from different sources into an Enterprise view and enables self-service analytics for ad-hoc reporting, advanced analytics and ML. It serves as a source for Departmental Analysts, Data Engineers and Data Scientists to further create projects and analysis to answer business problems via enterprise and departmental data projects in the Gold Layer.In the lakehouse data engineering paradigm, typically the ELT methodology is followed vs. ETL - which means only minimal or \"just-enough\" transformations and data cleansing rules are applied while loading the Silver layer. Speed and agility to ingest and deliver the data in the data lake is prioritized, and a lot of project-specific complex transformations and business rules are applied while loading the data from the Silver to Gold layer. From a data modeling perspective, the Silver Layer has more 3rd-Normal Form like data models. Data Vault-like, write-performant data models 76can be used in this layer.Gold layer (curated business-level tables)Data in the Gold layer of the lakehouse is typically organized in consumption-ready \"project-specific\" databases. The Gold layer is for reporting and uses more de-normalized and read-optimized data models with fewer joins. The final layer of data transformations and data quality rules are applied here. Final presentation layer of projects such as Customer Analytics, Product Quality Analytics, Inventory Analytics, Customer Segmentation, Product Recommendations, Marking\/Sales Analytics etc. fit in this layer. We see a lot of Kimball style star schema-based data models or Inmon style Data marts fit in this Gold Layer of the lakehouse.So you can see that the data is curated as it moves through the different layers of a lakehouse. In some cases, we also see that lot of Data Marts and EDWs from the traditional RDBMS technology stack are ingested into the lakehouse, so that for the first time Enterprises can do \"pan-EDW\" advanced analytics and ML - which was just not possible or too cost prohibitive to do on a traditional stack. (e.g. IoT\/Manufacturing data is tied with Sales and Marketing data for defect analysis or health care genomics, EMR\/HL7 clinical data markets are tied with financial claims data to create a Healthcare Data Lake for timely and improved patient care analytics.)Medallion architecture and data meshThe Medallion architecture is compatible with the concept of a data mesh. Bronze and silver tables can be joined together in a \"one-to-many\" fashion, meaning that the data in a single upstream table could be used to generate multiple downstream tables.[ Try Databricks for free today ]Additional ResourcesWhat is a Data Lakehouse?Data Lakehouse Platform by DatabricksHow Incremental ETL Makes Life Simpler With Data Lakes - Databricks BlogSimplify Your Medallion Architecture with Delta Lake's CDF FeatureBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/celebal-technologies-databricks-migration","text":"Migrate to Databricks by Celebal Technologies and DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionMigrate to Databricks by Celebal TechnologiesMigration solution developed by Celebal Technologies and powered by the Databricks Lakehouse Platform\nGet startedQuicker migration from on-premises at lower costCelebal Technologies has proven tools and accelerators to help you migrate from Hadoop, Snowflake, SAP Business Warehouse (BW) or HANA to the Databricks Lakehouse Platform. Their solution for migrating to Databricks from an on-premises\/cloud Hadoop environment addresses the key challenges of scalability, performance and workload diversity to enable comprehensive analytics. By leveraging the capabilities of Databricks, Celebal Technologies helps leading enterprises with an SAP BW or HANA footprint to optimize data processing with a suite of comprehensive analytics solutions. Lastly, migrating from Snowflake to Databricks can significantly reduce costs and increase performance. Celebal Technologies helps you move ETL workloads, use Databricks to run SQL queries and deploy ready-to-go ML\/AI use cases that:Save you up to 40% in costs and 60% in time due to automatic schema and data migrationProvide better control over the data migration processReduce the cost of scaling data management and analyticsGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/zs-intelligent-data-management-biomedical","text":"Intelligent Data Management by ZS | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionIntelligent Data Management by ZSIndustry-specific solution developed by ZS and powered by the Databricks Lakehouse Platform\nGet startedTransforming biomedical research data into insightsIntelligent Data Management for Biomedical Research by ZS is a modular solution that transforms scientific data into an enterprise asset by creating an end-to-end value chain, helping customers move closer to the vision of precision medicine at scale and at speed. The solution, built on the Databricks Lakehouse Platform, solves speed and cost issues around ingestion, storage and querying of petabyte-scale genomic data sets, and provides quality control management for data from disparate sources.Expedite query response times of excessive data sets, reduce infrastructure costs and increase time-to-valueMaintain data provenance and enhance searchability of raw dataMaximize structured data modeling with access to deep domain and technical expertiseGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jun-rong-lau\/#","text":"Jun Rong Lau - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJun Rong LauData Engineer\/Analyst at GrabTaxi Holding Pte LtdBack to speakersFrom the Analytics Data Platform and Finance Data + AI transformation TeamLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/consulting-and-si","text":"Databricks-Consulting-Partner \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks-Consulting-PartnerVernetzen Sie sich mit Databricks-Partnern weltweit, die Sie bei der Entwicklung, Bereitstellung oder Migration zur Databricks Lakehouse-Plattform unterst\u00fctzenDatabricks-Consulting-Partner sind Experten auf ihrem jeweiligen Gebiet und bieten Ihnen kompetente Unterst\u00fctzung bei der Implementierung und Skalierung von Initiativen in den Bereichen Data Engineering, Collaborative Data Science, Full-Cycle-Machine-Learning und Business Analytics.\nMit ihrem technischen, branchenspezifischen und anwendungsbezogenen Expertenwissen helfen sie Ihnen, das Meiste aus der Databricks Lakehouse-Plattform herauszuholen. Das Serviceangebot umfasst etwa die Entwicklung einer auf Ihr Unternehmen zugeschnittenen Datentransformationsstrategie, Datenmodernisierung und -migration, Datenmanagement und Governance und vieles mehr.Loading...ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/can-elfeoglu","text":"Can Elfeoglu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCan ElfeogluStaff Product Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/surya-turaga","text":"Surya Turaga - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSurya TuragaSr. Solutions Architect at DatabricksBack to speakersIn the past I have been responsible for Strategic client development, working with senior client stakeholders to act as a thought leader and evangelist across the Advanced Analytics space. Strong conceptual hands-on experience in Cloud and Big Data environments.\nI have also spoken at multiple large events like +30,000 like AWS re:Invent 2022 and Qubole Data Lake Summit etc., \nI love building analytical solutions that combine Machine Learning & Artificial Intelligence. In my career, I have always had the luxury of working very close to technology and love working on challenges around scaling up analytic methods in distributed computing environments.\nI am passionate about turning ideas into data products. I enjoy developing high-performance teams, mentoring data science enthusiasts and working in cross-functional teams.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabian-jakobs","text":"Fabian Jakobs - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabian JakobsSr Staff Software Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Databricks kostenlos testen | DatabricksDatabricks kostenlos testenTesten Sie die komplette Databricks-Plattform 14 Tage lang kostenlos in AWS, Microsoft Azure oder Google Cloud. Die Wahl des Cloud-Anbieters liegt bei Ihnen.Datenaufnahme vereinfachen und ETL automatisierenNehmen Sie Daten aus Hunderten von Quellen auf. Verwenden Sie einen einfachen deklarativen Ansatz zur Erstellung von Datenpipelines.In Ihrer bevorzugten Sprache zusammenarbeitenCode in Python, R, Scala und SQL mit Co-Authoring, automatischer Versionierung, Git-Integrationen und RBAC.12x besseres Preis\/Leistungsverh\u00e4ltnis als Cloud Data WarehousesErfahren Sie, warum mehr als 7.000 Kunden weltweit auf Databricks f\u00fcr all ihre Workloads von BI bis KI vertrauen.Erstellen Sie Ihr Databricks-Konto1\/2VornameNachnameBerufliche E-Mail-AdresseUnternehmenStellenbezeichnungRufnummer (Optional)Bitte ausw\u00e4hlenLandWeiterDatenschutzhinweis (aktualisiert)Terms of UseIhre DatenschutzwahlenIhre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/media-and-entertainment","text":"Databricks para o setor de m\u00eddia e entretenimento | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWDatabricks para o setor de m\u00eddia e entretenimentoDados, an\u00e1lises e IA para o futuro da m\u00eddiaComece agoraAgendar uma demonstra\u00e7\u00e3oOs quatro desafios de dados do setor de m\u00eddia e entretenimentoCria\u00e7\u00e3o de um perfil de p\u00fablico unificado\nComo os dados s\u00e3o coletados, armazenados e gerenciados em sistemas diferentes, as empresas de m\u00eddia n\u00e3o conseguem obter uma vis\u00e3o completa de seu p\u00fablico e das informa\u00e7\u00f5es dos anunciantes.Proporcionar uma experi\u00eancia excelente a consumidores\nOs consumidores esperam experi\u00eancias personalizadas e individualizadas sem fric\u00e7\u0000\u00e3o o tempo todo, em todos os seus dispositivos. O desafio \u00e9 proporcionar essas experi\u00eancias em tempo real, em grande escala.Maximizar todos os seus dados de m\u00eddia\nOs data warehouses tradicionais s\u00e3o incapazes de processar dados n\u00e3o estruturados, como arquivos de v\u00eddeo, imagem e \u00e1udio, o que impede as empresas de aproveitarem todo o potencial de seus ativos mais valiosos.Al\u00e9m da agrega\u00e7\u00e3o, an\u00e1lises avan\u00e7adas\nCasos complexos de uso de IA em publicidade e todo o ciclo de vida do consumidor atualmente exigem que enormes conjuntos de dados sejam adquiridos e harmonizados a um custo consider\u00e1vel.Conhe\u00e7a o Data Lakehouse: o melhor dos dois mundos em uma \u00fanica plataformaUm data lakehouse combina o melhor dos data warehouses e data lakes em uma plataforma \u00fanica e simples para abordar todos os seus dados, an\u00e1lises e casos de uso de IA. Ele \u00e9 constru\u00eddo em uma funda\u00e7\u00e3o de dados aberta e confi\u00e1vel que lida com efici\u00eancia com todos os tipos de dados e aplica uma abordagem comum de seguran\u00e7a e governan\u00e7a a todas as suas plataformas de dados e nuvem.Saiba maisLakehouse na pr\u00e1ticaSaiba como o Databricks Lakehouse empodera sua ind\u00fastria \u00fanicaTecnologias de publicidade e marketingGerencie margens e acrescente rigor baseado em dados nas suas opera\u00e7\u00f5es, melhore o desempenho da m\u00eddia e otimize o trabalho criativo para agilizar o trabalho das equipes.Saiba maisTransmiss\u00e3o e streamingCrie experi\u00eancias individualizadas em escala, melhore o desempenho da publicidade e extraia mais valor de todo o seu portf\u00f3lio de conte\u00fado.Saiba maisJogosAproveite os dados e a IA para melhorar o design do jogo, aumentar a aquisi\u00e7\u00e3o e o engajamento dos jogadores e maximizar a monetiza\u00e7\u00e3o e a reten\u00e7\u00e3o.Saiba maisPor que Databricks para o setor de m\u00eddia e entretenimento?Todos os seus dados, an\u00e1lises e IA em uma \u00fanica plataforma\nAproveite o valor total dos seus dados para otimizar o engajamento do p\u00fablico, monetiza\u00e7\u00e3o e otimiza\u00e7\u00e3o de publicidade.Otimizado para tempo real\nDescubra insights acion\u00e1veis, alcance suas metas de personaliza\u00e7\u00e3o individualizada e aprimore a experi\u00eancia do seu p\u00fablico com machine learning.Acelere seus resultados comerciais\nAproveite nossos aceleradores de solu\u00e7\u00e3o para ingerir mais facilmente os dados do consumidor, incluindo a an\u00e1lise do engajamento do fluxo de cliques. Forne\u00e7a casos de uso poderosos, como mecanismos de recomenda\u00e7\u00e3o e atribui\u00e7\u00e3o multi-touch.Confiabilidade e desempenho de alto n\u00edvel\nO Databricks Lakehouse oferece uma combina\u00e7\u00e3o incompar\u00e1vel de velocidade, escalabilidade e economia. N\u00e3o \u00e9 de admirar que o melhor data warehouse seja um lakehouse.Transforma\u00e7\u00e3o do setor de m\u00eddia e entretenimento com lakehouse\n\u201cCom a Plataforma Databricks Lakehouse na AWS, a Warner Bros. Discovery est\u00e1 impulsionando o futuro da descoberta de conte\u00fado e a experi\u00eancia do p\u00fablico. Ao aproveitar os dados para prever com mais precis\u00e3o o comportamento do consumidor e fornecer recomenda\u00e7\u00f5es de conte\u00fado personalizadas em tempo real, personalizamos a experi\u00eancia do espectador e melhoramos o engajamento geral dos nossos clientes.\u201d\u2014 Martin Ma, GVP, engenharia na Warner Bros. DiscoveryInsights executivos sobre dados, an\u00e1lises e IASaiba mais sobre o que outros executivos de m\u00eddia e entretenimento est\u00e3o fazendo para fortalecer sua estrat\u00e9gia de dadosSaiba maisO que voc\u00ea pode fazer com o lakehouse?\nAcelerar os resultados de audi\u00eancia e publicidade com uma plataforma aberta e colaborativa para dados, an\u00e1lises e IAVis\u00e3o 360\u00ba do p\u00fablico\nRe\u00fana todos os seus dados estruturados e n\u00e3o estruturados (cliques, dados demogr\u00e1ficos e redes sociais) em uma \u00fanica plataforma dedicada a an\u00e1lises e IA. Com uma vis\u00e3o hol\u00edstica da jornada do consumidor, as organiza\u00e7\u00f5es podem interpretar as prefer\u00eancias de conte\u00fado para ajustar a personaliza\u00e7\u00e3o de experi\u00eancias e o direcionamento de publicidade e engajamento.Reduzir churn e aumentar ARPU\nCom uma plataforma \u00e1gil baseada em nuvem, as empresas podem processar rapidamente grandes quantidades de dados com alto n\u00edvel de confiabilidade e aliment\u00e1-los em sistemas downstream para oferecer experi\u00eancias individualizadas em todos os canais, a qualquer momento. Os consumidores esperam cada vez mais recomenda\u00e7\u00f5es em tempo real, e sua aten\u00e7\u00e3o \u00e9 ferozmente disputada pelas empresas de m\u00eddia. Nesse contexto, uma capacidade de personaliza\u00e7\u00e3o quase em tempo real torna-se imperativa para muitas organiza\u00e7\u00f5es.Bibliotecas de conte\u00fado como fonte de receita\nAs empresas do setor de m\u00eddia dependem de dados n\u00e3o estruturados (arquivos de v\u00eddeo, imagens e \u00e1udio), portanto, devem ser capazes de analis\u00e1-los para garantir um gerenciamento eficaz de seus ativos de m\u00eddia. O lakehouse para o setor de m\u00eddia e entretenimento permite que os profissionais de marketing usem o conte\u00fado arquivado para criar campanhas. Tamb\u00e9m permite que as equipes de produ\u00e7\u00e3o busquem conte\u00fado existente para incluir em novas produ\u00e7\u00f5es e equipes de vendas identifiquem o conte\u00fado para vender para outras empresas de m\u00eddia.Aproveite os modelos pr\u00e9-criados para ML\/IA. Coloque ML no centro do seu neg\u00f3cio\nLibere o potencial do machine learning para entender melhor as necessidades de consumidores, funcion\u00e1rios e anunciantes. Depois que todos os seus dados estiverem centralizados e perfeitamente conectados por um conjunto completo de an\u00e1lises colaborativas e ferramentas de machine learning, as equipes de dados podem trabalhar em conjunto para criar modelos preditivos poderosos que impulsionam a inova\u00e7\u00e3o em personaliza\u00e7\u00e3o, monetiza\u00e7\u00e3o de conte\u00fado e publicidade.Baixar e-bookParceiros e solu\u00e7\u00f5es\nComece com uma variedade de solu\u00e7\u00f5es e modelos de an\u00e1lise e dados espec\u00edficos para o setor de m\u00eddia e entretenimento\nExplore o nosso Portal de ParceirosAtribui\u00e7\u00e3o multi-touchAvalie a efic\u00e1cia da campanha e otimize os gastos com marketing melhorando a atribui\u00e7\u00e3o de canalComece agoraToxicidade de jogadores e usu\u00e1riosMantenha uma atmosfera saud\u00e1vel em suas comunidades de usu\u00e1rios detectando linguagem e comportamento t\u00f3xicos em tempo realComece agoraAn\u00e1lise sobreviv\u00eancia\/valor de tempo de vidaIdentifique os riscos de churn entre seus consumidores e os fatores que prolongam seu ciclo de vidaComece agoraPropens\u00e3o a churnOtimize a reten\u00e7\u00e3o, obtenha uma vis\u00e3o precisa do ciclo de vida e reduza sua taxa de churnComece agoraSegmenta\u00e7\u00e3o comportamentalCrie segmentos avan\u00e7ados para obter melhores previs\u00f5es de compra com base em comportamentosComece agoraPrevis\u00f5es e atribui\u00e7\u00e3o de vendasAumente os resultados de publicidade segmentando os canais de melhor desempenhoComece agoraRecomenda\u00e7\u00f5esAumente as convers\u00f5es e o engajamento com recomenda\u00e7\u00f5es omnicanal personalizadasComece agoraReconhecimento de imagem\/LabelboxFa\u00e7a anota\u00e7\u00f5es em imagens e v\u00eddeos para direcionar a segmenta\u00e7\u00e3o contextual de an\u00fancios no lakehouse\n\u00a0\nEm breveQualidade de experi\u00eancia em v\u00eddeoAnalise dados em lote e streaming para garantir o desempenho da experi\u00eancia de streaming de conte\u00fadoComece agoraLances em tempo realSaiba como prever a visibilidade de an\u00fancios em tempo real para refinar sua estrat\u00e9gia de RTBComece agoraVer todas as solu\u00e7\u00f5esLakehouse para o setor de m\u00eddia e entretenimento na pr\u00e1ticaRecursos\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre dados e IA para o setor de m\u00eddia e entretenimento\nExplorar recursose-booksBaixarWebinarsSaiba maisBlogsSaiba maisTudo pronto para come\u00e7ar?Adorar\u00edamos saber sobre seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteAgendar uma demonstra\u00e7\u00e3oProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/technology?_ga=2.248875269.304211706.1676394659-1273371566.1673997209","text":"Databricks Technology Partners - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Technology PartnersConnect with Databricks Technology Partners to integrate data ingestion, business intelligence and governance capabilities with the Databricks Lakehouse Platform.\u201cWith Databricks and Fivetran, we will be able to significantly improve marketing insights in the future. From a technical standpoint, the two tools interact harmoniously together and the integration feels very native.\u201d\u2014 Jan-Niklas M\u00fchlenbrock, Team Lead, Business Intelligence & ERP at Paul HewittDatabricks Technology Partners integrate their solutions with Databricks to provide complementary capabilities for ETL, data ingestion, business intelligence, machine learning and governance.These integrations enable customers to leverage the Databricks Lakehouse Platform\u2019s reliability and scalability to innovate faster while deriving valuable data insights.Partner ConnectBring together all your data, analytics and AI tools on one open platform. With Partner Connect, Databricks provides a fast and easy way to connect your existing tools to your lakehouse using validated integrations, and helps you discover and try new solutions.Become a partnerLearn moreLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gavita-regunath","text":"Gavita Regunath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGavita RegunathPrincipal Data Scientist at Advancing AnalyticsBack to speakersGavita Regunath is a passionate data scientist with Advancing Analytics, a mother, wife, mentor, and addicted to learning new things. In her spare time, she loves spending time with her family and enjoys fulfilling her STEM role, where she delivers AI and machine learning lessons to primary school children.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arun-pamulapati","text":"Arun Pamulapati - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArun PamulapatiSr. Staff Security Field Engineer at DatabricksBack to speakersArun is a security engineer with Databricks for 5 years and has 20+ years of experience in building data products including over a decade of experience in big data analytics. Arun led and co-created the Security Analysis Tool (SAT) and is a core member of the Security Field Engineering team at Databricks. He has worked with customers in both the private and regulated industries on security. Arun has Bachelor's in Computer Sci and holds Cloud security, Bigdata, and AI\/ML industry certifications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/automl?itm_data=product-link-autoML","text":"Databricks AutoML - Automated Machine Learning | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAutoMLAugment experts. Empower citizen data scientists.Try for freeSchedule a demoDatabricks AutoML allows you to quickly generate baseline models and notebooks. ML experts can accelerate their workflow by fast-forwarding through the usual trial-and-error and focus on customizations using their domain knowledge, and citizen data scientists can quickly achieve usable results with a\u00a0low-code approach.Jump-start new ML projectsDatabricks AutoML provides the training code for every trial run to help data scientists jump-start their development. Data scientists can use this to quickly assess the feasibility of using a data set for machine learning (ML) or to get a quick sanity check on the direction of an ML project.No ML problem too bigLeverage AutoML to tackle a variety of machine learning problems ranging from classification, regression, and forecasting. AutoML uses multiple algorithms from a variety of machine learning libraries for each problem type, and lets you pick the best for your problem.Automate the grind of machine learningAutomatically set up your machine learning project with the training libraries, MLflow integration for experiment tracking and built-in ML best practices such as training and testing split, normalizing of features and hyperparameter tuning.A \u201cglass box\u201d approach to AutoMLUse generated editable notebooks to easily customize baseline models with your domain expertise. You can also leverage these notebooks to explain how your AutoML models were trained to fulfill audit and compliance requirements.ResourcesVirtual eventsAutoML: Rapid, simplified machine learning for everyoneAutomating the ML Lifecycle With Databricks Machine LearningBuilding Machine Learning PlatformsDocumentationDatabricks AutoML DocumentationeBooksState-of-the-Art Machine Learning CapabilitiesReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cort-lunke","text":"Cort Lunke - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCort LunkeData & Analytics Lead - Truterra at Land O'LakesBack to speakersSpeaker Bio\nA software architect at Land O\u2019Lakes and adjunct instructor at the University of St. Thomas Graduate Programs in Software, Cort has over 10 years of experience spanning data, analytics, server engineering, and cloud platforms. He currently leads the data and analytics team for Truterra, a Land O\u2019Lakes business and leading provider of sustainability programs in agriculture and food.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/product\/azure?itm_data=menu-item-azureProduct","text":"Azure Databricks - \ubaa8\ub4e0 \ubd84\uc11d \ubc0f AI \uc6cc\ud06c\ub85c\ub4dc \ud1b5\ud569 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 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\uc2dc\uac04\uc5d0 \ub2ec\ud558\ub294\n\uc11c\ubc84 \uc2dc\uac04\nAzure Databricks\ub294 34\uac1c \uc774\uc0c1\uc758\u00a0Azure \ub9ac\uc804\uc5d0\uc11c \uace0\uac1d\uc0ac \uc218\ucc9c \uacf3\uc774 \ub9e4\uc77c \uc218\ubc31\ub9cc \uc2dc\uac04\uc5d0 \ub2ec\ud558\ub294 \uc11c\ubc84 \uc2dc\uac04\uc744 \uc2e4\ud589\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\uc0ac\uc6a9 \ud3b8\uc774\uc131\nAzure Portal\uc5d0\uc11c \ud074\ub9ad \ud55c \ubc88\uc73c\ub85c \uc2dc\uc791\ud558\uba74 Azure \ubcf4\uc548 \ubc0f \ub370\uc774\ud130 \uc11c\ube44\uc2a4\ub97c \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud611\uc5c5 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uacfc \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\ub85c \u0000\u0000\ucd5c\ub300 25%\uae4c\uc9c0 \uc0dd\uc0b0\uc131\uc744 \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\uc0b0\uc5c5 \uc0ac\uc6a9 \uc0ac\ub840\uae08\uc735 \uc11c\ube44\uc2a4Swiss Re\n\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ubc0f \uc560\ub110\ub9ac\uc2a4\ud2b8\ub4e4\uc758 \ub370\uc774\ud130 \ubd84\uc11d\uc744 \ud1b5\ud569\ud588\uc2b5\ub2c8\ub2e4.HSBC\nAzure Databricks\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub514\uc9c0\ud138 \uacb0\uc81c \ud50c\ub7ab\ud3fc\uc744 \uad6c\ucd95\ud588\uc2b5\ub2c8\ub2e4.ABN AMRO\n\ud611\uc5c5, AI \uc778\uc0ac\uc774\ud2b8 \ubc0f \uace0\uae09 \uc790\ub3d9 \uba38\uc2e0 \ub7ec\ub2dd \uae30\ub2a5\uc744 \uc9c0\uc6d0\ud558\uc5ec \ubd84\uc11d \uc6cc\ud06c\ud50c\ub85c\ub97c \uac1c\uc120\ud588\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ub9ac\ud14c\uc77c\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559Azure Databricks \uc774\ubca4\ud2b8 \ucc38\uc5ecDatabricks, Microsoft \ubc0f \ud30c\ud2b8\ub108\uc0ac\ub4e4\uc774 Azure Databricks\ub97c \uc704\ud55c \uc774\ubca4\ud2b8\ub97c \uac1c\ucd5c\ud569\ub2c8\ub2e4. Azure\uc5d0\uc11c \uac00\uc7a5 \ube60\ub974\uac8c \uc131\uc7a5\ud558\uace0 \uc788\ub294 \ub370\uc774\ud130 + AI \uc11c\ube44\uc2a4\uc5d0 \ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub824\uba74 \uac00\uae4c\uc6b4 \uacf3\uc5d0\uc11c \uc5f4\ub9ac\ub294 \uc774\ubca4\ud2b8\uc5d0 \ucc38\uc5ec\ud574\ubcf4\uc138\uc694! \uc8fc\uc81c\uc640 \ud615\uc2dd\uc740 \ub2e4\ub97c \uc218 \uc788\uc73c\ubbc0\ub85c, \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uac01 \uc774\ubca4\ud2b8 \ud398\uc774\uc9c0\ub97c \ucc38\uc870\ud558\uc138\uc694.\u00a0\uc790\uc138\ud788Azure\uc5d0 \ucd5c\uc801\ud654Azure \ub370\uc774\ud130 \uc2a4\ud1a0\uc5b4\uc640 \uc11c\ube44\uc2a4\ub97c \uc804\ubb38 \ucee4\ub125\ud130\uc640 \ud1b5\ud569\ud558\uc5ec \ud658\uacbd \uc548\uc758 \ub370\uc774\ud130\uc5d0 \ube60\ub974\uac8c \uc561\uc138\uc2a4\ud558\uace0 \uac04\ub2e8\ud788 \uad00\ub9ac\ud558\uc138\uc694. \uc190\uc27d\uac8c \u0000\ubcf4\uc548 \ucee8\ud2b8\ub864\uc744 \uc124\uc815\ud558\uace0, \ud658\uacbd\uc744 \uad00\ub9ac\ud558\uba70, \ubaa8\ub4e0 Azure \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ucd94\ucc9c \ud1b5\ud569Azure Active DirectoryAzure Active Directory\uc758 SSO\ub294 Azure Databricks\uc5d0 \ub85c\uadf8\uc778\ud558\uae30\uc5d0 \uac00\uc7a5 \uc88b\uc740 \ubc29\ubc95\uc785\ub2c8\ub2e4. Azure Databricks\ub294 Azure AD\uc758 \uc790\ub3d9\ud654\ub41c \uc0ac\uc6a9\uc790 \ud504\ub85c\ube44\uc800\ub2dd\uc73c\ub85c \uc0c8\ub85c\uc6b4 \uc0ac\uc6a9\uc790\ub97c \uc0dd\uc131\ud558\uc5ec \uc801\uc808\ud55c \uc218\uc900\uc758 \uc561\uc138\uc2a4 \uad8c\ud55c\uc744 \uc81c\uacf5\ud558\uace0, \uc0ac\uc6a9\uc790\ub97c \uc81c\uac70\ud558\ub294 \uc561\uc138\uc2a4 \uad8c\ud55c \ub514\ud504\ub85c\ube44\uc800\ub2dd \uae30\ub2a5\ub3c4 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key Vault\ub9ac\uc18c\uc2a4\ubc31\uc11c\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \uc704\ud55c Azure DatabricksAzure Databricks: ML \ubc0f AI\ub97c \uc2e4\ud589\ud558\uae30 \uc704\ud55c \ucd5c\uace0\uc758 \ud50c\ub7ab\ud3fc3\uac00\uc9c0 \uc2e4\uc6a9\uc801\uc778 Azure Databricks \uc0ac\uc6a9 \uc0ac\ub840Azure Databricks\uc5d0\uc11c Apache Spark \uc2dc\uc791\ud558\uae30\uc601\uc0c1Data + AI Summit NA 2021 \ud0a4\ub178\ud2b8 \ubc1c\ud45c: Ali Ghodsi, Rohan Kumar(CVP, Microsoft)\uc758 \ub2f4\ud654 \uc138\uc158Azure Databricks \ud074\ub77c\uc6b0\ub4dc \ud1b5\ud569 \ub370\ubaa8Azure Databricks\uc5d0\uc11c Delta Lake\ub85c \ub370\uc774\ud130 \uc218\uc9d1Databricks SQL\uc744 \uc0ac\uc6a9\ud55c \ub370\uc774\ud130 \ud0d0\uc0c9eBook2021 Gartner\u00ae Magic Quadrant\u2122 \ub370\uc774\ud130 \uc0ac\uc774\u0000\uc5b8\uc2a4 \ubc0f \uba38\uc2e0 \ub7ec\ub2dd \ud50c\ub7ab\ud3fc \ubd80\ubb38\ucd5c\uc2e0 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\uc758 \uae30\ucd08\uac1c\ubc1c\uc790\ub97c \uc704\ud55c Delta Lake\ub85c Apache Spark\u2122 \ubc30\uc6b0\uae30 8\ub2e8\uacc4Apache Spark\u2122\uc758 \uc6d0\ub9ac: \ucf54\uc5b4 \uc544\ud0a4\ud14d\ucc98 \ubc0f \uae30\ubcf8 \uac1c\ub150 \uc2dc\uc791\ud558\uae30\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \uc608\uc57d\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/neil-patel\/#","text":"Neil Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNeil PatelLead Specialist Solutions Architect at DatabricksBack to speakersNeil Patel is an SSA at Databricks. He has worked on a variety of use cases and problems across different customers.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rakesh-kumar\/#","text":"Rakesh Kumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRakesh KumarStaff Software Engineer at Lyft IncBack to speakersRakesh Kumar is a staff software engineer on the Realtime Optimization Platform team at Lyft. He started his career as an embedded software engineer for mobile devices; later he moved to server-side engineer to tackle bigger challenges in distributed systems. His interests include machine learning and streaming systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anup-segu","text":"Anup Segu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnup SeguCo-Head of Data Engineering at YipitDataBack to speakersAnup is the Co-Head of Data Engineering at YipitData, a leader in the alternative data industry that provides data insights for investment firms and corporations. At YipitData, Anup helped found its Data Engineering department, architected its petabyte-scale data platform, and drove adoption of data analytics and spark across the company. Previously, Anup worked in investment banking at Citigroup and studied at Indiana University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"P\u00e1gina de parceiros: Parceiros de consultoria e IS | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPrograma de parceiros de C&ISO programa de parceria Databricks C&SI (consultoria e integra\u00e7\u00e3o de sistemas) \u00e9 orientado por valores e aproveita nossa colabora\u00e7\u00e3o para oferecer \u00f3timos resultados.Inscreva-se agoraJunte-se a um ecossistema global de provedores de dados e servi\u00e7os da IA: juntos, ajudamos nossos clientes em comum a se tornarem empresas orientadas por dados. Como parceiro, voc\u00ea desempenha um papel estrat\u00e9gico:Impacto nas vendas\nInteraja com nossas equipes de campo para vender a vis\u00e3o do lakehouse e expandir a pegada da Databricks.Valor do cliente\nTreine sua equipe na plataforma para desenvolver as capacidades e habilidades da sua pr\u00e1tica.Inova\u00e7\u00e3o\nDemonstre sua experi\u00eancia desenvolvendo solu\u00e7\u00f5es repet\u00edveis para lidar com casos de uso de clientes de alto impacto.Acesse os benef\u00edcios de engajamento e ativa\u00e7\u00e3o para expandir sua pr\u00e1tica e fortalecer a parceria:Treinamento T\u00e9cnico DatabricksAcesso \u00e0 Plataforma Databricks LakehouseSuporte t\u00e9cnico e de vendasRegistro de oportunidade e taxas de refer\u00eanciaFundos de investimento do clienteCapacita\u00e7\u00e3o e recursos de entrada no mercadoTudo pronto para come\u00e7ar?Inscreva-se agoraEncontrar uma parceriaProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/data-partner-program","text":"Programma Data Partner | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWData Provider Partner ProgramAccedi a un ampio ecosistema aperto di consumatori di dati con DatabricksIscrivitiDatabricks aiuta i Data Provider Partner a monetizzare il loro patrimonio di dati proponendolo a un ampio ecosistema aperto di consumatori di dati, tutto da un'unica piattaforma. I nostri partner possono cos\u00ec sfruttare la Databricks Lakehouse Platform per raggiungere pi\u00f9 clienti, ridurre i costi e offrire un'esperienza di qualit\u00e0 eccellente per tutte le esigenze di condivisione dei dati.Vantaggi per i Data Provider PartnerAmpliamento del portafoglio clientiRaggio d'azione pi\u00f9 ampio per entrare in contatto con i consumatori di dati da un'unica piattaforma aperta e sicuraMigliore esperienza per il clienteRiduzione dei tempi di configurazione e attivazione per i consumatori di datiSupporto per il marketingMaggiore visibilit\u00e0 grazie ai servizi di Databricks per il marketingTecnologie per prodotti di gestione dei datiSfrutta la Lakehouse Platform leader di mercato per la gestione e l'analisi dei dati e per l'AIAccesso al team di prodotti e R&DAccesso a prodotti, progettazione e personale dell'assistenza DatabricksSoluzioni per settori specificiCollabora con i nostri team settoriali per sviluppare soluzioni per settori specifici progettate per i casi d'uso di ciascun clienteDelta Sharing per fornitori di datiDatabricks si integra in maniera nativa con Delta Sharing, il primo protocollo aperto al mondo per la condivisione sicura dei dati in tempo reale fra diverse organizzazioni, indipendentemente dalla piattaforma su cui i dati risiedono.Delta Sharing \u00e8 supportato da un ampio ecosistemaClient open-sourceClient commercialiBusiness IntelligenceAnalisiGovernanceFornitori di datiPronto per cominciare?IscrivitiTrova un partnerProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/p\/register-your-interest-for-databricks-partner-connect?itm_data=TechnologyPartnerProgram-HeroCTA-Apply","text":"Partner Connect | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner ConnectEasily discover and integrate data, analytics and AI solutions with your lakehouseWatch demosPartner Connect makes it easy for you to discover data, analytics and AI tools directly within the Databricks platform \u2014 and quickly integrate the tools you already use today. With Partner Connect, you can simplify tool integration to just a few clicks and rapidly expand the capabilities of your lakehouse.Connect your data and AI tools to the lakehouseEasily connect your preferred data and AI tools to the lakehouse and power any analytics use caseDiscover validated data and AI solutions for new use casesA one-stop portal for validated partner solutions so you can build your next data application fasterSet up in a few clicks with pre-built integrationsPartner Connect simplifies your integrations by automatically configuring resources \u2014 including clusters, tokens and connection files \u2014 to connect with partner solutionsGet started as a partnerDatabricks partners are uniquely positioned to deliver faster analytics insights for customers. Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partner\u201cBuilding on our longtime partnership, Partner Connect enables us to design an integrated experience between our companies and customers. With Partner Connect, we\u2019re delivering a streamlined experience that makes it easier than ever for the thousands of Databricks customers, whether they use Fivetran today or discover us through Partner Connect, to unlock insights in their data, discover more analytics use cases, and get value from their lakehouse faster by easily connecting hundreds of data sources to their lakehouse.\u201d\u2014 George Fraser, CEO at FivetranDemosFivetranConnect data from 180+ popular apps, including SaaS apps (Salesforce, Google Analytics, etc.) into the lakehousedbtGet started with dbt Cloud and Databricks to build data transformationsPower BIBring the advantages of Databricks Lakehouse performance and technology to all your usersTableauEmpower all users with a data lakehouse for modern analytics by connecting Tableau Desktop to Databricks SQLRiverySimplify the data journey from ingestion to transformation and delivery into Delta LakeLabelboxEasily prepare unstructured data for AI and Analytics in the LakehouseProphecyBuild and deploy Spark and Delta pipelines using a visual drag-and-drop interfaceArcionConnect data sources to the lakehouse with a distributed CDC-based replication platformTry for freeResourcesBlogFeb 2023 \u2013 Announcing New Partner Integrations in Partner ConnectSept 2022 \u2013 Introducing New Partner Integrations in Partner ConnectJune 2022 \u2013 Announcing New Partner Integrations in Partner ConnectBuild Your Business on Databricks With Partner ConnectDocumentationDatabricks Partner Connect guideReady to learn more?Take advantage of Databricks\u2019 development and partner resources to grow alongside our open, cloud-based platform.Become a partnerContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/data-engineering","text":"Data Engineering | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData EngineeringTens of millions of production workloads run daily on DatabricksGet startedWatch demo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowEasily ingest and transform batch and streaming data on the\u00a0Databricks Lakehouse Platform. Orchestrate reliable production workflows while Databricks automatically manages your infrastructure at scale. Increase the productivity of your teams with built-in data quality testing and support for software development best practices.Unify batch and streamingEliminate silos on one platform with a single and unified API to ingest, transform and incrementally process batch and streaming data at scale.Focus on getting value from dataDatabricks automatically manages your infrastructure and the operational components of your production workflows so you can focus on value, not on tooling.Connect your tools of choiceAn open Lakehouse Platform to connect and use your preferred data engineering tools for data ingestion, ETL\/ELT and orchestration.Build on the Lakehouse PlatformThe Lakehouse Platform provides the best foundation to build and share trusted data assets that are centrally governed, reliable and lightning-fast.\u201cTo us, Databricks is becoming the one-stop shop for all of our ETL work. The more we work with the Lakehouse Platform, the easier it is for both users and platform administrators.\u201d\u2014 Hillevi Crognale, Engineering Manager, YipitDataHow does it work?Simplified data ingestionAutomated ETL processingReliable workflow orchestrationEnd-to-end observability and monitoringNext-generation data processing engineFoundation of governance, reliability and performanceSimplified data ingestionIngest data into your\u00a0Lakehouse Platform\u00a0and power your analytics, AI and streaming applications from one place.\u00a0Auto Loader\u00a0incrementally and automatically processes files landing in cloud storage \u2014 without the need to manage state information \u2014 in scheduled or continuous jobs. It efficiently tracks new files (scaling to billions) without having to list them in a directory, and can also automatically infer the schema from the source data and evolve it as it changes over time. The\u00a0COPY INTO\u00a0command makes it easy for analysts to perform batch file ingestion into\u00a0Delta Lake\u00a0via SQL.\u201cWe\u2019ve seen a 40% productivity uplift for data engineering \u2014 reducing the time it takes to develop new ideas from days to minutes and increasing the availability and accuracy of our data.\u201d\u2014 Shaun Pearce, Chief Technology Officer,\u00a0GoustoLearn moreAutomated ETL processingOnce ingested, raw data needs transforming so that it\u2019s ready for analytics and AI. Databricks provides powerful ETL capabilities for data engineers, data scientists and analysts with\u00a0Delta Live Tables\u00a0(DLT). DLT is the first framework that uses a simple declarative approach to build ETL and ML pipelines on batch or\u00a0streaming data, while automating operational complexities such as infrastructure management, task orchestration, error handling and recovery, and performance optimization. With DLT, engineers can also treat their data as code and apply software engineering best practices like testing, monitoring and documentation to deploy reliable pipelines at scale.Learn moreReliable workflow orchestrationDatabricks\u00a0Workflows\u00a0is the fully managed orchestration service for all your data, analytics and AI that is native to your\u00a0Lakehouse Platform. Orchestrate diverse workloads for the full lifecycle including\u00a0Delta Live Tables\u00a0and\u00a0Jobs\u00a0for SQL,\u00a0Spark, notebooks, dbt, ML models and more. Deep integration with the underlying Lakehouse Platform ensures you will create and run reliable production workloads on any cloud while providing deep and centralized monitoring with simplicity for end users.\u201cOur mission is to transform the way we power the planet. Our clients in the energy sector need data, consulting services and research to achieve that transformation. Databricks Workflows gives us the speed and flexibility to deliver the insights our clients need.\u201d\u2014 Yanyan Wu, Vice President of Data,\u00a0Wood MackenzieLearn moreEnd-to-end observability and monitoringThe Lakehouse Platform gives you visibility across the entire data and AI lifecycle so data engineers and operations teams can see the health of their production workflows in real time, manage data quality and understand historical trends. In Databricks\u00a0Workflows\u00a0you can access dataflow graphs and dashboards tracking the health and performance of your production jobs and\u00a0Delta Live Tables\u00a0pipelines. Event logs are also exposed as\u00a0Delta Lake\u00a0tables so you can monitor and visualize performance, data quality and reliability metrics from any angle.Next-generation data processing engineDatabricks data engineering is powered by\u00a0Photon, the next-generation engine compatible with Apache Spark APIs delivering\u00a0record-breaking\u00a0price\/performance while automatically scaling to thousands of nodes.\u00a0Spark Structured Streaming\u00a0provides a single and unified API for batch and stream processing, making it easy to adopt\u00a0streaming on the lakehouse\u00a0without changing code or learning new skills.Learn moreState-of-the art data governance, reliability and performanceData engineering on Databricks means you benefit from the foundational components of the\u00a0Lakehouse Platform\u00a0\u2014 Unity Catalog and Delta Lake. Your raw data is optimized with\u00a0Delta Lake, an open source storage format providing reliability through ACID transactions, and scalable metadata handling with lightning-fast performance. This combines with\u00a0Unity Catalog\u00a0to give you fine-grained governance for all your data and AI assets, simplifying how you govern, with one consistent model to discover, access and share data across clouds. Unity Catalog also provides native support for\u00a0Delta Sharing, the industry\u2019s first open protocol for simple and secure data sharing with other organizations.Migrate to DatabricksTired of the data silos, slow performance and high costs associated with legacy systems like Hadoop and enterprise data warehouses? Migrate to the Databricks Lakehouse: the modern platform for all your data, analytics and AI use cases.Migrate to DatabricksIntegrationsProvide maximum flexibility to your data teams \u2014 leverage\u00a0Partner Connect\u00a0and an ecosystem of\u00a0technology partners\u00a0to seamlessly integrate with popular data engineering tools. For example, you can ingest business-critical data with Fivetran, transform it in place with dbt, and orchestrate your pipelines with Apache Airflow.Data Ingestion and ETL+ Any other Apache Spark\u2122\ufe0f compatible clientCustomer StoriesDiscover moreDelta LakeWorkflowsDelta Live TablesDelta SharingRelated content\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.\nExplore resourceseBooksRise of the Data Lakehouse by Bill Inmon, father of the data warehouseData, Analytics and AI governanceData Management 101The Big Book of Data EngineeringExplore the new Delta Sharing SolutionMigrating from a Data Warehouse to a Data Lakehouse for DummiesEventsTackle Data Transformation With, Delta Live TablesHassle-Free Data Ingestion Webinar SeriesData + AI Summit 2022Modernize your Data WarehouseBlogsAnnouncing General Availability of Databricks Delta Live Tables (DLT)Introducing Databricks WorkflowsAn Overview of All the New Structured Streaming Features Developed in 2021 for Databricks and Apache Spark10 Powerful Features to Simplify Semi-structured Data Management in the Databricks LakehouseReady to get started?Try for freeJoin the communityProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/andy-hanks","text":"Andy Hanks - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAndy HanksSenior Data Architect, Analytics Platform at CRISP Shared ServicesBack to speakersA trained physician, Andy leads the Data Analytics team at CRISP Shared Services. CRISP is the designated health information exchange in Maryland and the District of Columbia and supports other affiliate States.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/built-on-partner-program","text":"Built on Databricks Partner Program | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWBuilt on Databricks Partner ProgramSviluppa, commercializza e incrementa il tuo business con DatabricksIscrivitiBuilt on Databricks Partner Program d\u00e0 accesso a risorse tecniche e commerciali per accelerare lo sviluppo di applicativi SaaS moderni ed espandere il business. Lo sviluppo di soluzioni sulla Databricks Lakehouse Platform offre un'esperienza unificata a costi contenuti per realizzare applicazioni, prodotti e servizi di gestione dei dati e per condividere in maniera trasparente dati su larga scala con un ecosistema globale aperto.Le aziende che partecipano al programma Built on Databricks generano valore su larga scala per il loro businessBlogLeggiWebinarGuardaBlogLeggiBenefici per i partner Built on di DatabricksAccesso agli esperti di Databricks\nInteragisci con il personale di Databricks che si occupa di prodotti, progettazione e assistenzaSviluppa l'attivit\u00e0 su una piattaforma moderna\nSfrutta la Lakehouse Platform leader di mercato per la gestione unificata di dati, analisi e AIRaggiungi pi\u00f9 clienti\nRaggio d'azione pi\u00f9 ampio per entrare in contatto con tutti i consumatori di dati da un'unica piattaforma aperta e sicuraSupporto per il marketing\nAccesso a investimenti di marketing per aumentare l'esposizione e ampliare il raggio d'azioneCollaborazione commerciale\nAumenta le opportunit\u00e0 commerciali grazie alla collaborazione con il reparto vendite di DatabricksComincia oggi stesso!IscrivitiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/consulting-and-si","text":"Partenaires de Databricks sp\u00e9cialis\u00e9s dans le conseil - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires de Databricks sp\u00e9cialis\u00e9s dans le conseilConnectez-vous avec les partenaires de Databricks dans le monde entier pour vous aider \u00e0 cr\u00e9er, d\u00e9ployer ou migrer vers la plateforme lakehouse de Databricks.Nos partenaires sp\u00e9cialis\u00e9s dans le conseil sont des experts qui occupent une position unique pour vous aider \u00e0 mettre en \u0153uvre et \u00e0 faire \u00e9voluer des initiatives de data engineering, de data science collaborative, de machine learning \u00e0 cycle de vie complet et d'analytique commerciale.\nIls apportent leur expertise en mati\u00e8re de technologie, de secteur d'activit\u00e9 et de cas d'usage pour vous aider \u00e0 tirer le meilleur parti de la plateforme lakehouse de Databricks. Les services comprennent la conception d'une strat\u00e9gie de transformation des donn\u00e9es unique \u00e0 votre entreprise, la modernisation, la migration, la gestion et la gouvernance des donn\u00e9es, et bien plus encore.Loading...ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u0000\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/jp\/blog\/category\/company","text":"Databricks \u30d6\u30ed\u30b0Skip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 PT\n\u3055\u3088\u3046\u306a\u3089\u3001\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3002\u3053\u3093\u306b\u3061\u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3002\n\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u304c\u6700\u65b0\u306e\u30c7\u30fc\u30bf\u30b9\u30bf\u30c3\u30af\u306b\u3069\u306e\u3088\u3046\u306b\u9069\u5408\u3059\u308b\u304b\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u51fa\u5e2d\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\u4eca\u3059\u3050\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c5\u67089\u65e5 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NOWLoading...\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/james-norman\/#","text":"James Norman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJames NormanPrincipal Software Engineer at NikeBack to speakersPrincipal Software Engineer, James has been in software for 20 years from Medical Imaging to developing enterprise Model Serving solutions. Passionate to simplify and streamline development process and build platforms to connect teams and applications with reliable data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/a-new-approach-to-data-sharing","text":"A New Approach to Data Sharing | DatabrickseBookShare live data across platformsExplore the new Delta Sharing solutionHomegrown data-sharing solutions based on SFTP or APIs aren\u2019t scalable and saddle you with operational overhead. Off-the-shelf data-sharing solutions only work on specific sharing networks, promoting vendor lock-in and can be costly. Databricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform without any replication so you can reach your customers where they are. Get the whole story in this eBook.You\u2019ll discover how you can:Share live data from where it lives, without replicating or moving it to another systemEasily share existing data in Delta Lake and Apache Parquet formats. Recipients don\u2019t have to be on the Databricks platform, the same cloud or a cloud at all.Drive collaboration with your partners, suppliers and lines of businessMeet governance, security and compliance needs while sharing assetsAccelerate time to value by consuming shared data directly from the tools of your choiceGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabio-luis-correia-da-silva","text":"Fabio Luis Correia da Silva - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabio Luis Correia da SilvaArchitecture Specialist at BradescoBack to speakersFabio Correia is an Architecture Specialist with over 35 years of experience in software development and analytical solutions. He has worked for companies in publishing, telecommunications, finance and technology sectors, always leading high performance development teams. He has been working for Bradesco since 2016. At Bradesco, Fabio joined the team responsible for implementing the Big Data Environment and now he is responsible for the Cloud Architecture for Data and Analytics, allowing business areas to efficiently transform data into value. Besides loving collectibles, Fabio loves street running and everything related to this sport. In his free time, he likes to study new running shoes technologies and he is currently training for a 30Km competition, with an eye on his first marathon in the near future.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/built-on-partner-program","text":"Programme partenaires Built on Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWProgramme partenaires Built on DatabricksCr\u00e9ez des solutions, commercialisez-les et d\u00e9veloppez votre activit\u00e9 avec DatabricksInscrivez-vous maintenantLe programme de partenariat Built on donne acc\u00e8s \u00e0 des ressources techniques et commerciales permettant d'acc\u00e9l\u00e9rer le d\u00e9veloppement de votre application SaaS moderne et de d\u00e9velopper votre activit\u00e9. La plateforme lakehouse Databricks offre une exp\u00e9rience unifi\u00e9e rentable pour le d\u00e9veloppement d'applications, de produits et de services de donn\u00e9es, mais aussi pour le partage des donn\u00e9es \u00e0 grande \u00e9chelle avec un \u00e9cosyst\u00e8me ouvert et mondial.Les entreprises Built on Databricks cr\u00e9ent de la valeur commerciale \u00e0 grande \u00e9chelleBlogLire la suiteWebinaireREGARDERBlogLire la suiteLes avantages des partenaires Built on DatabricksAcc\u00e9dez aux conseils des experts Databricks\n\u00c9changez avec les \u00e9quipes en charge des produits, du data engineering et de l'assistance de DatabricksD\u00e9veloppez sur une plateforme moderne\nExploitez les possibilit\u00e9s de la plateforme Lakehouse, leader sur le march\u00e9, pour les donn\u00e9es unifi\u00e9es, l'analytique et l'IATouchez davantage de clients\nProposez vos solutions \u00e0 tous les consommateurs de donn\u00e9es \u00e0 partir d'une plateforme ouverte et s\u00e9curis\u00e9eSupport marketing\nAcc\u00e9dez \u00e0 des investissements marketing pour accro\u00eetre votre exposition et votre champ d'actionCollaboration commerciale\nMultipliez les opportunit\u00e9s en b\u00e9n\u00e9ficiant de l'appui et de la collaboration des Ventes DatabricksLancez-vous d\u00e8s aujourd'hui\u00a0!Inscrivez-vous maintenantProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/healthcare-and-life-sciences","text":"Lakehouse for Healthcare and Life Sciences - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLakehouse for Healthcare and Life SciencesDeliver better patient outcomes with the power of data and AIGet startedSchedule a demoFour data challenges in healthcare and life sciencesFragmented patient data\nData silos and limited support for unstructured data prevent organizations from understanding the patient journey.Rapidly growing health data\nLegacy on-premise data architectures are complex to manage and costly to scale for today\u2019s massive volumes of healthcare data, including growth in imaging and genomics.Real-time care and operations\nData warehouses and disjointed tools impede the delivery of real-time insights needed for critical care decisions and the safe production and delivery of important therapeutics.Complex advanced health analytics\nLightweight ML capabilities are preventing organizations from tackling everything from next-gen patient care models to predictive analytics for drug R&D.Lakehouse for Healthcare and Life SciencesUnified data and AI platform\nA single platform that brings together all your data and analytics workloads to enable transformative innovations in patient care and drug R&D.\nPartner solutions\nThe world\u2019s leading healthcare and life sciences solution providers such as Deloitte, Accenture, and ZS Associates are building for the lakehouse. Take advantage of pre-built offerings that accelerate data-driven transformation in drug R&D and patient care.\nTools to accelerate\nDatabricks and our partners have built a suite of Solution Accelerators that make it easy to ingest healthcare data, such as HL7 messages, and deliver on use cases like medical text analytics and drug safety monitoring.\nIndustry collaboration\nEnable secure and open data sharing and collaboration with organizations across the health ecosystem to accelerate life-saving research and improve how you deliver care.\nDelivering the future of care with Lakehouse\n\u00a0\n\u201cThe Databricks Lakehouse for Healthcare and Life Sciences provides GE Healthcare with a modern, open and collaborative platform to build patient views across care pathways. With these capabilities, we\u2019ve diminished costly legacy data silos and equipped our teams with timely and accurate insights.\u201d\u2014 Joji George, Chief Technology Officer, LCS Digital, GE HealthcareWhy Lakehouse for Healthcare and Life Sciences?\nAccelerate research and improve patient outcomes on an open, collaborative platform for data and AI360\u00b0 view of the patient\nBring together all your structured and unstructured data \u2014 patient, R&D and operations \u2014 on a single platform for analytics and AI. With a holistic view of the patient journey, organizations can deliver more personalized treatments.Infinite scale for population-level studies\nQuickly and reliably analyze data for millions of patients with a scalable platform in the cloud. With population-scale insights, organizations gain a more complete view of health trends and in turn can develop better therapeutics.Real-time analytics, real-time operations\nRapidly ingest and process streaming data from anywhere to power real-time analytics, with applications ranging from managing hospital bed capacity to optimizing the manufacturing and distribution of pharmaceuticals.ML-powered drug discovery and patient care\nUnlock the power of machine learning to better understand diseases and predict health needs. All your data is seamlessly connected with a full suite of collaborative tools for advanced analytics.Download the eBookPartners and solutionsGet started with a variety of data and analytics solutions and templates specific to healthcare and life sciencesIntelligent HealthcareImprove patient experiences and health outcomes with personalized patient journeys and access to care.Get startedPrecisionView\u2122Expand capabilities, increase capacity and enrich internal collaboration for health and life sciences.Get startedHealth Data InteroperabilityAutomate the ingestion of streaming FHIR bundles into the lakehouse for downstream patient analytics at scale.Get startedIntelligent Data Management for Biomedical ResearchTransform scientific data into an enterprise asset by creating an end-to-end value chain.Get startedSee all partner solutionsData Models and Cohort Building: OMOP and Propensity Score MatchingEasily ingest and standardize real-world data into your lakehouse for observational analysis at scaleGet startedInteroperability: Ingest HL7V2 MessagesAutomate the ingest of streaming HL7V2 messages into your lakehouse for real-time analyticsGet startedInteroperability: Ingest FHIR BundlesAutomate the ingest of streaming FHIR bundles into your lakehouse for downstream patient analyticsGet startedImage: Digital Pathology ClassificationAugment diagnostic workflows with deep learning by detecting metastases from digital pathology slidesGet startedR&D: Drug Target IdentificationAnalyze genetic associations at massive scale to help R&D teams identify new drug targetsGet startedPopulation Health: Disease Risk PredictionBuild predictive models for disease risk to improve care management programsGet startedNLP: Detect Adverse EventsImprove drug safety monitoring with adverse drug event detection using our joint NLP solution with John Snow LabsGet startedNLP: Extract Real-World Oncology DataTransform unstructured oncology notes into novel patient insights using our joint NLP solution with John Snow LabsGet startedNLP: Automate PHI RemovalAutomate the removal of sensitive patient information from text data using our joint NLP solution with John Snow LabsGet startedSee all solutionsLakehouse for Healthcare and Life Sciences in actionWant to learn more?Healthcare\nDeliver patient-centric care with the power of data and AILife Sciences\nBringing new treatments to patients in need with data analytics and AIImproving Health Outcomes With Data and AIDownload the eBook \u2192Resources\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on data and AI for healthcare and life sciences.\nExplore resourceseBooksImproving Outcomes With the Lakehouse for Healthcare and Life SciencesUncover New Patient Insights With Natural Language Processing at ScaleDelivering on the Promise of Real-world Data with the LakehouseSolution Sheet: Introducing the Lakehouse for Healthcare and Life SciencesWebinarsWorkshop: FHIR Up Real-Time Patient Analytics With the LakehouseWebinar: Driving healthcare innovations with the Chesapeake Regional Information System for our PatientsWorkshop: Standardizing Data With OMOP and Predicting Disease Risk With MLWorkshop: Extract Real-World Data With NLPWorkshop: Accelerate R&D With Real-World Data + AIBlogsAmgen Accelerates Drug Development & Delivery With the Lakehouse for Healthcare and Life SciencesIntroducing the Lakehouse for Healthcare and Life SciencesImproving Drug Safety With Adverse Event Detection Using NLPDatabricks\u2019 Open Source Genomics Toolkit Outperforms Leading ToolsExtracting Oncology Insights From Real-World Clinical Data With NLPReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=dbsql-promocard-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/retail-industry-solutions","text":"Die Data Lakehouse-L\u00f6sung f\u00fcr Einzelhandel und CPG \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse f\u00fcr den Einzelhandel erkundenDie vereinheitlichten Daten-, Analyse- und KI-Plattformen, die Einzelh\u00e4ndler verwenden, um jede Phase der Customer Journey zu optimierenRegistrierenKontaktBessere Leistung, gr\u00f6\u00dfere Skalierbarkeit, niedrigere TCOLakehouse f\u00fcr den EinzelhandelVereinheitlichen Sie Ihre Daten- und KI-Workloads mit integrierter Freigabe und Governance, damit interne und externe Teams bei Bedarf auf die n\u00f6tigen Daten zugreifen k\u00f6nnenWirkung \u00fcber die gesamte Wertsch\u00f6pfungsketteKundenbindungRelevanz und Hyperpersonalisierung f\u00fcr jeden KontaktpunktMit genauen 360\u00b0-Echtzeitansichten ihrer Kunden haben Einzelh\u00e4ndler alles, was sie brauchen, um Beziehungen zu den Bedingungen jedes Kunden aufzubauen: Verst\u00e4ndnis der Stimmung \u00fcber alle Kan\u00e4le hinweg und Personalisierung von Empfehlungen. Das Ergebnis? Erh\u00f6hte Rentabilit\u00e4t und Kundentreue.BetriebseffizienzMitarbeiterproduktivit\u00e4tProdukt-PerformanceEinzelhandelsl\u00f6sungen und PartnerKompromisslose Data Analytics- und KI-L\u00f6sungen, die speziell f\u00fcr Ihre Branche entwickelt wurdenDatabricks Solution Accelerators sind speziell entwickelte Leitf\u00e4den\u00a0\u2013 voll funktionsf\u00e4hige Notebooks und Best Practices\u00a0\u2013 f\u00fcr schnellere Ergebnisse im Einzelhandel. Sparen Sie Zeit beim Analysieren, Entwerfen, Entwickeln und Testen von Anwendungsf\u00e4llen wie Propensity Scoring, Customer Lifetime Value, Optimierung der Kommissionierung usw.Detaillierte PrognosenUmfassende Prognosen in k\u00fcrzerer Zeit generieren\nF\u00fchren Sie auf effiziente Weise detaillierte Prognosen auf Ladenartikelebene durch, indem Sie die verteilte Datenverarbeitungsleistung der Databricks Lakehouse-Plattform nutzen.Erste SchritteKundensegmentierungKunden f\u00fcr eine bessere Zielgruppenausrichtung segmentieren\nErstellen Sie erweiterte Kundensegmente mithilfe von Verkaufsdaten, Kampagnen, Werbesystemen und mehr, um bessere Kaufprognosen basierend auf Verhaltensweisen zu erzielen.Erste SchrittePoint-of-Sale-Analytics in EchtzeitBest\u00e4nde in Echtzeit \u00fcber mehrere Filialstandorte hinweg berechnen, um die Einzelhandelsmargen zu verbessern\nErfassen Sie schnell und in gro\u00dfem Umfang alle Point-of-Sale-Datenquellen und -typen, um Echtzeit-Erkenntnisse zu gewinnen, die den dringenden Informationsbedarf im Laden decken.Erste SchritteAccelerators f\u00fcr den Einzelhandel erkundenWir sind eine Partnerschaft mit f\u00fchrenden Beratungsunternehmen eingegangen, um innovative, branchenspezifische L\u00f6sungen zu liefern. Databricks Brickbuilder Solutions helfen Ihnen, Kosten zu senken und den Wert Ihrer Daten zu steigern. Gest\u00fctzt auf jahrzehntelange Branchenkenntnis \u2013 und entwickelt f\u00fcr die Databricks Lakehouse-Plattform \u2013 sind die Brickbuilder Solutions genau auf Ihre Bed\u00fcrfnisse zugeschnitten.Unified View of DemandMaximieren Sie Genauigkeit, Granularit\u00e4t und Aktualit\u00e4t mit einem Bedarfsplan aus einer einzigen Informationsquelle.Mehr InformationenRevenue Growth ManagementF\u00fchren Sie schnell Analysen von Rechnungsdaten, externen Marktdaten, Nachrichten und Web-Scraping-Daten durch, um Einzelhandelsmuster zu untersuchen.Mehr InformationenTrellisL\u00f6sen Sie Herausforderungen in Bezug auf Bedarfsprognose, Nachschub, Beschaffung, Preisgestaltung und Werbedienstleistungen.Mehr InformationenBrickbuilder-L\u00f6sungen erkunden\u201eWir k\u00f6nnen jetzt Informationen \u00fcber Online- und Offline-K\u00e4ufe auf Kundenebene kombinieren, was zuvor eine gro\u00dfe Herausforderung war. Diese Omnichannel-Ansicht erm\u00f6glicht es uns, online eine umfassendere Empfehlungs-Engine zu erstellen, die hervorragend angenommen wird.\u201c\n\u2013 Wendell Kuling, Manager of Data Science and Analytics, Jumbo\n\u201eDatabricks erm\u00f6glicht es uns, die Kundenerwartungen in jedem Markt zu \u00fcbertreffen und erstklassigen Service zu bieten. Mit der Lakehouse-Plattform k\u00f6nnen unsere Stakeholder und Entwickler besser zusammenarbeiten und wichtige Trends und Erkenntnisse aufdecken, die f\u00fcr die Betreuung unserer 180\u00a0Millionen Kunden erforderlich sind.\u201c\n\u2013 Sergiy Tkachuk, Head of Data Science, Reckitt\n\u201eImmer mehr Gesch\u00e4ftsbereiche nutzen die Plattform im gesamten Unternehmen auf eine Selfservice-Weise, die zuvor nicht m\u00f6glich war. Ich kann den positiven Einfluss nicht genug loben, den Databricks auf Columbia hatte.\u201c\n\u2013 Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear\nRessourcenIndividuelle TourAlle Ressourcen f\u00fcr ausf\u00fchrliche Informationen zum Lakehouse f\u00fcr den EinzelhandelWebinareMehr Echtzeitentscheidungen im EinzelhandelE-BookDas Big Book of Retail\u00a0\u2013 Anwendungsf\u00e4lleProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/james-norman","text":"James Norman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJames NormanPrincipal Software Engineer at NikeBack to speakersPrincipal Software Engineer, James has been in software for 20 years from Medical Imaging to developing enterprise Model Serving solutions. Passionate to simplify and streamline development process and build platforms to connect teams and applications with reliable data.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/newsroom","text":"Newsroom | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn\u2019t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld,\u00a0May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch,\u00a0May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN,\u00a0May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat,\u00a0May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider,\u00a0May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World\u2019s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email\u00a0protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email\u00a0protected] and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/virtual-experience\/#","text":"Virtual Experience - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVirtual ExperienceTune in, June 28-29, from anywhere in the world.\n*Asia Pacific & Japan Keynotes Rebroadcast\u00a0\nEnglish,\u00a0Japanese,\u00a0Korean\u00a0and\u00a0Mandarin\nJune 29 and June 30\n8.30 AM IST | 11 AM SGT | 12 PM JST | 12 PM KST | 1 PM AEST\nRegister nowThis year\u2019s Data + AI Summit Virtual Experience brings you a host of live content including major industry and product announcements, expert keynotes, curated breakout sessions, exclusive interviews with guest speakers and Databricks founders, as well as 250+ breakouts available on demand after the event.Featured speakersCheck back in mid May to see the full speaker lineup for our virtual event.\nDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAgendaWednesday, June 28*8:15 AM \u2013 11:00 AM | Keynote Day 1\n1:00 PM - 5:40 PM | Breakout Sessions 1-6\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nThursday, June 29*8:30 AM \u2013 11:00 AM |\u00a0 Keynote Day 2\n12:00 PM - 4:40 PM | Breakout Sessions 7-11\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nOn DemandAll 250+ breakout sessions delivered onsite in San Francisco will be recorded and available on demand soon after the event. More updates coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-starbird","text":"Scott Starbird - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott StarbirdGeneral Counsel, Public Affairs and Strategic Partnerships at DatabricksBack to speakersScott Starbird heads the Public Affairs function at Databricks, and has held various leadership positions within Databricks\u2019 Legal Department since early 2016. Scott is a member of the Board of Directors of BSA | The Software Alliance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/enterprise-cloud-service","text":"Enterprise Cloud Service | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWEnterprise Cloud ServiceA massively scalable and secure multi-cloud service running millions of machines every day\nGet startedSchedule a demoOverviewYour JourneyWhat You GetBenefitsGet StartedEnterprise Cloud Service provides native security, simple organization-wide administration, and automation at scale for the Unified Data Analytics Platform across multiple clouds.\nMicrosoft AzureLearn moreAWSLearn moreGoogle CloudLearn moreAlibaba Cloud\nLearn moreSetup, secure, manage and scale your data platform effortlesslySetupEffortlessly integrate with your cloud security, identity provider, data storage, databases, warehouses, catalogs, streaming and ML services.SecureExtend existing controls to protect your data while creating compliant, private and isolated analytics environments for your users.ManageEasily set policies to administer users, control budget, and manage infrastructure. Audit all activities and know who is accessing what.ScaleProgrammatically add thousands of users across hundreds of teams with the right access controls and team workspaces.\nWhat You GetPlatform SecurityGive all your users the right access to the right data with comprehensive audit trails by using your existing cloud security policies and identity management system to create compliant, private, and isolated workspaces.\u00a0Learn more about Platform Security.360\u00b0 AdministrationQuickly spin up and down collaborative workspaces for any project while being equipped with the right tools to manage user access, control spend, audit usage, and analyze activity across every workspace, all while seamlessly enforcing user and data governance.\u00a0Learn more about 360\u00b0 Administration.Elastic ScalabilityUse fully-configured data environments and API\u2019s to quickly take initiatives from development to production. Once in production, data teams can use on-demand autoscaling to optimize performance and reduce down time of data pipelines and ML models in production by efficiently matching resources to demand.\u00a0Learn more about Elastic Scalability.Multi-cloud ManagementSecurely integrate a single platform into each cloud to enable your data teams to do data analytics and machine learning without asking your users to learn cloud-specific tools and processes. Learn more about Databricks for\u00a0Microsoft Azure,\u00a0Amazon Web Services\u00a0and\u00a0Google Cloud.\nBenefitsFor Security AnalystsKeep your data where it is and get the tools you need to extend your existing security policies rather than creating new ones.For IT AdministratorsSet policies for various teams and bill departments with chargebacks. Get enterprise-wide visibility and receive notifications on policy violations.For Cloud ArchitectsArchitect a multi-cloud data and analytics solution by seamlessly integrating AWS and Azure services you are already familiar with.For DevOpsVersion control, track source code and automate your CI\/CD pipelines. Deploy and monitor production workloads for downtime and performance.\nReady to get started?Sign up for your free accountSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/burberry","text":"Burberry keeps standing out with Databricks and Labelbox | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYCatching the eye with bold fashions10Head count saved by implementing Labelbox rather than building in-house4Years of continually decreasing total cost of ownership (TCO) with Databricks70%Improvement in time savings for generating insights from images INDUSTRY: Retail and consumer goods SOLUTION: Advertising effectiveness PLATFORM USE CASE: Lakehouse,Delta Lake,data science,machine learning PARTNERS: Labelbox CLOUD: AWS\u201cWith Databricks Lakehouse Platform and Labelbox, we\u2019re able to realize our full ambition of creatively led, data-driven content creation. Labelbox continually gives our team insights on how to optimize our campaigns. And Databricks helps us maintain an efficient, sector-leading analytics capability in the cloud.\u201d\n\u2014 Ben Halsall, Analytics Technology Director, BurberryBurberry is a British luxury brand, headquartered in London. As they market the company\u2019s daring apparel, Burberry\u2019s stakeholders search for the exact combinations of images that will capture the imagination, command attention and win sales. Seeking an efficient way to annotate its thousands of highly specific marketing assets, Burberry implemented Labelbox within its Databricks Lakehouse Platform environment. Image annotation projects that used to take months now take hours, and marketing team members now have access to powerful content insights without asking for help from data scientists. Meanwhile, Databricks Lakehouse Platform continues to give Burberry a total lower cost of ownership than the company\u2019s original business case projected.Curating data threatens to become a marketing bottleneckWith a catalog of bold, high-fashion apparel, Burberry uses thousands of images from multiple sources in its marketing campaigns. The company must classify these valuable assets precisely so that it can use them effectively in its campaigns to drive the right action by the right audience.\u201cWe work with high-volume unstructured data sets to train our object detection and classification models,\u201d explained Harry Collings, Data Science Manager at Burberry. \u201cIt\u2019s simply not feasible to identify and label all those images manually. And because our image recognition models must identify highly specific products, we eventually realized we needed a dedicated solution that could work precisely while taking the manual effort out of the process.\u201dTo that end, Burberry recently began looking for a solution that would provide the technology to improve the data for training its models quickly and easily. The company hoped to be able to produce labels for thousands of images and place them seamlessly into a model development pipeline where they could be conveniently reused. Burberry first tried using an open source tool designed for image annotation. The application worked, but with serious drawbacks.\u201cOur open source tool lacked a proper interface that could be read from our data sources,\u201d Collings recalled. \u201cAll the images had to be stored locally on a data scientist\u2019s machine, which was not ideal for a company of our size. To label, say, 1,000 images would take someone two hours \u2014 and they could only save their progress in a JSON file. We knew it was time to look for a more robust commercial solution.\u201dLabelbox and Databricks deliver insights that drive smarter marketing decisionsAs Burberry evaluated potential image annotation solutions, the company favored platforms that would integrate well with its Databricks implementation. Burberry was already experiencing the benefits of having a single, unified analytics platform for all its stakeholders.\u201cWhen we first went live on Databricks Lakehouse Platform, our collaboration skyrocketed among data engineers, analysts and business users,\u201d said Ben Halsall, Analytics Technology Director at Burberry. \u201cTeams could easily interact with each other through notebooks and share ownership of jobs. With the lakehouse, we broke free from the limitations of traditional data warehouses. Suddenly, our analysts could take any data set \u2014 structured or unstructured \u2014 and start deriving business value from it right away.\u201dBurberry began evaluating Labelbox in part because of its tight integration with Databricks. The company soon discovered that Labelbox offered a far more customer-centric purchase process than its competitors.\u201cThe Labelbox team immediately spoke to us in terms that were relevant to luxury retail like they had really done their homework,\u201d said Halsall. \u201cThe fact that Labelbox understood our needs so well made us very eager to spin up a proof of concept. We were very impressed with the responsiveness and support they provided early on.\u201dGetting up and running with Labelbox was easy for Burberry \u2014 and the solution quickly proved it could meet Burberry\u2019s needs. \u201cThe lightbulb moment was when we saw how easily we could import our images to Labelbox from our Amazon S3 bucket via API,\u201d reported Collings.Once Burberry had officially selected Labelbox, Halsall and his team connected Labelbox to the company\u2019s core virtual private cloud and S3. They then built a smaller integration that delivers most of their master assets into S3. The team now treats images just like any other data set within its Databricks Lakehouse Platform. The solution was up and running within a month for DS team members \u2014 and following internal demonstrations, business and marketing users have also been onboarded expediently.\u201cThanks to Labelbox and Databricks, stakeholders across our business can upload images and put them against pretrained models that help them predict what kind of engagement these images will get in upcoming campaigns, based on models of previous campaigns,\u201d explained Collings. \u201cStakeholders can see a ranking of the images they\u2019ve uploaded and gain insights that help them make better decisions for the current marketing campaign.\u201dGenerating two months of insights in just two hoursBefore Burberry implemented Labelbox, generating insights on images was a task that took two months and involved hands-on work by the data science team. Today, it\u2019s a two-hour self-service process on Labelbox \u2014 and faster time to insight is translating to better decisions.\u201cWe\u2019re not only helping our stakeholders choose the best images to use in campaigns but also tracking the revenues generated by the emails they send,\u201d said Collings. \u201cThis information influences each batch of imagery we produce and leads to continuous improvement in our marketing programs.\u201dWithout Labelbox, Burberry simply wouldn\u2019t have had the in-house resources to build a product that could annotate a massive volume of images so efficiently while finding edge cases that boost model performance. \u201cI would have had to ask for a 10-person team just to build a product that would let us view all our imagery, let alone generate insights on it,\u201d Collings remarked. \u201cIn our day-to-day workflow, Labelbox saves us countless hours while delivering a tremendous amount of value.\u201dMeanwhile, Burberry\u2019s Databricks Lakehouse Platform continues to exceed the company\u2019s expectations. When Burberry originally built a business case for Databricks against its previous cloud platform, the company expected comparable performance. Since then, Databricks has released its Photon engine, cluster optimizations and other enhancements.\u201cWhen we look at performance over a five-year period, the relentless product road map of technology innovation in Databricks Lakehouse Platform has meant our cloud costs are actually decreasing, despite growing our user community,\u201d said Halsall. \u201cWe achieved parity in year one and have reduced the total cost of ownership since then while still providing an improved experience for our engineers, analysts and data scientists. Databricks allows us to take on any analytical challenge with confidence.\u201dAs Burberry continues to ramp up its marketing programs and ingest further data, the company will rely on Databricks Unity Catalog to help it keep data secure and comply with data privacy regulations. Burberry also appreciates that Databricks and Labelbox price their solutions aligned to business value.\u201cDatabricks and Labelbox charge us based on consumption of resources rather than number of users,\u201d concluded Collings. \u201cThat model aligns more closely with the value we\u2019re getting from these solutions and gives us a better idea of what to expect as we grow. We\u2019re extremely confident in the partners we\u2019ve chosen to take us forward.\u201dReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aikaterini-kalou\/#","text":"Aikaterini Kalou - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAikaterini KalouPrincipal Data Scientist at CitrixBack to speakersAikaterini Kalou is a Principal Data Scientist with nine years of solid experience in successfully leading complex data-driven initiatives from inception to modelling and design to successful release. She has numerous achievements in leading product differentiation through machine learning and advanced analytics in various domains (networking, security and employee productivity). Aikaterini has demonstrated technical leadership of cross-functional teams and actively practicing employee growth, coaching and mentoring, along with effective communication experience up to executive level. Building up on own curiosity and solid research practice foundations obtained during PhD studies, she is a proven innovator driving intellectual property creation (numerous patents filed\/granted) and contributing to organization vision. Participating actively in Dev Conf, Tech Fair and Tech Talk events. Aikaterini is excited about leveraging the power of Analytics & Data Science at the heart of decision making in customer and enterprise world. Passionate about leading diverse teams, fostering team culture, and consistently delivering measurable results.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chris-inkpen\/#","text":"Chris Inkpen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChris InkpenSolutions architect at HoneywellBack to speakersChris Inkpen has written software now since 1987. He has a PhD in Knowledge modeling from Brighton University in the UK. He is currently working within Honeywell Building Technologies as a technical evangelist and data engineer specialist helping the scrum teams design and develop solutions using the most appropriate technological solutions.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gilad-asulin\/#","text":"Gilad Asulin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGilad AsulinBig Data Engineer Team Leader at Akamai Technologies, IncBack to speakersGilad Asulin is a Senior Big Data Team Leader at Akamai.\nHe has over 20 years of experience in development and software architecture. \nGilad specialties are Big Data, cloud security and cloud technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/privacypolicy\/","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anton-okolnychyi","text":"Anton Okolnychyi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnton OkolnychyiSoftware Engineer at AppleBack to speakersAnton is an Apache Iceberg PMC member and Apache Spark contributor at Apple. He has been working on various internals of Big Data systems for the last six years. Anton's recent focus is on building secure, efficient and reliable data lakes. Before joining Apple, he optimized and extended a proprietary distribution of Apache Spark at SAP. Anton holds a Master\u2019s degree in Computer Science from RWTH Aachen University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/angela-chu\/#","text":"Angela Chu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAngela ChuSenior Solution Architect at DatabricksBack to speakersAngela Chu has turned data into information for more than 25 years, the last three have been spent as a Solutions Architect and Streaming Subject Matter Expert at Databricks. She enjoys learning about different technologies and solving complex problems with it, and then sharing her learnings with my customers and peers. When she is not having fun with technology, she is spending time with my family and traveling to different countries so her kids can experience the amazing cultures from around the world.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks VenturesInvesting in the future of data, analytics and AI\nDatabricks Ventures invests in innovative companies that share our view of the future for data, analytics and AI. Our inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.Portfolio company benefitsExclusive insight into the product roadmap and support for building deep technical integrationsGuidance and best practices from the network of Databricks mentorsBroader reach by partnering with Databricks go-to-market programsLakehouse Fund investment\nfocusA shared vision to build the future of data, analytics and AI on the lakehouse architectureInvestments in early to growth-stage companies in partnership with a lead investorProjects and entrepreneurs that share Databricks\u2019 commitment to open source and building on open platforms, much like the Databricks LakehouseOur PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\nLearn moreArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\nLearn moredbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\nLearn moreHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.Learn moreThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.Learn moreThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.Learn moreLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.Learn moreMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.Learn morePerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.Learn moreRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.Learn moreTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.Learn moreFAQsWhy partner with Databricks Ventures?\nDepending on the size and stage of the investment, Databricks will provide unique access to product roadmap direction, technical integration support, and go-to-market support; access to Databricks mentors for guidance and best practices; and exposure in Databricks\u2019 global go-to-market programs, including our Data + AI Summit series.What are Databricks Ventures\u2019 investment criteria?\nWe are investing in innovative founders of private companies who share our view of the future for data and AI and are committed to extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.What stages does Databricks invest in?\nWe invest in early through growth-stage private companies within the data, analytics and AI ecosystem.Does Databricks Ventures lead investment rounds?\nNo, we do not lead rounds. Our strategy is to invest alongside a lead institutional investor.What is Databricks Ventures\u2019 typical investment size?\nDatabricks Ventures takes minority positions in rounds led by institutional VCs; typical check size varies based on stage of company and size of funding round.Does Databricks take board seats?No, Databricks does not plan to take board seats in portfolio companies.Build your startup on DatabricksDatabricks for Startups offers free credits, expert advice and go-to-market support.Learn moreProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/01\/28\/how-to-accelerate-demand-planning-from-4-5-hours-to-under-1-hour-with-azure-databricks.html","text":"How to Accelerate Supply Chain Analytics From 4.5 Hours to Under 1 Hour Using Azure Databricks - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHow to Accelerate Demand Planning From 4.5 Hours to Under 1 Hour With Azure Databricksby Adam Wasserman and Clinton FordJanuary 28, 2021 in Engineering BlogShare this postThe importance of supply chain analyticsRapid changes in consumer purchase behavior can have a material impact on supply chain planning, inventory management, and business results. Accurate forecasts of consumer-driven demand are just the starting point for optimizing profitability and other business outcomes. Swift inventory adjustments across distribution networks are critical to ensure supply meets demand while minimizing shipping costs for consumers. In addition, consumers redeem seasonal offers, purchase add-ons and subscriptions that affect product supply and logistics planning.\nSupply chain analytics at ButcherBoxButcherBox faced extremely complex demand planning as it sought to ensure inventory with sufficient lead times, meet highly-variable customer order preferences, navigate unpredictable customer sign-ups and manage delivery logistics. It needed a predictive solution to address these challenges, adapt quickly and integrate tightly with the rest of its Azure data estate.\n\u201cThough ButcherBox was cloud-born, all our teams used spreadsheets,\u201d said Jimmy Cooper, Head of Data, ButcherBox. \u201cBecause of this, we were working with outdated data from the moment a report was published. It\u2019s a very different world now that we\u2019re working with Azure Databricks.\u201dHow ButcherBox streamlined supply chain analyticsButcherBox uses Azure Databricks to generate its Demand Plan. When Azure Data Factory (ADF) triggers the Demand Plan run, Azure Databricks processes supply chain data from Azure Data Lake, vendor data and Hive caches. New outputs are stored in a data lake, then Azure Synapse updates Demand Plan production visualizations.\n Batching\/microbatching orchestration with Azure DatabricksButcherBox leverages Azure Databricks to ingest all real-time streams of raw data from vendors, internal sources and historical data. Azure Databricks reconciles this data into item, box and distribution levels for users to view demand for the upcoming year. This data is then used for retention modeling, and pushed to Azure Synapse for historical comparison.\nApache Spark SQL in Azure Databricks is designed to be compatible with Apache Hive. ButcherBox uses Hive to cache data from CSV files and then processes the cached data in Azure Databricks, enabling Demand Plan calculation times to decrease from 4.5 hours to less than one hour. This enabled an updated Demand Plan to be available for business users every morning to aid decision-making. Ingestion of these data streams also created trustworthy datasets for other processes and activities to consume. These new tools and capabilities helped ButcherBox quickly understand and adjust to changes in member behavior, especially in the midst of he COVID-19 pandemic.\nCreate your first demand forecast using Azure DatabricksTo get started using Azure Databricks for demand forecasts, download this sample notebook and import it into your Azure Databricks workspace.\nStep 1: Load Store-Item Sales Data\nOur training dataset is five years of transactional data across ten different stores. We\u2019ll define a schema, read our data into a DataFrame and then create a temporary view for subsequent querying.\nfrom pyspark.sql.types import *\n\n# structure of the training data set\ntrain_schema = StructType([\n  StructField('date', DateType()),\n  StructField('store', IntegerType()),\n  StructField('item', IntegerType()),\n  StructField('sales', IntegerType())\n  ])\n\n# read the training file into a dataframe\ntrain = spark.read.csv(\n  '\/FileStore\/tables\/demand_forecast\/train\/train.csv', \n  header=True, \n  schema=train_schema\n  )\n\n# make the dataframe queryable as a temporary view\ntrain.createOrReplaceTempView('train')Step 2: Examine data\nAggregating the data at the month level, we can observe an identifiable annual seasonality pattern, which grows over time. We can optionally restructure our query to look for other patterns such as weekly seasonality and overall sales growth.\nStep 3: Assemble historical dataset\nFrom our previous loaded data, we can build a Pandas DataFrame by querying the \u201ctrain\u201d temporary view and then remove any missing values.\n# query to aggregate data to date (ds) level\nsql_statement = '''\n  SELECT\n    CAST(date as date) as ds,\n    sales as y\n  FROM train\n  WHERE store=1 AND item=1\n  ORDER BY ds\n  '''\n\n# assemble dataset in Pandas dataframe\nhistory_pd = spark.sql(sql_statement).toPandas()\n\n# drop any missing records\nhistory_pd = history_pd.dropna()\nStep 4: Build modelBased on exploration of the data, we will want to set model parameters in accordance with the observed growth and seasonal patterns. As such, we opted for a linear growth pattern and enabled the evaluation of weekly and yearly seasonal patterns. Once our model parameters are set, we can easily fit the model to the historical, cleansed data.\n# set model parameters\nmodel = Prophet(\n  interval_width=0.95,\n  growth='linear',\n  daily_seasonality=False,\n  weekly_seasonality=True,\n  yearly_seasonality=True,\n  seasonality_mode='multiplicative'\n  )\n\n# fit the model to historical data\nmodel.fit(history_pd)\nStep 5: Use a trained model to build a 90-day forecastSince our model is trained, we can use it to build a forecast similar to the one ButcherBox uses in their Demand Plan. This can be done quickly using historical data as shown below.\n# define a dataset including both historical dates & 90-days beyond the last available date\nfuture_pd = model.make_future_dataframe(\n  periods=90, \n  freq='d', \n  include_history=True\n  )\n\n# predict over the dataset\nforecast_pd = model.predict(future_pd)\n\ndisplay(forecast_pd)\n\nOnce we predict over the future dataset, we can produce general and seasonal trends in our model as graphs (also shown below).\ntrends_fig = model.plot_components(forecast_pd)\ndisplay(trends_fig)\nLearn more by joining an Azure Databricks event and get started right away with this 3-part training series.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2023\/03\/29\/security-operations-data-lakehouse-hunters-soc-platform-now-available.html","text":"Security Operations on the Data Lakehouse: Hunters SOC Platform is now available for Databricks customers - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorSecurity Operations on the Data Lakehouse: Hunters SOC Platform is now available for Databricks customersby Lipyeow Lim and Guy YasoorMarch 27, 2023 in Platform BlogShare this postCybersecurity is a big data problem: The growing volume and complexity of data flowing in and out of enterprises have created new cybersecurity challenges. Existing SIEM solutions cannot scale with the velocity of data growth without taxing security budgets and draining existing resources.Today, cybersecurity company Hunters is announcing the availability of its SOC Platform for Databricks customers. For the first time, Databricks customers will be able to attain an end-to-end, security operations platform on their own Databricks Lakehouse Platform deployments, while keeping the flexibility of owning all the data and having the power to build their own additional security analytics on the Lakehouse.Hunters SOC Platform is a modern SIEM alternative that ingests, normalizes and analyzes data from all security data sources of an organization, including endpoint telemetry, network traffic, identity management, and cloud infrastructure. Not only does Hunters provide a wider variety of security-related data integrations, but the platform also identifies threats in real-time across the attack surface and provides security teams prioritized incidents to handle, reducing the time needed to contain and remediate threats to the organization.What can Databricks customers do with Hunters to create even more value?Build a Security Data LakeOne of the biggest burdens of security teams today is managing the ingestion of terabytes of data from dozens of security products. Hunters eases this process with a state-of-the-art engine that provides scalable ingestion, monitoring and optimization. Moreover, it comes prebuilt with a large library of off-the-shelf integrations that can be set up in minutes.Hunters SOC Platform ingests and performs the ETL of all security-related data into the customer's Databricks Lakehouse using the customer's cloud storage: the customer retains ownership of all the security data. The Hunters ETL follows the Databricks' Medallion Architecture model storing the raw data and also normalizing the data into a unified schema that will facilitate further analysis. While Hunters already provides a rich set of analytical capabilities, customers with advanced cybersecurity analytics teams can augment the Hunters capabilities by leveraging Databricks Data Science and Machine Learning capabilities and the partner technologies in the Databricks ecosystem. For example, many customers have AI\/ML models for detecting threats that are highly specific and customized to their specific organizational context (eg. insider threats). Such detections are so specific that it does not make sense for a vendor like Hunters to build into their product. Hunters provides the flexibility for customers to leverage the Databricks lakehouse for such use cases.Detect and Investigate IncidentsHunters provides a library of hundreds of built-in detection rules that cover the majority of the threat landscape, mapped onto a common industry framework (the MITRE ATT&CK). This allows customers to visualize coverage and understand their security gaps. All detection rules are pre-verified on real-world customer data to minimize false positives and excessive alerting. The detection rules are deployed directly to all customer tenants without requiring any action or tweaking, thereby automatically reducing the cybersecurity risk with little operational overhead.Each alert also passes through an investigation engine, where it is automatically enriched with contextual information from various sources, and sophisticated dynamic scoring is applied to it to reduce alert fatigue. Not all signals from the same detection logic require the same urgency. For example, alerts that involve sensitive assets (e.g., C-level, domain servers, etc.) are prioritized, and risk for known benign behaviors is lowered (e.g., an executable IoC signed by Microsoft). Addressing the priority of alerts or incidents with dynamic scoring helps security teams manage their SOC workloads more efficiently.When the SOC analyst gets to an alert, all contextual information is provided in a single pane of glass to expedite triage and investigation. The contextual information goes beyond 'simple' enrichment of IP addresses with threat intelligence feeds, to deep correlation such as linking the user name in a CrowdStrike EDR alert with login records from the Okta authentication logs. Hunters' deep correlation capability is powered by a graph correlation engine: Alerts across entities and attack surfaces are automatically correlated on a graph. This graph correlation capability enables Hunters to highlight high-fidelity threat activity and provides analysts the flexibility to leverage low-fidelity signals that are often overlooked without generating more noise.For incidents requiring investigations from multiple organizations including third party service providers and\/or government agencies, Databricks provides cleanrooms where collaborating investigators can jointly investigate an incident using the relevant subsets of data and the custom analytics that can be proprietary to different organizations.Search & Incident ResponseHaving all of your security data stored in a modern data lake has great advantages for incident responders, and anyone who wants to gain insights on massive amounts of data.Using Hunters and Databricks, customers can not only store petabytes of data, but also make use of them in their day-to-day investigations and in their most critical incidents. Some capabilities that support this are the following:IOC Search: Purpose-built search capability, allows responders to search all organizational data ingested by Hunters that resides on the Lakehouse for IOCs (IP, domain, hash) in seconds within the SOC Platform itself.Entity Search: Makes it easy to see all information about an entity in the environment in a centralized place. For example, from one suspicious login alert, customers can easily pivot to see the latest logins of the user in question across all endpoints, cloud infrastructure, and SaaS providers. In the same user interface, a responder can observe which alerts a user in question was involved in, and what is their role in the organization. Entity related views create huge efficiencies and productivity for security teams.Raw data access: all of your security data is available for you to dive into as you see fit, both from within the Hunters console, and from your familiar Databricks interface. You can run queries on months of data to find that needle in a haystack, create operational dashboards that help expedite investigations, and run your own AI\/ML models.The openness of the Hunters and Databricks integration encourages security teams to innovate in their fight against cyber criminals. The Hunters SOC Platform not only helps security teams to do their day-to-day job more efficiently and effectively, but also provides all the data in a Databricks lakehouse where they can experiment, create, and test their own security analytics and AI\/ML models and contribute these back to the cybersecurity community at large. Cybersecurity is a team sport. Let a thousand flowers bloom.If you want to try Hunters out on your Databricks Lakehouse, please request a demo!Try Databricks for freeGet StartedRelated postsCybersecurity in the Era of Multiple Clouds and RegionsAugust 30, 2022 by Zafer Bilaloglu and Lipyeow Lim in Product\nIn 2021, more than three quarters of all enterprises have infrastructure in multiple clouds. This trend shows no signs of slowdown with hybrid...\nCybersecurity in ManufacturingMarch 1, 2023 by Lipyeow Lim and Bala Amavasai in Manufacturing\nWith the increasing push toward smart manufacturing, cybersecurity has taken center stage in the operational risk profile of manufacturers. A study by Deloitte...\nAnalyzing Okta Logs With Databricks Lakehouse Platform to Detect Unusual ActivityApril 7, 2022 by Arun Pamulapati in Product\nWith the recent social media reports of an Okta incident through a third party contractor, security teams ran to their logs and asked...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/p\/whitepaper\/the-hidden-value-of-hadoop-migration-aws","text":"Migration Guide: Hadoop to Databricks | DatabricksTechnical GuideMigration Guide: Hadoop to DatabricksBreak free from Hadoop and boost data valueThe decision\u2019s been made: Farewell, Hadoop. It\u2019s time to unlock the full potential of data, empower data teams to innovate faster on data science and AI\/ML use cases, and realize higher ROI. It\u2019s time to modernize.Most Hadoop users, when planning the future of their data strategy, are frustrated with their existing Hadoop platforms due to the inability to scale data science and AI\/ML capabilities, the high cost of operations and poor performance.Customers with legacy Hadoop environments find themselves gearing up for massive modernization initiatives to get to the cloud. If not planned properly, the process can be overwhelming and complex. This comprehensive self-guided playbook will assist you step-by-step with migrating from Hadoop to the Databricks Lakehouse Platform.Combining the best elements of data lakes and data warehouses, the Databricks Lakehouse Platform delivers the reliability, strong governance and performance of data warehouses with the openness, flexibility and machine learning support of data lakes.In this technical guide, you will learn how to:Get started with platform administrationJump into application deployment, testing and development \u2014 with code snippets and sample notebooksExplore the path forward after migrationAccelerate your data science and ML\/AI workloadsGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ellie-hajarian","text":"Ellie Hajarian - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEllie HajarianSnr IT Manager at TD BankBack to speakersDriven Information Technologist with a strategic mindset in delivering superior solutions. A passionate problem solver who thrives in challenging, fast-paced IT organizations for over 20 years demonstrating solid knowledge in delivery excellence, risk management and emerging technologies. \nAn advocate for diversity and inclusion, leading the 'Women In Leadership' Committee and a member of 'Girls in STEM' committee at my current workplace.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mostafa-mokhtar","text":"Mostafa Mokhtar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMostafa MokhtarPrincipal Software Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jonathan-neo\/#","text":"Jonathan Neo - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJonathan NeoData Engineer at CanvaBack to speakersJonathan is a Data Engineer at Canva where he is building data platforms that scale for petabytes of data and hundreds of internal users. Prior to Canva, he has spent the last 5 years building a dozen data platforms for ASX-listed enterprises, and startups. Jonathan is also the Founder of Data Engineer Camp, a 16 week intensive bootcamp to cultivate the next generation of data engineers, with students working at companies like Microsoft, Tencent, and Fidelity International.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suze-howse","text":"Suze Howse - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuze HowseHead of Enterprise Data at Marks and SpencerBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kieran-taylor","text":"Kieran Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKieran TaylorSenior Software Engineer II at InstacartBack to speakersKieran Taylor is a senior software engineer with Instacart. He works on the Data Platform team to build the data infrastructure used by data analysts, scientists and pipeline engineers that powers Instacart. Kieran is passionate about functional programming, data intensive applications and the unbounded use cases that are still to be unlocked in the space. Outside of work you can find Kieran travelling, playing tennis or beach volleyball in Santa Monica.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/oliver-dykstra\/#","text":"Oliver Dykstra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingOliver DykstraData Engineer at Texas RangersBack to speakersOliver Dykstra is a data engineer with the Texas Rangers. He builds scalable, future-proof data pipelines to support\nanalytics and machine learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/pricing","text":"Prezzi di Databricks | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPromozione SQL a lungo termine - Risparmio del 40% e oltre Approfitta della promozione di 15 mesi su Serverless SQL e sul nuovissimo SQL ProMaggiori informazioniPrezzi di DatabricksUn'unica piattaforma semplice per unificare tutti i carichi di lavoro di dati, analisi e AI su tutti i tuoi cloud preferitiComincia la prova gratuitaCome funziona il listino prezzi di Databricks?Pagamento a consumoDatabricks offre un approccio \"a consumo\" senza costi iniziali. Si pagano solo i prodotti utilizzati e conteggiati al secondo.Maggior risparmio con gli sconti per livelli di utilizzo garantitiDatabricks aiuta a ridurre i costi con sconti per i clienti che garantiscono determinati livelli di utilizzo. Maggiore \u00e8 l'impegno a utilizzare le risorse, maggiore \u00e8 lo sconto rispetto all'utilizzo a consumo. Si possono assumere impegni di spesa su diversi cloud. Contattaci per maggiori informazioni.Esplora i prodottiFlussi di lavoro e streamingJobsStarting at $0.07 \/ DBUEsegui pipeline di data engineering per costruire i data lake e gestisci i dati su larga scalaMaggiori informazioniFlussi di lavoro e streaming Delta Live TablesStarting at $0.20 \/ DBUCostruisci facilmente pipeline ETL in streaming o in batch di alta qualit\u00e0 usando Python o SQL con la DLT Edition pi\u00f9 adatta al tuo carico di lavoroMaggiori informazioniData warehouseDatabricks SQLStarting at $0.22 \/ DBUEsegui query SQL per reportistica, analisi e visualizzazione BI per ricavare tempestivamente informazioni approfondite da data lake. Disponibile nelle versioni Classic and Serverless (gestito) Compute.Maggiori informazioniData science e machine learningPer tutti gli usiStarting at $0.40 \/ DBUEsegui carichi di lavoro interattivi per data science e machine learning. Ideale anche per data engineering, BI e analisi di datiMaggiori informazioniData science e machine learningInferenza serverless in tempo realeStarting at $0.07 \/ DBURealizza previsioni dal vivo dentro app e siti web.\nMaggiori informazioniPiattaforma e moduli aggiuntivi (add-on) di DatabricksPiattaforma e moduli aggiuntivi (add-on) di DatabricksLivelli di piattaforma: funzionalit\u00e0 trasversali alla piattaforma che offrono il giusto livello di gestione, governance e sicurezza per eseguire tutti i carichi di lavoro, dai pi\u00f9 semplici a quelli critici\nAdd-on di piattaforma: migliorie trasversali al prodotto per la piattaforma Databricks che aggiungono funzionalit\u00e0 di gestione, governance e sicurezzaMaggiori informazioniProva Databricks gratisComincia gratisProgramma una demoDomande frequentiChe cosa comprende la prova gratuita?La prova gratuita di 14 giorni offre:Un ambiente collaborativo nel quale i team di gestione dei dati possono costruire soluzioni insiemeNotebook interattivi per utilizzare Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn e altroAttenzione: il fornitore di servizi cloud addebiter\u00e0 i costi delle risorse (ad es. istanze di calcolo) utilizzate con il tuo account durante la prova gratuitaChe cosa succede al termine della prova gratuita?Al termine della prova gratuita, viene attivato automaticamente l'abbonamento al piano utilizzato durante il periodo di prova. L'abbonamento pu\u00f2 essere disdetto in qualsiasi momento.Il prezzo \u00e8 basato sull'utilizzo o sul volume di storage?I prezzi di Databricks sono basati sull'utilizzo delle risorse di calcolo. I costi di storage, networking e servizi correlati varieranno in base ai servizi scelti e al fornitore di servizi in cloud.Che cos'\u00e8 una DBU?Un'unit\u00e0 di Databricks (DBU) \u00e8 un'unit\u00e0 standard di potenza di elaborazione sulla Databricks Lakehouse Platform, utilizzata a scopo di misurazione e definizione dei prezzi. Il numero di DBU consumate da un carico di lavoro dipende dalle metriche di elaborazione, che possono comprendere le risorse di calcolo utilizzate e la quantit\u00e0 di dati elaborati. I prezzi sono uguali in tutte le regioni?I prezzi di Databricks e i prezzi per l'infrastruttura cloud possono variare in base all'area geografica e al fornitore di servizi cloud. Per maggiori dettagli, consulta il listino prezzi di Databricks per ciascun prodottoDatabricks \u00e8 conveniente come altri servizi in cloud o soluzioni open-source?I prezzi dei prodotti Databricks sono studiati per assicurare al cliente costi di gestione totali (TCO) allettanti per i loro carichi di lavoro. Per stimare i risparmi offerti da Databricks, \u00e8 importante considerare gli aspetti chiave di soluzioni alternative, come il tasso di completamento dei lavori, la durata, il lavoro manuale e le risorse richiesti da ogni lavoro. Per stimare con precisione il risparmio, raccomandiamo di confrontare direttamente i risultati nel contesto di un'implementazione proof-of-concept. Ad esempio, scopri l'accelerazione ottenuta da questo cliente e i risultati dei test comparativi di questo cliente. Contattaci per cominciare.Che cos'\u00e8 Databricks Community Edition?Databricks Community Edition \u00e8 una piattaforma gratuita con funzionalit\u00e0 limitate progettata per chiunque voglia imparare a utilizzare Spark. Registrati qui.Come avviene la fatturazione?Per default, i costi verranno addebitati mensilmente sulla carta di credito calcolando i secondi di utilizzo effettivi. Contattaci per conoscere altre opzioni di pagamento, ad esempio fatturazione o abbonamento annuale.Fornite assistenza tecnica?Forniamo anche assistenza tecnica. Ti invitiamo anche a consultare la documentazione tecnica. Contattaci per maggiori informazioni.ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=Homepage-BottomCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rajesh-iyer\/#","text":"Rajesh Iyer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRajesh IyerVice President Financial Services Insights & Data at CapgeminiBack to speakersRajesh is the head of AI COE for Financial Services globally and drives growth in the Machine Learning and Artificial Intelligence Practice, as part of the Insights & Data Global Service Line at Capgemini.\u00a0He\u00a0has 27 years of Financial Services Data Sciences and AI\/ML experience across multiple domains, such as Risk, Distribution, Operations and Marketing, but working mostly with very large financial services institutions across the Banking and Capital Markets and Insurance verticals.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/company\/board-of-directors","text":"Conseil d'administration Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLeadershipAvec une vision \u00e0 long terme, notre \u00e9quipe de direction s'appuie sur des d\u00e9cennies d'exp\u00e9rience pour mettre en place une nouvelle voie pour les donn\u00e9es et l'IAD\u00e9couvrez notre \u00e9quipe\u00c9quipe de directionFoundersConseil d'administrationIon StoicaCofondateur et pr\u00e9sident ex\u00e9cutifBen HorowitzCofondateur d'Andreessen HorowitzElena DonioMembre du conseil d'administrationAli GhodsiCofondateur et directeur g\u00e9n\u00e9ralPete SonsiniGeneral Partner chez New Enterprise AssociatesJonathan ChadwickMembre du conseil d'administrationMatei ZahariaCofondateur et Chief TechnologistScott ShenkerProfesseur d'informatique chez UC BerkeleyProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yuki-saito","text":"Yuki Saito - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYuki SaitoTechnical Evangelist at NTT DATA CorporationBack to speakersYuki Saito is a cloud architect and data engineer at NTT DATA. He has a decade of experience in system development related to data management and utilization. He promotes the use of Databricks to accelerate data and AI democratization in Japanese companies.\nYuki's strength is his understanding of a wide range of technologies. In particular, he was certified as a Databricks Solutions Architect Champion for the first time in Japan. In addition, he is certified as a Japan AWS Top Engineer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos","text":"Databricks Product & Partner Demo Hub - Solution Accelerator Demo | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDemo HubGet a firsthand look at Databricks from the practitioner\u2019s perspective with these simple on-demand videos. Each of the demos below is paired with related materials \u2014 including notebooks, videos and eBooks \u2014 so that you can try it out for yourself on Databricks.Get started for freeProduct demosDatabricks PlatformIn this demo, we walk through a high-level overview of the Databricks Lakehouse Platform, including discussion of how open source projects, such as Apache Spark\u2122, Delta Lake, MLflow and Koalas, fit into the Databricks ecosystem.Learn moreDatabricks SQLDatabricks WorkflowsUnity CatalogData Science and Machine LearningDelta SharingDelta LakeDelta Live TablesDelta Lake Data Integration (Auto Loader and COPY INTO)Partner demosAzure Databricks Cloud IntegrationThe Azure Databricks Lakehouse Platform gives you the best of data lakes and data warehouses, on a simple, open and collaborative platform that securely integrates with your existing Azure services. In this demo, we cover several of the most common Azure Databricks integrations, including Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Azure IoT Hub, Azure Synapse Analytics, Power BI and more.Learn moreDatabricks on AWS Cloud IntegrationDeploying Databricks on Google CloudPartner ConnectIndustry SolutionsFrom idea to proof of concept in as little as two weeksDatabricks Solution Accelerators are purpose-built guides \u2014 fully functional notebooks and best practices \u2014 that speed up results. Databricks customers are saving hours of discovery, design, development and testing, with many going from idea to proof of concept (PoC) in as little as two weeks.Explore AcceleratorsCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet StartedProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeffrey-parkinson","text":"Jeffrey Parkinson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey ParkinsonVP, Core Data Engineering at Northwestern MutualBack to speakersJeff Parkinson joined Northwestern Mutual nine months ago as the Vice President of Core Data Engineering, overseeing all enterprise data solutions across both analytical and operational concerns and creating their first ML Ops function across Data Science and Data Engineering.\nPrior to Northwestern Mutual, Jeff spent 13 years at Dow Jones running the Data Engineering function and creating world-class data platforms across Martech, Fintech and B2B Analytics. He has over 30 years of experience spanning data & software engineering, machine learning, data science and sales enablement.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/young-bang","text":"Young Bang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and Technology at U.S. ArmyBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aayush-patel\/#","text":"Aayush Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAayush PatelData & Platform Engineer at SkywatchBack to speakersAayush is a data and platform engineer at Skywatch, where he focuses on developing robust data platforms and scalable data products. He specializes in creating high-fidelity data systems and is currently working on building a collaborative enterprise solution for large organizations to purchase and share earth observation data. Aayush has previously built data frameworks, such as a no-code reporting platform that leverages a centralized metrics catalog to generate uniform data reports.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeffrey-parkinson\/#","text":"Jeffrey Parkinson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey ParkinsonVP, Core Data Engineering at Northwestern MutualBack to speakersJeff Parkinson joined Northwestern Mutual nine months ago as the Vice President of Core Data Engineering, overseeing all enterprise data solutions across both analytical and operational concerns and creating their first ML Ops function across Data Science and Data Engineering.\nPrior to Northwestern Mutual, Jeff spent 13 years at Dow Jones running the Data Engineering function and creating world-class data platforms across Martech, Fintech and B2B Analytics. He has over 30 years of experience spanning data & software engineering, machine learning, data science and sales enablement.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/04\/13\/identifying-financial-fraud-with-geospatial-clustering.html","text":"Fighting Credit Card Fraud Through AI and Geospatial Analysis - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIdentifying Financial Fraud With Geospatial Clusteringby Antoine AmendApril 13, 2021 in Engineering BlogShare this postCheck out the solution accelerator for the accompanying notebooks\u00a0For most financial service institutions (FSI), fraud prevention often implies a complex ecosystem made of various components \u2013- a mixture of traditional rules-based controls and artificial intelligence (AI) and a patchwork of on-premises systems, proprietary frameworks and open source cloud technologies. Combined with strict regulatory requirements (such as model explainability), high governance frameworks, low latency and high availability (sub second response time for card transactions), these systems are costly to operate, hard to maintain and even harder to adapt to customers changing behaviors and fraudsters alike. Similar to risk management, a modern fraud prevention strategy must be agile at its core and combines a collaborative data-centered operating model with an established delivery strategy of code, data and machine learning (ML) such as DataOps, DevOps and MLOps. In a previous solution accelerator, we addressed the problem of combining rules with AI in a common orchestration framework powered by MLflow.As consumers become more digitally engaged, large FSIs often have access to real-time GPS coordinates of every purchase made by their customers. With around 40 billion card transactions processed in the US every year, retail banks have a lot of data they can leverage to better understand transaction behaviors for customers opting into GPS-enabled banking applications. Given the data volume and complexity, it often requires access to a large amount of compute resources and cutting-edge libraries to run geospatial analytics that do not \"fit well\" within a traditional data warehouse and relational database paradigm.Geospatial clustering to identify customer spending behaviorsIn this solution centered around geospatial analytics, we show how the Databricks Lakehouse Platform enables organizations to better understand customers spending behaviors in terms of both who they are and how they bank. This is not a one-size-fits-all based model, but truly personalized AI. After all, identifying abnormal patterns can only be achieved with the ability to first understand what normal behaviour is, and doing so for millions of customers is a challenge that requires data and AI combined into one platform.Geospatial clustering as part of a fraud prevention strategyAs part of this real-world solution, we are releasing a new open source geospatial library, GEOSCAN, to detect geospatial behaviors at massive scale, track customers patterns over time and detect anomalous card transactions. Finally, we demonstrate how organizations can surface anomalies from an analytics environment to an online data store (ODS) with tight SLA requirements following a Lambda-like infrastructure underpinned by Delta Lake, Apache Spark and MLflow.Geospatial clustering of card transactionsDBSCAN (density-based spatial clustering of applications with noise) is a common ML technique used to group points that are closely packed together. Compared to other clustering methodologies, it doesn't require you to indicate the number of clusters beforehand, can detect clusters of varying shapes and sizes and effectively finds outliers that don't belong in any dense area. This makes it a great candidate for geospatial analysis of credit card transactions and potentially fraudulent activities. However, it comes with a serious price tag: DBSCAN requires all points to be compared to every other point to find dense neighbourhoods, which is a significant limitation given the scale large FSIs operate at. As we could not find a viable solution that can scale to millions of customers or more than a few hundreds of thousands of records, we created our own open source AI library: GEOSCAN. Available with both Scala and Python APIs, GEOSCAN is our implementation of DBSCAN algorithm for geospatial clustering at big data scale.Density based clustering (DBSCAN)Leveraging Uber\u2019s H3 library to only group points we know are in close vicinity (sharing at least one H3 polygon) and relying on GraphX API, this can detect dense areas at massive scale, understand user spending behaviors and detect anomalous transactions in near real time.In order to validate our framework, we created a synthetic dataset of credit card transactions in the NYC area. Our dataset only contains a tokenized value for users, a geospatial coordinate (as latitude and longitude), a timestamp and a transaction amount. In real life, the same should also contain additional transaction context (such as merchant narrative or MCC code) and often has been enriched with clean brand information (the latter will be addressed as part of a future Databricks Solution Accelerator). In this demo, we will extract dense clusters that correspond to areas with higher transaction activities such as high streets and shopping malls.There are two modes supported by our GEOSCAN implementation, distributed and pseudo distributed.For distributed, our framework detects clusters from an entire dataframe (i.e. across all our users base).For, pseudo-distributed, it retrieves clusters for a grouped predicate, hence training millions of models for millions of customers in parallel. Both modes are useful to better understand customers\u2019 shopping behaviour for a personalized fraud prevention strategy.Detecting dense shopping areasWorking fully distributed, the core of the GEOSCAN algorithm relies on GraphX to detect points having distance (expressed in meters) and neighbors > minPoints. \nfrom geoscan import Geoscan\n\ngeoscan = Geoscan() \\\n   .setLatitudeCol('latitude') \\\n   .setLongitudeCol('longitude') \\\n   .setPredictionCol('cluster') \\\n   .setEpsilon(200) \\\n   .setMinPts(20)\n\nmodel = geoscan.fit(points_df)\nclusters_df = model.transform(points_df)\nAs a strong advocate of open standard, we built GEOSCAN to support RFC7946 (aka GeoJSON) as a model output that can be processed as-is with any geospatial library (such as geopandas), GIS database (geomesa) or visualization (folium). As represented below, MLflow natively supports the use of GeoJSON as a model artifact. MLflow displaying GeoJSON file format Let\u2019s walk through an example of GEOSCAN in action. With this solution, we have programmatically extracted geographical shapes corresponding to high density of card transactions in the New York City (NYC) area. As represented above, our parameters resulted in a relatively large shape covering most of NYC. Although reducing minPts value or increasing epsilon could help refine that shape, it may certainly impact less dense areas such as Williamsburg in Brooklyn. Largely domain-specific, we explore different approaches to tune our model and improve performance in the notebooks reported at the end of this blog. Model inference and cluster tilingAs the core of GEOSCAN logic relies on the use of H3 polygons, it becomes natural to leverage the same for model inference instead of bringing in extra GIS dependencies for expensive points in polygons queries. Our approach consists in \"tiling\" our clusters with H3 hexagons that can easily be joined to our original dataframe, exploiting at best Delta Lake optimizations (such as ZORDER indexing) and offering complex geospatial queries as a form of a simple SQL operation. Tiling a geo shape with H3 hexagons Personalized clusteringWe have demonstrated how GEOSCAN can be used across our entire dataset. However, the aim was not to machine learn the shape of NYC, nor to find the best place to go shopping, but to track user spending behaviour over time and - most importantly - where transactions are the least expected to happen for a given customer, therefore requiring a personalized approach to geospatial clustering. \nfrom geoscan import GeoscanPersonalized\n\ngeoscan = GeoscanPersonalized() \\\n   .setLatitudeCol('latitude') \\\n   .setLongitudeCol('longitude') \\\n   .setPredictionCol('cluster') \\\n   .setGroupedCol('user') \\\n   .setEpsilon(500) \\\n   .setMinPts(3)\n\nmodel = geoscan.fit(points_df)\nclusters_df = model.transform(points_df)\nSimilar to our distributed approach, models can be stored and retrieved as per the standard Spark ML API. In this mode, we return a dataframe made of GeoJSON objects rather than a single file in which each card holder has an associated record capturing their spending geographical patterns. Understanding customer specific patternsIt is important to step back and reflect on the insights gained so far. As we learn more about our entire customer base (distributed approach), we could leverage this information to better understand the behaviour that is specific to each individual. If everyone were to shop at the same location, such an area would be less specific to a particular user. We can detect \"personalized\" zones as how much they overlap with common areas, better understanding our end customers and pave the way towards truly personalized banking. Detecting areas that are the most descriptive for each user is similar to detecting keywords that are more descriptive to each sentence in Natural Language processing use cases. We can use a Term Frequency \/ Inverse document frequency (TF-IDF) approach to increase the weight of user-specific locations while reducing weight around common areas. Geographical spending patterns for a given customer We suddenly have gained incredible insights about our customers' shopping behaviour. Although the core of this user\u2019s transactions are made in the Chelsea and financial district areas of NYC, what seems to better define this user are their transactions around the Plaza Hotel on the 5th avenue and Williamsburg. Given a specific user and a location, this framework can be used to better understand whether a card transaction falls within a known shopping pattern at a specific time of day or day of the week. Fraud prevention using personalized AIIn the previous section, we showed that geospatial data analysis can tell us a lot of information about customers behaviour and trends, hence a critical component to anomaly detection model in an over-hatching fraud prevention strategy. In this section, we demonstrate how to use these insights to detect suspicious behaviour in real time. More often than not, fraud detection systems run outside of an analytics environment due to the combination of data sensitivity (PII), regulatory requirements (PCI\/DSS) and model materiality (high SLAs and low latency). For these reasons, we explore multiple strategies to serve our insights either as a self-contained framework using MLflow or through a relational or NoSQL online datastore such as Redis, MongoDB, Redshift or ElastiCache, although many other solutions may be viable. Extracting anomaliesSince we have stored and indexed all of our personalized ML models as H3 polygons in a Delta table, it becomes easy to enrich each transaction with their cluster using a simple JOIN operation. In the example below, we can extract anomalies (transactions not matching any known pattern of a given user) given a specific H3 resolution (see resolution table) embedded in a user defined function. \nfrom pyspark.sql import functions as F\n\nanomalous_transactions = (\n spark\n   .read\n   .table('geospatial.transactions')\n   .withColumn('h3', to_h3('latitude', 'longitude', 10))\n   .join(tiles, ['user', 'h3'], 'left_outer')\n   .filter(F.expr('cluster IS NULL'))\nOut of half a million transactions, we extracted 81 records in less than 5 seconds. Not necessarily fraudulent, maybe not even suspicious, but these transactions did not match any of our users\u2019 \"normal\" behaviors, and as such, should be flagged as part of an over-hatching fraud prevention framework and further combined with other rules and models. In a real-life example, we should factor for time and additional transactional context. Would the same transaction happening on a Sunday afternoon or a Wednesday morning be suspicious given user characteristics we could learn? With millions of transactions and low latency requirements, it would not be realistic to join these large datasets in real time. Although we could load all clusters (their H3 tiles) in memory, we may have evaluated multiple models at different time of the days, for different segments, different transaction indicators (e.g. for different brand category or MCC codes) and for millions of consumers resulting in a complex system that requires efficient lookup strategies against millions of variables. Bloom filteringHere comes Bloom filters, an efficient probabilistic data structure that can test the existence of a given record without keeping an entire set in memory. Although Bloom filters have been around for a long time, its usage has not - sadly - been democratized beyond blurry engineering techniques such as database optimization engines and daunting execution planners (Delta engine leverages Bloom filters optimizations under the hood, among other techniques). This technique is a powerful tool worth having in a modern data science toolkit. The concept of a Bloom filter is to convert a series of records (in our case, a card transaction location as a H3 polygon) into a series of hash values, overlaying each of their byte arrays representations as vectors of 1 and 0. Testing the existence of a given record results in testing the existence of each of its bits set to 1. The memory efficiency of Bloom filters comes with a non-negligible downside in the context of fraud detection. Although Bloom filters offer a false negative rate of 0, there is a non-zero false positive rate (records we wrongly assume have been seen due to hash collision) that can be controlled by the length of our array and the number of hash functions. We will be using the pybloomfilter Python library to validate this approach, training a Bloom filter against each and every known H3 tile of every given user. Although our filter may logically contain millions of records, we would only need to physically maintain 1 byte array in memory to enable a probabilistic search, sacrificing 1% of anomalous transactions (our false positive rate) for higher execution speed. \nimport pybloomfilter\n\ndef train_bloom(records):\n num_records = len(records)\n cluster = pybloomfilter.BloomFilter(num_records, 0.01)\n cluster.update(records)\n return cluster\n\nrecords = list(tiles.filter(F.col('user') == user).toPandas().h3)\nbloom = train_bloom(records)\nTesting the (in-)existence of a specific card transaction location can be enabled at lightning speed. \nanomalies = transactions[transactions['h3'].apply(lambda x: x not in bloom)]\nIn the notebooks listed in this blog, we demonstrate how data scientists can embed that business logic as an MLflow experiment that can be further delivered to a batch or stream processing or to external APIs with higher throughput requirements (see MLflow deployments). \nimport mlflow\nmodel = mlflow.pyfunc.load_model('models:\/bloom\/production')\nanomalies = model.predict(transactions)\nanomalies = anomalies[anomalies['anomaly'] != 0]\nHowever, this approach poses an important operational challenge for large financial services organizations, as new models would need to be constantly retrained and redeployed to adapt to users changing behaviors. Let's take an example of a user going on holidays. Although their first card transactions may be returned as anomalous (not necessarily suspicious), such a strategy would need to adapt and learn the new \"normal\" as more and more transactions are observed. One would need to run the same process with new training data, resulting in a new version of a model being released, reviewed by an independent team of experts, approved by a governance entity and eventually updated to a fraud production endpoint outside of any change freeze. Technically possible and definitely made easier with Databricks due to the platform\u2019s collaborative approach to data management, this approach may not be viable for many. Online data storeIt is fairly common for financial services institutions to have an online data store decoupled from an analytics platform. A real-time flow of incoming card transactions usually accessed from an enterprise message broker such as Kafka, Event Hub (Azure) or Kinesis (AWS) are compared with reference data points in real time. An alternative approach to the above is to use an online datastore (like MongoDB) to keep \"pushing\" reference data points to a live endpoint as a business as usual process (hence outside of ITSM change windows). Any incoming transaction would be matched against a set of rules constantly updated and accessible via sub-seconds look up queries. Using MongoDB connector (as an example), we show how organizations can save our geo clusters dataframes for real-time serving, combining the predictive power of advanced analytics with low latency and explainability of traditional rules-based systems. \nimport com.mongodb.spark._\n\ntiles\n .withColumn(\"createdAt\", current_timestamp())  \n .write\n .format(\"mongo\")\n .mode(\"append\")\n .option(\"database\", \"fraud\")\n .option(\"collection\", \"tiles\")\n .save()\nIn the example above, we append new reference data (card transaction H3 location) to a MongoDB collection (i.e. a table) for each of our millions card holders at regular time intervals. In that setting, new transactions can be compared to reference historical data stored on MongoDB as a simple request. Given a user and a transaction location (as a H3 polygon), is this card transaction happening in a known user pattern? \nmongo > use fraud\nmongo > db.tiles.find({\"user\": \"Antoine\", \"tile\": \"8A2A1008916FFFF\"})\nAs part of this solution, we want to leverage another built-in capability of MongoDB: Time to Live (TTL). Besides the operation benefits of not having to maintain this collection (records are purged after TTL expires), we can bring a temporal dimension to our model in order to cope with users changing patterns. With a TTL of 1 week (for example) and a new model trained on Databricks every day, we can track clusters over time while dynamically adapting our fraud strategy as new transactions are being observed, purposely drifting our model to follow users\u2019 changing behaviors. Example of how change in customers' transactional behaviors could be tracked over time In the visualization above, we show an example of how change in customers' transactional behaviors could be tracked over time (thanks to our TTL on MongoDB in real time and \/ or time travel functionality on Delta), where any observed location stays active for a period of X days and wherein anomalous transactions can be detected in real time. Closing thoughts: Geospatial analytics for customer-centric bankingCard fraud transactions will never be addressed by a one-size-fits-all model but should always contextualize isolated indicators coming from different controls as part of an over-hatching fraud prevention strategy. Often, this combines advanced modeling techniques (such as neural networks) with rules-based systems, integrates advanced technologies and legacy processes, cloud-based infrastructures and on-premises systems, and must comply with tight regulatory requirements and critical SLAs. Although this solution does not aim at identifying fraudulent transactions on its own, we demonstrated through the release of a new open source library, GEOSCAN, how geospatial analytics can greatly contribute to extracting anomalous events in a timely, cost-effective (self maintained) and fully-explainable manner, hence a great candidate to combat financial fraud more effectively in a coordinated rules + AI strategy. As part of this exercise, we also discovered something equally important in financial services. We demonstrated the ability of the Lakehouse infrastructure to transition from traditional to personalized banking where consumers are no longer segmented by demographics (who they are) but by their spending patterns (how they bank), paving the way towards a more customer-centric and inclusive future of retail banking. Getting startedCheck out the solution accelerator and try these notebooks on Databricks to accelerate your fraud prevention development strategy today and contact us to learn more about how we assist customers with similar use cases.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rafi-kurlansik","text":"Rafi Kurlansik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRafi KurlansikLead Solutions Architect at DatabricksBack to speakersRafi is a Lead Solutions Architect at Databricks where he specializes in Data Science, Machine Learning and the Developer Experience. He has also helped many customers scale their R workloads with Spark. In his spare time he enjoys gardening with native plants, cooking up a storm, and long video game sessions with his three children.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/federal-government#videoinfo-9","text":"Federal Government Industry Solutions \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData analytics and AI for federal agenciesUnlock innovation to deliver better public services with data and machine learningFrom the Federal Data Strategy to the AI Executive Order, it\u2019s clear that the U.S. federal government is focused on modernizing its data analytics and warehousing capabilities.The Databricks Lakehouse Platform empowers federal agencies to unlock the full potential of their data to deliver on their mission objectives and better serve citizens.Empowering Federal agencies to leverage data\u00a0and AI to deliver on mission objectivesTrusted by leading public sector agencies+ Any other Apache Spark\u2122\ufe0f compatible clientSee how industry leaders are using Databricks to improve the experience for citizens across all public servicesLatest blog posts, webinars, and case studiesWhy Databricks for the federal governmentModernize your data analytics130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Deliver mission outcomes effectively and efficiently130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Create better experiences for citizens130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Learn moreExtensive compliance for quick and easy approval to operate (ATO)Databricks has achieved ATOs on the regions, networks and compliance controls that support your mission objectivesCloudsC2S\nSC2S\nGovCloud\nPublic Cloud\nNetworksPublic\nNIPR\nSIPR\nJWICS\nCompliance controlsFedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICS-503\nHow Databricks fuels innovation for the federal governmentHealthcareImprove the delivery and quality of healthcare services for citizens with powerful analytics and a 360\u00b0 view of patients.\nPatient 360\u00a0\nSupply chain optimization\u00a0\nInsurance management\u00a0Genomics\u00a0\nDrug discovery and deliveryDefenseApply the power of predictive analytics to geospatial, IoT and surveillance data to improve operations and protect the nation.\u00a0\nLogistics\nPredictive maintenance\u00a0\nSurveillance and reconnaissance\u00a0\nLaw enforcement and readinessHomeland SecurityDetect and prevent criminal activities and national threats with real-time analytics and data-driven decision-making.\u00a0\nCustoms and border protection\u00a0\nImmigration and citizenship\u00a0\nCounter-terrorism\u00a0\nFederal emergency aid managementPublic Authority\/CommerceProactively detect anomalies with machine learning to mitigate risk and prevent fraudulent activity.\u00a0\nTax fraud and collection\u00a0\nProcess and operations management\u00a0\nGrants management\u00a0\nCustomer 360EnergyImprove energy management with data insights that ensure energy resiliency and sustainability.\u00a0\nSecurity of energy infrastructure\u00a0\nSmarter energy management\u00a0\nEnergy exploration\u00a0\nElectrical grid reliabilityIntelligence CommunityLeverage real-time insights to make informed decisions that can impact the safety of our citizens and the world.\u00a0\nThreat detection\u00a0\nNeutralize cyberattacks\u00a0\nIntelligence surveillance and reconnaissance\u00a0\nSocial media analyticsResourcesCustomer StoriesDriving Digital Transformation to Put Patients First at CMSData Governance Best Practices \u2014 Lessons Learned From the Centers for Medicare and Medicaid ServicesLessons Learned From Modernizing the USCIS Data Analytics PlatformModernizing the Air Force With Big Data and AIWebinarsRapid Response to Hospital Operations Using Data and AI During COVID-19Geospatial Analytics and AI in the Public SectorModern Data Analytics Architecture for the GovernmentImproving Threat Detection With Big Data and AINewsAzure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)Government-Grade Security in the AWS CloudBringing Unified Analytics to Government ClientsEmpowering the U.S. Intelligence Community With Mission-Critical Analytics and AISummit talksAutomating the Federal Aviation Administration\u2019s (FAA) System-Wide Information Management (SWIM) Data Ingestion and AnalysisGeospatial Analytics at Scale: Analyzing Human Movement Patterns During a PandemicReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.\u00a0Try for freeContact usProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/product\/mlflow-model-registry","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/agenda?itm_data=hp-hamburger-agenda-dais23","text":"Agenda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAgenda at a glanceExplore sessionsSTARTING AT $1,795In Person EventFREEVirtual EventMonday, June 26, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALTuesday, June 27, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALBreakout Sessions30010Partner SummitLightning Talks, AMA\u2019s, & Meetups on topics such as Apache Spark \u2122, Delta Lake, MLflow, and moreWednesday, June 28, 2023KeynotesIN PERSONVIRTUALBreakout Sessions30010100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsClosing PartyThursday, June 29, 2023KeynotesIN PERSONVIRTUALBreakout Sessions100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsOn Demand Library HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/pages\/the-rise-of-the-lakehouse-paradigm?itm_data=lakehouse-link-riseoflakehouse","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jay-bhankharia","text":"Jay Bhankharia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJay BhankhariaSenior Director, Data Partnerships at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steve-mahoney\/#","text":"Steve Mahoney - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteve MahoneySr Manager, Product Management at DatabricksBack to speakersSteve has spent the past 18 years building platform-driven businesses in the data analytics and infrastructure space as a founding engineer and leading product. He brings his healthy obsession for analytics, visualization, and data-driven storytelling as the product leader for Databricks' collaboration products including Delta Sharing, Databricks Marketplace, Clean Rooms, and OEMs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dilip-biswal","text":"Dilip Biswal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDilip BiswalSenior Architect at AdobeBack to speakersDilip Biswal is a Software Architect at Adobe working on Adobe Experience Platform. He is an active Apache Spark contributor and works in the open source community. He is experienced in Relational Databases, Distributed Computing and Big Data Analytics. He has extensively worked on SQL engines like Informix, Derby, and Big SQLLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the \u201cPlatform Services\u201d), which are subject to the\u00a0Databricks Terms of Service\u00a0(or with respect to the Community Edition, the\u00a0Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (\u201cDatabricks\u201d) and our subscribers (\u201cSubscribers\u201d) (any such agreement, a \u201cServices Agreement\u201d).PLEASE READ CAREFULLY THESE TERMS AND THE\u00a0DATABRICKS PRIVACY POLICY\u00a0(\u201cPRIVACY POLICY\u201d) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. 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The availability or exercise of our right to obtain injunctive relief will not limit our right to seek or obtain any other remedy.You agree that we will not be liable for delays, failures, or inadequate performance of the Sites resulting from conditions outside of our reasonable control, including but not limited to natural disasters or other acts of God, failure of telecommunications networks or any other network or utility, threatened or actual acts of terrorism or war, riots, labor strikes, or governmental acts or orders.Last Updated May 25, 2018ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/walgreens","text":"Customer Story: Walgreens | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYPersonalizing pharmacy care to improve patient outcomes825 Millionprescriptions delivered across 9,000 locations$ Millionssaved in supply chain costsWatch now INDUSTRY: Healthcare SOLUTION: Recommendation engines,demand forecasting,customer segmentation PLATFORM USE CASE: Delta Lake,Databricks SQL,data science CLOUD: Azure\u201cWith Databricks Lakehouse, we can create insights from data to better understand how best to engage and communicate with patients, from sharing vital information about medications to providing guidance on their journey toward a healthier life.\u201d\n\u2014 Luigi Guadagno, Vice President, Pharmacy and Healthcare Platform Technology, WalgreensAs an innovator in retail pharmacy, Walgreens uses technology and a human touch to enhance patient experiences that lead to better outcomes. Walgreens\u2019 vision was to ensure that the right medications were always on shelves when patients needed them, and to help their pharmacists spend less time on administrative tasks like prescriptions and more time with patients. To accomplish this, they needed a scalable and secure platform that unlocks access to all their data to provide both supply chain insights as well as personalized patient information at the point of care. Using Databricks Lakehouse Platform on Azure, Walgreens created an intelligent data platform that is able to forecast demand and redistribute medications across its network of nearly 9,000 pharmacies, while delivering near real-time insights and recommendations for pharmacists to help provide more personalized advice to patients.On lakehouse, every Walgreens pharmacist can personalize patient care using near real-time insightsHarnessing data to deliver medications to millions of patientsSeventy percent of Walgreens\u2019 business comes from its pharmacy operations, where more than 825 million prescriptions are filled for millions of patients each year. That translates to tens of thousands of transactions taking place every second, and each transaction produces hundreds of helpful data points from supply chain inventory to patient behaviors.The potential value of this data to Walgreens to help modernize and transform the patient experience was immense, but the data infrastructure supporting it did not have the ability to process it efficiently to produce actionable insights. Walgreens legacy on-premises solution was built on Teradata and Hadoop technologies that were both costly and unable to scale to support new business requirements. Models were built on old data, they could not be updated in a timely fashion, and were difficult to deploy, which made them almost obsolete to data scientists.\u201cThere was about a 48-hour turnaround time to make the data from store operations usable and useful. Once we got it, we didn\u2019t really have an efficient or effective way to make it all work together. There just wasn\u2019t a way to deliver better outcomes for the people who rely on our supply chain \u2013 our patients,\u201d said Sashi Venkatesan, Director of Product Engineering \u2013 Pharmacy and Healthcare Data at Walgreens.Limited insights into the supply chain resulted in both online and in-store order issues and miscalculated inventory levels. Pharmacists tried to keep up with inventory on the existing demand planners, but the result was low productivity and high operational costs. Also, time-consuming prescription operations further compromised the patient experiences as pharmacists spent less time on meaningful interactions with patients. In order to empower pharmacists and pharmacies to deliver the high-quality care patients deserve, Walgreens needed a modern, reliable and scalable data solution that would serve accurate inventory insights and streamline operations so they could focus on the patient.Enabling real-time data insights with the LakehouseWalgreens chose to complete their digital transformation with Microsoft Azure and the Databricks Lakehouse Platform because of its security, performance and production scale. Bringing all of Walgreens\u2019 data (structured, unstructured and semi-structured) into the Lakehouse enabled lightning speed data insights, with horizontally scalable data engineering pipelines across petabytes of data.Luigi Guadagno, Group Vice President, Pharmacy Healthcare Technology Platform at Walgreens, explained, \u201cThere are two components of Databricks Lakehouse Platform that really stand out. One is that we can bring so much data together into a single location, and in real time, collate it and understand it. Two is that it allows all of our different data teams to work better together. We\u2019re getting better and smarter algorithms and generating new types of reporting that help people understand the supply chain, store labor and productivity, patient vaccine scheduling, and prescription pickup processes.\u201dUsing Databricks Lakehouse, Walgreens built their own Information, Data, and Insights (IDI) platform on an event-based microservices architecture to accelerate and streamline prescription processes. Now, pharmacists can avoid expensive out-of-stock situations with accurate inventory numbers, and have the ability to plan and forecast based on store need across their network of nearly 9,000 locations. Walgreens is also enabling pharmacists to provide better care to patients with robust patient profiles. With the secure Databricks Lakehouse Platform, pharmacists have access to patient data alongside drug facts to drive safer drug administration. The platform notifies pharmacists of potential drug interactions, changes in drug profiles, and other notes to discuss with patients during prescription refills.\u201cData that comes from the store goes back to the store in a much more actionable way, and that helps us serve the patient better because we have a better understanding of who they are,\u201d said Guadagno.Exceeding patient needs from product supply to point-of-serviceSince migrating to Databricks Lakehouse, Walgreens has optimized their supply chain by right-sizing inventory levels to save millions of dollars. Now processing 40,000 data events per second, Walgreens has the scalability to apply data insights for significant wins. Store stocking requirements are now determined by data, along with modern demand planners in updated pharmacy systems. These tools have increased productivity by 20%. Not only do data efficiencies give pharmacists more time with patients, but their data platform is also improving the quality of care they provide.Melanie Owens, Pharmacy Manager at Walgreens, explains the improvements: \u201cDuring our prescription review and verification process, we\u2019re automatically alerted to patient allergies, drug sensitivities and drug interactions. We can also see what the drug looks like \u2013 the color and shape of the pill \u2013 which makes patients feel more comfortable taking drugs that have changed. And the look and manufacturers of drugs do change fairly often.\u201d She goes on to say, \u201cThere\u2019s a lot of value in the accessibility this gives people. Patients have a first line of defense to discuss their medical needs and concerns with. No matter who you are, what your insurance is, how much money you have, you\u2019re getting clinical care, even if it\u2019s just in a snapshot.\u201dWalgreens continues to build on their digital transformation with Databricks to improve the overall patient experience. Everything from care-based initiatives that enable specialized services for terminal stage breast cancer patients, to convenience improvements that reduce the number of times patients are picking up prescripts each month, Databricks is at the center of implementation. Sashi says, \u201cWe use Databricks for high-speed data in motion. It really helps us transform the speed at which we can respond to our patients\u2019 needs either in-store or online. We have about a dozen initiatives right now and all of those are served out of the data in Databricks.\u201dRelated ContentPress Release Databricks Launches Data Lakehouse for Retail and Consumer Goods CustomersVideoWalgreens uses Databricks Lakehouse to personalize patient experiences & optimize their supply chainReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/naresh-yegireddi","text":"Naresh Yegireddi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNaresh YegireddiStaff Data Engineer at Indigo AGBack to speakersNaresh was born and raised in India. After finishing masters in Electrical Engineering in the year 2007, joined an MNC as a software engineer. Moved to the United States in 2010. Currently working as a Staff Data Engineer at Indigo AG, prior to that, had opportunities to work for SONY PlayStation, GRUBHUB, COMCAST, DELL and AT&T in data warehousing and business intelligence technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/brendan-barsness\/#","text":"Brendan Barsness - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBrendan BarsnessData and Analytics Architect at DeloitteBack to speakersBrendan Barsness is an advanced analytics consultant helping organizations apply data and AI solutions. He develops technical architectures and drives the deployment and adoption of cloud resources and services to meet the scalable demand for enterprise analytics and data management. Brendan is a Databricks Solutions Architect Champion at Deloitte and currently supports the State Department\u2019s Center for Analytics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/derek-slager","text":"Derek Slager - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDerek SlagerCTO at AmperityBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/liping-huang","text":"Liping Huang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLiping HuangSenior Solutions Architect at DatabricksBack to speakersDatabricks Senior Solutions Architect, ex-Microsoft, specializing in Big Data Analytics, Enterprise Data Warehouse, and Business Intelligence, passionate about solving real world problems using data and technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/05\/02\/high-scale-geospatial-processing-with-mosaic.html","text":"High Scale Geospatial Processing With Mosaic From Databricks Labs - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHigh Scale Geospatial Processing With Mosaicby Milos Colic, Stuart Lynn, Michael Johns and Kent MartenMay 2, 2022 in Platform BlogShare this postBreaking through the scale barrier (discussing existing challenges)At Databricks, we are hyper-focused on supporting users along their data modernization journeys.A growing number of our customers are reaching out to us for help to simplify and scale their geospatial analytics workloads. Some want us to lay out a fully opinionated data architecture; others have developed custom code and dependencies from which they do not want to divest. Often customers need to make the leap from single node to distributed processing to meet the challenges of scale presented by, for example, new methods of data acquisition or feeding data-hungry machine learning applications.In cases like this, we frequently see platform users experimenting with existing open source options for processing big geospatial data. These options often have a steep learning curve which can pose challenges unless customers have already developed a familiarity with a given framework's best practices and patterns for deploying and using. Users struggle to achieve the required performance through their existing geospatial data engineering approach and many want the flexibility to work with the broad ecosystem of spatial libraries and partners.While design decisions always come with a tradespace, we have listened to and learned from our customers while building a new geospatial library called Mosaic. The purpose of Mosaic is to reduce the friction of scaling and expanding a variety of workloads, as well as serving as a repository for best practice patterns developed during our customer engagements.At its core, Mosaic is an extension to the Apache Spark\u2122 framework, built for fast and easy processing of very large geospatial datasets. Mosaic provides:A geospatial data engineering approach that uniquely leverages the power of Delta Lake on Databricks, while remaining flexible for use with other libraries and partnersHigh performance through implementation of Spark code generation within the core Mosaic functionsMany of the OGC standard spatial SQL (ST_) functions implemented as Spark Expressions for transforming, aggregating and joining spatial datasetsOptimizations for performing spatial joins at scaleEasy conversion between common spatial data encodings such as WKT, WKB and GeoJSONConstructors to easily generate new geometries from Spark native data types and conversion to JTS Topology Suite (JTS) and Environmental Systems Research Institute (Esri) geometry typesThe choice among Scala, SQL and Python APIsDiagram 1: Mosaic Functional DesignEmbrace the ecosystemOur idea for Mosaic is for it to fit between Spark and Delta on one side and the rest of the existing ecosystem on the other side. We envision Mosaic as a library that brings the know-how of integrating geospatial capabilities into systems able to benefit from a high level of parallelism. Popular frameworks such as Apache Sedona or GeoMesa can still be used alongside Mosaic, making it a flexible and powerful option even as an augmentation to existing architectures.On the other hand, systems designed without additionally required geospatial tools can be migrated onto data architectures with Mosaic, thus leveraging high scalability and performance with minimal effort due to support of multiple languages and a unified APIs. The added value being that since Mosaic naturally sits on top of Lakehouse architecture, it can unlock AI\/ML and advanced analytics capabilities of your geospatial data platform.Diagram 2: Mosaic and the geospatial ecosystemFinally, solutions like CARTO, GeoServer, MapBox, etc. can remain an integral part of your architecture. Mosaic aims to bring performance and scalability to your design and architecture. Visualization and interactive maps should be delegated to solutions better fit for handling that type of interactions. Our aim is not to reinvent the wheel but rather to address the gaps we have identified in the field and be the missing tile in the mosaic.Using proven patternsMosaic has emerged from an inventory exercise that captured all of the useful field-developed geospatial patterns we have built to solve Databricks customers' problems. The outputs of this process showed there was significant value to be realized by creating a framework that packages up these patterns and allows customers to employ them directly.You could even say Mosaic is a mosaic of best practices we have identified in the field.We had another reason for choosing the name for our framework. The foundation of Mosaic is the technique we discussed in this blog co-written with Ordnance Survey and Microsoft where we chose to represent geometries using an underlying hierarchical spatial index system as a grid, making it feasible to represent complex polygons as both rasters and localized vector representations.Diagram 3: Mosaic approach for vector geometry representation using BNGThe motivating use case for this approach was initially proven by applying BNG, a grid-based spatial index system for the United Kingdom to partition geometric intersection problems (e.g. point-in-polygon joins). While our first pass of applying this technique yielded very good results and performance for its intended application, the implementation required significant adaptation in order to generalize to a wider set of problems.This is why in Mosaic we have opted to substitute the H3 spatial index system in place of BNG, with potential for other indexes in the future based on customer demand signals. H3 is a global hierarchical index system mapping regular hexagons to integer ids. By their nature, hexagons provide a number of advantages over other shapes, such as maintaining accuracy and allowing us to leverage the inherent index system structure to compute approximate distances. H3 comes with an API rich enough for replicating the mosaic approach and, as an extra bonus, it integrates natively with the KeplerGL library which can be a huge enabler for rendering spatial content within workflows that involve development within the Databricks notebook environment.Diagram 4: Mosaic approach for vector geometry representation using H3Mosaic has been designed to be applied to any hierarchical spatial index system that forms a perfect partitioning of the space. What we refer here to as a perfect partitioning of the space has two requirements:no overlapping indices at a given resolutionthe complete set of indices at a given resolution forms an envelope over observed spaceIf these two conditions are met we can compute our pseudo-rasterization approach in which, unlike traditional rasterization, the operation is reversible. Mosaic exposes an API that allows several indexing strategies:Index maintained next to geometry as an additional columnIndex separated within a satellite tableExplode original table over the index through geometry chipping or mosaic-ingEach of these approaches can provide benefits in different situations. We believe that the best tradeoff between performance and ease of use is to explode the original table. While this increases the number of rows in the table, the approach addresses the within-row skew and maximizes opportunity to utilize techniques like Z-Order and Bloom Filters. In addition, due to simpler geometries being stored in each row, all geospatial predicates will run faster because they will operate on simple local geometry representations.The focus of this blog is on the mosaic approach to indexing strategies that take advantage of Delta Lake. Delta Lake comes with some very useful capabilities when processing big data at high volumes and it helps Spark workloads realize peak performance. Z-Ordering is a very important Delta feature for performing geospatial data engineering and building geospatial information systems. In simple terms, Z ordering organizes data on storage in a manner that maximizes the amount of data that can be skipped when serving queries.Diagram 5: Comparison between Z-Order and Linear Order of data in storage.Geospatial datasets have a unifying feature: they represent concepts that are located in the physical world. By applying an appropriate Z-ordering strategy, we can ensure that data points that are physically collocated will also be collocated on storage. This is advantageous when serving queries with high locality. Many geospatial queries aim to return data relating to a limited local area or co-processing data points that are near to each other instead of the ones that are far apart.This is where indexing systems like H3 can be very useful. H3 ids on a given resolution have index values close to each other if they are in close real-world proximity. This makes H3 ids a perfect candidate to use with Delta Lake's Z-ordering.Making Geospatial on Databricks simpleToday, the sheer amount of data processing required to address business needs is growing exponentially. Two consequences of this are clear - 1) data does not fit into a single machine anymore and 2) organizations are implementing modern data stacks based on key cloud-enabled technologies.The Lakehouse architecture and supporting technologies such as Spark and Delta are foundational components of the modern data stack, helping immensely in addressing these new challenges in the world of data. However, when it comes to using these tools to run large scale joins with highly complex geometries, this can still be a daunting task for many users.Mosaic aims to bring simplicity to geospatial processing in Databricks, encompassing concepts that were traditionally supplied by multiple frameworks and were often hidden from the end users, thus generally limiting users' ability to fully control the system. The aim is to provide a modular system that can fit the changing needs of users, while applying core geospatial data engineering techniques which serve as the baseline for follow-on processing, analysis, and visualization. Mosaic supports runtime representations of geometries using either JTS or Esri types. With simplicity in mind Mosaic brings a unified abstraction for working with both geometry packages and is optimally designed for use with Dataset APIs in Spark. Unification is very important as switching between these two packages (both have their pros and cons and fit better different use cases) shouldn't be a complex task and it should not affect the way you build your queries.\n%python\nfrom mosaic import enable_mosaic\nspark.conf.set(\n  \"spark.databricks.mosaic.geometry.api\",\n  \"JTS\"\n)\nenable_mosaic(spark, dbutils)\n\nleft_df.join(\n  right_df,\n  on=[\"h3_index\"],\n  how=\"inner\"\n).groupBy(\n  key\n).count()\nDiagram 6: Mosaic query using H3 and JTS\n%python\nfrom mosaic import enable_mosaic\nspark.conf.set(\n  \"spark.databricks.mosaic.geometry.api\",\n  \"ESRI\"\n)\nenable_mosaic(spark, dbutils)\n\nleft_df.join(\n  right_df,\n  on=[\"h3_index\"],\n  how=\"inner\"\n).groupBy(\n  key\n).count()\nDiagram 7: Mosaic query using H3 and EsriThe approach above is intended to allow easy switching between JTS or Esri geometry packages for different tasks, though not to be mixed within the same notebook. We strongly recommend that you use a single Mosaic context within a single notebook and\/or single step of your pipelines.Bringing the indexing patterns together with easy-to-use APIs for geo-related queries and transformations unlocks the full potential of your large scale system by integrating with both Spark and Delta.\n%python\ndf = df.withColumn(\n  \"index\", mosaic_explode(col(\"shape\"))\n)\ndf.write.format(\"delta\").save(location)\n\n%sql\nCREATE TABLE table_name \n  USING DELTA\n  LOCATION location\n \nOPTIMIZE table_name \n  ZORDER BY (index.h3)  \nDiagram 8: Mosaic explode in combination with Delta Z-orderingThis pseudo-rasterization approach allows us to quickly switch between high speed joins with accuracy tolerance to high precision joins by simply introducing or excluding a WHERE clause.\n%python\n# rasterized query\n# faster but less precise\nleft_df.join(\n  right_df,\n  on=[\"index.h3\"],\n  how=\"inner\"\n).groupBy(\n  key\n).count()\nDiagram 9: Mosaic query using index only\n%python\n# detailed query\n# slower but more precise\nleft_df.join(\n  right_df,\n  on=[\"index.h3\"],\n  how=\"inner\"\n).where(\n  col(\"is_core\") ||\n   st_contains(col(\"chip\"), col(\"point\"))\n).groupBy(\n  key\n).count()\nDiagram 10: Mosaic query using chip detailsWhy did we choose this approach? Simplicity has many facets and one that gets often overlooked is the explicit nature of your code. Explicit is almost always better than implicit. Having WHERE clauses determine behavior instead of using configuration values leads to more communicative code and easier interpretation of the code. Furthermore, code behavior remains consistent and reproducible when replicating your code across workspaces and even platforms.Finally, if your existing solutions leverage H3 capabilities, and you do not wish to restructure your data, Mosaic can still provide substantial value through simplifying your geospatial pipeline. Mosaic comes with a subset of H3 functions supported natively.\n%python\ndf.withColumn(\n  \"indices\", polyfill(col(\"shape\"))\n)\nDiagram 11: Mosaic query for polyfill of a shape\n%python\ndf.withColumn(\n  \"index\", point_index_geom(col(\"point\"))\n)\nDiagram 12: Mosaic query for point indexAccelerating pace of innovationOur main motivation for Mosaic is simplicity and integration within the wider ecosystem; however, that flexibility means little if we do not guarantee performance and computational power. We have evaluated Mosaic against 2 main operations: point in polygon joins and polygon intersection joins. In addition we have evaluated expected performance for the indexing stage. For both use cases we have pre-indexed and stored the data as Delta tables. We have run both operations before using ZORDER optimization and after to highlight the benefits that Delta can bring to your geospatial processing efforts.For polygon-to-polygon joins, we have focused on a polygon-intersects-polygon relationship. This relationship returns a boolean indicator that represents the fact of two polygons intersecting or not. We have run this benchmark with H3 resolutions 7,8 and 9, and datasets ranging from 200 thousand polygons to 5 million polygons.Diagram 13: Mosaic polygon intersects polygon benchmarksWhen we compared runs at resolution 7 and 8, we observed that our joins on average have a better run time with resolution 8. Most notably the largest workload of 5 million polygons joined against 5 million polygons resolution in over 1.5 billion matches ran in just over 2 hours on resolution 8 while it took about 3 hours at resolution 7. Choosing the correct resolution is an important task. If we select a resolution that is too coarse (lower resolution number) we risk of under-representing our geometries which leads to situations where geometrical data skew was not addressed and performance will degrade. If we select resolution that is too detailed (higher resolution number) we risk over-representing our geometries which leads to a high data explosion rate and performance will degrade. Striking the right balance is crucial and in our benchmarks it led to ~30% runtime optimization which highlights how important it is to have an appropriate resolution. The average number of vertices in both our datasets ranges from 680 to 690 nodes per shape - demonstrating that the Mosaic approach can handle complex shapes at high volumes.When we increased the resolution to 9 we observed a decrease in performance - this is due to over-representation problems - using too many indices per polygon will result in too much time wasted on resolving index matches and will slow down the overall performance. This is why we have added capabilities to Mosaic that will analyze your dataset and indicate to you the distribution of the number indices needed for your polygons.\n%python\nfrom mosaic import MosaicAnalyzer\n\nanalyzer = MosaicAnalyzer()\noptimal_resolution = analyzer.get_optimal_resolution(geoJsonDF, \"geometry\")\noptimal_resolution  \nDiagram 14: Determining the optimal resolution in MosaicFor the full sets of benchmarks please refer to the Mosaic documentation page where we discuss the full range of operations we ran and provide an extensive analysis of the obtained results.Building an atlas of use casesWith Mosaic we have achieved the balance of performance, expression power and simplicity. And with such balance we have paved the way for building end to end use cases that are modern, scalable, and ready for future Databricks product investments and partnerships across the geospatial ecosystem. We are working with customers across multiple industry verticals and we have identified many applications of Mosaic in the real world domains. Over the next months we will build solution accelerators, tutorials and examples of usage. Mosaic github repository will contain all of this content along with existing and follow-on code releases. You can easily access Mosaic notebook examples using Databricks Repos and kickstart your modern geospatial data platform - stay tuned for more content to come!Getting startedTry Mosaic on Databricks to accelerate your Geospatial Analytics on Lakehouse today and contact us to learn more about how we assist customers with similar use cases.Mosaic is available as a Databricks Labs repository here.Detailed Mosaic documentation is available here.You can access the latest code examples here.You can access the latest artifacts and binaries following the instructions provided here.Try Databricks for freeGet StartedRelated postsProcessing Geospatial Data at Scale With DatabricksDecember 5, 2019 by Nima Razavi and Michael Johns in Engineering Blog\nThis blog was written 3 years ago. Please refer to these articles for up-to-date approaches to geospatial processing and analytics with your Databricks...\nAnnouncing CARTO\u2019s Spatial Extension for Databricks -- Powering Geospatial Analysis for JLLDecember 9, 2021 by Kent Marten and Javier de la Torre in Platform Blog\nThis is a collaborative post by Databricks and CARTO. We thank Javier de la Torre, Founder and Chief Strategy Officer at CARTO for...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sanket-amin\/#","text":"Sanket Amin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSanket AminSenior Manager of CAS Data Science and Analytics at Collins AerospaceBack to speakersSanket Amin\u2019s data analysis journey starts with research and development of vibration based predictive algorithms for jet engines. This naturally led him to investigate opportunities to analyze large volumes and other aircraft data signals. He has worked on projects with many important aerospace companies and organizations including NASA, GE, Pratt and Whitney, NAVAIR, and AFRL. He currently leads a team a data science team at Collins Aerospace\u2019s Connected Aviation Solutions business unit.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/natalia-demidova","text":"Natalia Demidova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North America at Hitachi Solutions America Ltd.Back to speakersNatalia has a Ph.D. in Mechanical Engineering. She is serving as a Director \u2013 Solution Principal in Data, Data Science and AI with Hitachi Solutions. Natalia led the design of the Real-time AI platforms with MLOps and LLMOps, and Machine Learning pipelines in alignment with Client\u2019s strategic business goals and KPIs. Some examples of Natalia's solutions with Azure Databricks involve the Intelligent Knowledge Management platform, AEC Construction Cloud with AI, IoT-based predictive maintenance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/catalyst-optimizer","text":"What is the Catalyst Optimizer?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCatalyst OptimizerAll>Catalyst OptimizerTry Databricks for freeGet StartedAt the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional programming constructs in Scala and designed with these key two purposes:Easily add new optimization techniques and features to Spark SQLEnable external developers to extend the optimizer (e.g. adding data source specific rules, support for new data types, etc.) Catalyst contains a general library for representing trees and applying rules to manipulate them. On top of this framework, it has libraries specific to relational query processing (e.g., expressions, logical query plans), and several sets of rules that handle different phases of query execution: analysis, logical optimization, physical planning, and code generation to compile parts of queries to Java bytecode. For the latter, it uses another Scala feature, quasiquotes, that makes it easy to generate code at runtime from composable expressions. Catalyst also offers several public extension points, including external data sources and user-defined types. As well, Catalyst supports both rule-based and cost-based optimization.Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/trust\/compliance","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueComplianceCustomers all over the world trust us with their most sensitive data. Databricks has put in place controls to meet the unique compliance needs of highly regulated industries.Due diligence packageFor self-service security reviews, you can download our due diligence package. It includes common compliance documents such as our ISO certifications and our annual pen test confirmation letter. You can also reach out to your Databricks account team for copies of our Enterprise Security Guide and SOC 2 Type II report.DownloadCertifications and standardsCloudsCCPA provides privacy protections for residents of California, U.S.Certification to standardize U.S. Department of Defense security authorizationsCertification to standardize U.S. government security authorizationsThe GDPR provides privacy protections for EU and EEA dataGxP provides guidelines, standards and regulations that ensure safe practices, such as manufacturingU.S. privacy regulation for protected health informationA set of controls designed to address regulations such as HIPAAInternational standard for information security management systemsInternational standard for securely utilizing or providing cloud servicesInternational standard for handling of PII in the public cloudRequirements for processing, storing, transmitting, or accessing credit card informationStandard for describing security controls of cloud service providersProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/resources\/analyst-paper\/databricks-named-leader-by-gartner?itm_data=gartnermqcdbms22","text":"Databricks nominata leader | Databricks2022 Gartner\u00ae Magic Quadrant\u2122Databricks nominata leadersistemi di gestione database in cloud (CDBMS)Databricks nominata leader nel Gartner\u00ae Magic Quadrant\u2122 2022 CDBMSDatabricks \u00e8 fiera di annunciare che Gartner ha inserito l'azienda fra i leader nel Magic Quadrant 2022 for Cloud Database Management Systems per il secondo anno consecutivo.Riteniamo che questo riconoscimento convalidi la nostra visione del lakehouse come un'unica piattaforma unificata per la gestione e l'ingegneria dei dati, nonch\u00e9 per l'analisi e l'AI.Scarica il report per scoprire perch\u00e9 Gartner ha inserito Databricks tra i leader e per ottenere ulteriori informazioni sui vantaggi che una piattaforma lakehouse pu\u00f2 offrire alla tua organizzazione.Accedi al report Gartner, Magic Quadrant for Cloud Database Management Systems, Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.\nGARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and\/or its affiliates and are used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner\u2019s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.\nThis graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/10\/15\/building-the-latinx-network-and-celebrating-our-heritage.html","text":"Celebrating Hispanic Heritage With the Databricks Latinx Network - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorBuilding the Latinx Network and Celebrating Our Heritageby Yvette Ramirez and Mike LiranzoOctober 15, 2020 in Company BlogShare this postVirtual performance from Mariachi Sol Mixteco during the Cafe con Leche event\u00a0This past spring, we launched our Latinx Network Employee Resource Group with a lot of excitement. We co-founded this group to foster a comunidad (community) that supports, learns and grows together. We love the diversity of our culture and want to embrace it and share it with our colleagues around the world. The mission of the Latinx Network is to promote inclusion, career growth, leadership, mentorship and networking within Databricks and our local communities.\nOver the last few months, our team came together to plan our first annual Hispanic Heritage Month at Databricks. This was a time for us to reflect on where we came from, where we are today and what we can do to create a better future for our community. To celebrate, we hosted a few events, one of which was called Caf\u00e9 con Leche, a virtual event that created space for our colleagues to share some of their favorite recipes, poetry and family stories. This was a great way for us to highlight our talented Latinx colleagues and allies across the globe while we connected over our individual and collective history.\nTo reflect back on this month, we connected with fellow Databricks employees to learn more about their perspectives on celebrating our heritage with their families and the importance of building community.\nCynthia Garcia \u2014 Sales Development RepresentativeCynthia (second to the left) with her familyQ: Why do you think it is important to have a Latinx Network at Databricks?\u00a0\nI believe that it\u2019s important to have a Latinx Network at Databricks because it creates a sense of community and belonging. Since going remote, this has been a great way to network with my colleagues who are outside my immediate team and learn from them, bounce ideas off them, and make more connections.\nQ: What are you most proud of as it relates to your Latin heritage?\nThere\u2019s a lot of things to be proud of when it comes to Latin heritage (food, music, family, etc.), but one thing that I am most proud of is how we always put family first. We spend all our special moments together laughing, crying and enjoying each other\u2019s company. Being Hispanic is more than just the parties and food, it\u2019s about our history, our struggles and our hard work. My parents sacrificed a lot to give my siblings and me a better opportunity and that is something I will always cherish.\nMiguel Peralvo \u2014\u00a0 Solutions Architect\u00a0\nMiguel (on the left) with his wife\nQ: Why do you think it is important to have a Latinx Network at Databricks?\u00a0\u00a0\nMy wife is Puerto Rican and I\u2019m Spanish. So having a Latinx Network at Databricks makes me feel a stronger sense of community. An open community, because at Databricks our Employee Resource Groups welcome and educate all people, regardless of their background. Sientes que perteneces. (You feel like you belong.)\nQ: What advice do you have for other people from the Latinx community who want to pursue a career in tech?\nAt the beginning of your career, try to work in places that allow you to fail quickly and embrace who you are, including your Latinx background. If there are things you don\u2019t like, try to change them. If you can\u2019t, that\u2019s a signal. You should feel like you are in charge of your career and situation. You should feel like what you are doing and how you are treated will help you blossom, eventually. Intenta cambiar la habitaci\u00f3n, y si no puedes, cambia de habitaci\u00f3n. (Try to change the room, and if you can\u2019t, change to another room.)\nDiane Romualdez \u2014 Sr. Event Marketing ManagerDiane (on the far left) with her sisters\u00a0Q: How do you and your family like to celebrate this month?\u00a0\nHispanic Heritage Month is a great time to reflect on the paths paved by our ancestors through song, dance, food and more. It is a\u00a0 time to revisit recipes passed down from generation to generation and come together over a reminiscent meal that is meaningful for our family and culture.\nQ: How have you and your family been involved in the events that our Latinx Network ERG group has hosted for Hispanic Heritage Month?\nI have had the pleasure to support the Latinx Network ERG with pre-planning and working on co-hosted events with other ERG groups such as the Intro to Stocks event with our Black Employee Network. There is a lot to look forward to beyond this month, and it is special that we are able to celebrate it with all Databricks employees.\nDaniel Alvarez \u2014 Recruiting CoordinatorDaniel (on the left) with his dadQ: How do you and your family like to celebrate this month?\nIn addition to enjoying the most delicious Salvadorian foods, we also celebrate this month by taking some time to look back at how far we have truly come as a family. My mom immigrated from El Salvador, and my dad is from Mexico. They both sacrificed an opportunity for a great life in order to give me and my brother an even better one. Now, I am a recruiting coordinator and my brother is a software engineer, and they couldn\u2019t be prouder! We are truly grateful to have our careers in the tech industry and to never forget our family\u2019s sacrifice that allowed us to reach this point.\nQ: What are you most proud of as it relates to your Latin heritage?\nI am most proud of the grit and resilience of our Latinx community. Our history is full of stories of parents who work countless hours to provide a roof and an education for their children. I am proud and inspired by the hardworking members of the Latinx community who dream of opportunities and turn them into reality because the will to succeed is always welcomed here.\nCreating a space to blend both our communities at home and within Databricks allowed us to connect with one another and celebrate Hispanic Heritage Month. To learn more about how you can join our community at Databricks, check out our Careers page.\u00a0Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/automated-phi-removal","text":"Automated PHI Removal | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorAutomated PHI RemovalPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedDetect and protect sensitive patient data with NLPHIPAA requires organizations to limit access to Protected Health Information (PHI). Removing PHI from unstructured data such as images and PDFs can be challenging and manually intensive. Our joint Solution Accelerator with John Snow Labs automates the detection of sensitive information contained within unstructured data using NLP models for healthcare. Extracted data is stored within the Lakehouse, where teams can use the pre-trained models to easily remove, obfuscate or mask data for downstream analytics at massive scale.Convert unstructured data like PDFs to structured text with OCR modelsEasily detect PHI using pre-trained NLP models for healthcareAutomatically remove or de-identify PHI for downstream analysisDownload notebookResourcesBlogRead nowOn-demand workshopWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/about-us","text":"About Databricks, founded by the original creators of Apache Spark\u2122Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks is the lakehouse companyWith origins in academia and the open source community, Databricks was founded in 2013 by the original creators of Apache Spark\u2122, Delta Lake and MLflow. As the world\u2019s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI.Explore the Lakehouse PlatformToday, more than 7,000 organizations worldwide \u2014 including ABN AMRO, Cond\u00e9 Nast, Regeneron and Shell \u2014 rely on Databricks to enable massive-scale data engineering, collaborative data science, full-lifecycle machine learning and business analytics.\n\u00a0\nHeadquartered in San Francisco, with offices around the world and hundreds of global partners, including Microsoft, Amazon, Tableau, Informatica, Capgemini and Booz Allen Hamilton, Databricks is on a mission to simplify and democratize data and AI, helping data teams solve the world\u2019s toughest problems.\nExplore Customer StoriesSee PartnersCustomersSee all customers\nLeadershipExecutive teamMeet our executivesFoundersMeet our foundersBoard of directorsMeet our boardInvestorsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/training\/#","text":"Training - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTrainingLevel up your data and AI skills through one of our Summit trainings. Whether you\u2019re new to the Lakehouse architecture or a seasoned pro looking to dive deep, we have a course for you.\nHide search filtersreset filtersSearchSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/prashanth-babu\/#","text":"Prashanth Babu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPrashanth BabuLead Product Specialist at DatabricksBack to speakersPrashanth is a Lead Product Specialist Solutions Architect at Databricks. He has more than a decade experience working on Big Data. Prior to that for a decade, he was a Java architect for a product. He has been using Spark since 2014 and joined Databricks in Sep 2018. He focuses on all things Data Engineering working closely with both the Product Management and the (EMEA) Field Engineering teams. Also leads EMEA Delta and Performance SME at Databricks and has been working with many enterprises advising them on Databricks Lakehouse best practices and guiding them expedite build, productionize and deploy their pipelines at scale.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/blog\/category\/company","text":"Databricks \ube14\ub85c\uadf8Skip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c 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\ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWLoading...\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\u0000\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/solutions\/data-science","text":"Collaborative Data Science | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCollaborative Data ScienceA unified experience to boost data science productivity and agilityGet startedData Scientists face numerous challenges throughout the data science workflow hindering productivity. As organizations continue to become more data-driven, a collaborative environment for easier access and visibility into the data, models trained against the data, reproducibility, and insights uncovered within the data is critical.The ChallengeData exploration at scale is difficult and costlySpending too much time managing infrastructure and DevOpsNeed to stitch together various open source libraries and tools for further analyticsMultiple handoffs between data engineering and data science teams are error prone and increase risksHard to transition from local to cloud-based development due to complex ML environments and dependenciesThe SolutionQuick access to clean and reliable data for downstream analyticsOne click access to pre-configured clusters from the data science workspaceBring your own environment and multi-language support for maximum flexibilityA unified approach to streamline the end-to-end data science workflow from data prep to modelling and insights sharingMigrate or execute your code remotely on pre-configured and customizable ML clustersDatabricks for Data ScienceAn open and unified platform to collaboratively run all types of analytics workloads, from data preparationto exploratory analysis and predictive analytics, at scale.WorkspaceWorkspaceOne central place to store and share notebooks, experiments, and projects backed with role-based access control.NotebooksData StoreDashboardsExperiments TrackingCollaborative Data Science at ScaleCollaboration across the entire data science workflow, and moreCollaboratively write code in Python, R, Scala, SQL, explore data with interactive visualizations, and discover new insights with Databricks notebooks.Confidently and securely share code with co-authoring, commenting, automatic versioning, Git integrations, and role-based access controls.Keep track of all experiments and models in one place, capture knowledge, publish dashboards, and facilitate hand-offs with peers and stakeholders across the entire workflow, from raw data to insights.Learn moreFocus on the data science, not the infrastructureYou don\u2019t have to be limited by how much data fits on your laptop anymore, or how much compute is available to you.Quickly migrate your local environment to the cloud with Conda support,\u00a0and connect notebooks to auto-managed clusters to scale your analytics workloads as needed.Learn moreUse PyCharm, Jupyter Lab or RStudio with scalable computeWe know how busy you are\u2026 you probably already have hundreds of projects on your laptop, and are accustomed to a specific toolset.Connect your favorite IDE to Databricks, so that you can still benefit from limitless data storage and compute. Or simply use RStudio or Jupyter lab directly from within Databricks for a seamless experience.Learn moreGet data ready for data scienceClean and catalog all your data in one place with\u00a0Delta Lake: either batch, streaming, structured or unstructured, and make it discoverable to your entire organization via a centralized data store.As data comes in, quality checks ensure data is ready for analytics. As data evolves with new data and further transformations, data versioning ensures you can meet compliance needs.Discover and share new insightsYou\u2019ve done all the work and identified new insights with built-in interactive visualizations or any other supported library like matplotlib or ggplot.Easily share and export results by quickly turning your analysis into a dynamic dashboard. The dashboards are always up to date, and can run interactive queries as well.Cells, visualizations, or notebooks can also be shared with role-based access control and exported in multiple formats including HTML and IPython Notebook.Learn moreSimple access to the latest ML frameworksGet going fast with one-click access to ready-to-use and optimized Machine Learning environments including the most popular frameworks like scikit-learn, XGBoost, TensorFlow, Keras and more. Or effortlessly migrate and customize ML environments with Conda. Simplified scaling on Databricks helps you go from small to big data effortlessly, so that you don\u2019t have to be limited with how much data fits on your laptop anymore.The ML Runtime provides built-in\u00a0AutoML\u00a0capabilities, including hyperparameter tuning, model search, and more to help accelerate the data science workflow. For example, accelerate training time with built-in optimizations on the most commonly used algorithms and frameworks, including Logistic Regression, Tree-based Models, and GraphFrames.Learn moreAutomatically track and reproduce resultsAutomatically track experiments from any framework, and log parameters, results, and code version for each run with managed\u00a0MLflow.Securely share, discover, and visualize all experiments across workspaces, projects, or specific notebooks across thousands of runs and multiple contributors.Compare results with search, sort, filter, and advanced visualizations to help find the best version of your model, and quickly go back to the right version of your code for this specific run.Learn moreOperationalize at scaleSchedule notebooks to automatically run data transformations, modelling, and share up to date results.Set up alerts and quickly access audit logs for easy monitoring and troubleshootingLearn more\nCustomer Story \n\nSaving millions in inventory management\nShell has deployed a data science tool globally to help it manage and optimise the $1 billion in spare part inventory it holds in case something breaks on its assets.\nLearn more\nSee more customer storiesResourcesReportGartner\u00ae Names Databricks a LeaderWebinarAutoML Rapid, Simplified Machine Learning For EveryoneeBookThe Big Book of Data Science Use CasesReady to get started?Try Databricks freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christian-acuna\/#","text":"Christian Acu\u00f1a - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristian Acu\u00f1aSenior Data Engineer at GrammarlyBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/devlina-das","text":"Devlina Das - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDevlina DasSenior Software Engineer at InstacartBack to speakersDevlina is a Software Engineer at Instacart focusing on data processing at scale. She has above 10 years of software development experience.\nArthur Li is a software engineer who has been working at Instacart for the past two years focusing on batch data processing infrastructure. He has contributed to the company's data platform team by implementing data collection and management strategies that have streamlined the company's data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/data-lakehouse","text":"Data Lakehouse Platform by Databricks - Schedule a Demo Now!Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe Databricks Lakehouse PlatformUnify your data warehousing and AI use cases on a single platformTry for free\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowSimple. Open. Multicloud.The Databricks Lakehouse Platform combines the best elements of data lakes and data warehouses to deliver the reliability, strong governance and performance of data warehouses with the openness, flexibility and machine learning support of data lakes.This unified approach simplifies your modern data stack by eliminating the data silos that traditionally separate and complicate data engineering, analytics, BI, data science and machine learning. It\u2019s built on open source and open standards to maximize flexibility. And, its common approach to data management, security and governance helps you operate more efficiently and innovate faster.SimpleThe unified approach simplifies your data architecture by eliminating the data silos that traditionally separate analytics, BI, data science and machine learning. With a lakehouse, you can eliminate the complexity and expense that make it hard to achieve the full potential of your analytics and AI initiatives.OpenDelta Lake\u00a0forms the open foundation of the lakehouse by providing reliability and\u00a0world-record-setting performance\u00a0directly on data in the data lake. You\u2019re able to avoid proprietary walled gardens, easily share data, and build your modern data stack with unrestricted access to the ecosystem of open source data projects and the broad Databricks partner network.Learn more about 450+ Partners across the data landscapeLearn moreMulticloudThe Databricks Lakehouse Platform offers you a consistent management, security, and governance experience across all clouds. You don\u2019t need to invest in reinventing processes for every cloud platform that you\u2019re using to support your data and AI efforts. Instead, your data teams can simply focus on putting all your data work to discover new insights.Learn moreUnlock the potential of your data \u2014 and your data teamsLearn more about how the Databricks Lakehouse Platform enables your data and AI workloadsData engineeringDatabricks SQLMachine learningRelated content\nAll the resources you need. All in one place.\nExplore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.\nExplore ResourcesLakehouseWhat is a Lakehouse?Dummies Book: Modern Cloud Data PlatformThe Rise of the Lakehouse ParadigmRise of the Data Lakehouse by Bill Inmon, father of the data warehouseDelta LakeThe Big Book of Data EngineeringDelta Lake: The Definitive Guide by O\u2019ReillyDefinitive Guide to Delta LakeDelta Lake: The Foundation to Your LakehouseMachine learningeBook: Standardizing the ML LifecycleVirtual Event: Building Machine Learning PlatformsVirtual Event: Build Your Own Large Language Model Like DollyReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sneh-kakileti\/#","text":"Sneh Kakileti - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSneh KakiletiVice President, Product Management at ZoomInfoBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners","text":"Partner | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks-PartnerDatabricks hat weltweit \u00fcber 1200+ Partner, die Daten-, Analytics- und KI-L\u00f6sungen und -Services f\u00fcr unsere gemeinsamen Kunden bereitstellen und dabei die Databricks Lakehouse-Plattform nutzen. Mithilfe von Databricks und diesen Partnern f\u00fchren Sie Ihre Daten- und KI-Workloads zusammen und gewinnen aussagekr\u00e4ftige Erkenntnisse.\u201eDatabricks schafft das Datenvolumen, w\u00e4hrend Tableau die schnelle Visualisierung erm\u00f6glicht. Diese L\u00f6sungen arbeiten im Kern unserer Plattform perfekt zusammen. So k\u00f6nnen wir unseren Kunden genau die Leistung bieten, die sie brauchen, um hochmoderne Funktionen f\u00fcr autonome Fahrzeuge zu liefern.\u201c\u2014 Patrick McAuliffe, Lead Engineer, InciteCloud-PartnerDatabricks l\u00e4uft auf AWS, Microsoft Azure, Google Cloud und Alibaba Cloud und ist eng mit den Infrastruktur-, Daten- und KI-Services der einzelnen Anbieter verzahntTechnologiepartnerTechnologiepartner integrieren ihre L\u00f6sungen mit Databricks, um erg\u00e4nzende Funktionen f\u00fcr ETL, Dateneingabe, BI, ML und Governance bereitzustellenConsulting-PartnerConsulting-Partner sind Experten, die Sie bei der Strategieentwicklung sowie bei Implementierung und Skalierung von Daten-, Analytics- und KI-Initiativen mit Databricks unterst\u00fctzenPartner werdenUnsere Partner entwickeln und implementieren in Zusammenarbeit mit Databricks innovative L\u00f6sungen f\u00fcr Kunden. Treten Sie dem Databricks Partner Program bei und erhalten Sie Zugang zu exklusiven Tools, Schulungen, Solution Accelerators und Go-to-Market-Programmen.Mehr InformationenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/modern-investment-data-platform","text":"How to build: A modern investment data platform | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: A modern investment data platformUse financial market data to its fullest in Delta Lake to productionize pipelinesLeverage common data sets in Delta Lake and productionize use cases, such as financial product volatility forecasting and market surveillance. Delta Lake enables financial services institutions to focus on product delivery for customers using a modern data architecture.Read the full write-upNotebook 1Bloomberg API Ingestion NotebookDownload NotebookNotebook 2Volatility Forecasting From Fundamental and Technical DataDownload NotebookNotebook 3Execution Quality and SpoofingDownload NotebookBenefits and business valueShare and productionizeShare data and monetize on analytical dashboards that customers can create for end users\nGet customer-focusedDeliver products and use cases for customers, resulting in increased AUM, decreased fraud and increased subscriptions as investing expands to retail investors\nInnovate fasterModernize your data lakes by moving from legacy systems to next-generation cloud platforms to drive innovation and productivity quickly and at scale\nReference ArchitectureDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/emad-mostaque","text":"Emad Mostaque - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEmad MostaqueCEO at stability.aiBack to speakersEmad Mostaque received his master's degree in mathematics and computer science from Oxford University in 2005. He then went on to spend 13 years working at various hedge funds in the United Kingdom. \nIn 2019 he founded Symmitree, a startup that aimed to reduce the cost of technology for individuals living in poverty, which he worked on for one year. In late 2020 he founded Stability AI. Much of the company's funding comes directly from Mostaque, who is a former hedge fund manager, as well as other investment companies such as Eros Investments. The company spent $600,000 of its $10 million initial funding to train Stable Diffusion (https:\/\/en.wikipedia.org\/wiki\/Stable_Diffusion) and announced a $100 million seed round of a valuation of $1 billion. \nIn March 2023, he signed an open letter calling for \"all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4\".Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-wellman","text":"Paul Wellman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul WellmanVP, Executive Product Owner, Data-as-a-Service at TD BankBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/product\/open-source","text":"\uc624\ud508 \uc18c\uc2a4 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 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\uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\uc624\ud508 \uc18c\uc2a4Databricks \uc5d4\uc9c0\ub2c8\uc5b4\ub294 \uc138\uacc4\uc5d0\uc11c \uac00\uc7a5 \ubcf4\ud3b8\uc801\uc778 \uc624\ud508 \uc18c\uc2a4 \ub370\uc774\ud130 \uae30\uc220\uc744 \uac1c\ubc1c\ud55c \uc8fc\uc5ed\ubaa8\uc784 \ucc38\uc11dDatabricks\uc758 \ub300\ud45c\uc801\uc778 \uc624\ud508 \uc18c\uc2a4 \ud504\ub85c\uc81d\ud2b8Apache Spark\u2122Apache Spark\ub294 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc640 ML \uc6cc\ud06c\ub85c\ub4dc \uc2e4\ud589\uc6a9 \ud1b5\ud569\ud615 \uc5d4\uc9c4\uc785\ub2c8\ub2e4.\nApache Spark\ub780 ?\nSpark\uc640 Databricks \ube44\uad50\u2192\nspark.apache.org \ubc29\ubb38\nDelta LakeDelta Lake\ub97c \uc0ac\uc6a9\ud558\uba74 AWS S3, ADLS, GCS \ubc0f HDFS\uc640 \uac19\uc740 \uc2a4\ud1a0\ub9ac\uc9c0 \uc2dc\uc2a4\ud15c\uc744 \uae30\ubc18\uc73c\ub85c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub97c \ube4c\ub4dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\nDelta Lake\uc5d0 \uad00\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30\nDelta.io \ubc29\ubb38\nTech Talks: Delta Lake \uc2dc\uc791\ud558\uae30\nMLFlowMLflow\ub294 \uc2e4\ud5d8, \uc7ac\ud604 \uac00\ub2a5\uc131, \ubc30\ud3ec\uc640 \uc911\uc559 \ubaa8\ub378 \ub808\uc9c0\uc2a4\ud2b8\ub9ac \ub4f1 ML \uc218\uba85 \uc8fc\uae30\ub97c \uad00\ub9ac\ud569\ub2c8\ub2e4.\nDatabricks\uc758 \uad00\ub9ac\ud615 MLflow\nmlflow.org \ubc29\ubb38\nTech Talks: ML \uc218\uba85 \uc8fc\uae30 \uad00\ub9ac\nRedashRedash\ub97c \uc0ac\uc6a9\ud558\uba74 \ub204\uad6c\ub098 SQL\uc744 \ud65c\uc6a9\ud574 \ud06c\uace0 \uc791\uc740 \ub370\uc774\ud130 \uc18c\uc2a4\ub85c\ubd80\ud130 \ub370\uc774\ud130\ub97c \ud0d0\uc0c9, \ucffc\ub9ac, \uc2dc\uac01\ud654\ud558\uace0 \uacf5\uc720\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\nGitHub\uc758 Redash \ubc29\ubb38\nDelta SharingDelta Sharing\uc740 \uc548\uc804\ud55c \ub370\uc774\ud130 \uacf5\uc720\ub97c \uc704\ud55c \uc5c5\uacc4 \ucd5c\ucd08\uc758 \uc624\ud508 \ud504\ub85c\ud1a0\ucf5c\ub85c, \ub2e4\ub978 \uc870\uc9c1\uacfc \uac04\ud3b8\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4.\nDelta Sharing \ubc29\ubb38\nDatabricks\uc5d0\uc11c \uc9c0\uc6d0\ud558\ub294 \uae30\ud0c0 \ubcf4\ud3b8\uc801\uc778 \uc624\ud508 \uc18c\uc2a4 \uae30\uc220TensorFlowDatabricks\uc5d0\uc11c\ub294 \ub525 \ub7ec\ub2dd\uacfc \ud074\ub7ec\uc2a4\ud130\uc5d0\uc11c\uc758 \uc77c\ubc18 \uc5f0\uc0b0\uc744 \uc704\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac Tensorflow \uc9c0\uc6d0\nDatabricks\uc758 TensorFlow\nPyTorch\u2122PyTorch \uac1c\ubc1c\uc790\uc778 Facebook\uacfc Databricks, \ud1b5\ud569\uc744 \uc704\ud574 \ud611\uc5c5\nDatabricks\uc758 PyTorch\nKeras\u2122Python\uc73c\ub85c \uc4f0\uc778 \ub525\ub7ec\ub2dd API\ub85c, TensorFlow \uae30\ubc18\uc73c\ub85c \uc2e4\ud589\ub429\ub2c8\ub2e4. Databricks Runtime for ML\uc5d0\uc11c \uc81c\uacf5\nDatabricks\uc758 Keras\nRStudioR\uc744 \uc0ac\uc6a9\ud55c \ud611\uc5c5\ud615 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc6a9 \uc624\ud508 \uc18c\uc2a4 \ud234 \uc2a4\uc704\ud2b8\u200b\n\ube45\ub370\uc774\ud130 R \ud504\ub85c\uadf8\ub798\ubc0d\nscikit-learnNumPy, SciPy \ubc0f Matplotlilb \uae30\ubc18\uc73c\ub85c \uad6c\ucd95\ub41c \ubcf4\ud3b8\uc801\uc778 \uba38\uc2e0 \ub7ec\ub2dd\uc6a9 Python \ud328\ud0a4\uc9c0\u200b\u200b\nDatabricks\uc758 Scikit-learn\nXGBoostPython, R \ubc0f C++ \ub4f1\uc758 \uc5b8\uc5b4\ub85c \ub41c \ubc14\uc778\ub529\uc744 \ud3ec\ud568\ud55c \ubd84\uc0b0\ud615 \uadf8\ub798\ub514\uc5b8\ud2b8 \ubd80\uc2a4\ud305(gradient boosting) \ub77c\uc774\ube0c\ub7ec\ub9acDatabricks\uc758 XGBoostTerraformHashiCorp Terraform\uc740 \uc5ec\ub7ec \ud074\ub77c\uc6b0\ub4dc \uc81c\uacf5\uc5c5\uccb4\uc5d0\uc11c \uc548\uc804\ud558\uace0 \uc608\uce21 \uac00\ub2a5\ud55c \ud074\ub77c\uc6b0\ub4dc \uc778\ud504\ub77c\ub97c \ub9cc\ub4dc\ub294 \ub370 \uc0ac\uc6a9\ud558\ub294 \uc778\uae30 \uc624\ud508 \uc18c\uc2a4 \ub3c4\uad6c\uc785\ub2c8\ub2e4. Databricks Terraform \uacf5\uae09\uc5c5\uccb4\ub294 \uace0\uac1d\uc774 \uc720\uc5f0\ud558\uace0 \uac15\ub825\ud55c \ub3c4\uad6c\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub098\uba38\uc9c0 \uc778\ud504\ub77c\uc640 \ud568\uaed8 Databricks \uc6cc\ud06c\uc2a4\ud398\uc774\uc2a4\ub97c \uad00\ub9ac\ud558\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \ub610\ud55c, Terraform\ub97c \uc0ac\uc6a9\ud558\ub294 \uace0\uac1d\uc740 \ucf54\ub4dc\ud615 \uc778\ud504\ub77c(IaC)\ub85c \ubaa8\ubc94 \uc0ac\ub840\ub97c \uc27d\uac8c \ub3c4\uc785\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.Databricks\uc758 Terraform\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\u0000\u0000\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/romit-jadhwani\/#","text":"Romit Jadhwani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRomit JadhwaniSr. Director, Data Analytics, Engineering and Integrations at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks MarketplaceMarketplace ouverte pour les donn\u00e9es, l'analytique et l'IAD\u00e9marrerTo play this video, click here and accept cookiesQu'est-ce que Databricks\nMarketplace\u00a0?\nBas\u00e9e sur le standard open source Delta Sharing, Databricks Marketplace est une place de march\u00e9 ouverte pour tous vos outils de donn\u00e9es, d'analytique et d'IA. Databricks Marketplace \u00e9largit vos possibilit\u00e9s d'innovation et vous aide \u00e0 progresser dans toutes vos initiatives d'analytique et d'IA.\u00a0\nObtenez des jeux de donn\u00e9es, ainsi que des assets d'IA et d'analytique \u2013 mod\u00e8les ML, notebooks, applications et tableaux de bord \u2013 sans d\u00e9pendre d'une plateforme propri\u00e9taire, suivre un processus ETL complexe ni payer de frais de r\u00e9plication. Gr\u00e2ce \u00e0 cette approche ouverte, vous allez exploiter les donn\u00e9es de tous vos clouds plus rapidement, avec les outils de votre choix.D\u00e9couvrez plus que des donn\u00e9esLib\u00e9rez l'innovation et faites progresser les initiatives de votre entreprise dans les domaines de l'IA, du ML et de l'analytique. Au-del\u00e0 des jeux de donn\u00e9es, acc\u00e9dez \u00e0 des mod\u00e8les ML, des notebooks, des applications et des solutions.\u00c9valuez plus rapidement les produits de donn\u00e9esGr\u00e2ce aux notebooks pr\u00e9d\u00e9finis et aux donn\u00e9es d'\u00e9chantillonnage, vous allez pouvoir \u00e9valuer rapidement les produits de donn\u00e9es et d\u00e9terminer en toute confiance s'ils sont adapt\u00e9s \u00e0 vos initiatives d'IA, de ML ou d'analytique.Gardez votre ind\u00e9pendance vis-\u00e0-vis des fournisseursR\u00e9duisez sensiblement le temps n\u00e9cessaire pour produire des insights et gardez votre ind\u00e9pendance en profitant d'un syst\u00e8me de partage et de collaboration \u00e0 la fois ouvert et transparent, couvrant l'ensemble des clouds, r\u00e9gions et plateformes. Int\u00e9grez directement les outils de votre choix et conservez vos workflows habituels.Fournisseurs de donn\u00e9es pr\u00e9sents sur Databricks MarketplaceDevenez fournisseur de donn\u00e9es sur notre marketplace\nRessources\u00c9v\u00e9nementInscrivez-vous d\u00e8s aujourd'hui pour la conf\u00e9rence Data + AI Summit 2023S'INSCRIREe-bookData Sharing, une nouvelle approche du partage des donn\u00e9esLire la suitee-bookDonn\u00e9es, analyses et gouvernance de l'IALire la suiteConf\u00e9renceGouvernance et partage des donn\u00e9es sur le lakehouse au Data + AI Summit 2022 BlogsLancement de la version anticip\u00e9e publique de MarketplaceLancement de Databricks Marketplace lors de Data + AI Summit 2022DocumentationAWSAzureGCPProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/glossary\/lambda-architecture","text":"What Is Lambda Architecture?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLambda ArchitectureAll>Lambda ArchitectureTry Databricks for freeGet StartedWhat is Lambda Architecture?Lambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solve the problem of computing arbitrary functions. The lambda architecture itself is composed of 3 layers:Batch LayerNew data comes continuously, as a feed to the data system. It gets fed to the batch layer and the speed layer simultaneously. It looks at all the data at once and eventually corrects the data in the stream layer. \u00a0Here we can find lots of ETL and a traditional data warehouse. This layer is built using a predefined schedule, usually once or twice a day. The batch layer has two very important functions:To manage the master datasetTo pre-compute the batch views.Serving LayerThe outputs from the\u00a0batch layer in the form of batch views and those coming from the speed layer in the form of near real-time views get forwarded to the serving. \u00a0This layer indexes the batch views so that they can be queried in low-latency on an\u00a0ad-hoc basis.Speed Layer (Stream Layer)This layer handles the data that are not already delivered in the batch view due to the latency of the batch layer. In addition, it only deals with recent data in order to provide a complete view of the data to the user by creating real-time views.Benefits of lambda architecturesHere are the main benefits of lambda architectures:No Server Management \u2013 you do not have to install, maintain, or administer any software.Flexible Scaling \u2013 your application can be either automatically scaled or scaled by the adjustment of its capacityAutomated High Availability \u2013 refers to the fact that serverless applications have already built-in availability and faults tolerance. It represents a guarantee that all requests will get a response about whether they were successful or not.Business Agility \u2013 React in real-time to changing business\/market scenariosChallenges with lambda architecturesComplexity \u2013 lambda architectures can be highly complex. Administrators must typically maintain two separate code bases for batch and streaming layers, which can make debugging difficult.RelatedDelta Lake: Unified batch and streaming source and sinkTo play this video, click here and accept cookiesAdditional ResourcesDelta Architecture, a Step Beyond Lambda Architecture WebinarApplying the Lambda Architecture with SparkLambda Architecture with Spark in the IoTBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeff-mroz","text":"Jeff Mroz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeff MrozTechnical SME for Cloud and Big Data at Woolpert \/ US Army Corps of EngineersBack to speakersJeff Mroz is a Woolpert technical Cloud SME working for government clients on Azure cloud data modernization and architecture, CI\/CD pipeline development, Geospatial Big Data and Lake House workflows, and cloud R&D projects in secure government clouds.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/bayesian-neural-network","text":"What is a Bayesian Neural Network?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBayesian Neural NetworkAll>Bayesian Neural NetworkTry Databricks for freeGet StartedWhat Are Bayesian Neural Networks?Bayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology so that everything has a probability distribution attached to it, including model parameters (weights and biases in neural networks). In programming languages, variables that can take a specific value will turn the same result every-time you access that specific variable. Let\u2019s begin with the revision of a simple linear model, which will predict the output by the weighted sum of a series of input features.  In comparison, in the Bayesian world, you can have similar entities also known as random variables that will give you a different value every time you access it. \u00a0In Bayesian terms, the historical data represents our prior knowledge of the overall behavior with each variable having its own statistical properties which vary with time. Let\u2019s assume that X is a random variable which represents the normal distribution, every time X gets accessed, the returned result will have different values This process of getting a new value from a random variable is called sampling. What value comes out depends on the random variable\u2019s associated probability distribution. That means, in the parameter space, one can deduce the nature and shape of the neural network's learned parameters. Recently there has been a lot of activity in this area, with the advent of numerous probabilistic programming libraries such as PyMC3, Edward, Stan etc. Bayesian methods are used in lots of fields: from game development to drug discovery.What Are Some of the Main Advantages of BNNs?Bayesian neural nets are useful for solving problems in domains where data is scarce, as a way to prevent overfitting. Example applications are molecular biology and medical diagnosis (areas where data often come from costly and difficult experimental work).Bayesian nets are universally usefulThey can obtain better results for a vast number of tasks however they are extremely difficult to scale to large problems.BNNs allow you to automatically calculate an error associated with your predictions when dealing with data of unknown targets.allow you to estimate uncertainty in predictions, which is a great feature for fields like medicineWhy should you use Bayesian Neural Networks?Instead of taking into account a single answer to one question, Bayesian methods allow you to consider an entire distribution of answers. With this approach, you can naturally address issues such as:regularization (overfitting or not),model selection\/comparison,without the need for a separate cross-validation data setAdditional ResourcesScalable Bayesian Inference with Spark, SparkR, and Microsoft R ServerBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/fabio-luis-correia-da-silva\/#","text":"Fabio Luis Correia da Silva - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFabio Luis Correia da SilvaArchitecture Specialist at BradescoBack to speakersFabio Correia is an Architecture Specialist with over 35 years of experience in software development and analytical solutions. He has worked for companies in publishing, telecommunications, finance and technology sectors, always leading high performance development teams. He has been working for Bradesco since 2016. At Bradesco, Fabio joined the team responsible for implementing the Big Data Environment and now he is responsible for the Cloud Architecture for Data and Analytics, allowing business areas to efficiently transform data into value. Besides loving collectibles, Fabio loves street running and everything related to this sport. In his free time, he likes to study new running shoes technologies and he is currently training for a 30Km competition, with an eye on his first marathon in the near future.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/demos\/deltasharing","text":"Data Sharing with Databricks Delta Sharing - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Sharing DemoGet started for freeTo play this video, click here and accept cookiesData sharing and data collaboration have become important in today\u2019s hyper-connected digital economy. Until now, the lack of a standards-based data sharing protocol has resulted in data sharing solutions tied to a single vendor or commercial product, resulting in vendor lock-in. Databricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform \u2014 without the hassle of replication \u2014 so you can reach your customers where they are.In this brief demonstration, discover how you can:Share live data from where it lives, without replicating or moving it to another systemEasily share existing data in Delta Lake and Apache Parquet formats. Recipients do not have to be on the Databricks platform, the same cloud or a cloud at allDrive collaboration with your partners, suppliers and lines of businessMeet governance, security and compliance needs while sharing assetsAccelerate time to value by consuming shared data directly from the tools of your choiceSee full list of demosDive deeper into Delta SharingLearn moreLearn moreCreate your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryGet started for freeReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/google-cloud?itm_data=menu-item-gcpProduct","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks on Google CloudOpen lakehouse platform meets open cloud to unify data engineering, data science and analyticsGet startedDatabricks on Google Cloud is a jointly developed service that allows you to store all your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all your analytics and AI workloads. Tight integration with Google Cloud Storage, BigQuery and the Google Cloud AI Platform enables Databricks to work seamlessly across data and AI services on Google Cloud.\nReliable data engineeringSQL analytics on all your dataCollaborative data scienceProduction machine learning\nWhy Databricks on Google Cloud?OpenBuilt on open standards, open APIs and open infrastructure so you can access, process and analyze data on your terms.OptimizedDeploy Databricks on Google Kubernetes Engine, the first Kubernetes-based Databricks runtime on any cloud, to get insights faster.IntegratedGet one-click access to Databricks from the Google Cloud Console, with integrated security, billing and management.Learn more from these customers\n\u201cDatabricks on Google Cloud simplifies the process of driving any number of use cases on a scalable compute platform, reducing the planning cycles that are needed to deliver a solution for each business question or problem statement that we use.\u201d\u2014 Harish Kumar, the Global Data Science Director at ReckittStreamlined integration with Google CloudGoogle Cloud StorageGoogle Cloud StorageEnable seamless read\/write access for data in Google Cloud Storage (GCS) and leverage the Delta Lake open format to add powerful reliability and performance capabilities within Databricks.Google Kubernetes EngineBigQueryBig Cloud IdentityGoogle Cloud AI PlatformGoogle Cloud BillingLookerPartner ecosystemResourcesVirtual EventsVirtual Workshop: The Open Data LakeNewsDatabricks Partners With Google Cloud to Deliver Its Platform to Global BusinessesBlogs and ReportsAnnouncing the Launch of Databricks on Google CloudIntroducing Databricks on Google Cloud \u2013 Now in Public PreviewDatabricks on Google Cloud DatasheetDatabricks on Google Cloud Now Generally AvailableData Engineering, Data Science and Analytics With Databricks on Google CloudReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jordan-peck\/#","text":"Jordan Peck - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJordan PeckPrincipal Technical Account Manager at SnowplowBack to speakersJordan Peck is Principal Technical Account Manager at Snowplow in Leeds, UK. He helps Snowplow's strategic customers unlock the full potential of the platform, with expertise in data modelling, behavioral tracking design and activating new use cases with behavioural data. With these expertise, Jordan helps Snowplow's most complex and strategic customers create tailored solutions to meet their unique challenges and build valuable data applications using Snowplow's cutting-edge technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/open-banking","text":"Open BankingPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWOpen BankingAll>Open BankingTry Databricks for freeGet StartedWhat is Open Banking?Open banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of customer data to non-bank third parties, consumers, etc. The innovation is both evolving the industry toward hyper-relevant, platform-based distribution and giving banks a rich opportunity to expand their ecosystems and extend their reach into new markets. With open banking, more financial service institutions (FSIs) expand access to customer data through application programming interfaces (APIs) and other data sharing models.\nA wave of change is coming as Open Banking initiatives and regulations mature and enable the creation of the open data economy. One early indication is the rapid growth of third-party providers (TPPs) in Europe, which is at the forefront of the Open Banking paradigm. There, TPPs have grown from around 100 to more than 450 in under two years, and their focus has expanded from payments and transactional retail banking to encompass the entire financial value chain.29% of banks' traditional retail products-based revenue streams are at risk.55% boost to banking revenue expected by 2020 from new opportunities created by open API-enabled services.Regulations on Open Banking have been vastly different between Europe and the U.S. As a result, Open Banking adoption in Europe has been largely regulatory-driven (this regulatory initiative is called PSD2) while in the US, open banking has and will likely continue to be market-driven.86%8 out of 1094%$9.9Bnof financial institutions recognize the value of Open Banking datafinancial institutions are adopting or plan to adopt Open Bankingof FinTech companies have considered how Open Banking can enhance current servicesestimated total Open Banking sector revenues by 2022Source: \"Open Banking: Rearchitecting the Financial Landscape\", FT Partners Research, March 2021; and OpenBanking.org, \"Facts and Statistics\"What is the history of Open Banking?Starting in the mid 2000s, regulations in Europe such as Payment Services Directive 1 (PSD1) was implemented to regulate and harmonize payments within Europe and assuage concerns surrounding security, data privacy and speed. PSD2 was drafted in 2013 and launched in 2018 to promote further interoperability between financial institutions and third parties. While PSD2 requires banks to open up their data, Open Banking Directive is a UK-specific initiative that requires banks to open up their data in a secure and standardized format in order to improve security as well as ease of use. This data includes customer financial data and transactions and is shared with third party providers only with the user's consent. While Open Banking began in the UK, it has spread to a number of countries in Asia and the United States.Why is Open Banking important?Open banking is more than a compliance exercise; it is an opportunity to enhance the customer experience. Heightened consumer expectations are driving banks to build open APIs \u2013 67% of financial customers say they would share more data with banks in return for more benefits.3 Open banking allows banks to offer personalized finance (refer to Glossary: Personalized Finance) with open APIs or through banking-as-a-service (BaaS) platforms. For customers, open banking provides greater flexibility in how their money is managed allowing, for instance, better visibility of accounts and more convenient access to payments.\nThe value of Open Banking will initiate mostly in retail channels. Strategic partnerships within larger, mutually beneficial ecosystems will position banks to be visible and present to sell their offers whenever and wherever there's an opportunity. Banks can also provide developers with portals and sandboxes to build and test applications; following authorization, third party applications that securely access financial data can be offered to consumers. Because of this, a greater number of companies are able to compete in the financial services landscape, which should result in greater competition and rapid innovation in the market. Source: \"Financial services unchained: The ongoing rise of open financial data,\" Mckinsey, July 2021What are the challenges with Open Banking integrations?4API performance and reliability. While developers can create public APIs to enable open banking, there's no guarantee the APIs will work reliably, especially across the various third-party applications and end-user configurations that they need to support. Testing third-party APIs is more important than ever.Consumer worries. Consumer hesitancy towards open banking can be attributed to privacy and security concerns around sharing their transactional data. It is perceived as one of the most sensitive forms of information, and as a result, the friction around the privacy and security of open banking is one of the most significant barriers.Lack of standardized compliance standards. Developers must contend with varying global compliance rules when creating open banking applications. This means there are no universal technical standards that define exactly how open banking integrations should work or how they can be used.How does Databricks help financial institutions with Open Banking standards and implementation?Lakehouse for Financial Services supports real-time analytics, business intelligence, and AI capabilities on all data types through a secure, multi-cloud environment. Specific solutions included for important financial use cases like open banking, compliance and regulatory reporting, post-trade analysis, risk management, and fraud detection.In addition, Databricks Lakehouse has two sets of integration.First, Databricks Delta Sharing empowers standardized, real-time data sharing with leading financial data providers like Nasdaq, FactSet and Intercontinental Exchange, making it easier to consume, share and monetize data through the platform. Second, it is also integrated with Legend, a cornerstone project of FINOS \u2014 the Fintech Open Source Foundation and a financial sector project of The Linux Foundation \u2014 to create an open ecosystem based on common standards for financial data throughout the entire banking ecosystem.\nThe potential benefits of open banking are substantial: improved customer experience, new revenue streams, and a sustainable service model for traditionally underserved markets, according to Mckinsey.5 Banks that do not build open APIs risk being left behind as consumers continue to shift to digital payments and banking applications.What are the benefits of leveraging Databricks for open banking\/open finance?Lakehouse for Financial Services enables banks and open banking aggregators to address the challenge of merchant classification to enrich card transaction data with contextual information and gain further insights on transaction behaviors. With Lakehouse, FSs are able to unify data and AI on an open and collaborative platform to deliver personalized customer experiences, minimize risk, and accelerate innovation. The Lakehouse platform is:Secure. PCI-DSS compliance for card transaction data and personal informationScalable. Ability to process billions of card transaction data categorized for millions of consumers and merchantsCollaborative. Combining ML models and domain expertise to learn spending behaviors that drive segmentation.2 www.openbank.org\/customers\/what-is-open-banking3 https:\/\/www.accenture.com\/_acnmedia\/accenture\/next-gen-3\/dandm-global-research-study\/accenture-financial-services-global-distribution-marketing-consumer-study.pdfla=en4 https:\/\/www.rtinsights.com\/4-challenges-for-open-banking-integration\/5 https:\/\/www.mckinsey.com\/industries\/financial-services\/our-insights\/data-sharing-and-open-bankingAdditional ResourcesBig Book of Use Cases in Financial ServicesGartner\u00ae Hype Cycle\u2122 for Financial Data and Analytics Governance, 2022Lakehouse for Financial Services solutionsTransaction Enrichment With Merchant Classification AcceleratorGeospatial Clustering AcceleratorBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rong-ma\/#","text":"Rong Ma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRong MaSoftware Engineer at intelBack to speakersRong Ma is a software engineer from Intel data analytics team. She has two years\u2019 experience in bigdata and cloud system optimization, focusing on computation, storage, network software stack performance analysis and optimization. She participated in the development works including Spark-Sql, Spark-Shuffle optimization, cache implementation, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/frank-munz","text":"Frank Munz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFrank MunzPrincipal Technical Marketing Engineer at DatabricksBack to speakersDr. Frank Munz works as a Principal Technical Marketing Engineer at Databricks after kickstarting DevRel EMEA. Previously, Frank built up technical evangelism for Amazon Web Services in Germany, Austria and Switzerland. Frank\u2019s focus is on Cloud strategies, Machine Learning, cloud-native\/containers, big & fast & non-relational data and High-Performance Computing.\nWith over 22 years of professional experience in distributed systems, Java Enterprise, microservices, SOA, and cloud computing, Frank has published 17 scientific articles in computer science and brain research as well as three computer science textbooks with some of them used by lecturers of US universities.\nHe trained keynote speakers for events with up to 3.500 attendees from many verticals including clinical research, pharmacy and genomics. Frank still presents regularly at conferences all over the world such as Devoxx, Java One, JConf, Voxxed Days, Code One, and KubeCon. \nHis prolific global and cross-industry experience in IT was awarded the Technologist of the Year Award for Cloud Computing and nominated as an independently working Oracle ACE Director. 2017 he was nominated as one of the first Developer Champions worldwide.\nFrank holds a Ph.D. with summa cum laude (1,0) in computer science from the Technische Universit\u00e4t M\u00fcnchen where he spent 4 years in supercomputing and distributed systems. He developed distributed functional algorithms for human brain research, cardiology and oncology. \nFrank sold his first computer program (a kind of mini e-business suite) with 16 years. After having jobs as a furniture mover in Paris he was hired as a data scientist at the German Cancer Research Center with the team of Prof. zur Hausen. The study Frank worked on won the Nobel prize in medicine for linking a human virus (HPV) to the development of cancer. The vaccine in use today saves over 30k people in the US from developing cancer.\nJust recently Frank unlocked his goal to present at major conferences on every continent except Antarctica (because it is so cold there). He enjoys writing about himself in the third person.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kasey-uhlenhuth","text":"Kasey Uhlenhuth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKasey UhlenhuthStaff Product Manager at DatabricksBack to speakersKasey Uhlenhuth is a product manager on the machine learning platform team at Databricks. Before Databricks, she worked on the Visual Studio and C# team at Microsoft building developer productivity tools. Kasey holds an MBA from the Stanford Graduate School of Business and a BA in Computer Science from Harvard University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/built-on-partner-program","text":"Built on Databricks Partner Program | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBuilt on Databricks Partner ProgramBuild, market and grow your business with DatabricksApply nowThe Built on Databricks Partner Program provides access to technical and go-to-market resources to accelerate development of your modern SaaS application and grow your business. Building on the Databricks Lakehouse Platform provides a cost-effective, unified experience to develop data applications, products and services, and seamlessly share data at scale with a global open ecosystem.Built on Databricks companies are unlocking business value at scaleBlogRead nowWebinarView nowBlogRead nowBuilt on Databricks partner benefitsAccess Databricks experts\nConnect with Databricks product, engineering and support staffBuild on a modern platform\nLeverage the market-leading Lakehouse Platform for unified data, analytics and AIReach more customers\nExpanded reach to any data customer from one open, secure platformMarketing support\nAccess marketing investments to help increase exposure and scale your reachSales collaboration\nDevelop more opportunities through enablement and collaboration with Databricks salesGet started today!Apply nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/megan-fogal","text":"Megan Fogal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMegan FogalSolutions Architect at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nabil-raad","text":"Nabil Raad - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNabil RaadSVP of Data and Analytics at GM FinancialBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kyle-hale","text":"Kyle Hale - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKyle HaleProduct Specialist at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/company\/partners\/technology-partner-program","text":"Programa de parcerias de tecnologia da Databricks | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPrograma de parceiros de tecnologiaInteraja com milhares de clientes da Databricks prontos para usar seu produtoInscreva-se agoraA Databricks se integra aos melhores produtos de dados e IA do mercado para promov\u00ea-lo. Fornecemos aos nossos parceiros o suporte t\u00e9cnico de entrada no mercado de que precisam para adquirir novos clientes e expandir neg\u00f3cios.Benef\u00edcios para parcerias de tecnologiaIncentivos de vendasIncentivos para equipes de campo da Databricks para ajudar a vender seu produtoAcesso de clientesAdquira novos clientes diretamente atrav\u00e9s do Databricks Partner ConnectSaiba maisSuporte de marketingAcesse investimentos de marketing para ajudar a expandir seu alcanceAcesso \u00e0 equipe de produto e P&DTenha acesso \u00e0s equipes de produto, engenharia e suporte da DatabricksAmbiente de sandbox gratuitoCrie e teste em um ambiente de sandbox gratuitoProgramas de marketing conjuntosParticipe de programas de marketing conjuntos com a DatabricksTudo pronto para se conectar?Inscreva-se agoraEncontrar uma parceriaProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-hayes\/#","text":"Matthew Hayes - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew HayesVice President of SAP Business at QlikBack to speakersMatthew Hayes is the Vice President of SAP Business at Qlik. He has been innovating solutions for the SAP market for over 20 years. With a strong technical background in SAP, Matt developed Gold Client for handling SAP Test Data Management. Currently, he works to extend Qlik\u2019s offerings to the SAP market and focuses on enabling those solutions for SAP customers and technology partners. Matt is based in Chicago and in the summer months prefers to work remotely from Wrigley Field.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/robinson-creighton\/#","text":"Robinson Creighton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRobinson CreightonPrincipal Analyst, Enterprise Data Ops at Comcast AdvertisingBack to speakersRobinson \"Robs\" Creighton is Sr. DataOps Lead, Advanced Analytics, for Comcast Effectv, responsible for their data stack architecture and lakehouse migration. Previously, she worked as a data analyst at Northwestern Mutual. She is a graduate of the University of Pennsylvania.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/support","text":"Support | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Support PolicyDatabricks provides a number of plans that provide you with dedicated supportand timely service for the Databricks platform and Apache Spark.FeatureBusinessEnhancedProductionMulti-Cloud SupportSupport for Databricks on permitted Cloud Service Providers and Databricks-Powered Services; Complimentary Success Credits available based on commitment size--YesYesSingle-Cloud SupportSupport for Platform Services on a single-chosen Cloud Service ProviderYesYesYesSupport Portal AccessOnline repository of documentation, guides, best practices, and more.YesYesYesUpdates & PatchesReceive updates, bug fixes, and patches without impact to your business.YesYesYesService Level Agreement (SLA)Receive support responses according to issue severity.Initial Response TimeInitial Response TimeInitial Response TimeStandard Support Severity 1Production system is down or severely impacted such that routine operation is impossible1st contact response\ntime: within 1\nbusiness day1st contact response\ntime: within 4 Hours1st contact response\ntime: within 1 HourStandard Support Severity 2Production issue where the system is functioning but in degraded or restricted capacity1st contact response\ntime: within\n1 business day1st contact response\ntime: within\n1 business day1st contact response\ntime: within 4 HoursStandard Support Severity 3Issue where minor functionality is impacted or a development issue occurs1st contact response\ntime: within 1\nbusiness day1st contact response\ntime: within 1\nbusiness day1st contact response\ntime: within 1\nbusiness dayStandard Support Severity 4Request for information or feature request with no impact on business operations\u00a0\u00a0\u00a0Support Service HoursLive support during customer\u2019s choice of time zone.9am \u2013\u00a06pm,\nBusiness Days*9am \u2013\u00a06pm,\nBusiness Days*Severity 1 & 2: 24x7x365,Severity 3 & 4: 9am \u2013 6pm,\nBusiness Days*Databricks Standard SupportLimited to break-fix support for the Databricks platform.YesYesYesDatabricks Chat Support Channel**Per customer dedicated real-time messaging (e.g., Slack, MSFT Teams) channel available during business hours* for informal communication between the two teams, such as basic questions and information exchange.NoOptional UpgradeYesMax Number of Technical Contacts\u2020The number of technical Contacts with access to the Databricks Help Center or Chat Support Channel (if available)248Databricks' Support for Spark\u2020\u2020Prioritized access to the world\u2019s leading Spark technical experts for troubleshooting problems using the product and services.Up to 2\nhours\/month\u2020Up to 4\nhours\/month\u2020Up to 8\nhours\/month\u2020* Support business hours are from Monday through Friday, from 9AM to 6PM (North America timezones (EST\/CST\/PST\/MST), Central Europe (CET), Singapore\/China (SGT\/CST) and Australia Eastern (AET) Timezone). Support business hours exclude local holidays in each timezone.**Chat Support channel is not covered under the Support SLA response times.\u2020 \u201cContact\u201d means a unique named user at Customer (whether by email address, chat ID); accounts may not be shared.\u2020\u2020 Additional assistance beyond the original limits can be purchased as Advisory Services which will be delivered by our professional services team.If no support is specified in an Order, Customer\u2019s support shall be limited to public documentation and open resources on the Databricks Help Center.View the resources available through our Customer Support Handbook for more information on support definitions, processes and terms.To accelerate your data projects, we recommend our Guided Success Subscriptions which complement Support by providing you with ongoing assistance from a Databricks expert, proactive recommendations, and technical coaching.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ganesh-deivarayan\/#","text":"Ganesh Deivarayan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGanesh DeivarayanSr Manager at American AirlinesBack to speakersCurrently leading the TechOps Data Strategy \nand Cloud Engineering StrategyLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/faq\/#","text":"FAQ - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQA's to your Q'sWhat is Data + AI Summit?This year, Data + AI Summit will be both in-person and online, bringing together the open source community to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse.\nJoin in-person in San Francisco to experience two keynotes, 200+ sessions, meetups, industry forums, an expo hall with over 100 sponsors, add-ons like hands-on training and certifications, and fun events like the Welcome Reception and Summit party. Learn more by exploring the Session Catalog or the Why Attend pages.\nCan\u2019t make it to the in-person event? Join thousands of attendees online to view the two keynotes, \u00a010live streamed breakout sessions and live interviews with Databricks executives and industry experts for the virtual event.\nWhen and where will the Data + AI Summit take place?Data + AI Summit will take place in San Francisco, CA at the Moscone Center, South during June 26 - 29. A few select Summit events will take place at the Intercontinental, San Francisco - a short walk from Moscone Center. Learn more about the in-person event and register now.\nHow much does the in-person Data + AI Summit cost to attend? Are there any group or special discounts?A full conference pass costs $1,795. Group discounts are available for purchases of 4 or more and a special discount for GOV\/EDU\/NFP. Visit the pricing page for details.\nWhen and where will the free virtual event take place?The free Virtual Data + AI Summit will be held June 28 - 29 on https:\/\/www.databricks.com\/dataaisummit\/. Learn more about the free virtual event and register now.\u00a0\nWill sessions be recorded and available after the event?Majority of the 200 breakout sessions delivered at the in-person event in San Francisco will be recorded and available on-demand on https:\/\/www.databricks.com\/dataaisummit\/. On-demand sessions can be accessed by registering for either the in-person and virtual events. These sessions will be available within a week of the live event.\nWhat topics and technologies will be covered and who are the speakers at the Data + AI Summit?With more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, lightning talks, industry forums, and more. Speakers include top experts, researchers and open source contributors from Databricks and across the data and AI community. \u00a0Learn more by exploring the Session Catalog, Speaker and \u00a0Why Attend pages.\nCan I pre-register or reserve a seat for sessions?There is no reserved seating or pre-registration for sessions. The most popular sessions will be repeated. Attendees can also plan ahead by viewing the session scheduler (available at the end of May) and creating their own custom agenda.\nWhat training course add-ons are available?Build and expand skills with pre-conference training. More than 15 instructor-led, hands-on training courses are available to be added on to your full conference pass. The trainings are either full or half-day, include both lecture, hands-on exercises and live Q&A and are available for all levels. See the full training schedule here.\nTraining add-ons are available for a fee. View prices here. Sign up for training during your Summit registration or if you have already registered but didn\u2019t add training, you can edit your registration details to add it at any time via the registration portal.\nCan I attend a training without attending the Summit?No. To sign up for trainings, you must select your desired course during registration or if you are already registered, you can add it any time via the registration portal.\nHow do I qualify for a group rate for training?Group rates are offered to groups of four or more attendees registering for training together. Contact [email\u00a0protected] to receive a group rate discount code.\nWill certification exams be available?Yes, we are offering the opportunity for in-person attendees to leverage complimentary Databricks certification exams ($200 USD value). The exams are 90-120 minutes long. The following Databricks certification exams qualify:\n\nDatabricks Certified Associate Developer for Apache Spark\u2122 3.0 \u2013 Python\nDatabricks Certified Associate Developer for Apache Spark\u2122 3.0 \u2013 Scala\nDatabricks Certified Data Analyst Associate \u00a0\nDatabricks Certified Data Engineer Professional\nDatabricks Certified Data Engineer Associate\nDatabricks Certified Hadoop Migration Architect\nDatabricks Certified Machine Learning Associate\nDatabricks Certified Machine Learning Professional\n\nHow do I make a change to my registration?If you need to update your registration, please send an email to the registration help desk.\nWhat is the cancellation policy?Substitutions\nSubstitution requests can be processed in person onsite or via written request, please contact the Help Center. If requested in writing, please provide the names and emails of both the original and substitute registrants with both parties copied in the email. All requests for substitutions must be received no later than 5:00 PM (PDT) on June 23, 2023. Onsite substitutions will incur a US $50 processing fee.\nCancellations\nThe Databricks Registration Team must receive all cancellation requests in writing; please contact the Help Center by June 21, 2023.\nRefunds\nWe will issue a full refund, minus a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PDT. Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PDT, will be issued a 50% refund, minus a 10% cancellation fee. No refunds will be offered for paid items after May 26, 2023.\nRefunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record. If you have not received a refund by July 1, 2023, please contact the Help Center.\n\u00a0\nCan someone attend in my place?Yes, if you are unable to attend please send an email to the registration help desk to initiate the substitution.\nAre there hotel blocks available?Yes, Databricks has reserved hotel blocks for Data + AI Summit. During your registration process, you will have the opportunity to book your room. Inventory is limited, available on a first-come, first-booked basis, and our discounted rates are only available until June 1 so book now in the attendee portal.\nReserved hotel blocks are available at The Canopy, Hyatt Regency Soma, Intercontinental, Marriott Union Square, Parc 55, The Clancy, The W and Westin St Francis.\nWhat prices are secured for attendees looking to book a hotel?\u00a0\n\n\n\nHotel\nGroup Rate\n\n\n\n\nW Hotel\n$349\n\n\nParc 55\n$309\n\n\nThe Clancy\n$339\n\n\nJW Marriott\n$329\n\n\nMarriott Union Square\n$309\n\n\nSt Regis\n$565\n\n\nHyatt Downtown SOMA\n$329\n\n\nIntercontinental\n$365\n\n\nWestin St Francis\n$359\n\n\nHilton San Francisco\n$309\n\n\n\n\u00a0\nHow do I make changes to an existing hotel reservation?Attendees may access their existing reservation to make changes via their confirmation email. Please click on the registration link within the email and make desired edits. Please remember to submit your changes.\nWhat is the hotel cancellation policy?The cancellation policy varies from property to property; typically 24 or 72 hours. Each cancellation policy is published within the housing portion of the registration. After the cancellation deadline has passed, attendees will be charged for the cost of one room night should they cancel or postpone their arrival date.\nIf I cancel my Summit registration, can I transfer my hotel reservation to another attendee?No. Credit card data may not transfer from one attendee to another, which makes transferring hotel confirmations from one to another not feasible.\nCan I book multiple rooms on my registration for myself and a colleague?Attendees may book only one hotel reservation under their registration.\nWhat if I don\u2019t check in on my scheduled arrival date?Guests who do not arrive on their confirmed check-in date will be charged a no-show fee by the hotel property, equal to (1) nights rate.\nDo I need a credit card to reserve a room?Yes. All attendees must provide a credit card in order to secure a guest room.\nCan I contact the hotel directly to make a hotel reservation and receive the discounted Summit rate?The group rate is available through group registration only.\nCan I contact the hotel directly to change my existing reservation?Please make edits to your reservation directly in the registration so that when the hotel pulls your reservation information, they capture all changes you require.\nOnly after the hotel cut-off date (June 1 or June 9, depending on the property you secure) can you contact the hotel directly for changes.\u00a0\nWhen will I receive my hotel confirmation?Hotel confirmations will be shared on June 16th.\nI want to arrive earlier\/stay later than the system is showing as available. How can I adjust my reservation?Guest room inventory within the registration platform is based on first come\/first serve. You are welcome to secure your extension directly with the hotel (at rack rate) and then ask the hotel to \u201clink\u201d your two reservations.\u00a0\nYou may also secure your own reservation, including your early\/late stay dates, at a property outside of what is offered on the group registration.\u00a0\nWhat are the health protocols in place for the Data + AI Summit?The health of our attendees is very important to us. As of now, we are not requiring vaccinations or masks. We acknowledge this is an ever-changing landscape and we are deeply committed to staying abreast of updated guidance from the Centers for Disease Control and Prevention (CDC) and federal, state, and local governments. Databricks reserves the right to adjust these protocols if guidance changes.\nWhat are the safety and security protocols in place for the Data + AI Summit?Your safety at the event is our top priority. You will likely see a strong security presence, and there will also be many people working behind the scenes to help keep you safe. We\u2019re prepared to respond to incidents in partnership with local, state, and federal authorities.\nEveryone will be required to show an ID when checking in at registration and will be required to wear their badge for all Data + AI Summit official events. We\u2019ll have metal detectors at the entrances to Moscone South. All bags will be subject to search upon entering any conference site.\nAre there any items I can\u2019t bring to the event?Prohibited items within the event space and after hours event space include, but are not limited to:\n\nWeapons, firearms, or knives (regardless of size) or items that can be mistaken as a weapon.\nPets or other animals, except approved service animals. Service animals should remain on a leash or in a harness and under the control of the owner at all times.\nPersonal mobility devices (with or without a motor) unless for ADA use. This includes but is not limited to: skateboards, hoverboards, bicycles, scooters, uniwheels, and all similar products.\nNo smoking (including e-cigarettes) is allowed within the facility.\nPoles and sticks; selfie sticks.\nLaser lights, laser pointers.\nMace\/pepper spray, tasers, stun guns, or similar devices.\nSharp and\/or pointed objects: razor blades, scissors, knitting needles, screwdrivers, etc.\nWhistles, noisemakers, and\/or sound\/voice enhancement devices, such as bullhorns.\nBanners, signs, or placards unless authorized by production or security management.\nFlashlights, unless authorized by production or security management.\nWi-Fi and\/or Bluetooth signal disruptors.\nTripods for cameras (does not apply to media).\nInflatable items (e.g., balloons).\nDrones, unless authorized by production or security management.\nNo outside alcohol.\nNo illegal substances.\n\nCan I participate as a sponsor in the event?If you are interested in sponsorships or have any sponsorship questions, please contact [email\u00a0protected].\nWhen and how will I receive more information about how to navigate the in-person event in San Francisco?We will be launching a mobile app at the beginning of June. The mobile app will include everything needed to navigate the event including information about meals, transportation, map, agenda and more. We will be sending out a series of emails along with the mobile app launch, which will help you make the most of your experience at Summit.\nWhat is the Data + AI code of conduct and event policies?We are committed to fostering Diversity, Equity and Inclusion. We will continue to create an inclusive event where everyone can learn, collaborate, and build community.\nCode of Conduct\nEvent Policies\nPrivacy Notice\nI still have some unanswered questions. Who can I contact?Send any other questions to the help desk.\nHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/training?itm_data=hp-hamburger-training-dais23","text":"Training - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTrainingLevel up your data and AI skills through one of our Summit trainings. Whether you\u2019re new to the Lakehouse architecture or a seasoned pro looking to dive deep, we have a course for you.\nHide search filtersreset filtersSearchSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/product\/pricing","text":"Databricks-Preise | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWPreisaktion f\u00fcr SQL \u00fcber einen l\u00e4ngeren Zeitraum \u2013 Mehr als 40\u00a0% sparen Unsere 15-monatige Aktion f\u00fcr Serverless SQL und das brandneue SQL Pro nutzenMehr InformationenDatabricks-PreiseEine einfache Plattform, auf der Ihre Daten-, Analytics- und KI-Workloads zusammengef\u00fchrt werden \u2013 in Ihren bevorzugten CloudsJetzt kostenlos testenWie funktioniert die Preisgestaltung bei Databricks?Nutzungsbasierte AbrechnungDatabricks bietet nutzungsbasierte Abrechnung ohne Vorlaufkosten. Sie zahlen nur f\u00fcr die Produkte, die Sie tats\u00e4chlich nutzen \u2013 und das sekundengenau.Jetzt sparen mit NutzungszusicherungenMit Databricks k\u00f6nnen Sie Ihre Kosten senken, indem Sie einen gewissen Nutzungsumfang zusichern und dadurch von Rabatten profitieren. Je umfangreicher die zugesicherte Nutzung, desto h\u00f6her ist auch Ihr Preisnachlass verglichen mit der nutzungsbasierten Abrechnung. Sie k\u00f6nnen die zugesicherte Nutzung dabei auch auf mehrere Clouds verteilen. Wenden Sie sich an uns, um mehr zu erfahren.Produkte erkundenWorkflows und StreamingJobsStarting at $0.07 \/ DBUF\u00fchren Sie Data Engineering-Pipelines aus, um Data Lakes zu erstellen und Daten im gro\u00dfen Ma\u00dfstab zu verwalten.Mehr InformationenWorkflows und Streaming Delta Live TablesStarting at $0.20 \/ DBUErstellen Sie m\u00fchelos hochwertige Streaming- oder Batch-ETL-Pipelines mit Python oder SQL mit der DLT Edition, die f\u00fcr Ihren Workload am besten geeignet ist.Mehr InformationenData-WarehousingDatabricks SQLStarting at $0.22 \/ DBUF\u00fchren Sie SQL-Abfragen f\u00fcr BI-Berichte, Analytics und Visualisierungen aus, um zeitnahe Erkenntnisse aus Data Lakes zu erhalten. Verf\u00fcgbar in Classic und Serverless (verwaltet) Compute.Mehr InformationenData Science und Machine LearningUniversell einsetzbarStarting at $0.40 \/ DBUF\u00fchren Sie interaktive Workloads f\u00fcr Data Science und Machine Learning aus. Auch gut f\u00fcr Data Engineering, BI und Data Analytics geeignet.Mehr InformationenData Science und Machine LearningServerless Real-Time InferenceStarting at $0.07 \/ DBUErstellen Sie Live-Prognosen in Ihren Apps und Websites.\nMehr InformationenDatabricks-Plattform und Add-OnsDatabricks-Plattform und Add-OnsPlattformstufen: Plattform\u00fcbergreifende Funktionen, die das richtige Ma\u00df an Management, Governance und Sicherheit bieten, um alles von einfachen bis hin zu unternehmenskritischen Workloads auszuf\u00fchren\nPlattform-Add-Ons:  Produkt\u00fcbergreifende Erweiterungen der Databricks-Plattform, die verbesserte Management-, Governance- und Sicherheitsfunktionen bietenMehr InformationenDATABRICKS KOSTENLOS TESTENJetzt kostenfrei testenPlanen Sie eine DemoFAQWas ist in der kostenlosen Testversion enthalten?Mit der kostenlosen 14-t\u00e4gigen Testversion erhalten Sie:Eine kollaborative Umgebung, in der Datenteams gemeinsam L\u00f6sungen entwickeln k\u00f6nnenInteraktive Notebooks f\u00fcr die Verwendung von Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn und anderenBitte beachten Sie, dass Ihr Cloud-Anbieter Ihnen w\u00e4hrend der kostenlosen Testphase weiterhin die Kosten f\u00fcr die von Ihrem Konto genutzten Ressourcen (z.\u00a0B. Compute-Instanzen) in Rechnung stellen wird.Was passiert, nachdem die kostenlose Testversion abgelaufen ist?Am Ende der Testversion werden Sie automatisch f\u00fcr den Tarif angemeldet, den Sie w\u00e4hrend der kostenlosen Testversion genutzt haben. Sie k\u00f6nnen Ihre Anmeldung jederzeit k\u00fcndigen.Basiert die Preisgestaltung auf der Nutzung oder dem Speichervolumen?Die Preise f\u00fcr Databricks basieren auf Ihrer Nutzung der Serverressourcen. Kosten f\u00fcr Speicherplatz, Netzwerkverbindungen usw. variieren je nach den von Ihnen gew\u00e4hlten Services und Ihrem Cloud-Anbieter.Was ist eine DBU?Eine DBU (Databricks Unit) ist eine normalisierte Verarbeitungseinheit auf der Databricks Lakehouse-Plattform und dient zu Mess- und Abrechnungszwecken. Wie viele DBUs von einer Workload verbraucht werden, h\u00e4ngt von den Verarbeitungsmetriken ab, zu denen die ben\u00f6tigten Serverressourcen und das verarbeitete Datenvolumen geh\u00f6ren. Sind die Preise in allen Regionen identisch?Databricks-Preise und Preise f\u00fcr die Cloud-Infrastruktur k\u00f6nnen je nach geografischer Region und Cloud-Anbieter variieren. Einzelheiten finden Sie auf den Databricks-Preisseiten f\u00fcr einzelne Produkte.Ist Databricks so kosteneffektiv wie andere Cloud-Services oder Open-Source-L\u00f6sungen?Die Produkte von Databricks sind preislich so gestaltet, dass sie den Kunden \u00fcberzeugende Gesamtbetriebskosten (TCO) f\u00fcr ihre Workloads bieten. Bei der Berechnung Ihrer Einsparpotenziale mit Databricks sollten Sie auf jeden Fall zentrale Aspekte der alternativen L\u00f6sungen pr\u00fcfen. Hierzu geh\u00f6ren etwa die Quote abgeschlossener Jobs, die Jobverarbeitungsdauer und der f\u00fcr die Unterst\u00fctzung eines Jobs erforderliche manuelle Aufwand. Damit Sie Ihre Einsparungen korrekt sch\u00e4tzen k\u00f6nnen, empfehlen wir Ihnen einen Direktvergleich der Ergebnisse im Rahmen einer Machbarkeitsstudie. Ziehen Sie auch die Angaben zu den von diesem Kunden erzielten Geschwindigkeitszuw\u00e4chsen und die Ergebnisse dieser Kunden-Benchmark zurate. Kontaktieren Sie uns, um loszulegen.Worum handelt es sich bei der Databricks Community Edition?Die Databricks Community Edition ist eine kostenlose Plattform mit eingeschr\u00e4nkter Funktionalit\u00e4t. Sie wurde f\u00fcr all diejenigen entwickelt, die Spark kennenlernen m\u00f6chten. Registrieren Sie sich hier.Wie erfolgt die Abrechnung?Die Abrechnung erfolgt standardm\u00e4\u00dfig monatlich \u00fcber Ihre Kreditkarte. Abgerechnet wird Ihre Nutzung unserer Dienstleistungen pro Sekunde. Kontaktieren Sie uns, um mehr \u00fcber weitere Abrechnungsoptionen, z.\u00a0B. die Abrechnung \u00fcber Rechnungsstellung oder einen j\u00e4hrlichen Abrechnungsplan zu erfahren.Bieten Sie technischen Support an?Wir bieten technischen Support an. Sie k\u00f6nnen auch die technische Dokumentation lesen. Kontaktieren Sie uns, um mehr zu erfahren.ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/glossary\/hadoop-distributed-file-system-hdfs","text":"What is Hadoop Distributed File System (HDFS)PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWHadoop Distributed File System (HDFS)All>Hadoop Distributed File System (HDFS)HDFSHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. HDFS is a key component of many Hadoop systems, as it provides a means for managing big data, as well as supporting big data analytics.There are many companies across the globe that use HDFS, so what exactly is it and why is it needed? Let's take a deep dive into what HDFS is and why it may be useful for businesses.What is HDFS?HDFS stands for Hadoop Distributed File System. HDFS operates as a distributed file system designed to run on commodity hardware.HDFS is fault-tolerant and designed to be deployed on low-cost, commodity hardware. HDFS provides high throughput data access to application data and is suitable for applications that have large data sets and enables streaming access to file system data in Apache Hadoop.So, what is Hadoop? And how does it vary from HDFS? A core difference between Hadoop and HDFS is that Hadoop is the open source framework that can store, process and analyze data, while HDFS is the file system of Hadoop that provides access to data. This essentially means that HDFS is a module of Hadoop.Let's take a look at HDFS architecture:As we can see, it focuses on NameNodes and DataNodes. The NameNode is the hardware that contains the GNU\/Linux operating system and software. The Hadoop distributed file system acts as the master server and can manage the files, control a client's access to files, and overseas file operating processes such as renaming, opening, and closing files.A DataNode is hardware having the GNU\/Linux operating system and DataNode software. For every node in a HDFS cluster, you will locate a DataNode. These nodes help to control the data storage of their system as they can perform operations on the file systems if the client requests, and also create, replicate, and block files when the NameNode instructs.The HDFS meaning and purpose is to achieve the following goals:Manage large datasets - Organizing and storing datasets can be a hard talk to handle. HDFS is used to manage the applications that have to deal with huge datasets. To do this, HDFS should have hundreds of nodes per cluster.Detecting faults - HDFS should have technology in place to scan and detect faults quickly and effectively as it includes a large number of commodity hardware. Failure of components is a common issue.Hardware efficiency - When large datasets are involved it can reduce the network traffic and increase the processing speed.The history of HDFSWhat are Hadoop's origins? The design of HDFS was based on the Google File System. It was originally built as infrastructure for the Apache Nutch web search engine project but has since become a member of the Hadoop Ecosystem.In the earlier years of the internet, web crawlers started to pop up as a way for people to search for information on web pages. This created various search engines such as the likes of Yahoo and Google.It also created another search engine called Nutch, which wanted to distribute data and calculations across multiple computers simultaneously. Nutch then moved to Yahoo, and was divided into two. Apache Spark and Hadoop are now their own separate entities. Where Hadoop is designed to handle batch processing, Spark is made to handle real-time data efficiently.Nowadays, Hadoop's structure and framework are managed by the Apache software foundation which is a global community of software developers and contributors.HDFS was born from this and is designed to replace hardware storage solutions with a better, more efficient method - a virtual filing system. When it first came onto the scene, MapReduce was the only distributed processing engine that could use HDFS. More recently, alternative Hadoop data services components like HBase and Solr also utilize HDFS to store data.What is HDFS in the world of big data?So, what is big data and how does HDFS come into it? The term \"big data\" refers to all the data that's difficult to store, process and analyze. HDFS big data is data organized into the HDFS filing system.As we now know, Hadoop is a framework that works by using parallel processing and distributed storage. This can be used to sort and store big data, as it can't be stored in traditional ways.In fact, it's the most commonly used software to handle big data, and is used by companies such as Netflix, Expedia, and British Airways who have a positive relationship with Hadoop for data storage. HDFS in big data is vital, as this is how many businesses now choose to store their data.There are five core elements of big data organized by HDFS services:Velocity - How fast data is generated, collated and analyzed.Volume - The amount of data generated.Variety - The type of data, this can be structured, unstructured, etc.Veracity - The quality and accuracy of the data.Value - How you can use this data to bring an insight into your business processes.Advantages of Hadoop Distributed File SystemAs an open source subproject within Hadoop, HDFS offers five core benefits when dealing with big data:Fault tolerance. HDFS has been designed to detect faults and automatically recover quickly ensuring continuity and reliability.Speed, because of its cluster architecture, it can maintain 2 GB of data per second.Access to more types of data, specifically Streaming data. Because of its design to handle large amounts of data for batch processing it allows for high data throughput rates making it ideal to support streaming data.Compatibility and portability. HDFS is designed to be portable across a variety of hardware setups and compatible with several underlying operating systems ultimately providing users optionality to use HDFS with their own tailored setup. These advantages are especially significant when dealing with big data and were made possible with the particular way HDFS handles data.\nThis graph demonstrates the difference between a local file system and HDFS.Scalable. You can scale resources according to the size of your file system. HDFS includes vertical and horizontal scalability mechanisms.Data locality. When it comes to the Hadoop file system, the data resides in data nodes, as opposed to having the data move to where the computational unit is. By shortening the distance between the data and the computing process, it decreases network congestion and makes the system more effective and efficient.Cost effective. Initially, when we think of data we may think of expensive hardware and hogged bandwidth. When hardware failure strikes, it can be very costly to fix. With HDFS, the data is stored inexpensively as it's virtual, which can drastically reduce file system metadata and file system namespace data storage costs. What's more, because HDFS is open source, businesses don't need to worry about paying a licensing fee.Stores large amounts of data. Data storage is what HDFS is all about - meaning data of all varieties and sizes - but particularly large amounts of data from corporations that are struggling to store it. This includes both structured and unstructured data.Flexible. Unlike some other more traditional storage databases, there's no need to process the data collected before storing it. You're able to store as much data as you want, with the opportunity to decide exactly what you'd like to do with it and how to use it later. This also includes unstructured data like text, videos and images.How to use HDFSSo, how do you use HDFS? Well, HDFS works with a main NameNode and multiple other datanodes, all on a commodity hardware cluster. These nodes are organized in the same place within the data center. Next, it's broken down into blocks which are distributed among the multiple DataNodes for storage. To reduce the chances of data loss, blocks are often replicated across nodes. It's a backup system should data be lost.Let's look at NameNodes. The NameNode is the node within the cluster that knows what the data contains, what block it belongs to, the block size, and where it should go. NameNodes are also used to control access to files including when someone can write, read, create, remove, and replicate data across the various data notes.The cluster can also be adapted where necessary in real-time, depending on the server capacity - which can be useful when there is a surge in data. Nodes can be added or taken away when necessary.Now, onto DataNodes. DataNodes are in constant communication with the NameNodes to identify whether they need to commence and complete a task. This stream of consistent collaboration means that the NameNode is acutely aware of each DataNodes status.When a DataNode is singled out to not be operating the way it should, the namemode is able to automatically re-assign that task to another functioning node in the same datablock. Similarly, DataNodes are also able to communicate with each other, which means they can collaborate during standard file operations. Because the NameNode is aware of DataNodes and their performance, they're crucial in maintaining the system.Datablocks are replicated across multiple datanotes and accessed by the NameNode.To use HDFS you need to install and set up a Hadoop cluster. This can be a single node set up which is more appropriate for first-time users, or a cluster set up for large, distributed clusters. You then need to familiarize yourself with HDFS commands, such as the below, to operate and manage your system.CommandDescription-rmRemoves file or directory-lsLists files with permissions and other details-mkdirCreates a directory named path in HDFS-catShows contents of the file-rmdirDeletes a directory-putUploads a file or folder from a local disk to HDFS-rmrDeletes the file identified by path or folder and subfolders-getMoves file or folder from HDFS to local file-countCounts number of files, number of directory, and file size-dfShows free space-getmergeMerges multiple files in HDFS-chmodChanges file permissions-copyToLocalCopies files to the local system-StatPrints statistics about the file or directory-headDisplays the first kilobyte of a file-usageReturns the help for an individual command-chownAllocates a new owner and group of a fileHow does HDFS work?As previously mentioned, HDFS uses NameNodes and DataNodes. HDFS allows the quick transfer of data between compute nodes. When HDFS takes in data, it's able to break down the information into blocks, distributing them to different nodes in a cluster.Data is broken down into blocks and distributed among the DataNodes for storage, these blocks can also be replicated across nodes which allows for efficient parallel processing. You can access, move around, and view data through various commands. HDFS DFS options such as \"-get\" and \"-put\" allow you to retrieve and move data around as necessary.What's more, the HDFS is designed to be highly alert and can detect faults quickly. The file system uses data replication to ensure every piece of data is saved multiple times and then assigns it across individual nodes, ensuring at least one copy is on a different rack than the other copies.This means when a DataNode is no longer sending signals to the NameNode, it removes the DataNode from the cluster and operates without it. If this data node then comes back, it can be allocated to a new cluster. Plus, since the datablocks are replicated across several DataNodes, removing one will not lead to any file corruptions of any kind.HDFS componentsIt's important to know that there are three main components of Hadoop. Hadoop HDFS, Hadoop MapReduce, and Hadoop YARN. Let's take a look at what these components bring to Hadoop:Hadoop HDFS - Hadoop Distributed File System (HDFS) is the storage unit of Hadoop.Hadoop MapReduce - Hadoop MapReduce is the processing unit of Hadoop. This software framework is used to write applications to process vast amounts of data.Hadoop YARN - Hadoop YARN is a resource management component of Hadoop. It processes and runs data for batch, stream, interactive, and graph processing - all of which are stored in HDFS.How to create an HDFS file systemWant to know how to create HDFS file system? Follow the steps below which will guide you on how to create the system, edit it, and remove it if needed.Listing your HDFSYour HDFS listing should be \/user\/yourUserName. To view the contents of your HDFS home directory, enter:\r\nhdfs dfs -lsAs you're just getting started, you won't be able to see anything at this stage. When you want to view the contents of a non-empty directory, input:\r\nhdfs dfs -ls \/userYou can then see the names of the home directories of all the other Hadoop users.Creating a directory in HDFSYou can now create a test directory, let's call it testHDFS. It will appear within your HDFS. Just enter the below:\r\nhdfs dfs -mkdir testHDFSNow you must verify that the directory exists by using the command you entered when listing your HDFS. You should see the testHDFS directory listed.Verify it again using the HDFS full pathname to your HDFS. Enter:\r\nhdfs dfs -ls \/user\/yourUserNameDouble check that this is working before you take the next steps.Copy a fileTo copy a file from your local file system to HDFS, start by creating a file you wish to copy. To do this, enter:\r\necho \"HDFS test file\" >> testFileThat is going to create a new file called testFile, including the characters HDFS test file. To verify this, input:lsAnd then to verify that the file was created, enter:\r\ncat testFileYou will then need to copy the file to HDFS. To copy files from Linux into HDFS, you need to use:\r\nhdfs dfs -copyFromLocal testFileNotice that you have to use the command \"-copyFromLocal\" because the command \"-cp\" is used to copy files within HDFS.Now you just need to confirm that the file has been copied over correctly. Do this by entering the following:\u00a0\r\ncode>hdfs dfs -ls\r\nhdfs dfs -cat testFile\u00a0Moving and copying filesWhen copying the testfile it was put into the base home directory. Now you can move it into the testHDFS directory you've already created. Use the following:\r\nhdfs dfs -mv testFile testHDFS\r\nhdfs dfs -ls\r\nhdfs dfs -ls testHDFS\/The first part moved your testFile from the HDFS home directory into the test one you created. The second part of this command then shows us that it's no longer in the HDFS home directory, and the third part confirms that it's now been moved to the test HDFS directory.To copy a file, input:\r\nhdfs dfs -cp testHDFS\/testFile testHDFS\/testFile2\r\nhdfs dfs -ls testHDFS\/Checking disk usageChecking disk space is useful when you're using HDFS. To do this you can enter the following command:\r\nhdfs dfs -duThis will then allow you to see how much space you are using in your HDFS. You can also view how much space is available in HDFS across the cluster by entering:\r\nhdfs dfs -dfRemoving a file\/directoryThere may come a time when you need to delete a file or directory in the HDFS. This can be achieved with the command:\r\nhdfs dfs -rm testHDFS\/testFile\r\nhdfs dfs -ls testHDFS\/You'll see that you still have the testHDFS directory and testFile2 leftover that you created. Remove the directory by entering:\r\nhdfs dfs -rmdir testhdfsIt will then pop up with an error message - but don't panic. It will read something like \"rmdir: testhdfs: Directory is not empty\". The directory needs to be empty before it can be deleted. You can use the \"rm\" command to bypass this and remove a directory including all the files it contains. Enter:\r\nhdfs dfs -rm -r testHDFS\r\nhdfs dfs -lsHow to install HDFSTo install Hadoop, you need to remember that there is a singlenode and a multinode. Depending on what you require, you can either use a singlenode or multinode cluster.A single node cluster means only one DataNode is running. It will include the NameNode, DataNode, resource manager, and node manager on one machine.For some industries, this is all that's needed. For instance, in the medical field, if you're conducting studies and need to collect, sort, and process data in a sequence, you can use a singlenode cluster. This can easily handle the data on a smaller scale, as compared to data distributed across many hundreds of machines. To install a singlenode cluster, follow these steps:Download the Java 8 Package. Save this file in your home directory.Extract the Java Tar File.Download the Hadoop 2.7.3 Package.Extract the Hadoop tar File.Add the Hadoop and Java paths in the bash file (.bashrc).Edit the Hadoop Configuration files.Open core-site.xml and edit the property.Edit hdfs-site.xml and edit the property.Edit the mapred-site.xml file and edit the property.Edit yarn-site.xml and edit the property.Edit hadoop-env.sh and add the Java path.Go to Hadoop home directory and format the NameNode.Go to hadoop-2.7.3\/sbin directory and start all the daemons.Check that all the Hadoop services are running.And there you have it, you should now have a successfully installed HDFS.How to access HDFS filesIt will come as no surprise that security is tight when it comes to HDFS, given that we're dealing with data. As HDFS is technically virtual storage, it spans across the cluster so you can only see the metadata on your file system, you won't be able to view the actual specific data.To access HDFS files you can download the \"jar\" file from HDFS to your local file system. You can also access the HDFS using its web user interface. Simply open your browser and type \"localhost:50070\" into the search bar. From there, you can see the web user interface of HDFS and move to the utilities tab on the right hand side. Then click \"browse file system,\" this shows you a full list of files located on your HDFS.HDFS DFS examplesHere are some of the most common Hadoop command examples.Example ATo delete a directory you need to apply the following (note: this can only be done if the files are empty):\r\n$Hadoop fs -rmdir \/directory-nameOr\r\n$hdfs dfs -rmdir \/directory-nameExample BWhen you have multiple files in an HDFS, you can use a \"-getmerge\" command. This will merge multiple files into a single file, which you can then download to your local file system. You can do this with the following:\r\n$ Hadoop fs -getmerge [-nl] \/source \/local-destinationOr\r\n$ hdfs dfs -getmerge [-nl] \/source \/local-destinationExample CWhen you want to upload a file from HDFS to local, you can use the \"-put\" command. You specify where you want to copy from, and what file you want to copy onto HDFS. Use the below:\r\n$ Hadoop fs -put \/local-file-path \/hdfs-file-pathOr\r\n$ hdfs dfs -put \/local-file-path \/hdfs-file-pathExample DThe count command is used to track the number of directories, files, and file size on HDFS. You can use the following:\r\n$ Hadoop fs -count \/hdfs-file-pathOr\r\n$ hdfs dfs -count \/hdfs-file-pathExample EThe \"chown\" command can be used to change the owner and group of a file. To activate this, use the below:\r\n$ Hadoop fs -chown [-R] [owner][:[group]] hdfs-file-pathOr\r\n$ hdfs dfs -chown [-R] [owner][:[group]] hdfs-file-pathWhat is HDFS storage?As we now know, HDFS data is stored in something called blocks. These blocks are the smallest unit of data that the file system can store. Files are processed and broken down into these blocks, which are then taken and distributed across the cluster - and also replicated for safety. Typically, each block can be replicated three times. This diagram shows big data and how it can be stored with HDFS.The first you will find on the DataNode, the second is stored on a separate DataNode within the cluster, and a third is stored on a DataNode in a different cluster. This is like a triple protection security step. So, if the worst should happen and one replica fails, the data is not gone for good.The NameNode keeps important information, such as the number of blocks and where the replicas are stored. In comparison, a DataNode is storing the actual data, and can create blocks, remove blocks, and replicate blocks on command. It looks like this:\r\nIn hdfs-site.xml\r\ndfs.NameNode.name.dirfile:\/Hadoop\/hdfs\/NameNode\r\ndfs.DataNode.data.dir\r\nfile:\/Hadoop\/hdfs\/DataNode\r\nDfs.DataNode.data.dirThis determines where DataNodes should store its blocks.How does HDFS store data?The HDFS file system consists of a set of Master services (NameNode, secondary NameNode, and DataNodes). The NameNode and secondary NameNode manage the HDFS metadata. The DataNodes host the underlying HDFS data.The NameNode tracks which DataNodes contain the contents of a given file in HDFS. HDFS divides files into blocks and stores each block on a DataNode. Multiple DataNodes are linked to the cluster. The NameNode then distributes replicas of these data blocks across the cluster. It also instructs the user or application where to locate wanted information.What is the Hadoop distributed file system (HDFS) designed to handle?Put simply, when asking \"what is the Hadoop distributed file system designed to handle?\" The answer is first and foremost - big data. This can be invaluable to large corporations that would otherwise struggle to manage and store data from their business and customers.With Hadoop, you can store and unite data, whether it's transactional, scientific, social media, advertising, and machine. It also means you can come back to this data and gain valuable insights into business performance and analytics.As it was designed to store data, HDFS can also handle raw data which is commonly used by scientists or those in the medical field who are looking to analyze such data. These are called data lakes. It allows them to combat more difficult questions without restraints.What's more, as Hadoop was primarily designed to handle enormous volumes of data in various ways, it can also be used to run algorithms for analytical purposes. This means it helps businesses to process and analyze data more efficiently, allowing them to discover new trends and anomalies. Certain datasets are even being removed from data warehouses and moved to Hadoop. It just makes it easier to store everything in one easily accessible place.When it comes to transactional data, Hadoop is also equipped to handle millions of transactions. Thanks to its storage and processing abilities, it can be used to store and analyze customer data. You can also deep dive into the data to discover emerging trends and patterns to help with business goals. Don't forget, Hadoop is constantly being updated with fresh data, and you can compare new and old data to see what has changed, and why.Considerations with HDFSBy default, HDFS is configured with 3x replication which means datasets will have two additional copies. While this improves the likelihood of localized data during processing, it does introduce overhead storage costs.HDFS works best when configured with locally attached storage. This ensures the best performance for the file system.Increasing the capacity of HDFS requires the addition of new servers (compute, memory, disk), not just storage media.HDFS vs. Cloud Object StorageAs mentioned above, HDFS capacity is tightly coupled with computing resources. Increasing storage capacity entails increasing CPU resources, even though the latter is not required. When adding more data nodes to HDFS, a rebalance operation is required to distribute existing data to the newly added servers.This operation can take some time. Scaling a Hadoop cluster in an on-premises environment can also be difficult from a cost and space perspective. HDFS uses locally attached storage which can provide IO performance benefits assuming YARN can provision processing on the servers that store the data to be processed.With heavily utilized environments, it's possible that most data read\/write operations will be over the network vs local. Cloud object storage includes technologies such as Azure Data Lake Storage, AWS S3, or Google Cloud Storage. It's independent of computing resources that access it and hence customers can store far larger amounts of data in the cloud.Customers that are looking to store Petabytes worth of data can easily do this in cloud object storage. However, all read and write operations against cloud storage will be over the network. So, it's important that applications that will access its data leverage caching where possible or include logic to minimize IO operations.Additional ResourcesHadoop to Lakehouse migration guideMigration hubCloud Modernization Ebook: A business guide into the hidden value of migration from HadoopOn-demand quick demo's of the Databricks Lakehouse PlatformBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ian-galloway\/#","text":"Ian Galloway - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIan GallowaySenior Director, Applications at Collins AerospaceBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/manu-sharma\/#","text":"Manu Sharma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingManu SharmaCEO at LabelboxBack to speakersManu is an engineer, designer, and serial entrepreneur. He is the Founder & CEO of Labelbox, an AI infrastructure software company. Previously, he developed products at Planet Labs and DroneDeploy and co-founded renewable energy and space exploration companies. He studied aerospace engineering and a wide range of robotics, electrical engineering, and industrial design subjects. He is an active pilot and holds M.S. & B.S. degrees from Stanford University and Embry-Riddle Aeronautical University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/trust","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueWe know that data is one of your most valuable assets and always has to be protected \u2014 that\u2019s why security is built into every layer of the Databricks Lakehouse Platform. Our transparency enables you to meet your regulatory needs while taking advantage of our platform.Trusted PlatformTrust comes through transparency. See how we secure the platform through industry-leading practices including penetration testing, vulnerability management and secure software development to protect the Databricks Lakehouse Platform.Learn moreSecurity FeaturesWe provide comprehensive security capabilities to protect your data and workloads, such as encryption, network controls, auditing, identity integration, access controls and data governance.Learn moreComplianceCustomers all over the world and across industries rely on the Databricks Lakehouse Platform. We have the certifications and attestations to meet the unique compliance needs of highly regulated industries.Learn morePrivacyWe value the privacy of your data and understand that it is important to both your organization and your customers. Databricks can help you comply with privacy laws and meet regulatory requirements.Learn morePerform your own self-service security review of Databricks using our due\ndiligence package, which includes documentation and compliance materials.Due Diligence PackageProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/data-warehouse","text":"What is a Data Warehouse?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData WarehouseAll>Data WarehouseWhat is a data warehouse?A data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business intelligence (BI), reporting and data analysis.Data warehouses make it possible to quickly and easily analyze business data uploaded from operational systems such as point-of-sale systems, inventory management systems, or marketing or sales databases. Data may pass through an operational data store and require data cleansing to ensure data quality before it can be used in the data warehouse for reporting.What are data warehouses used for?Data warehouses are used in BI, reporting, and data analysis to extract and summarize data from operational databases. Information that is difficult to obtain directly from transactional databases can be obtained via data warehouses. For example, management wants to know the total revenues generated by each salesperson on a monthly basis for each product category. Transactional databases may not capture this data, but the data warehouse does.ETL and ELT on the data warehouseETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are two different ways of transforming data. Data engineers often use ETL, or extract-transform-load, to extract data from different data sources and move it into the data warehouse, where they can easily cleanse and structure it. ELT, on the other hand, loads data into the warehouse in its original format first, and cleanses and structures it as it is processed.ETL is typically done more centrally via Enterprise Data Engineering teams to apply company-wide data cleansing and conforming rules. ELT implies transformations are done at a later stage which are typically more project\/business team specific - to enable self-service analytics.Transaction processing (OLTP) vs. analytics processing (OLAP)An Online Transaction Processing (OLTP) system captures and maintains transactional data in a database. Transactions involve individual database records made up of multiple fields or columns. OLTP databases are commonly used in applications like online banking, ERP systems, or inventory management, enabling quick updates to row-level data that are processed nearly instantly.An Online Analytical Processing (OLAP) system applies complex queries to large amounts of historical data, aggregated from OLTP databases and other sources, for data mining, analytics, and business intelligence projects. Data warehouses are OLAP systems. OLAP databases and data warehouses give analysts and decision-makers the ability to use custom reporting tools to turn data into information and action. Query failure on an OLAP database does not interrupt or delay transaction processing for customers, but it can delay or impact the accuracy of business intelligence insights.Data lake vs. data warehouseWhat is the difference between a data lake and a data warehouse?A data lake and a data warehouse are two different approaches to managing and storing data.\u00a0A data lake is an unstructured or semi-structured data repository that allows for the storage of vast amounts of raw data in its original format. Data lakes are designed to ingest and store all types of data \u2014 structured, semi-structured or unstructured \u2014 without any predefined schema. Data is often stored in its native format and is not cleansed, transformed or integrated, making it easier to store and access large amounts of data.A data warehouse, on the other hand, is a structured repository that stores data from various sources in a well-organized manner, with the aim of providing a single source of truth for business intelligence and analytics. Data is cleansed, transformed and integrated into a schema that is optimized for querying and analysis.What is the difference between a data lake, a data warehouse and a data lakehouse?A data lakehouse is a hybrid approach that combines the best of both worlds. It is a modern data architecture that integrates the capabilities of a data warehouse and a data lake in a unified platform. It allows for the storage of raw data in its original format like a data lake while also providing data processing and analytics capabilities like a data warehouse.In summary, the main difference between a data lake, a data warehouse and a data lakehouse is their approach to managing and storing data. A data warehouse stores structured data in a predefined schema, a data lake stores raw data in its original format, and a data lakehouse is a hybrid approach that combines the capabilities of both.\u00a0Data lakeData lakehouseData warehouseTypes of dataAll types: Structured data, semi-structured data, unstructured (raw) dataAll types: Structured data, semi-structured data, unstructured (raw) dataStructured data onlyCost$$$$$FormatOpen formatOpen formatClosed, proprietary formatScalabilityScales to hold any amount of data at low cost, regardless of typeScales to hold any amount of data at low cost, regardless of typeScaling up becomes exponentially more expensive due to vendor costsIntended usersLimited: Data scientistsUnified: Data analysts, data scientists, machine learning engineersLimited: Data analystsReliabilityLow quality, data swampHigh quality, reliable dataHigh quality, reliable dataEase of useDifficult: Exploring large amounts of raw data can be difficult without tools to organize and catalog the dataSimple: Provides simplicity and structure of a data warehouse with the broader use cases of a data lakeSimple: Structure of a data warehouse enables users to quickly and easily access data for reporting and analyticsPerformancePoorHighHighCan a data lake replace a data warehouse?A data lake and a data warehouse are two different approaches to managing and storing data, each with its own strengths and weaknesses. While a data lake can complement a data warehouse by providing raw data for advanced analytics, it cannot in its traditional sense fully replace a data warehouse. Instead, a data lake and a data warehouse can complement each other, with the data lake serving as a source of raw data for advanced analytics, and the data warehouse providing a structured, organized and trustworthy source of business data for reporting and analysis.Can a data lakehouse replace a data warehouse?\u00a0A data lakehouse, however, is a modern data architecture that combines the benefits of a data warehouse and a data lake into a unified platform. A data lakehouse can serve as a replacement for a traditional data warehouse because it provides the capabilities of both a data lake and a data warehouse in a single platform.A data lakehouse allows for the storage of raw data in its original format like a data lake while also providing data processing and analytics capabilities like a data warehouse. It also provides a schema-on-read approach, which allows for flexibility in data processing and querying. The combination of a data lake and a data warehouse in a single platform provides increased flexibility, scalability and cost-effectiveness.What is the difference between a data lake and a database?A database is a structured repository that stores data in a predefined schema, optimized for transactional processing and business applications. Databases are designed to handle structured data and provide fast, efficient and reliable querying and data processing capabilities. They use a schema-on-write approach, which means that data must be structured and defined before it can be stored in the database. Databases are often used in applications such as e-commerce, banking, and inventory management, where transactional processing is critical for business operations.A data lake is an unstructured or semi-structured data repository designed to ingest and store all types of data in its original format \u2014 structured, semi-structured or unstructured \u2014 without any predefined schema. The data stored in its native format is often not cleansed, transformed or integrated, making it easier to store and access large amounts of data. Data lakes are often used for advanced analytics and machine learning applications, where data exploration and discovery are critical for gaining insights and building predictive models.What is the difference between a data lake and ETL?A data lake and ETL (extract, transform, load) are two different concepts related to data management and integration. The main difference is that a data lake is a centralized repository for storing and processing vast amounts of raw data, while ETL is a process for extracting, transforming and loading structured data from multiple sources into a target data repository. A data lake allows for the storage and processing of all types of data, without any predefined schema, while ETL is typically used for integrating structured data into a predefined schema.Benefits of data warehousesConsolidate data obtained from many sources; acting as a single point of access for all data, rather than requiring users to connect to dozens or even hundreds of individual data stores.Historical intelligence. A data warehouse integrates data from many sources to show historic trends.Separate analytics processing from transactional databases, improving the performance of both systems.Data quality, consistency, and accuracy. Data warehouses use a standard set of semantics around data, including consistency in naming conventions, codes for various product types, languages, currencies, and so on.Challenges with data warehousesNo support for unstructured data like images, text, IoT data, or messaging frameworks like HL7, JSON, and XML. Traditional data warehouses are only capable of storing clean and highly structured data, even though Gartner estimates that up to 80% of an organization's data is unstructured. Organizations that want to use their unstructured data to unlock the power of AI have to look elsewhere.No support for AI and machine learning. Data warehouses are purpose-built and optimized for common DWH workloads including historical reporting, BI, and querying \u2014 they were never designed for or intended to support machine learning workloads.SQL-only \u2014 DWHs typically offer no support for Python or R, the languages of choice for app developers, data scientists, and machine learning engineers.Duplicated data \u2014 Many enterprises have data warehouses and subject-area or (departmental) data marts in addition to a data lake, which results in duplicated data, lots of redundant ETL, and no single source of truth.Tough to keep in sync - keeping two copies of the data synchronized between the lake and the warehouse adds complexity and fragility that is tough to manage. Data drift can cause inconsistent reporting and faulty analysis.Closed, proprietary formats increase vendor lock-in \u2014 most enterprise data warehouses use their own proprietary data format, rather than formats based on open source and open standards. This increases vendor lock-in, makes it difficult or impossible to analyze your data with other tools, and makes it more difficult to migrate your data.Expensive \u2014 commercial data warehouses charge you for storing your data, and also for analyzing it. Storage and compute costs are therefore still tightly coupled together. Separation of compute and storage with a lakehouse means you can independently scale either as needed.How lakehouses solve these challengesLakehouse architectures specifically solve these challenges in order to offer the best of both data lakes and warehouses. See the value of an open lakehouse architecture on Databricks.Databricks Lakehouse for Data WarehousingTo build a successful lakehouse, organizations have turned to Delta Lake, an open source, open format data management and governance layer that combines the best of both data lakes and data warehouses. The Databricks Lakehouse Platform uses Delta Lake to give you:World record data warehouse performance at data lake economics.Serverless SQL compute that removes the need for infrastructure management.Seamless integration with the modern data stack, like dbt, Tableau, PowerBI, and Fivetran to ingest, query, and transform data in-place.A first class SQL development experience for every data practitioner across your organization with ANSI-SQL support.Fine-grained governance with data lineage, table\/row level tags, role-based access controls and more.Additional ResourcesDatabricks SQL product pageeBook - Why Is the Lakehouse Your Next Data Warehouse?Databricks Sets Official Data Warehousing Performance RecordDatabricks Named a Leader in 2021 Gartner Magic Quadrant for Data Science and Machine Learning PlatformsBill Inmon - Building the Data LakehouseBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/bioinformatics","text":"What is Bioinformatics?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBioinformaticsAll>BioinformaticsTry Databricks for freeGet StartedBioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.Bioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data. An outstanding amount of data is being generated by genome sequencing projects and other studies, as a result of this data wave, most of the challenges in biology have actually turned into provocations in computing. The term bioinformatics was first used by Paulien Hogeweg and Ben Hesper in 1970. Its meaning was different from today as its usage was in relation to \"the study of informatic processes in biotic systems\" and it was coined when the first biological sequence data began to be shared. The term is currently used much more broadly, including computational structural biology, chemical biology, and systems biology (both data integration as well as the modeling of systems). This highly interdisciplinary field involves the knowledge of several branches such as applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry. Bioinformatics is essential for management of data in modern biology and medicine. This interesting field of science has numerous applications and research areas where it can be applied, some of the most well known are:Sequence AnalysisPrediction of Protein StructureGenome AnnotationComparative GenomicsHealth and Drug discoveryWaste cleanupBiotechnologyAdditional ResourcesVariant-Apache Spark for BioinformaticsAccelerating Discovery with a Unified Analytics Platform for GenomicsBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/greg-kroleski\/#","text":"Greg Kroleski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGreg KroleskiProduct Management at DatabricksBack to speakersGreg leads Product Management for Databricks Billing and Cost Management. He was previously Group Product Manager of Google Cloud's Billing Platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=dbsql-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/virtual-experience?itm_data=hp-hamburger-virtualx-dais23","text":"Virtual Experience - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVirtual ExperienceTune in, June 28-29, from anywhere in the world.\n*Asia Pacific & Japan Keynotes Rebroadcast\u00a0\nEnglish,\u00a0Japanese,\u00a0Korean\u00a0and\u00a0Mandarin\nJune 29 and June 30\n8.30 AM IST | 11 AM SGT | 12 PM JST | 12 PM KST | 1 PM AEST\nRegister nowThis year\u2019s Data + AI Summit Virtual Experience brings you a host of live content including major industry and product announcements, expert keynotes, curated breakout sessions, exclusive interviews with guest speakers and Databricks founders, as well as 250+ breakouts available on demand after the event.Featured speakersCheck back in mid May to see the full speaker lineup for our virtual event.\nDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAgendaWednesday, June 28*8:15 AM \u2013 11:00 AM | Keynote Day 1\n1:00 PM - 5:40 PM | Breakout Sessions 1-6\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nThursday, June 29*8:30 AM \u2013 11:00 AM |\u00a0 Keynote Day 2\n12:00 PM - 4:40 PM | Breakout Sessions 7-11\nBreakout sessions will be announced in May. Check back to find out about the livestreamed sessions covering the Lakehouse Platform and the latest open source technologies such as Apache Spark\u2122, Delta Lake, MLflow, Presto\/Trino and dbt\n\u201cLive From the Lakehouse\u201d | between breakout sessions, stay tuned for exclusive interviews with Databricks co-founders, guest speakers and industry leaders, as well as insider tips and tricks \u2014 all coming to you live from the Lakehouse. More details to follow soon.\n*All times PT\nOn DemandAll 250+ breakout sessions delivered onsite in San Francisco will be recorded and available on demand soon after the event. More updates coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/explore\/retail-resources","text":"\n\n\n\n\n\n\n\nExplore Lakehouse for Retail\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVideo is muted due to browser restrictions. Adjust the volume on the video player to unmute.\n\n\n\nSelected language is not available in captions.\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/dillon-bostwick","text":"Dillon Bostwick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDillon BostwickSolutions Architect at DatabricksBack to speakersDillon Bostwick has spent the last 5 years as a Solutions Architect at Databricks, where he has an extensive background in working with data engineers, data scientists, and business stakeholders to productionize data and machine learning projects. He is also active in developing new field projects intended to accelerate the management of data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/greg-kroleski","text":"Greg Kroleski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGreg KroleskiProduct Management at DatabricksBack to speakersGreg leads Product Management for Databricks Billing and Cost Management. He was previously Group Product Manager of Google Cloud's Billing Platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-art-of-collaborative-data-science-at-scale","text":"The Art of Collaborative Data Science at Scale | DatabricksData science simplifiedThe Art of Collaborative Data Science at ScaleFind out how a collaborative notebook environment makes it easier to tap into the power of Apache Spark\u2122 and the latest ML frameworks, explore data at scale, train accurate ML models, track and compare experiments, and share insights with others. Get the eBook to learn:How to overcome key issues that hamper fragmented data science teamsHow to focus on your data, not DevOpsHow to accelerate innovation through collaborative workspacesHow Shell\u2019s data science team achieved 32x performance gain on inventory analysisGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/wood-mackenzie","text":"Wood Mackenzie helps customers transition to a more sustainable future | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLAKEHOUSE PRODUCT SPOTLIGHT: WORKFLOWSWorkflows enables automation and collaboration in the energy sector12 BillionData points processed each week80-90%Reduction in processing timeCost SavingsIn operations through workflow automation INDUSTRY: Energy and utilities PLATFORM USE CASE: Lakehouse,Workflows CLOUD: AWS\u201cOur mission is to transform the way we power the planet. Our clients in the energy sector need data, consulting services and research to achieve that transformation. Databricks Workflows gives us the speed and flexibility to deliver the insights our clients need.\u201d\n\u2014 Yanyan Wu, Vice President of Data, Wood MackenzieWood Mackenzie offers customized consulting and analysis for a wide range of clients in the energy and natural resources sectors. Founded in Edinburgh, the company first cultivated deep expertise in upstream oil and gas, then broadened its focus to deliver detailed insight for every interconnected sector of the energy, chemicals, metals and mining industries. Today it sees itself playing an important role in the transition to a more sustainable future. Using Databricks Workflows to automate ETL pipelines helps Wood Mackenzie ingest and process massive amounts of data. Using a common workflow provided higher visibility to engineering team members, encouraging better collaboration. With an automated, transparent workflow in place, the team saw improved productivity and data quality and an easier path to fix pipeline issues when they arise.Delivering insights to the energy industryFulfilling Wood Mackenzie\u2019s mission, the Lens product is a data analytics platform built to deliver insights at key decision points for customers in the energy sector. Feeding into Lens are vast amounts of data collected from various data sources and sensors used to monitor energy creation, oil and gas production, and more. Those data sources update about 12 billion data points every week that must be ingested, cleaned and processed as part of the input for the Lens platform. Yanyan Wu, Vice President of Data at Wood Mackenzie, manages a team of big data professionals that build and maintain the ETL pipeline that provides input data for Lens. The team is leveraging the Databricks Lakehouse Platform and uses Apache Spark\u2122 for parallel processing, which provides greater performance and scalability benefits compared to an earlier single-node system working sequentially. \u201cWe saw a reduction of 80-90% in data processing time, which results in us providing our clients with more up-to-date, more complete and more accurate data,\u201d says Wu.Improved collaboration and transparency with a common workflowThe data pipeline managed by the team includes several stages for standardizing and cleaning raw data, which can be structured or unstructured and may be in the form of PDFs or even handwritten notes.Different members of the data team are responsible for different parts of the pipeline, and there is a dependency between the processing stages each team member owns. Using Databricks Workflows, the team defined a common workstream that the entire team uses. Each stage of the pipeline is implemented in a Python notebook, which is run as a job in the main workflow.Each team member can now see exactly what code is running on each stage, making it easy to find the cause of the issue. Knowing who owns the part of the pipeline that originated the problem makes fixing issues much faster. \u201cWithout a common workflow, different members of the team would run their notebooks independently, not knowing that failure in their run affected stages downstream,\u201d says Meng Zhang, Principal Data Analyst at Wood Mackenzie. \u201cWhen trying to rerun notebooks, it was hard to tell which notebook version was initially run and the latest version to use.\u201dUsing Workflows\u2019 alerting capabilities to notify the team when a workflow task fails ensures everyone knows a failure occurred and allows the team to work together to resolve the issue quickly. The definition of a common workflow created consistency and transparency that made collaboration easier. \u201cUsing Databricks Workflows allowed us to encourage collaboration and break up the walls between different stages of the process,\u201d explains Wu. \u201cIt allowed us all to speak the same language.\u201dCreating transparency and consistency is not the only advantage the team saw. Using Workflows to automate notebook runs also led to cost savings compared to running interactive notebooks manually.Improved code development productivityThe team\u2019s ETL pipeline development process involves iteration on PySpark notebooks. Leveraging interactive notebooks in the Databricks UI makes it easy for data professionals on the team to manually develop and test a notebook. Because Databricks Workflows supports running notebooks as task type (along with Python files, JAR files and other types), when the code is ready for production, it\u2019s easy and cost effective to automate it by adding it to a workflow. The workflow can then be easily revised by adding or removing any steps to or from the defined flow. This way of working keeps the benefit of manually developing notebooks with the interactive notebook UI while leveraging the power of automation, which reduces potential issues that may happen when running notebooks manually.The team has gone even further in increasing productivity by developing a CI\/CD process. \u201cBy connecting our source control code repository, we know the workflow always runs the latest code version we committed to the repo,\u201d explains Zhang. \u201cIt\u2019s also easy to switch to a development branch to develop a new feature, fix a bug and run a development workflow. When the code passes all tests, it is merged back to the main branch and the production workflow is automatically updated with the latest code.\u201dGoing forward, Wood Mackenzie plans to optimize its use of Databricks Workflows to automate machine learning processes such as model training, model monitoring and handling model drift. The firm uses ML to improve its data quality and extract insights to provide more value to its clients. \u201cOur mission is to transform how we power the planet,\u201d Wu says. \u201cOur clients in the energy sector need data, consulting services and research to achieve that transformation. Databricks Workflows gives us the speed and flexibility to deliver the insights our clients need.\u201dReady to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u6d3b\u7528\u3057\u3066\u3001\u30c6\u30ad\u30b9\u30c8\u30c7\u30fc\u30bf\u304b\u3089\u6a5f\u5bc6\u6027\u306e\u9ad8\u3044\u60a3\u8005\u60c5\u5831\u3092\u81ea\u52d5\u7684\u306b\u524a\u9664\u3057\u307e\u3059\u3002\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u5168\u3066\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u898b\u308b\u533b\u7642\u30d8\u30eb\u30b9\u30b1\u30a2\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u5c0e\u5165\u4e8b\u4f8b\u3055\u3089\u306b\u8a73\u3057\u304f\u533b\u7642\u30fb\u30d8\u30eb\u30b9\u30b1\u30a2\n\u30c7\u30fc\u30bf\u3068 AI \u306b\u3088\u308b\u60a3\u8005\u4e2d\u5fc3\u306e\u30b1\u30a2\u306e\u5b9f\u73fe\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\n\u30c7\u30fc\u30bf\u5206\u6790\u3068AI\u306e\u6d3b\u7528\u3067\u60a3\u8005\u306b\u65b0\u305f\u306a\u6cbb\u7642\u6cd5\u3092\u63d0\u4f9b\u30c7\u30fc\u30bf\u3068 AI \u306b\u3088\u308b\u60a3\u8005\u30a2\u30a6\u30c8\u30ab\u30e0\u306e\u6539\u5584eBook \u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\n\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u4e00\u89a7\n\u30d8\u30eb\u30b9\u30b1\u30a2\u3068\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u305f\u3081\u306e\u30c7\u30fc\u30bf\u3068AI\u306b\u95a2\u3059\u308b\u96fb\u5b50\u30d6\u30c3\u30af\u3084\u30d3\u30c7\u30aa\u3092\u63a2\u3059\u306b\u306f\u3001\u30ea\u30bd\u30fc\u30b9\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u3054\u5229\u7528\u304f\u3060\u3055\u3044\u3002\n\u8a73\u3057\u304f\u898b\u308beBook\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3088\u308b\u30a2\u30a6\u30c8\u30ab\u30e0\u306e\u5411\u4e0a\u5927\u898f\u6a21\u306a NLP \u306e\u6d3b\u7528\u306b\u3088\u308b\u60a3\u8005\u306e\u77e5\u898b\u62bd\u51fa\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3088\u308b\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u30c7\u30fc\u30bf\u306e\u5b9f\u73fe\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30b7\u30fc\u30c8\uff1a\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u5165\u9580\u7de8Web \u30bb\u30df\u30ca\u30fc\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff1aFHIR \u306e\u5c0e\u5165 \u2013 \u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3088\u308b\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u60a3\u8005\u5206\u6790\u306e\u5f37\u5316Web \u30bb\u30df\u30ca\u30fc\uff1aCRISP\uff08\u30c1\u30a7\u30b5\u30d4\u30fc\u30af\u5730\u57df\u306e\u60a3\u8005\u60c5\u5831\u30b7\u30b9\u30c6\u30e0\uff09\u306b\u3088\u308b\u533b\u7642\u30a4\u30ce\u30d9\u30fc\u30b7\u30e7\u30f3\u306e\u63a8\u9032\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff1aOMOP \u306b\u3088\u308b\u30c7\u30fc\u30bf\u306e\u6a19\u6e96\u5316\u3068\u6a5f\u68b0\u5b66\u7fd2\u306b\u3088\u308b\u75be\u60a3\u30ea\u30b9\u30af\u4e88\u6e2c\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff1aNLP \u306b\u3088\u308b\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u306e\u30c7\u30fc\u30bf\u62bd\u51fa\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff1a\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u306e\u30c7\u30fc\u30bf\u3068 AI \u306e\u6d3b\u7528\u306b\u3088\u308b\u7814\u7a76\u958b\u767a\u306e\u52a0\u901f\u30d6\u30ed\u30b0\u30a2\u30e0\u30b8\u30a7\u30f3\u306b\u304a\u3051\u308b\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306b\u3088\u308b\u5275\u85ac\u306e\u52a0\u901f\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u5411\u3051\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u5165\u9580\u7de8NLP \u3092\u6d3b\u7528\u3057\u305f\u6709\u5bb3\u4e8b\u8c61\u691c\u51fa\u306b\u3088\u308b\u533b\u85ac\u54c1\u5b89\u5168\u6027\u306e\u5411\u4e0a\u4e3b\u8981\u306a\u30c4\u30fc\u30eb\u3092\u51cc\u99d5\u3059\u308b Databricks \u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30b2\u30ce\u30df\u30af\u30b9\u30c4\u30fc\u30eb\u30ad\u30c3\u30c8\u81e8\u5e8a\u30c7\u30fc\u30bf\u306b\u3088\u308b\u816b\u760d\u5b66\u306e\u77e5\u898b\u62bd\u51fa\u306b NLP \u3092\u6d3b\u7528\u7121\u6599\u304a\u8a66\u3057\u30fb\u305d\u306e\u4ed6\u3054\u76f8\u8ac7\u3092\u627f\u308a\u0000\u0000\u307e\u3059\u304a\u5ba2\u69d8\u306e\u30d3\u30b8\u30cd\u30b9\u30b4\u30fc\u30eb\u3092\u304a\u805e\u304b\u305b\u304f\u3060\u3055\u3044\u3002Databricks \u306e\u30b5\u30fc\u30d3\u30b9\u30c1\u30fc\u30e0\u304c\u304a\u5f79\u306b\u7acb\u3061\u307e\u3059\u3002Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u30ea\u30af\u30a8\u30b9\u30c8\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joe-walsh\/#","text":"Joe Walsh - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoe WalshDirector of Measurement & Attribution at EffectvBack to speakersJoe is the Director of Measurement & Attribution at Effectv, a Comcast Company, where his main focus is creating innovative, 1st party solutions to help advertisers measure the performance of their media against outcomes that matter most to their business. Prior to joining Effectv, Joe was Head of TV Analytics at LiveRamp where he leveraged the Data + Math measurement platform to empower brands and agencies with industry-leading cross-screen insights. Prior to LiveRamp, Joe was Head of Analytics at dataxu (acquired by Roku), where he helped transform the business from a traditional DSP to an industry-leading advanced TV platform. Joe is a die-hard Boston sports fan, and holds a Bachelors degree in Economics and a Masters in Econometrics, both from the University of Massachusetts, Amherst.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/darshana-sivakumar","text":"Darshana Sivakumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDarshana SivakumarStaff Product Manager at DatabricksBack to speakersDarshana is a Product Manager on the Marketplace team at Databricks. She is passionate about helping organizations propel innovation through data and AI. Prior to Databricks, she spent some years at HashiCorp, building Vault. Before that, she was at AWS for a few years, where she helped launch brand new analytics services such as AWS Glue and Amazon Athena.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130WEBINAR May 18 \/ 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8Public Sector\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30Solutions by Use Case\uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc158\ubc14\uc774\uc624\uc81c\uc57d \uacbd\uc601\uc9c4\uc744 \ub300\uc0c1\uc73c\ub85c \ud55c \uc0c8\ub85c\uc6b4 \uc124\ubb38\uc870\uc0ac\uc5d0\uc11c \uc2e4\uc99d\uc801 \uc99d\uac70\ub85c \ub4b7\ubc1b\uce68\ub418\ub294 \uc2e4\uc81c \uc131\uacf5 \uc0ac\ub840\ub97c \uc218\uc9d1\ud588\uc2b5\ub2c8\ub2e4.\n\uc124\ubb38\uc870\uc0ac \uacb0\uacfc \ubcf4\uae30\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeaconsJoin Generation AI in San Francisco June 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessions\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \ubc0f \ud45c\ucc3d\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30Databricks \ubca4\ucc98\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\uc758 \ubbf8\ub798\uc5d0 \ud22c\uc790\nDatabricks Ventures\ub294 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\uc758 \ubbf8\ub798\uc5d0 \ub300\ud55c \uacac\ud574\ub97c \uacf5\uc720\ud558\ub294 \ud601\uc2e0\uc801\uc778 \uae30\uc5c5\uc5d0 \ud22c\uc790\ud569\ub2c8\ub2e4. \uccab \uc774\ub2c8\uc154\ud2f0\ube0c\uc778 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud380\ub4dc\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud655\uc7a5\ud558\uac70\ub098 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud558\uc5ec \ucc28\uc138\ub300 \ub370\uc774\ud130 \ubc0f AI \uae30\ubc18 \uae30\uc5c5\uc744 \ub9cc\ub4e4\uace0\uc790 \ud558\ub294 \ucd08\uae30 \ubc0f \uc131\uc7a5 \ub2e8\uacc4 \uae30\uc5c5\uc5d0 \ucd08\uc810\uc744 \ub9de\ucda5\ub2c8\ub2e4.\ud3ec\ud2b8\ud3f4\ub9ac\uc624 \uae30\uc5c5 \ud61c\ud0dd\uc81c\ud488 \ub85c\ub4dc\ub9f5\uc5d0 \ub300\ud55c \ub3c5\uc810\uc801 \uc778\uc0ac\uc774\ud2b8, \uc2ec\uce35\uc801 \uae30\uc220 \ud1b5\ud569 \uad6c\ucd95 \uc9c0\uc6d0Databricks \uba58\ud1a0 \ub124\ud2b8\uc6cc\ud06c\uc758 \uc9c0\uce68 \ubc0f \ubaa8\ubc94 \uc0ac\ub840Databricks \uc2dc\uc7a5 \uc9c4\ucd9c \ud504\ub85c\uadf8\ub7a8\uc5d0 \ucc38\uc5ec\ud558\uc5ec \ub3c4\ub2ec \ubc94\uc704 \ud655\ub300Lakehouse Fund investment focus\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\uc758 \ubbf8\ub798\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\uc5d0\uc11c \uad6c\ucd95\ud558\uace0\uc790 \ud558\ub294 \uacf5\ub3d9\uc758 \ube44\uc804\ub9ac\ub4dc \ud22c\uc790\uc790\uc640 \ud568\uaed8 \ud611\ub825\ud558\uc5ec \ucd08\uae30 \ubc0f \uc131\uc7a5 \ub2e8\uacc4 \uae30\uc5c5\uc5d0 \ud22c\uc790\uc624\ud508 \uc18c\uc2a4\uc640 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc640 \uac19\uc740 \uac1c\ubc29\uc801 \ud50c\ub7ab\ud3fc \uac1c\ubc1c\uc5d0 \ud22c\uc790\ud558\uace0\uc790 \ud558\ub294 Databricks\uc640 \uac19\uc740 \uc2e0\ub150\uc744 \uacf5\uc720\ud558\ub294 \ud504\ub85c\uc81d\ud2b8 \ubc0f \uae30\uc5c5Databricks \ud3ec\ud2b8\ud3f4\ub9ac\uc624Alation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\n\uc790\uc138\ud788Arcion\uc740 \ud074\ub77c\uc6b0\ub4dc \ub124\uc774\ud2f0\ube0c \ubd84\uc0b0\ud615 CDC \uae30\ubc18 \ub370\uc774\ud130 \ubcf5\uc81c \ud50c\ub7ab\ud3fc\uc73c\ub85c, \uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uac04\ub2e8\ud788 \uad6c\ucd95\ud560 \uc218 \uc788\ub3c4\ub85d \ud569\ub2c8\ub2e4. Arcion\uc740 \uae30\uc5c5\uc5d0\uc11c \ubd88\uc548\uc815\ud55c \ud30c\uc774\ud504\ub77c\uc778\uacfc \ub370\uc774\ud130 \uc0ac\uc77c\ub85c\ub97c \uc81c\uac70\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\n\uc790\uc138\ud788dbt\ub294 \ub370\uc774\ud130 \ubcc0\ud658 \ud504\ub808\uc784\uc6cc\ud06c\uc785\ub2c8\ub2e4. \uc0ac\uc6a9\uc790\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub098 \uc6e8\uc5b4\ud558\uc6b0\uc2a4 \ub0b4\uc5d0\uc11c \uc9c1\uc811 \uc791\uc5c5\ud558\uace0, \ubcf4\uace0\uc640 ML \ubaa8\ub378\ub9c1, \uc6b4\uc601 \uc6cc\ud06c\ud50c\ub85c\ub97c \uc704\ud55c \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294 \ub370\uc774\ud130 \uc138\ud2b8\ub97c \ube60\ub974\uac8c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc790\uc138\ud788Hex\ub294 \ud611\uc5c5\uc801 \ubd84\uc11d \ubc0f \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\ub97c \uc704\ud55c \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4. \uc0ac\uc6a9\uc790\ub294 \ub370\uc774\ud130\uc5d0 \uc5f0\uacb0\ud558\uc5ec \ud611\uc5c5\uc801 SQL \ubc0f Python \uae30\ubc18 \ub178\ud2b8\ubd81\uc73c\ub85c \ubd84\uc11d\ud558\uace0, \ub204\uad6c\ub098 \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \uc778\ud130\ub799\ud2f0\ube0c \ub370\uc774\ud130 \uc571\uc73c\ub85c \uc791\uc5c5 \ub0b4\uc6a9\uc744 \uacf5\uc720\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788Hunters SOC \ud50c\ub7ab\ud3fc\uc740 \ubcf4\uc548\ud300\uc774 \uc911\uc694\ud55c \uc778\uc2dc\ub358\ud2b8\ub97c \uc790\ub3d9\uc73c\ub85c \ucc3e\uc544\ub0b4 \ub300\uc751\ud558\ub3c4\ub85d \uc9c0\uc6d0\ud558\uace0, \ubcf4\uc548\ud300\uc5d0\uc11c SIEM\ubcf4\ub2e4 \ube60\ub974\uace0 \uc548\uc815\uc801\uc73c\ub85c \uc2e4\uc81c \uc704\ud611\uc744 \uc644\ud654\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788The Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.\uc790\uc138\ud788Labelbox\ub294 \ub808\uc774\ube14\uc774 \uc9c0\uc815\ub41c \ub370\uc774\ud130\ub97c \uc27d\uac8c \uc0dd\uc131\ud558\uace0 \uad00\ub9ac\ud558\ub294 \ud611\uc5c5\uc801 \ud6c8\ub828 \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\uc744 \uad6c\ucd95\ud568\uc73c\ub85c\uc368 AI \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc2e0\uc18d\ud788 \ubc30\ud3ec\ud558\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\uc790\uc138\ud788Matillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.\uc790\uc138\ud788Perplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.\uc790\uc138\ud788Revelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.\uc790\uc138\ud788Tecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.\uc790\uc138\ud788FAQDatabricks Ventures\uc640 \ud30c\ud2b8\ub108\ub97c \ub9fa\uc5b4\uc57c \ud558\ub294 \uc774\uc720\ub294 \ubb34\uc5c7\uc778\uac00\uc694?\nDatabricks\ub294 \ud22c\uc790 \uaddc\ubaa8\uc640 \ub2e8\uacc4\uc5d0 \ub530\ub77c, \ub85c\ub4dc\ub9f5 \ubc29\ud5a5, \uae30\uc220 \ud1b5\ud569, \uc2dc\uc7a5 \uc9c4\ucd9c \uc9c0\uc6d0\uc5d0 \ub300\ud55c \uace0\uc720\ud55c \uc561\uc138\uc2a4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. Databricks \uba58\ud1a0\uc5d0\uac8c \uc9c0\uce68\uacfc \ubaa8\ubc94 \uc0ac\ub840\ub97c \uc0c1\ub2f4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Databricks\uc758 \uae00\ub85c\ubc8c \uc2dc\uc7a5 \uc9c4\ucd9c \ud504\ub85c\uadf8\ub7a8(\uc608: Data + AI Summit \uc2dc\ub9ac\uc988)\uc5d0 \ub178\ucd9c\ub429\ub2c8\ub2e4.Databricks Ventures \ud22c\uc790 \uae30\uc900\uc740 \ubb34\uc5c7\uc778\uac00\uc694?\nDatabricks\ub294 \ub370\uc774\ud130\uc640 AI\uc73c \ubbf8\ub798\uc5d0 \ub300\ud574 \uac19\uc740 \uacac\ud574\ub97c \uacf5\uc720\ud558\uace0 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud655\uc7a5\ud558\uac70\ub098 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud558\uc5ec \ucc28\uc138\ub300 \ub370\uc774\ud130 \ubc0f AI \uae30\ubc18 \uae30\uc5c5\uc744 \ub9cc\ub4e4\uace0\uc790 \ud558\ub294 \ube44\uacf5\uac1c \uae30\uc5c5\uc758 \ud601\uc2e0\uc801 \ucc3d\uc5c5\uc790\uc5d0\uac8c \ud22c\uc790\ud569\ub2c8\ub2e4.Databricks\ub294 \uc5b4\ub5a4 \ub2e8\uacc4\uc5d0 \ud22c\uc790\ud558\ub098\uc694?\n\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc5d0\ucf54\uc2dc\uc2a4\ud15c \ub0b4\uc5d0\uc11c \uc131\uc7a5 \ub2e8\uacc4 \ube44\uacf5\uac1c \uae30\uc5c5\uc744 \ud1b5\ud574 \uc870\uae30\uc5d0 \ud22c\uc790\ud569\ub2c8\ub2e4.Databricks Ventures\uac00 \ud22c\uc790 \ub77c\uc6b4\ub4dc\ub97c \uc8fc\ub3c4\ud558\ub098\uc694?\n\uc544\ub2c8\uc694, Databricks\ub294 \ud22c\uc790\ub97c \uc8fc\ub3c4\ud558\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4. Databricks\ub294 \ub9ac\ub4dc \uae30\uad00 \ud22c\uc790\uc790\uc640 \ud568\uaed8 \ud22c\uc790\ud558\ub294 \uc804\ub7b5\uc744 \ucd94\uad6c\ud569\ub2c8\ub2e4.Databricks Ventures\uc758 \uc77c\ubc18\uc801 \ud29c\uc790 \uaddc\ubaa8\ub294 \uc5bc\ub9c8\uc778\uac00\uc694?\nDatabricks Ventures\ub294 \uae30\uad00 VC\uac00 \uc8fc\ub3c4\ud558\ub294 \ud22c\uc790\uc5d0\uc11c \uc18c\uc218 \uc785\uc7a5\uc744 \ucde8\ud569\ub2c8\ub2e4. \uc77c\ubc18\uc801 \ud22c\uc790 \uaddc\ubaa8\ub294 \ud68c\uc0ac\uc758 \ub2e8\uacc4, \ud380\ub9c1 \ub77c\uc6b4\ub4dc \uaddc\ubaa8\uc5d0 \ub530\ub77c \ub2ec\ub77c\uc9d1\ub2c8\ub2e4.Databricks\uac00 \uc774\uc0ac\uc9c1\uc744 \ub9e1\ub098\uc694?\uc544\ub2c8\uc694, Databricks\ub294 \ud3ec\ud2b8\ud3f4\ub9ac\uc624 \uae30\uc5c5\uc5d0\uc11c \uc774\uc0ac\ub97c \ub9e1\uc744 \uacc4\ud68d\uc774 \uc5c6\uc2b5\ub2c8\ub2e4.Databricks\uc5d0\uc11c \uc2a4\ud0c0\ud2b8\uc5c5 \uad6c\ucd95Databricks for Startups\ub294 \ubb34\ub8cc \ud06c\ub808\ub527, \uc804\ubb38\uac00 \uc870\uc5b8, \uc2dc\uc7a5 \uc9c4\ucd9c\uc5d0 \ub300\ud55c \uc9c0\uc6d0\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks \ucc44\uc6a9 \ud655\uc778\ud558\uae30\uc138\uacc4\uc801\uc778English (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/introducing-dbt-with-databricks","text":"Introducing dbt with Databricks | DatabricksOn-demandIntroducing dbt with DatabricksData transformation in the lakehouse made simpleAvailable on-demandWe\u2019re bringing analytics engineering with dbt to your data lakehouse to make it easier than ever to manage all your data in one place. The native, SQL-first integration between Databricks and dbt Cloud is now available in just a few clicks. Analytics teams can collaborate in the same workspace as data engineers and data scientists to build production-grade data transformation pipelines on the lakehouse. No more waiting for critical data to be accessible in SQL, no more unreliable dashboards and no more separate data warehouses.You\u2019ll learn how to:Create a data model in dbt using data in Delta LakeBuild autonomous ELT pipelines for analytics and BI workflowsTest and deploy your own data modelsCollaborate using the same data trusted by your data science counterpartsSpeakersAmy ChenSenior Partner Engineerdbt LabsJason PohlPrincipal Solution ArchitectDatabricksFelippe Felisola CasoSenior Business Analytics ManagerLoftEvent Sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)Register nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/05\/10\/introducing-databricks-workflows.html","text":"Introducing Databricks Workflows - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks WorkflowsReliable orchestration for data, analytics, and AIby Stacy Kerkela, Robert Saxby, Roland F\u00e4ustlin, Lennart Kats, Bilal Aslam, Richard Tomlinson, Frank Munz and Erika EhrliMay 10, 2022 in Platform BlogShare this postToday we are excited to introduce Databricks Workflows, the fully-managed orchestration service that is deeply integrated with the Databricks Lakehouse Platform. Workflows enables data engineers, data scientists and analysts to build reliable data, analytics, and ML workflows on any cloud without needing to manage complex infrastructure. Finally, every user is empowered to deliver timely, accurate, and actionable insights for their business initiatives.\nThe lakehouse makes it much easier for businesses to undertake ambitious data and ML initiatives. However, orchestrating and managing production workflows is a bottleneck for many organizations, requiring complex external tools (e.g. Apache Airflow) or cloud-specific solutions (e.g. Azure Data Factory, AWS Step Functions, GCP Workflows). These tools separate task orchestration from the underlying data processing platform which limits observability and increases overall complexity for end-users.\nDatabricks Workflows is the fully-managed orchestration service for all your data, analytics, and AI needs. Tight integration with the underlying lakehouse platform ensures you create and run reliable production workloads on any cloud while providing deep and centralized monitoring with simplicity for end-users.\nOrchestrate anything anywhereWorkflows allows users to build ETL pipelines that are automatically managed, including ingestion, and lineage, using Delta Live Tables. You can also orchestrate any combination of Notebooks, SQL, Spark, ML models, and dbt as a Jobs workflow, including calls to other systems. Workflows is available across GCP, AWS, and Azure, giving you full flexibility and cloud independence.\nReliable and fully managedBuilt to be highly reliable from the ground up, every workflow and every task in a workflow is isolated, enabling different teams to collaborate without having to worry about affecting each other\u2019s work. As a cloud-native orchestrator, Workflows manages your resources so you don't have to. You can rely on Workflows to power your data at any scale, joining the thousands of customers who already launch millions of machines with Workflows on a daily basis and across multiple clouds.\nSimple workflow authoring for every userWhen we built Databricks Workflows, we wanted to make it simple for any user, data engineers and analysts, to orchestrate production data workflows without needing to learn complex tools or rely on an IT team. Consider the following example which trains a recommender ML model. Here, Workflows is used to orchestrate and run seven separate tasks that ingest order data with Auto Loader, filter the data with standard Python code, and use notebooks with MLflow to manage model training and versioning. All of this can be built, managed, and monitored by data teams using the Workflows UI. Advanced users can build workflows using an expressive API which includes support for CI\/CD.\n\u201cDatabricks Workflows allows our analysts to easily create, run, monitor, and repair data pipelines without managing any infrastructure. This enables them to have full autonomy in designing and improving ETL processes that produce must-have insights for our clients. We are excited to move our Airflow pipelines over to Databricks Workflows.\u201d Anup Segu, Senior Software Engineer, YipitDataWorkflow monitoring integrated within the LakehouseAs your organization creates data and ML workflows, it becomes imperative to manage and monitor them without needing to deploy additional infrastructure. Workflows integrates with existing resource access controls in Databricks, enabling you to easily manage access across departments and teams. Additionally, Databricks Workflows includes native monitoring capabilities so that owners and managers can quickly identify and diagnose problems. For example, the newly-launched matrix view lets users triage unhealthy workflow runs at a glance:\nAs individual workflows are already monitored, workflow metrics can be integrated with existing monitoring solutions such as Azure Monitor, AWS CloudWatch, and Datadog (currently in preview).\n\n\u201cDatabricks Workflows freed up our time on dealing with the logistics of running routine workflows. With newly implemented repair\/rerun capabilities, it helped to cut down our workflow cycle time by continuing the job runs after code fixes without having to rerun the other completed steps before the fix. Combined with ML models, data store and SQL analytics dashboard etc, it provided us with a complete suite of tools for us to manage our big data pipeline.\u201d Yanyan Wu VP, Head of Unconventionals Data, Wood Mackenzie \u2013 A Verisk Business Get started with Databricks WorkflowsTo experience the productivity boost that a fully-managed, integrated lakehouse orchestrator offers, we invite you to create your first Databricks Workflow today.\nIn the Databricks workspace, select Workflows, click Create, follow the prompts in the UI to add your first task and then your subsequent tasks and dependencies. To learn more about Databricks Workflows visit our web page and read the documentation.\nWatch the demo below to discover the ease of use of Databricks Workflows:\nTo play this video, click here and accept cookiesIn the coming months, you can look forward to features that make it easier to author and monitor workflows and much more. In the meantime, we would love to hear from you about your experience and other features you would like to see.Try Databricks for freeGet StartedRelated postsSave Time and Money on Data and ML Workflows With \u201cRepair and Rerun\u201dMay 6, 2022 by Jan van der Vegt in Platform Blog\nDatabricks Jobs is the fully managed orchestrator for all your data, analytics, and AI. It empowers any user to easily create and run...\nAnnouncing the Launch of Delta Live Tables: Reliable Data Engineering Made EasyMay 27, 2021 by Michael Armbrust, Awez Syed and Sam Steiny in Announcements\nSIGN UP FOR PUBLIC PREVIEW As the amount of data, data sources and data types at organizations grow, building and maintaining reliable data...\nNow in Public Preview: Orchestrate Multiple Tasks With Databricks JobsJuly 13, 2021 by Roland F\u00e4ustlin in Platform Blog\nREAD DOCUMENTATION As companies undertake more business intelligence (BI) and artificial intelligence (AI) initiatives, the need for simple, clear and reliable orchestration of...\nSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mahesh-prakriya","text":"Mahesh Prakriya - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMahesh PrakriyaDirector in Intelligence Platform at MicrosoftBack to speakersMahesh Prakriya is a Director in Azure Data focused on ISVs and partnerships. Over 20+ years at Microsoft and industry, Mahesh shipped some of the key data and app platforms customer depend on including Power BI, Data Integration components, SQL Server, .NET Framework, Windows & Bing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacek-laskowski","text":"Jacek Laskowski - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacek LaskowskiIT Freelancer at japila.plBack to speakersI\u2019m Jacek Laskowski, an IT freelancer specializing in Apache Spark, Delta Lake, Databricks and Apache Kafka (incl. Kafka Streams and ksqlDB) (with brief forays into a wider data engineering space, e.g. Trino, Dask and dbt, mostly during Warsaw Data Engineering meetups). He is best known by The Internals Of online books at https:\/\/books.japila.pl.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=MachineLearning-HeroCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alessandro-garavaglia","text":"Alessandro Garavaglia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlessandro GaravagliaLead ML Engineer at GucciBack to speakersAlessandro holds a Ph.D. in Applied Mathematics with a dissertation about stochastic models for complex networks. He spent some years in consulting, working both as a Data Scientist and as Cloud Developer. He joined Gucci in 2021, where as Lead ML Engineer he is the architect and administrator of the Data Science Platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zeashan-pappa","text":"Zeashan Pappa - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZeashan PappaSenior Product Specialist - Data Governance at DatabricksBack to speakersZeashan is a technology executive and architect who has 20+ years of enterprise software architecture, engineering, consulting, and project management expertise. \nZeashan has advised and successfully managed complex technical projects for some of the world's largest companies and across many industry verticals, including brand names such as Humana, Kaiser, Starbucks, Credit Suisse, MetLife, Microsoft, Bank of America, Astrazeneca, Kodak, Prudential, Dell, American Express, Disney, Walmart, Target, Pfizer, JP Morgan Chase, Bristol Myers Squibb, Wells Fargo, Pfizer, and Office Depot.\nZeashan is currently a field product leader at Databricks, helping to lead GTM strategy and NPI for Unity Catalog, Delta Sharing, Cleanrooms and Marketplace.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/durga-kala\/#","text":"Durga Kala - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDurga KalaSr. Director at Visa Inc.Back to speakersManaging Visa's global fraud detection and decisioning products, such as Visa Risk Manager. Responsible for strategy and development of new risk Fraud products that optimize consumer experience while minimizing fraud losses. Extensive experience with developing innovative products and increasing adoption of open source software.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/supply-chain-management","text":"Supply Chain Management | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSupply Chain ManagementAll>Supply Chain ManagementWhat is supply chain management?Supply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end customer. It includes the coordination and optimization of all activities involved in sourcing, procurement, production and delivery of products and services as well as the management of information flow and financial transactions.The key elements of supply chain management include supplier management, inventory management, production planning and scheduling, logistics and transportation management and customer service. Effective supply chain management can help businesses reduce costs, improve product quality and delivery times, increase customer satisfaction and gain a competitive advantage in the marketplace.\u00a0Important aspects of supply chain managementEffective supply chain management requires a coordinated effort between various stakeholders including suppliers, manufacturers, distributors and retailers. Some of the important aspects of supply chain management include:\u00a0Planning: Planning for supply chain involves developing a strategy for the supply chain, forecasting demand, setting inventory levels and developing production schedulesSourcing: This involves identifying suppliers, negotiating contracts and managing relationships with vendorsProduction: Production involves managing the manufacturing process, including scheduling production, managing quality control and optimizing operationsInventory management: Considered one of the most critical aspects of supply chain management, managing inventory includes monitoring stock levels, forecasting demand and managing order quantities to ensure customers get the products they want without holding extra inventoryLogistics and transportation: Logistics and transportation are essential components of supply chain management that involve managing the movement of products from suppliers to customers, including transportation, warehousing and distribution. Efficient transportation systems and logistics networks can improve delivery times and reduce transportation costs.\u00a0Information management: This involves managing the flow of information throughout the supply chain, including gaining visibility into the supply chain and sharing data between suppliers, manufacturers and customersCollaboration: Effectively working with suppliers, partners and customers is critical to improve efficiency, reduce costs and enhance overall performance\u00a0Why forecasting is important in supply chain managementForecasting is a vital element of supply chain management. It helps organizations make informed decisions about how to manage inventory levels, such as deciding the correct amounts of safety stock needed and \u2014 perhaps most importantly \u2014 being able to accurately meet customer demand.Of course, businesses use supply chain forecasting for a myriad of reasons besides these two, including:Managing inventory: By forecasting demand, businesses can optimize their inventory levels, minimizing the risk of stockouts and avoiding overstockingReducing costs: Forecasting can help businesses streamline their supply chain processes, from reducing waste and optimizing production to saving on transportation costsImproving efficiency: Accurate forecasting can improve supply chain efficiency by reducing lead times, optimizing production schedules and minimizing the need for expedited shipmentsAnalyzing trends: Identifying potential supply chain disruptions and taking proactive measures mitigate the negative effects on business operations. For example, if a business forecasts a shortage of raw materials, it can work with suppliers to secure additional inventory or adjust production schedules to account for this shortfall.Types of forecasting in the supply chainCommon forecasting methods include:Exponential smoothing: This is based on a form of weighted averaging, so more recent observations are given greater weight than older ones, with the weights decreasing exponentially over time\u00a0Moving average forecasting: This calculates the average of a certain number of past observations and uses that value to forecast future values. Ideal for smoothing out fluctuations in a time series and identifying trends over time.\u00a0Auto-regressive integrated moving average: A time-series analysis and forecasting method that refers to past values to predict future ones. A methodology that\u2019s most accurate within timeframes of 18 months.\u00a0Multiple aggregation prediction algorithm: A hybrid forecasting method combining multiple models and aggregation techniques to improve forecast accuracy\u00a0Bottom-up forecasting: Estimating demand or sales for each individual product, service or market segment. This information is then aggregated to develop an overall projection.How effective supply chain management impacts a business\u00a0Effective supply chain management can have significant impact on the business, including:\u00a0Cost reduction: Effective supply chain management can help organizations reduce costs associated with procurement, production and logistics. It can also help reduce inventory carrying costs and minimize waste.Improved customer service: Effective supply chain management can help organizations improve customer service by ensuring timely delivery of products and servicesIncreased agility: Effective supply chain management can improve an organization\u2019s agility by enabling it to respond quickly to changes in customer demand or market conditions. It\u2019s critical to be agile enough to react to unforeseen disruptions to your supply chain so you can look for new flows of goods and a new supply chain network setup. These decisions need to account for a huge amount of detailed data, fast processing and lots of scenarios that need to be evaluated.Competitive advantage: Effective supply chain management can provide a competitive advantage by enabling organizations to deliver products and services faster and at a lower cost to their customers\u00a0How data is at the core of supply chain managementData and effective data management are critical to effective supply chain management, as data helps businesses effectively manage and optimize processes. Some key ways data can be used to improve supply chain management include:\u00a0Demand forecasting: Data helps organizations forecast demand, identify trends and plan inventory levels. Accurate demand forecasting can help organizations optimize inventory levels and reduce stockouts. Effective data management that leverages all data sources allows organizations to collect and analyze things like historical sales data, customer demand data, and market trends to improve their demand forecasting accuracy.Supply chain visibility: Data can be used to provide real-time visibility into the supply chain. This can help stakeholders identify potential bottlenecks and proactively respond to disruptions. Visibility and optimization require the ability to manage huge amounts of data. Many of today\u2019s supply chain systems have to slice and dice the supply chains as they are not able to manage the full set of data and cannot optimize problems of this size.Performance monitoring: Data can be used to monitor supplier performance, logistics performance and other key performance indicators. This can help organizations identify areas of improvement and optimize supply chain performance.Risk management: Data can be used to identify and manage supply chain risks. This can help organizations proactively mitigate risks and ensure continuity of the supply chain.\u00a0Data sharing: In today\u2019s supply chains, it has become more and more critical to expand beyond the four walls of your enterprise and to collaborate with customers and suppliers. Data sharing with customers enables a better understanding about their demand, while sharing demand forecasts for raw materials with suppliers can ensure steady supply.Overall, data and effective data management play a critical role in supply chain management by allowing businesses to collect, organize and analyze data from across the supply chain. This allows them to identify areas for improvement, make informed decisions and optimize their supply chain processes to reduce costs, improve efficiency and enhance customer satisfaction.Data sources critical to supply chain managementSupply chain management involves the coordination of various activities and processes across different organizations to ensure the timely and efficient delivery of goods and services to customers. In order to make informed decisions and optimize supply chain operations, different types of data are used. Some of the common types of data used in supply chain management include:\u00a0Demand data: Used to forecast the demand for products or services. It includes historical sales data, market trends, customer behavior and other relevant information that can help predict future demand.\u00a0Inventory data: Used to track the inventory levels of products and raw materials. It includes information like stock levels, lead times and reorder points.\u00a0Transportation data: Used to track the movement of goods and services through the supply chain. It includes information like shipment schedules, carrier performance and delivery times.\u00a0Production data: Used to monitor the production process and ensure that it is running efficiently. Includes information like production schedules, machine performance and labor productivity.\u00a0Supplier data: Used to manage relationships with suppliers and ensure they are meeting their obligations. It includes information like supplier performance, contract terms and pricing.\u00a0Financial data: Used to track the financial performance of the supply chain. Includes information like cost, margins and revenue.What are the 5 basic steps of supply chain data management?Data collection: In this step, companies gather data from various sources, including suppliers, customers, logistics, providers and internal systems. This data can include information on sales, inventory levels, production schedules, shipping status and supplier performance and can come in any format (structured, unstructured, semi-structured).\u00a0Data analysis: In this step, companies use various tools and techniques to analyze the data collected in the first step. This can include data mining, predictive analytics and machine learning algorithms. The goal is to identify patterns, trends and insights that can inform decision-making and improve supply chain performance.\u00a0Data sharing: In this step, companies share data with supply chain partners, including suppliers, logistics providers and customers. This can help to improve coordination, reduce uncertainty and enhance visibility across the supply chain.\u00a0Data visualization: In this step, companies use data visualization tools to present the insights and analysis generated in the second step. This can include charts, graphs and dashboards that help managers to quickly identify areas of concern and take action to address them.\u00a0Continuous improvement: In this step, companies use the insights gained from the previous step to continuously improve their supply chain performance. This can involve making changes to processes, policies and systems to optimize supply chain efficiency, reduce costs and improve customer satisfaction.Why Databricks is the best platform for supply chain managementThe Databricks Lakehouse Platform enables you to build a resilient and predictive supply chain by eliminating the trade-off between accuracy or depth of analysis and time. With scalable, fine-grained forecasts to predict or sense demand, or perform supply chain planning and optimization, Databricks improves the accuracy of decisions, leading to higher revenue growth and lower costs. Here are a few reasons why the Databricks Lakehouse Platform is the best choice for supply chain management:\u00a0Scalability: Databricks can handle large volumes of data and scale up or down as needed, making it an ideal platform for managing the large volumes of supply chain data. Databricks can unify data from any source and in any format, like sensor data, social media or transactional data, which are critical for supply chain management.\u00a0Real-time analytics: Databricks enables real-time analytics, which is critical to manage the supply chain effectively. Real-time analytics helps organizations monitor and respond to supply chain events in real time, like changes in demand or supply chain disruptions.\u00a0Machine learning: Databricks provides advanced machine learning capabilities that allow organizations to build predictive models to optimize their supply chain. By leveraging machine learning, organizations can improve their demand forecasting, reduce inventory costs and optimize their logistics and transportation operations.\u00a0Security: Databricks provides robust security features, including encryption, access control and compliance certifications, which is critical when managing sensitive supply chain data\u00a0Collaboration: The Databricks Lakehouse Platform provides collaboration features that enable team members to work together on data analysis and modeling, which is critical to supply chain management. These collaboration features help teams work more efficiently and make better decisions.\u00a0Data sharing: With an open solution to securely share live data from your lakehouse to any computing platform along with the ability to centrally manage and audit shared data across organizations, the Lakehouse lets you confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs.Learn more about how the Databricks Lakehouse helps retailers, manufacturers and all industries alike build a resilient and predictive supply chain and continuously optimize for cost and efficiency.Additional ResourcesSolution Accelerator: Supply Chain Distribution OptimizationBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/agenda","text":"Agenda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAgenda at a glanceExplore sessionsSTARTING AT $1,795In Person EventFREEVirtual EventMonday, June 26, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALTuesday, June 27, 2023Hands-On Training Courses & Certification for Data Engineering, Machine Learning, LLMs, and more*IN PERSONVIRTUALBreakout Sessions30010Partner SummitLightning Talks, AMA\u2019s, & Meetups on topics such as Apache Spark \u2122, Delta Lake, MLflow, and moreWednesday, June 28, 2023KeynotesIN PERSONVIRTUALBreakout Sessions30010100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsClosing PartyThursday, June 29, 2023KeynotesIN PERSONVIRTUALBreakout Sessions100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail, Healthcare & Life Sciences, Media & Entertainment, Public Sector, and ManufacturingCertificationsOn Demand Library HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/07\/jumbo-transforms-how-they-delight-customers-with-data-driven-personalized-experiences.html","text":"How Jumbo Transformed the Grocery Shopping Experience With Data and AI - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorJumbo Transforms How They Delight Customers With Data-Driven Personalized Experiencesby Wendell KulingJune 7, 2022 in Company BlogShare this postThis is a collaborative post between Databricks and Jumbo. We thank Wendell Kuling, Manager Data Science and Analytics at Jumbo Supermarkten, for his contribution.\u00a0\nAt Jumbo, a leading supermarket chain in the Netherlands and Belgium with more than 100 years of history, we pride ourselves on a \u2018customers first, data second\u2019 approach to business. However, this doesn\u2019t mean that data isn\u2019t central to our mission. Rather, our organization and data teams are completely built around customer satisfaction and loyalty. Supermarkets operate in an extremely competitive and complex space, in which all components of the customer experience require optimization, including inventory, assortment selection, pricing strategies, and product importance per segment.When we rolled out our loyalty program, the amount of new customer data points that started coming in got our data teams to rethink about how we optimize the customer experience at scale. At its core, Jumbo seeks to delight customers and deliver optimal grocery shopping experiences. Running differentiated store formats on one hand, and personalizing messages and offers to customers on the other, made it impossible to continue working in the traditional way. That\u2019s where data analytics and AI come in: they help us to make decisions at the scale required for personalization and differentiation.With the rollout of our revamped customer loyalty program, we were suddenly able to better understand a wide range of our individual customer preferences, such as which products are most important and which are often forgotten, as well as the best time of day to communicate with customers and on which channel. However, as data volumes grew exponentially, our analytics and ML capabilities began to slow as we weren\u2019t equipped to handle such scale. Increased data volumes meant increased complexity and resources required to try to handle it from an infrastructure perspective, which impacted our ability to deliver insights in a timely manner. Long processing and querying times were unacceptable. After years on a traditional statistical software package connecting to a traditional RDBMS and analytics in Jupyter notebooks, we knew that if we wanted to best use this data and deliver shopping experiences that make a difference, it was time for us to take steps to modernize our approach and the underlying technologies that enable it. We needed a platform that was able to crunch through customer-level data and train models at a scale much more than we could handle on our individual machines.In addition to needing to modernize our infrastructure to help us thrive with big data analytics, we also needed better ways to increase the speed from concept to production, decrease onboarding time for new people, collaborate and deliver self-service access to data insights for our analysts and business users to help serve insights around pricing, inventory, merchandising, and customer preferences. After looking into a variety of options, we selected the Databricks Lakehouse Platform as the right solution for our needs.From foundational customer loyalty to exceptional customer experiencesWith Databricks\u2019 Lakehouse implemented, we now run a substantial number of data science and data engineering initiatives in parallel to turn our millions of customers into even more loyal fans.As an example of data products exposed directly to customers, we\u2019re now able to combine, on a customer level, information about purchases made online and offline which was very challenging before. This omnichannel view allows us to create a more comprehensive recommendation engine online, which has seen tremendous engagement. Now, based on past purchasing history as well as first party data collected with consent, we can serve product-relevant recommendations that pique the interests of the consumer. Obviously, this is great from a business perspective, but the real benefit is how happy it\u2019s made our customers. Now, they\u2019re less likely to forget important items or purchase more than they need. This balance has significantly increased customer loyalty.One example data products that have helped improve the customer experience, we continually run an algorithm that proactively suggests assortment optimizations to assortment managers. This algorithm needs to run at scale at acceptable costs, as it optimizes using large quantities of data on physical store and online customers, the overall market, financials and store-level geographical characteristics. Once opportunities are identified, it is presented in combination with the same breadth and depth of data upon which it was based.From a technical perspective, the Databricks Lakehouse architecture is able to drive these improved experiences with the help of Microsoft Azure Synapse. Together, this combo has allowed us to manage, explore and prepare data for analysis for automated (proposed) decision making, and make that analysis easy to digest via BI tools such as Power BI. With deeper insights, we have helped spread a more meaningful understanding of customer behavior and empowered our data teams to more effectively predict the products and services they would want.Databricks is now fully integrated into our end-to-end workflow. The process starts with a unified Lakehouse architecture, which leverages Delta Lake to standardize access to all relevant data sources (both historical and real-time). For example, Delta Lake also helps to build data pipelines that enable scalable, real-time analytics to reduce in-store stockouts for customers and at the same time reduce unnecessary food waste due to over-ordering perishables, such as fresh produce, that won\u2019t sell. At the same time, Databricks SQL provides our data analysts with the ability to easily query our data to better understand customer service issues, processed with NLP in the background, and relate these issues to the operational performance of different departments involved. This helps us to make improvements faster that improve the customer experience most.We would not have been able to accelerate our modernization efforts without the expert training and technical guidance from the Databricks Academy and Customer Success Engineer, which acts as a direct injection of knowledge for our data science department. This deeper understanding of how to leverage all our data has led to significant improvements in how we manage our assortment, supply chain, make strategic decisions, and better support our customers\u2019 evolving needs.Excellence has no ceiling when driven by data and AIBy focusing on improving the customer experience through Delta Lakehouse, we were enabled beyond our initial expectations. The steps we\u2019ve taken to modernize our approach to how we can use data have really set us up as we continue to transform our business in a way that pushes our industry forward.It\u2019s remarkable to see how quickly data and AI capabilities are becoming the new normal and we are now well positioned to realize the direct impact of our efforts to be data-driven. The output of sophisticated machine learning models is considered \u2018common practice\u2019 within 4 weeks after introduction. And the speed of idea to production is counted in weeks nowadays, not months.Going forward, we\u2019ll continue to see the adoption level increase, not just at Jumbo, but across all of commerce. And for those who are also embarking on a data transformation, I would strongly recommend that they take a closer look at improvement possibilities in the experience they're providing customers. Feeding back your analytics data-products into operational processes at scale is key to transforming all areas of the business forward and successfully into the future.Try Databricks for freeGet StartedRelated postsSegmentation in the Age of PersonalizationMarch 16, 2021 by Bryan Smith and Rob Saker in Engineering Blog\nQuick link to notebooks referenced through this post. Personalization is heralded as the gold standard of customer engagement. Organizations successfully personalizing their digital...\nHyper-Personalization Accelerator for Banks and Fintechs Using Credit Card TransactionsMarch 3, 2022 by Antoine Amend in Engineering Blog\nJust as Netflix and Tesla disrupted the media and automotive industry, many fintech companies are transforming the Financial Services industry by winning the...\nPersonalizing the Customer Experience with RecommendationsDecember 18, 2020 by Rob Saker, Bryan Smith, Bilaji Raman, Ye Wang, Yiyan Zhang and Terry Tang in Engineering Blog\nGo directly to the Recommendation notebooks referenced throughout this post. Retail made a giant leap forward in the adoption of e-commerce in 2020...\nSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/glossary\/materialized-views","text":"Materialized viewsPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMaterialized viewsAll>Materialized viewsTry Databricks for freeGet StartedDelta Pipelines \/ Materialized Views in Databricks DeltaIntroDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve data reliability, and scale operations.\u00a0Instead of coding transformations and scheduling jobs for your data, you can easily define the end state you want for your data by building declarative pipelines.\u00a0 You can chain the dependencies between various tasks such that updating one table will automatically trigger all downstream reprocessing.\u00a0With Delta Lake, you will have reliable data lakes; with delta pipelines, you will have reliable data pipelines for your data workflows.Delta Pipelines DatasetsThe primary abstraction in Delta Pipelines is what\u2019s known as a Dataset.\u00a0A Dataset is basically a query or view of an underlying table that can be expressed using APIs.\u00a0 Below is an example using the Scala API:\r\ndataset(\"events\")\r\n   .query {\r\n       input(\"base_table\")\r\n       .select(...)\r\n       .filter(...)\r\n   }\r\nCreating Materialized Views of DatasetsDelta Pipelines also offers the ability to create a materialized view of the data by simply chaining the .materialize() operator on to the dataset set like such:\r\ndataset(\"events\")\r\n  .query {\r\n     input(\"base_table\")\r\n     .select(...)\r\n     .filter(...)\r\n  }\r\n     .materialize()\r\n\r\nThis means that the \u201cevents\u201d materialized view will be continuously updated as data flows through the Delta Pipeline. As new data arrives and is committed to the base table via ACID transactions, the materialized view is continuously updated incrementally for each of those transactions as well. Users need not worry about when or how frequently to refresh the materialized view or even things like when to run OPTIMIZE or VACUUM commands -- it\u2019s all done in the background automatically.See the below video for more details on Delta PipelinesTo play this video, click here and accept cookiesBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Experimente o Databricks | DatabricksExperimente o Databricks gratuitamente Experimente a plataforma Databricks completa gratuitamente por 14 dias em sua nuvem AWS, Microsoft Azure ou Google Cloud.Simplique a ingest\u00e3o de dados e automatize processos de ETLImporte dados de centenas de fontes. Utilize uma abordagem asseverativa e simples para construir pipelines de dados.Colabore em sua linguagem preferidaCode em Python, R, Scala e SQL com colabora\u00e7\u00e3o, versionamento autom\u00e1tico, integra\u00e7\u00f5es com Git e controles de acesso (RBAC) Pre\u00e7o\/Performance at\u00e9 12x superior a data warehouses em nuvemDescubra porque mais de 7000 clientes de todo mundo confiam na Databricks para todos os seus workloads de Dados, de BI a AI.Crie sua conta Databricks1\/2Primeiro NomeSegundo NomeEmailEmpresaT\u00edtuloTelefone (Opcional)SelecionarPa\u00edsContinuarAviso de privacidade (atualizado)Termos de UsoSuas op\u00e7\u00f5es de privacidadeSeus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rodrigo-beceiro","text":"Rodrigo Beceiro - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRodrigo BeceiroCTO & Cofounder at MarvikBack to speakersRodrigo Beceiro is Marvik co-founder and CTO, a machine learning development startup that specializes in Computer Vision, Predictive Analytics and Natural Language Processing. Rodrigo is an Telecommunications Engineer, Scrum Master, graduated from Udacity\u2019s AI nanodegree and from a Master in technological business management. He has also completed the MIT Deep Tech Bootcamp.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marius-panga","text":"Marius Panga - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarius PangaSolutions Architect at DatabricksBack to speakersSolutions Architect at Databricks with considerable experience in business intelligence, data warehousing, and data engineering. Deeply committed to exploring the potential of data and technology to tackle real-world issues.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2023\/03\/15\/enhancing-amperity-cdp-personalized-product-recommendations.html","text":"Enhancing the Amperity CDP with Personalized Product Recommendations - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorEnhancing the Amperity CDP with Personalized Product Recommendationsby Justin Fenton, Brian Shumsky, Jason Meketa, Nicole Lu and Bryan SmithMarch 15, 2023 in IndustriesShare this postPersonalization provides organizations a means to more directly connect with customers' needs and preferences. In a crowded retail landscape, such targeted engagement is often seen as a key differentiator, attracting customers, elevating their spend, and increasing their loyalty to particular brands. Consumers themselves increasingly express a desire to be seen and heard by the outlets with which they spend their time and money, and even when pulling back spend in the face of economic concerns, 52% of consumers in a recent survey stated they expect a better experience from brands in return for their spend.This shift towards personalization has even extended into the realm of consumer packaged goods. With relationships to consumers mediated by retail outlets, CPG manufacturers have long pursued mass-marketing strategies intended to increase demand for their goods across more general populations of consumers. But recent shifts in consumer habits and brand loyalties and the growth of private label brands have created a sense of urgency amongst manufacturers to connect more directly with consumers. The rise in retail media networks and consumer interest in DTC models all create an opportunity for this kind of relationship, but with these opportunities comes a new expectation for personalized engagement.The Need for a Customer Data Platform (CDP)The key to delivering personalized experiences is access to timely, high-quality data about the consumer. Information such as a customer's transaction history is critical but so are data on returns, product feedback, browsing history, customer service records, and so much more. These data, internally generated as well as externally captured, provide a 360-degree view of the customer from which new insights and experiences may be derived.While developing such a Customer-360 platform sounds straightforward, the reality is that it is not. Customer identity is often an elusive concept, large data volumes and complex data structures may make accessing information challenging, and sophisticated insights such as behavioral segment assignments and personalized product recommendations derived from base data in the 360-degree view may require access to sophisticated analytic capabilities. Many organizations with ambitions to establish a customer data platform (CDP) have found their efforts falling short, with only 14% of organizations achieving what they would qualify as success according to a recent survey.But there have been some successes, and as this space matures, we are seeing the emergence of a repeatable pattern that some refer to as a hybrid-CDP and others refer to as a composable-CDP.With this pattern (which we will refer to as a composable-CDP), many core challenges such as customer identity resolution, the acquisition and integration of frequently employed data and the derivation of standard metrics are largely addressed by more-or-less off-the-shelf CDP technologies. High-volume and complex data are accumulated on more flexible Data Lake or Lakehouse platforms where data may be pre-processed for downstream integration into the core CDP system. Advanced analytics needs may be tackled by pushing a subset of the harmonized information from the core CDP back into the Lakehouse where models may be trained and predictive insights generated which are themselves pushed back into the core CDP environment.While the composable-CDP entails quite a bit of data movement, it balances the strengths of the dual platforms, providing organizations the right combination of capabilities required to meet their Customer-360 needs.Integrating Amperity and Databricks to Form a Composable-CDPTo illustrate the combined power of the composable-CDP architecture, let's examine a simple integration between Amperity, a market leader in the CDP space with a deep specialization in ML-driven customer identity resolution, and Databricks, the platform that defined the Lakehouse approach to analytic data management (Figure 1).Figure 1. Integrating Amperity with Databricks to form a composable-CDPLeveraging Amperity's Databricks Delta table destination feature, data can easily be pushed and pulled between the Amperity CDP and the Databricks platform. We might leverage such an integration to push customer transactional history, enhanced by Amperity for reliable customer identification, to the Databricks environment. There, data may be used to train a model to generate customer-specific product recommendations. Those recommendations may then be pushed back to the Amperity CDP to be integrated into the Customer-360 where it can then be activated in a variety of channels like email, sms, push notifications, and paid media\/advertising like Google, TikTok, Facebook, Instagram, LiveRamp, Criteo and more.The key to this workflow is not simply the integration of the two platforms, but what each contributes to the end product, i.e. personalized product recommendations. While Databricks has long been recognized for its ability to train large and complex models such as those used in recommendation systems, the output of these models is only as good as the data they are trained upon.Amperity's ML-based identity resolution capabilities are critical in ensuring that data associated with a customer are accurately attributed to them. A study of Amperity customers' legacy identity resolution strategies found that on average organizations struggle to correctly identify 23% of their customers representing 53% of the revenue associated with those brands. It's hard to extract the benefits of personalization when you can't properly align the data from your best customers (Figure 2).Figure 2. Organizations typically struggle to correctly identify their top customersWant to See This in Action?To demonstrate the power of combining the Amperity CDP with the Databricks Lakehouse, we've put together a demonstration notebook exploring the generation of personalized product recommendations in a composable-CDP architecture. In this notebook, we demonstrate exactly how data is pushed from the Amperity CDP to Databricks, how enhanced transaction history from Amperity is used to train a recommender and how recommendations generated in Databricks are pushed back into the Amperity CDP.This is but one of many scenarios where our mutual customers are finding success in meeting their needs for a 360-view of their customers and creating a foundation for success in their personalization efforts. If you'd like to explore how Amperity and Databricks can help your organization achieve similar success, please contact either your Amperity or Databricks representatives.Try Databricks for freeGet StartedRelated postsProducts We Think You Might Like: Generating Personalized Recommendations Using Matrix FactorizationJanuary 6, 2023 by Eduardo Brasileiro, Yang Wang, Brian Law and Bryan Smith in Industries\nCheck our Solution Accelerator for Matrix Factorization for more details and to download the notebooks. Recommenders are a critical part of the modern...\nGetting Started with Personalization through Propensity ScoringJune 3, 2022 by Tian Tan, Sam Steiny and Bryan Smith in Industries\nConsumers increasingly expect to be engaged in a personalized manner. Whether it's an email message promoting products to complement a recent purchase, an...\nPersonalization Meets Scale: An Introduction to 1:1\u221eOctober 18, 2022 by Michael Griffiths in Data Strategy\nHow do you build meaningful, lasting relationships? With personalization as we're used to thinking about it, a blog like this would help drive...\nSee all Industries postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amine-benhamza\/#","text":"Amine Benhamza - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmine BenhamzaLead Solutions Architect at DatabricksBack to speakersAmine is a Sr. Solutions Architect specializing in Cloud, Data & AI, Migrations, and Enterprise Architecture. He has a significant experience and skills in: \n- Designing Cloud-Native Enterprise Architecture for SMBs and Fortune 500 Companies\n- Building & Lead Cross-Functional SME teams\n- Collaborating with Marketing and GTM teams to evangelize cloud-native technology to customers & partnersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/artem-meshcheryakov","text":"Artem Meshcheryakov - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArtem MeshcheryakovConsultant at ORAYLIS GmbHBack to speakersArtem Meshcheryakov has been working in BI & BigData for more than 5 years. \nStarting with Microsoft SQL Server and Oracle for traditional Data Warehousing Projects,\nwithin several years he switched to modern data platforms in the Azure Cloud with the main focus on Azure Databricks. \nFor several years now, he has been working in this area, \nhe has been involved in building solutions using Azure Databricks at \nlarge Scale and developing BigData Use Cases with Databricks.\nAt Oraylis, Artem works as a consultant and is responsible for implementing \nlarge-scale modern data platform in various Azure cloud scenarios.\nArtem is also a certified Databricks champion. \nHe is particularly interested in developing large-scale Big Data use cases \nusing Databricks and the Unity catalog in large enterprise environments.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anil-puliyeril","text":"Anil Puliyeril - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnil PuliyerilSenior Architect at HabuBack to speakersAnil Puliyeril, Senior Architect at Habu, has 10+ years of experience building innovative, highly scalable and best in class software systems using open source technologies. He is a specialist in Microservices, Cloud Services, and a self-proclaimed API-enthusiast. \nBefore Habu, Anil was a Principle Software Engineer at Salesforce where he was part of the Data Management Platform (DMP) Engineering Team that provided cloud-based data management services to organizations across the world. Prior to that, Anil held numerous engineering roles at Saba where he led the design and development of an api management framework and data integration platform. \nAnil has a Master of Science, Computer Software Engineering degree from the Birla Institute of Technology and Science, Pilani and a Bachelor of Engineering, Computer Science from the University of Mumbai.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/roger-dunn","text":"Roger Dunn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRoger DunnCo-founder, CTO at ExponamBack to speakersRoger is founder and CTO of Exponam, the most recent in a series of technology product companies he has launched. Roger is a pioneer in design of complex systems at the intersection of security, data, and massively scalable distributed computing. He has 30+ years corporate and government experience in architecture and development. He has held senior positions at Apple, Microsoft, and KPMG.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/devlina-das\/#","text":"Devlina Das - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDevlina DasSenior Software Engineer at InstacartBack to speakersDevlina is a Software Engineer at Instacart focusing on data processing at scale. She has above 10 years of software development experience.\nArthur Li is a software engineer who has been working at Instacart for the past two years focusing on batch data processing infrastructure. He has contributed to the company's data platform team by implementing data collection and management strategies that have streamlined the company's data infrastructure.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matei-zaharia","text":"Matei Zaharia - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark\u2122 and MLflow at DatabricksBack to speakersMatei Zaharia is a Cofounder and Chief Technologist at Databricks as well as an Assistant Professor of Computer Science at Stanford. He started the Apache Spark project during his PhD at UC Berkeley in 2009, and has worked broadly on other widely used data and machine learning software, including MLflow, Delta Lake and Apache Mesos. He works on a wide variety of projects in data management and machine learning at Databricks and Stanford. Matei\u2019s research was recognized through the 2014 ACM Doctoral Dissertation Award, an NSF CAREER Award, and the US Presidential Early Career Award for Scientists and Engineers (PECASE).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/apache-kudu","text":"What is Apache Kudu?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache KuduAll>Apache KuduTry Databricks for freeGet StartedWhat is Apache Kudu?Apache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows together with great analytical access patterns. It is a Big Data engine created make the connection between the widely spread Hadoop Distributed File System [HDFS] and HBase NoSQL Database.Main advantages of Apache Kudu in the support of business intelligence [BI] on HadoopEnables real-time analytics on fast dataApache Kudu merges the upsides of HBase and Parquet. It is as fast as HBase at ingesting data and almost as quick as Parquet when it comes to analytics queries. It supports multiple query types, allowing you to perform the following operations:Lookup for a certain value through its key.Lookup for a range of keys that have been sorted in a key-order.Carry out arbitrary queries across as many columns as neededFully distributed and fault tolerantApache Kudu uses the RAFT consensus algorithm, as a result, it can be scaled up or down as required horizontally. In addition it comes with a support for update-in-place feature.Takes advantage of the upcoming generation of hardwareApache Kudu comes optimized for SSD and it is designed to take advantage of the next persistent memory. It is able to scale to 10s of cores per server and even benefit of SIMD operations for data-parallel computation.Provides the mutability required for BI on big dataIt features a \u2018slowly changing dimension\u2019 also known as SCD. This capability allows the user to keep track of changes inside a dimensional reference data.Kudu Supports SQL if used with Spark or ImpalaDo you want to access data via SQL? Then, you\u2019ll be happy to hear that Apache Kudu has tight integration with Apache Impala as well as Spark. As a result, you will be able to use these tools to insert, query, update and delete data from Kudu tablets by using their SQL syntax. Moreover, you can use JDBC or ODBC to connect existing or new applications no matter the language they have been written in, frameworks, and even business intelligence tools to your Kudu data, using Impala as the tootle to do this.Additional ResourcesApache Kudu and Spark SQL for Fast Analytics on Fast DataBuilding Real-Time BI Systems with Kafka, Spark, and KuduBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/will-girten\/#","text":"Will Girten - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWill GirtenSr. Specialist Solutions Architect at DatabricksBack to speakersAs a Lead SSA at Databricks and author of the Node.js connector for Delta Sharing, Will is driven by his passion for open-source technologies and creating a more connected, data-driven world. He has over a decade of experience in big data, data warehousing, and performance optimizations. Will is committed to pushing the limits of what's possible and delivering transformative results. Contributing to the Delta Sharing project is just one way he's working to make a difference.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/trust?itm_data=menu-item-securitytrustcenter","text":"\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an Issue\ub370\uc774\ud130\ub294 \uace0\uac1d\uc758 \uac00\uc7a5 \uc911\uc694\ud55c \uc790\uc0b0\uc774\uace0 \uc5b8\uc81c\ub098 \ubcf4\ud638\ud574\uc57c \ud560 \ub300\uc0c1\uc785\ub2c8\ub2e4. \uadf8\ub798\uc11c \ubcf4\uc548\uc740 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \ubaa8\ub4e0 \uacc4\uce35\uc5d0 \uae30\ubcf8\uc73c\ub85c \ub4e4\uc5b4\uac11\ub2c8\ub2e4. Databricks\ub294 \ud22c\uba85\uc131\uc744 \uc9c0\ucf1c \uace0\uac1d\uc774 \ub2f9\uc0ac \ud50c\ub7ab\ud3fc\uc744 \ud65c\uc6a9\ud558\ub294 \ub3d9\uc548 \ud544\uc218\uc801\uc778 \uaddc\uc815\uc744 \uc900\uc218\ud560 \uc218 \uc788\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\ub370\uc774\ud130\ub294 \uace0\uac1d\uc758 \uac00\uc7a5 \uc911\uc694\ud55c \uc790\uc0b0\uc774\uace0 \uc5b8\uc81c\ub098 \ubcf4\ud638\ud574\uc57c \ud560 \ub300\uc0c1\uc785\ub2c8\ub2e4. \uadf8\ub798\uc11c \ubcf4\uc548\uc740 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \ubaa8\ub4e0 \uacc4\uce35\uc5d0 \uae30\ubcf8\uc73c\ub85c \ub4e4\uc5b4\uac11\ub2c8\ub2e4. Databricks\ub294 \ud22c\uba85\uc131\uc744 \uc9c0\ucf1c \uace0\uac1d\uc774 \ub2f9\uc0ac \ud50c\ub7ab\ud3fc\uc744 \ud65c\uc6a9\ud558\ub294 \ub3d9\uc548 \ud544\uc218\uc801\uc778 \uaddc\uc815\uc744 \uc900\uc218\ud560 \uc218 \uc788\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\uc2e0\ub8b0\ubc1b\ub294 \ud50c\ub7ab\ud3fc\uc2e0\ub8b0\ub294 \ud22c\uba85\uc131\uc5d0\uc11c \uc0dd\uaca8\ub0a9\ub2c8\ub2e4. Databricks\uac00 \uc5b4\ub5bb\uac8c \uce68\ud22c \ud14c\uc2a4\ud2b8, \ucde8\uc57d\uc131 \uad00\ub9ac, \ubcf4\uc548 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \uac1c\ubc1c \ub4f1, \uc5c5\uacc4 \ucd5c\uace0\uc758 \ud50c\ub7ab\ud3fc \ubcf4\uc548 \uae30\uc220\ub85c Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \ubcf4\ud638\ud558\ub294\uc9c0 \ud655\uc778\ud574 \ubcf4\uc138\uc694.\uc790\uc138\ud788\ubcf4\uc548 \uae30\ub2a5\ub370\uc774\ud130\uc640 \uc6cc\ud06c\ub85c\ub4dc\ub97c \ubcf4\ud638\ud558\uae30 \uc704\ud55c \ud3ec\uad04\uc801 \ubcf4\uc548 \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 \uc554\ud638\ud654, \ub124\ud2b8\uc6cc\ud06c \ucee8\ud2b8\ub864, \uac10\uc0ac, ID \ud1b5\ud569, \uc561\uc138\uc2a4 \ucee8\ud2b8\ub864, \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4 \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\uaddc\uc815 \uc900\uc218\uc804 \uc138\uacc4\uc801\uc73c\ub85c \ubaa8\ub4e0 \uc0b0\uc5c5\uc5d0\uc11c \uace0\uac1d\ub4e4\uc774 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc778\uc99d\uacfc \uc99d\uac70\ub97c \ud1b5\ud574 \uaddc\uc81c\uac00 \ub9e4\uc6b0 \uc5c4\uaca9\ud55c \uc0b0\uc5c5\uc758 \uace0\uc720\ud55c \uaddc\uc815 \uc900\uc218 \uc694\uad6c \uc0ac\ud56d\uc744 \uc9c0\ud0b5\ub2c8\ub2e4.\uc790\uc138\ud788\uac1c\uc778\uc815\ubcf4 \ubcf4\ud638Databricks\ub294 \ub370\uc774\ud130 \ubcf4\ud638\ub97c \uc911\uc694\ud558\uac8c \uc0dd\uac01\ud558\uba70, \uace0\uac1d\uacfc \uace0\uac1d\uc758 \uc870\uc9c1 \ubaa8\ub450\uc5d0\uac8c \uc911\uc694\ud558\ub2e4\ub294 \uac83\uc744 \uc54c\uace0 \uc788\uc2b5\ub2c8\ub2e4. Databricks\ub294 \uace0\uac1d\uc774 \uac1c\uc778\uc815\ubcf4 \ubcf4\ud638\ubc95\uc744 \uc900\uc218\ud558\uace0 \uaddc\uc81c \uc694\uac74\uc744 \uc704\ubc18\ud558\uc9c0 \uc54a\ub3c4\ub85d \ub3c4\uc6c0\uc744 \ub4dc\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ubb38\uc11c, \uaddc\uc815 \uc900\uc218 \uc790\ub8cc\uac00 \ud3ec\ud568\ub41c \uc2e4\uc0ac \ud328\ud0a4\uc9c0\ub97c \uc0ac\uc6a9\ud558\uc5ec Databricks\uc758 \ubcf4\uc548\uc744 \uc9c1\uc811 \uac80\ud1a0\ud574 \ubcf4\uc138\uc694.\uc2e4\uc0ac \ud328\ud0a4\uc9c0\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yang-you\/#","text":"Yang You - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYang YouPresidential Young Professor at National University of SingaporeBack to speakersProf. Yang You is a Presidential Young Professor at the National University of Singapore. His team broke the world record of ImageNet and BERT training speed. He is a winner of the IPDPS Best Paper Award, ICPP Best Paper Award, AAAI Distinguished Paper Award, ACM\/IEEE George Michael HPC Fellowship, Siebel Scholar, Lotfi A. Zadeh Prize, and nominated for the ACM Doctoral Dissertation Award. He also made Forbes 30 Under 30 Asia list (2021) for young leaders and IEEE-CS TCHPC early career award.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/pricing?_gl=1*13qxq5q*_ga*NjJmNzBjYzgtOGFhYi00MTYwLTg3MjktMTcxYzIyZTAzYjM0*_ga_PQSEQ3RZQC*MTY4MTY4Nzg5My4xMDUuMS4xNjgxNjk1MzEwLjQ4LjAuMA..&_ga=2.69652304.1988636371.1681687893-62f70cc8-8aab-4160-8729-171c22e03b34&_gac=1.261427839.1680277031.Cj0KCQjwiZqhBhCJARIsACHHEH-M4XCl4tuJ05NvqDEChz-8-RE-4XIPYaVm_HzJBijsf9XqoKC5dmwaAjv9EALw_wcB","text":"Pricing - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPricingConference\n\n\n\n\n\n\n\n\n\n\n\nFull Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1795 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nGroup DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1295 IN-PERSONEACH\n\n\n\n\n\n\n\n\n\n\n\nGOV\/EDU\/NFPDiscounted pass for Government\/Education\/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1395 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\nVirtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event.\n $0 VIRTUALTraining\n\n\n\n\n\n\n\n\n\n\nTwo-Day CourseThis includes a two-day course and the certification exam.\n$1125 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nFull-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic.\n$750 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nHalf-Day TrainingA 4-hour, in-depth session covering your chosen topic.\n$375 IN-PERSONCertification\n\n\n\n\n\n\n\n\n\n\n\nCertification ExamRegister for training and take a certification exam onsite for free.\n$0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/blog\/2021\/05\/04\/databricks-on-google-cloud-now-generally-available.html","text":"Databricks on Google Cloud Now Generally Available - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorDatabricks on Google Cloud Now Generally Availableby Hiral Jasani and Joel ThomasMay 4, 2021 in PartnersShare this postToday, we announced the general availability of Databricks on Google Cloud, a jointly developed service that combines an open Lakehouse platform with an open cloud. Since the announcement of Databricks on Google Cloud, we have seen tremendous momentum for this partnership as customers pursue a multi-cloud approach to their analytics and DS\/ML workloads. Customers are demanding a simple, unified platform as they move workloads to Databricks on Google Cloud built on open standards with technologies like Delta Lake, MLflow and Google Kubernetes Engine. This GA release is now available in multiple regions in the US and Europe with additional regions coming soon.\nWhat's new in GAThe GA release includes several new features:\nRepo and Project support to sync your work with remote Git repositoryTable ACLs that lets you programmatically grant and revoke access to data from Python and SQLDB Connect to connect to Databricks from your favorite IDECluster Tags for DBU Usage trackingNotebook scoped libraries to create and share custom Python environments that are specific to a notebookLocal SSD Support for caching and improved performanceTableau connector to Databricks on Google CloudTerraform provider to easily provision and manage Databricks along with associated cloud infrastructure.Reckitt was among the first to use Databricks on Google Cloud. Databricks delivers tight integrations with Google Cloud\u2019s compute, storage, analytics and management products. This includes the first Google Kubernetes Engine (GKE) based, fully containerized Databricks runtime on any cloud, pre-built connectors to seamlessly and quickly integrate Databricks with BigQuery, Google Cloud Storage, Looker and Pub\/Sub. In addition, customers can deploy Databricks from the Google Cloud Marketplace for simplified procurement and user provisioning, Single Sign-On and unified billing. With Databricks on Google Cloud for data and AI workloads, Reckitt unlocks competitive advantages such as cost savings, agility, increased innovation and business continuity planning. Let\u2019s take a closer look.\nReckitt: AI-focused customer analytics platformReckitt, a multinational consumer goods company that serves millions of retail customers worldwide, is on a mission to improve their analytics workflows with AI-driven decisions. Reckitt\u2019s struggle was similar to many other companies - they were dealing with tons of data and disjointed pipelines, and each time the team implemented a data science project, they found themselves reinventing the wheel. This led them to make AI a priority at an enterprise-level with a \u201cubiquitous AI\u201d vision:\nTo infuse trusted, AI-driven decisions into daily workflows and liberate our people's limitless potential for innovationOne of the first projects was a Customer Analytics platform aimed at improving marketing ROI across 50 brand-market units in 13 countries with metrics like audience activation and media effectiveness.\nReckitt chose Databricks on Google Cloud to enable their customer analytics efforts. By unifying media data from hundreds of sources for consumer identification, Reckitt is building a highly-modular data platform that can support key use cases such as measuring the performance of a propensity model to drive sales uplift or the impact of first-party data on their conversion funnel.\nThe above diagram shows Reckitt\u2019s Databricks on Google Cloud Marketing ROI solution architecture. The main features of the diagram include:\nData Collection: Read structured and unstructured data into BigQuery from 114 unique media datastreams from sources such as Facebook, YouTube and Pinterest and Google Analytics; unstructured data from IoT devices and SaaS applications such as Salesforce is stored in GCS.Transformation: Apply business rules and aggregation in Delta Lake and calculate KPIs. Delta Lake allows Reckitt to reuse existing data pipelines from other public clouds since it stores the data in an open-source parquet format that can be easily stored in GCS.Analyze: Use SQL Analytics, Cloud Natural Language and MLflow for further analysis.Visualize: Data scientists, business analysts and executives use Power BI and Data Studio for visualization. Insights are leveraged downstream across ad platforms, email, CRM and other systems.DataOps and MLOps are critical drivers of Reckitt\u2019s multi-cloud architecture. Databricks on Google Cloud makes it possible to reuse PySpark scripts and existing data pipelines on Delta Lake, greatly simplifying data engineering and data science at scale. The result is a hyper-targeted set of audiences that are engaged across multiple media channels, measured by ROI uplift across those channels. Audience activations and marketing ROI boost has yielded 44% efficiency in cost-per-view, 11% reduced cost-per-1000 impressions and 10% improved view-thru-rate. Learn more about Reckitt\u2019s data analytics journey here.\nBroad partner supportDatabricks on Google Cloud is supported by our broad ecosystem of partners who share their commitment to open standards, integrations and solution expertise for Databricks on Google Cloud. These partners bring deep experience in the Databricks Lakehouse architecture for building the AI and ML foundation across targeted industry solutions. We are pleased to have these partners invest in working with us above and beyond to support the GA launch of Databricks on Google Cloud:\nBI Partners: Tableau, Qlik, LookerIngest Partners: Fivetran, Fishtown Analytics, Talend, Qlik, Infoworks, Trifacta, and InformaticaCatalog Partners: CollibraGovernance: Immuta, PrivaceraData Sources: Confluent, MongoDBConsulting Partners: Accenture, Cognizant, Deloitte, Insight, SoftServe, Slalom, TCSTalking with customers through the public preview, it is clear that multi-cloud is a growing strategy for cloud data and analytics workloads. The general availability of Databricks on Google Cloud further advances the potential of multi-cloud with the open, simple Databricks Lakehouse platform that brings analytics workloads to multiple clouds.\nSign Up for Free TrialTry Databricks for freeGet StartedSee all Partners postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shir-chorev","text":"Shir Chorev - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShir ChorevCTO at DeepchecksBack to speakersShir is the co-founder and CTO of Deepchecks, an MLOps startup for continuous validation of ML models and data. Previously, Shir worked at the Prime Minister\u2019s Office and at Unit 8200, conducting and leading research in various Machine Learning and Cybersecurity related challenges. Shir has a B.Sc. in Physics from the Hebrew University, which she obtained as part of the Talpiot excellence program, and an M.Sc. in Electrical Engineering from Tel Aviv University. Shir was selected as a featured honoree in the Forbes Europe 30 under 30 class of 2021.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/keshav-santhanam\/#","text":"Keshav Santhanam - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKeshav SanthanamPhD Student at Stanford UniversityBack to speakersKeshav is a 4th-year PhD student at Stanford University advised by Matei Zaharia. His research is broadly centered on optimizing systems for machine learning, with a recent focus on improving resource efficiency for neural information retrieval systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/careers","text":"Karriere bei Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Karriere bei DatabricksWir betrachten es als unseren Auftrag, Datenteams bei der L\u00f6sung hochkomplexer Probleme zu unterst\u00fctzen. M\u00f6chten Sie mitmachen?Offene Stellen anzeigen OverviewCultureBenefitsDiversityStudents & new gradsKarriere machen, Zukunft gestaltenDatabricks ist die Speerspitze der Daten- und KI-Revolution. Das von uns entwickelte Lakehouse war seinerzeit etwas ganz Neues. Heute wird es von vielen Tausend Unternehmen genutzt, um so unterschiedliche Probleme wie Klimawandel, Betrug, Kundenabwanderung und mehr in den Griff zu bekommen. Wenn Sie nach einer M\u00f6glichkeit suchen, Ihre Karriere wirklich zu befeuern, dann sind Sie bei uns richtig.Warum das Lakehouse die Zukunft istWarum Databricks?Wir wachsen schnell und gewinnen die kl\u00fcgsten K\u00f6pfe. Die Menschen, die bei uns arbeiten, zeichnen sich durch hohe Intelligenz, ausgepr\u00e4gte Neugier und eine betr\u00e4chtliche Auffassungsgabe aus. Nicht umsonst bezeichnen wir uns intern mit Stolz als \u201eBrickster\u201c. Und wenn Sie einen Brickster fragen, was ihm an der Arbeit hier gef\u00e4llt, werden Sie wahrscheinlich vor allem etwas \u00fcber unsere Unternehmenskultur erfahren.Grunds\u00e4tze unserer Unternehmenskultur anzeigenFinden Sie Ihr TeamVerwaltungGesch\u00e4ftsentwicklungCustomer SuccessEngineeringField EngineeringFinanzenITRechtlichesMarketingBetriebPersonalwesenProduktProfessionelle ServicesPersonalbeschaffungVertriebSicherheitsfragenPraktika und KarrierestartSozialleistungen, Verg\u00fcnstigungen und HybridarbeitWenn Sie Ihr Bestes geben wollen, sind Gesundheit und Wohlbefinden entscheidend. Deshalb bieten wir erstklassige Sozialleistungen und Verg\u00fcnstigungen, z.\u00a0B. hohe Flexibilit\u00e4t bei den Arbeitszeiten. Am Ende h\u00e4ngt schlie\u00dflich alles davon ab, was f\u00fcr Sie und Ihr Team am besten funktioniert.Unsere Sozialleistungen erkundenDiversit\u00e4t, Gleichstellung und InklusionWir sind davon \u00fcberzeugt, dass vielf\u00e4ltige Hintergr\u00fcnde, Perspektiven und Kompetenzen zu unserem Erfolg beitragen. Deshalb arbeiten wir gezielt auf die Schaffung eines integrativen und flankierenden Umfeldes hin. Erfahren Sie, was wir tun, um Lohnunterschiede zu beseitigen, beim Recruitment die Auswirkungen unbewusster Vorbehalte zu entfernen und mehr.Mehr zu Inklusion in AktionStandorteUnser Hauptsitz befindet sich im kalifornischen San Francisco. Au\u00dferdem betreiben wir mittlerweile mehr als 20\u00a0Niederlassungen in zw\u00f6lf L\u00e4ndern. Mit \u00fcber 4.500\u00a0Brickstern weltweit und einer ehrgeizigen Wachstumsstrategie geh\u00f6ren wir zu den am schnellsten wachsenden Cloud-Unternehmen f\u00fcr Unternehmenssoftware.Niederlassungen weltweit anzeigenAmerika\n\u00a0San FranciscoSeattleWashingtonNew YorkMehr lesenEuropa\n\u00a0LondonAmsterdamBerlinM\u00fcnchenMehr lesenAsien-Pazifik\n\u00a0TokioSingapurSeoulHangzhouMehr lesenChancen f\u00fcr Studierende und frische AbsolventenWir arbeiten konsequent am Aufbau der n\u00e4chsten F\u00fchrungskr\u00e4ftegeneration bei Databricks. Deshalb achten wir auch ganz bewusst darauf, dass unsere Praktikanten und Absolventen, die ihren Abschluss frisch in der Tasche haben, bei der Entwicklung unserer Plattform eine wichtige Rolle spielen.Mit unserem University Program m\u00f6chten wir Ihnen helfen, das Beste aus Ihrer Zeit bei uns zu machen. Die Veranstaltungen umfassen ein breites Spektrum von technischen Hackathons \u00fcber die Praktikantenolympiade bis hin zu Spieleabenden und Happy Hours.Praktikumsangebote erkunden Transparenz des Krankenversicherungsschutzes (nur USA)ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/arujit-pradhan\/#","text":"Arujit Pradhan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingArujit PradhanSoftware Engineer at CoinbaseBack to speakersArujit is a Software Engineer working on the Data Platform & Services team at Coinbase, where he builds frameworks for Centralized Streaming Ingestion and Change Data Capture Infrastructure. Before joining Coinbase he worked at Gojek in the Data & ML Platform team building Streaming Processing and Feature Store Infrastructure and was one of the core developers in the Open DataOps Foundation. When not working, he watches anime, reads Manga and bikes.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joanna-gurry\/#","text":"Joanna Gurry - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoanna GurryExecutive, Data Delivery at National Australia Bank (NAB)Back to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/learn\/training\/lakehouse-fundamentals?itm_data=learn-promocard-lakehousefundamentals","text":"Lakehouse Fundamentals | DatabricksFree Training: Databricks Lakehouse FundamentalsBuild your skills with 4 short videosThe Lakehouse architecture is quickly becoming the new industry standard for data, analytics, and AI. Get up to speed on Lakehouse by taking this free on-demand training \u2014 then earn a badge you can share on your LinkedIn profile or resume.Watch 4 short tutorial videos, pass the knowledge test and earn an accreditation for Lakehouse Fundamentals \u2014 it\u2019s that easy.Videos included in this training:Intro to Data LakehouseIntro to Databricks Lakehouse PlatformIntro to Databricks Lakehouse Platform Architecture and Security FundamentalsIntro to Supported Workloads on the Databricks Lakehouse PlatformEarn your accreditation today and share your accomplishment on LinkedInLearn Lakehouse FundamentalsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/resources\/ebook\/put-your-erp-data-work","text":"Put Your ERP Data to Work | DatabrickseBookPut Your ERP Data to WorkEnd data silos with the lakehouseSupply chain disruptions and rapid inflation are threatening your bottom line. But with the right data and the right insights, you can make decisions that minimize volatility and variability \u2014 and give you a competitive edge. Find out how in this new eBook from Databricks.You\u2019ll discover how to:Extract SAP IT data and integrate it with non-SAP dataRetain historical data for a longer period to enhance reporting and analysisSupport real-time advanced analytics at a much lower TCOUnderstand the full picture of your value chains with reporting and predictive analyticsGet more from your ERP dataProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/industries\/gaming","text":"Databricks for GamingSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for GamingAll your game analytics, data and AI on one platform. Learn how Databricks can help you know, grow and retain engaged players.Get startedSchedule a demoTo play this video, click here and accept cookiesMeet Data Lakehouse: The best of both worlds in one platformA data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It\u2019s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all your data and cloud platforms.Learn moreWhy Databricks for Gaming?Create better in-game experiences\nBring together all your structured and unstructured data in a single platform to gain real-time insights you can act on.Drive stronger business outcomes through collaboration\nDatabricks\u2019 collaborative workspace for data and AI means teams can innovate and deploy solutions faster.Scale based on your game\nDatabricks helps you automatically scale your data workloads based on game traffic to avoid over-provisioning and paying for wasted compute.Leverage pre-built models for ML and AI\nDatabricks has a collaborative notebook environment with managed runtime for machine learning models, as well as Solution Accelerators for common use cases including customer lifetime value, churn prediction and toxicity detection.Databricks for Gaming use casesUse Databricks in pre-production to accelerate your development and create a tighter game loop. Then leverage the 360-degree view of your players to drive more effective engagement and monetization over time.Game development lifecycle\nUse big data and AI to drive game design through enhanced insights and predictive intelligence\nGame design\nGame balancing\nGame play insights\nImage analytics\/toxicity analysis\nLoyalty promotions\nGamer acquisition and experience\nCreate a personalized, frictionless journey to move gamers from anonymous to superfan\nAd click-through analysis\nReal-time ad targeting\nRecommendation engine\nChurn prediction and prevention\nQuality of service analysis\nGamer monetization and sentiment\nLeverage insights to increase gamer lifetime value, find look-alike gamers and drive growth\nPlayer 360\/gamer lifetime value\nPlayer performance tracking\nProduct placement and pricing\nSocial sentiment analysis\nNext best offer\/product\nLearn moreCreating an optimal in-game experience for SEGA\n\u201cWith Databricks Lakehouse, we have access to data inputs across our entire player community, gaining insights that we can quickly build into new features they\u2019ll love.\u201d\u2014 Felix Baker, Data Services Manager, SEGA EuropeDatabricks for Gaming in actionLearn how Databricks powers games on AWS and Microsoft AzureAWS\nDatabricks on AWS has the services to help you build your game with increased flexibility, scalability and reliabilityMicrosoft Azure\nCombine Azure Databricks with PlayFab to gain real-time insights that you can act onResourceseBooksLearn moreWebinarsWatch nowBlogsLearn moreReady to get started?We\u2019d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/solutions\/audience\/digital-native","text":"\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4 \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\uc2dc\uc7a5 \uc9c4\ucd9c \ubc0f \uacf5\ub3d9 \ub9c8\ucf00\ud305 \ud61c\ud0dd\uc744 \ud65c\uc6a9\ud558\uc5ec \ub3c4\ub2ec \ubc94\uc704\ub97c \ud655\uc7a5\ud558\uace0 \ube44\uc988\ub2c8\uc2a4\ub97c \uc131\uc7a5\uc2dc\ud0a4\uc2ed\uc2dc\uc624.\uc790\uc138\ud788Databricks\ub97c \uae30\ubc18\uc73c\ub85c \ud558\ub294 \ucc28\uc138\ub300 \ube44\uc988\ub2c8\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub97c \uc704\ud55c \uc194\ub8e8\uc158 \uc544\ud0a4\ud14d\ucc98\uc6b0\uc218\ud55c \uc131\ub2a5\uc758 \ud655\uc7a5\ud615 ETL \ud30c\uc774\ud504\ub77c\uc778\ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uac00\uce58 \uc788\ub294 \uc778\uc0ac\uc774\ud2b8\ub97c \uc81c\uacf5\ud558\ub294 \ub370 \uc9d1\uc911\ud560 \uc218 \uc788\ub294 \uc804\uccb4\uc801\uc778 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubc0f ETL \ud50c\ub7ab\ud3fc\uc744 \uad6c\ucd95\ud574 \ubcf4\uc138\uc694. \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc5ec \uad00\ub9ac\ud558\uac70\ub098, 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\ubcf4\uc7a5\ud558\uace0 \ub370\uc774\ud130 \uac74\ub108\ub6f0\uae30\ub97c \ud5a5\uc0c1\ud574 \ubcf4\uc138\uc694.\uc2dc\uc791\ud558\uae30SQL \ubd84\uc11d \ubc0f \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ud55c \uacf3\uc5d0\uc11c \uc190\uc27d\uac8c \ubaa8\ub4e0 \ub370\uc774\ud130\ub97c \uc218\uc9d1, \ubcc0\ud658, \ucffc\ub9ac\ud558\uace0 \uc2e4\uc2dc\uac04 \ube44\uc988\ub2c8\uc2a4 \uc778\uc0ac\uc774\ud2b8\ub97c \ub354\uc6b1 \ube60\ub974\uac8c \uc81c\uacf5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uac00\uaca9 \ub300\ube44 \ucd5c\ub300 12\ubc30 \ud5a5\uc0c1\ub41c \uc131\ub2a5\uc73c\ub85c \ubaa8\ub4e0 SQL \ubc0f BI \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc2e4\ud589\ud574 \ubcf4\uc138\uc694. \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\uc640 \ubcf4\uc548\uc744 \ubcf4\uc7a5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ucef4\ud4e8\ud305 \ub9ac\uc18c\uc2a4\uc758 \uc644\uc804 \uad00\ub9ac\ud615 \ubd80\ud558 \ubd84\uc0b0\uacfc \ud655\uc7a5\uc73c\ub85c \ub192\uc740 \ub3d9\uc2dc\uc131\uc744 \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uac1c\ubc29\uc801 \ud615\uc2dd\uacfc API\ub97c \ud65c\uc6a9\ud558\uace0, \ub9de\ucda4\ud615 \ucee4\ub125\ud130\ub85c \uc6d0\ud558\ub294 \uc218\uc9d1, \ubcc0\ud658 \ubc0f BI \ub3c4\uad6c\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc11c\ubc84\ub9ac\uc2a4 \ucef4\ud4e8\ud305\uc73c\ub85c \ub9ac\uc18c\uc2a4 \uad00\ub9ac \uc624\ubc84\ud5e4\ub4dc\ub97c \ub0ae\ucda5\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\ud601\uc2e0\uc801\uc778 \uba38\uc2e0 \ub7ec\ub2dd\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \uc0dd\uc0b0\uc131\uacfc \ud611\uc5c5\uc744 \uac1c\uc120\ud558\uc5ec ML \ubc0f \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\ub97c \uac00\uc18d\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uae00\ub798\uc2a4 \ubc15\uc2a4 AutoML\uc6a9 \ud611\uc5c5 \ub3c4\uad6c\uc640 \uc635\uc158\uc744 \ud65c\uc6a9\ud574 \ubcf4\uc138\uc694.\ubaa8\ub378 \uad00\ub9ac\uc640 \ud638\uc2a4\ud305 Feature Store\ub97c \uc81c\uacf5\ud558\ub294 \ud55c\ud3b8, \uc140\ud504 \uc11c\ube44\uc2a4 \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130\uc640 \ud2b9\uc9d5\uc744 \uc900\ube44, \ucc98\ub9ac\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.MLflow\ub97c \ud1b5\ud574 \uc2e4\ud5d8\uc5d0\uc11c \ud504\ub85c\ub355\uc158\uae4c\uc9c0 ML \uc218\uba85 \uc8fc\uae30\ub97c \ud45c\uc900\ud654\ud558\uace0, \ubaa8\ub378 \ub9e4\uac1c\ubcc0\uc218, \uc9c0\ud45c, \uc774\ud130\ub808\uc774\uc158\uc744 \uc7a5\uae30\uc801\uc73c\ub85c \ucd94\uc801\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ubc30\uce58\uc5d0\uc11c \ub610\ub294 \uc11c\ubc84\ub9ac\uc2a4 \uc2e4\uc2dc\uac04 REST \uc5d4\ub4dc\ud3ec\uc778\ud2b8\ub97c \ud65c\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \ubc30\ud3ec\ud558\uc138\uc694.\uc2dc\uc791\ud558\uae30\uae30\uc220 \ud30c\ud2b8\ub108\nDatabricks \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc790\uc8fc \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \ubc0f AI \ub3c4\uad6c\uc640 \uc11c\ube44\uc2a4\ub97c \ubc1c\uacac\ud558\uace0 \ud1b5\ud569\ud574 \ubcf4\uc138\uc694\nPartner Connect \ub458\ub7ec\ubcf4\uae30\uc0b0\uc5c5 \uc194\ub8e8\uc158\ucc28\uc138\ub300 \uc5c5\uacc4 \ub9ac\ub354\ub4e4\uc774 Databricks\ub85c \ub370\uc774\ud130 \ubd84\uc11d \ubc0f AI \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud558\ub294 \uc911\uc785\ub2c8\ub2e4\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158 \ub458\ub7ec\ubcf4\uae30\uc18c\ub9e4 \ubc0f \uc18c\ube44\uc7ac\n\uc2e4\uc2dc\uac04\uc73c\ub85c \uacb0\uc815\uc744 \ub0b4\ub9ac\uace0 \uace0\uac1d \uacbd\ud5d8\uc744 \uac15\ud654\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc790\uc138\ud788\uae08\uc735 \uc11c\ube44\uc2a4\n\ubbf8\ub798\uc5d0 \ub300\ube44\ud55c \ub370\uc774\ud130 \ubc0f AI \uc911\uc2ec \uae08\uc735 \uc11c\ube44\uc2a4\ub97c \uc6b4\uc601\ud574 \ubcf4\uc138\uc694.\n\uc790\uc138\ud788\uac8c\uc784\n\ub370\uc774\ud130 \ubc0f AI \ud798\uc744 \ud65c\uc6a9\ud558\uc5ec \ucc28\uc138\ub300 \uac8c\uc784 \uacbd\ud5d8\uc744 \uac1c\ubc1c\ud574 \ubcf4\uc138\uc694.\n\uc790\uc138\ud788\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\u00a0\n\ucc28\uc138\ub300 \uc0ac\uc6a9\uc790 \uacbd\ud5d8\uc744 \uc704\ud55c \ub370\uc774\ud130 \ubc0f AI \uc911\uc2ec \ubbf8\ub514\uc5b4\ub97c \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc790\uc138\ud788\uae30\uc220 \ubc0f \uc18c\ud504\ud2b8\uc6e8\uc5b4\n\uace0\uae09 \ub370\uc774\ud130 \ubc0f ML \uae30\ub2a5\uc73c\ub85c \ucc28\uc138\ub300 \uc194\ub8e8\uc158\uc744 \uac1c\ubc1c\ud574 \ubcf4\uc138\uc694.\n\uc790\uc138\ud788\uc758\ub8cc \uae30\uc220\n\ub370\uc774\ud130\uc640 AI\uc758 \ud798\uc73c\ub85c \ud658\uc790 \uce58\ub8cc \uc131\uacfc\ub97c \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\uc790\uc138\ud788\uae30\uc220 \uac00\uc774\ub4dc eBook\uc77c\ubc18\uc801\uc778 \ub370\uc774\ud130 \ubb38\uc81c \ud574\uacb0\uc2a4\ud0c0\ud2b8\uc5c5 \ubc0f \ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \uae30\uc5c5\uc6a9\ud655\uc7a5\ud560 \ub54c \ub370\uc774\ud130 \uc0ac\uc6a9 \uc0ac\ub840\ub97c \uc9c0\uc6d0\ud558\ub294 \ub3d9\uc2dc\uc5d0 \ube44\uc6a9 \ud6a8\uc728\uc131\uacfc \uc0dd\uc0b0\uc131\uc744 \ub192\uc774\ub294 \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\uc2ed\uc2dc\uc624. \uc544\ud0a4\ud14d\ucc98 \ub2e4\uc774\uc5b4\uadf8\ub7a8, \ub2e8\uacc4\ubcc4 \uc194\ub8e8\uc158 \ubc0f \ube60\ub978 \uc2dc\uc791 \uac00\uc774\ub4dc\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c Grammarly, Rivian, ButcherBox, Abnormal Security, Iterable \ubc0f Zipline\uacfc \uac19\uc740 \uc120\ub3c4 \uae30\uc5c5\uc758 \uc2e4\uc81c \uc0ac\uc6a9 \uc0ac\ub840\ub3c4 \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc0ac\ubcf8 \ub2e4\uc6b4\ub85c\ub4dc\ub9ac\uc18c\uc2a4eBook\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub780 \ubb34\uc5c7\uc785\ub2c8\uae4c?\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 Big Book\uba38\uc2e0 \ub7ec\ub2dd \uc0ac\uc6a9 \uc0ac\ub840 Big BookDelta Lake \uc644\uc804 \uc815\ubcf5 \uac00\uc774\ub4dcDelta Lake: \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ucd08MLOps Big BookDatabricks Lakehouse \ud50c\ub7ab\ud3fc\uc5d0 \ub300\ud55c \ub370\uc774\ud130 \ud300 \uac00\uc774\ub4dc\ube60\ub978 \uc2dc\uc791 \uac00\uc774\ub4dcETL \uc6cc\ud06c\ub85c\ub4dc \uc2e4\ud589Delta Live Tables\ub97c \uc0ac\uc6a9\ud55c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778SQL \uac00\uc774\ub4dc: \ucffc\ub9ac \ubc0f \ub300\uc2dc\ubcf4\ub4dc\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4 \ube60\ub978 \uc2dc\uc791\uba38\uc2e0 \ub7ec\ub2dd \ube60\ub978 \uc2dc\uc791\ube14\ub85c\uadf8\uacf5\uc9c0\uc0ac\ud56d\uc624\ud508 \uc18c\uc2a4\uc0b0\uc5c5 \uc778\uc0ac\uc774\ud2b8\uc194\ub8e8\uc158\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uccb4\ud5d8 \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=lakehouse-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mat-keep","text":"Mat Keep - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMat KeepSenior Director, MongoDB Products Team at MongoDBBack to speakersMat Keep is a Senior Director in the Product team at MongoDB. Working with developer communities, MongoDB users and industry analysts, Mat helps shape the product roadmap and then takes those new products to market. Mat has been with MongoDB for 10 years. Prior to MongoDB, he worked in product roles for MySQL, Oracle, and Sun Microsystems and comes from a background as an analyst\/programmer.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/blog\/category\/company","text":"O Blog DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWLoading...ProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/discover\/managing-machine-learning-lifecycle","text":"Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and\nAI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse\nSee all customers\nLakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL \u2014 up to 12x better price\/performance than traditional cloud data warehouses \u2014 data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning \u2014 a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR\u00a0 May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/joseph-bradley","text":"Joseph Bradley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJoseph BradleyLead Product Specialist at DatabricksBack to speakersJoseph Bradley works as a Lead Solutions Architect at Databricks, specializing in Machine Learning, and is an Apache Spark committer and PMC member. Previously, he was a Staff Software Engineer at Databricks and a postdoc at UC Berkeley, after receiving his Ph.D. in Machine Learning from Carnegie Mellon.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=DeltaLake-HeroCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/glossary","text":"Glossaries Archive | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWGlossaryA-ZsearchACID Transactions What is a transaction?\nIn the context of databases and data storage systems, a transaction is any operation that is treated as a single unit of work, which either completes fully or does not complete at all, and leaves the storage system in a cons{...}AdaGrad Gradient descent is the most commonly used optimization method deployed in machine learning and deep learning algorithms. It\u2019s used to train a machine learning model.\nTypes of Gradient Descent\nThere are three primary types of gradient descent {...}Alternative Data What is Alternative Data?\nAlternative data is information gathered by using alternative sources of data that others are not using; &nbsp;non-traditional information sources. Analysis of alternative data can provide insights beyond that which an in{...}Anomaly Detection Anomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like{...}Apache Hive What is Apache Hive?\nApache Hive is open-source data warehouse software designed to read, write, and manage large datasets extracted from the Apache Hadoop Distributed File System (HDFS) , one aspect of a larger Hadoop Ecosystem.\nWith exten{...}Apache Kudu What is Apache Kudu?\nApache Kudu is a free and open source columnar storage system developed for the Apache Hadoop. It is an engine intended for structured data that supports low-latency random access millisecond-scale access to individual rows to{...}Apache Kylin What is Apache Kylin?\nApache Kylin is a distributed open source online analytics processing (OLAP) engine for interactive analytics Big Data. Apache Kylin has been designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop\/S{...}Apache Spark What Is Apache Spark?\nApache Spark is an open source analytics engine used for big data workloads. It can handle both batches as well as real-time analytics and data processing workloads.&nbsp;Apache Spark started in 2009 as a research project at {...}Apache Spark as a Service What is Apache Spark as a Service?\nApache Spark is an open source cluster computing framework for fast real-time large-scale data processing.&nbsp;Since its inception in 2009 at UC Berkeley\u2019s AMPLab, Spark has seen major growth. It is currently ra{...}Artificial Neural Network What is an Artificial Neural Network?\nAn artificial neuron network (ANN) is a computing system patterned after the operation of neurons in the human brain.\nHow Do Artificial Neural Networks Work?\nArtificial Neural Networks can be best viewed{...}Automation Bias What is Automation Bias?\nAutomation bias is an over-reliance on automated aids and decision support systems. As the availability of automated decision aids is increasing additions to critical decision-making contexts such as intensive care units, {...}Bayesian Neural Network What Are Bayesian Neural Networks?\nBayesian Neural Networks (BNNs) refers to extending standard networks with posterior inference in order to control over-fitting. From a broader perspective, the Bayesian approach uses the statistical methodology {...}Big Data Analytics The Difference Between Data and Big Data Analytics\nPrior to the invention of Hadoop, the technologies underpinning modern storage and compute systems were relatively basic, limiting companies mostly to the analysis of \"small data.\" Even this relat{...}Bioinformatics Bioinformatics is a field of study that uses computation to extract knowledge from large collections of biological data.\nBioinformatics refers to the use of IT in biotechnology for storing, retrieving, organizing and analyzing biological data.{...}Catalyst Optimizer At the core of Spark SQL is the Catalyst optimizer, which leverages advanced programming language features (e.g. Scala\u2019s pattern matching and quasi quotes) in a novel way to build an extensible query optimizer. Catalyst is based on functional program{...}Complex Event Processing What is Complex Event Processing [CEP]?\nComplex event processing [CEP] also known as event, stream or event stream processing is the use of technology for querying data before storing it within a database or, in some cases, without it ever being s{...}Continuous Applications Continuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate{...}Convolutional Layer In deep learning, a convolutional neural network (CNN or ConvNet) is a class of deep neural networks, that are typically used to recognize patterns present in images but they are also used for spatial data analysis, computer vision, natural language {...}Data Analysis Platform What is a Data Analysis Platform?\nA data analytics platform is an ecosystem of services and technologies that needs to perform analysis on voluminous, complex and dynamic data that allows you to retrieve, combine, interact with, explore, and visua{...}Data Governance What is Data Governance?\nData governance is the oversight to ensure data brings value and supports the business strategy. Data governance is more than just a tool or a process. It aligns data-related requirements to the business strategy using a f{...}Data Lakehouse What is a Data Lakehouse?\nA data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business int{...}Data Mart What is a data mart?\nA data mart is a curated database including a set of tables that are designed to serve the specific needs of a single data team, community, or line of business, like the marketing or engineering department. It is normally smal{...}Data Sharing What is data sharing?\nData sharing is the ability to make the same data available to one or many consumers. Nowadays, the ever-growing amount of data has become a strategic asset for any company. Sharing data - within your organization or external{...}Data Vault What is a data vault?\nA data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.\nHubs represent core business concepts, {...}Data Warehouse What is a data warehouse?\nA data warehouse is a data management system that stores current and historical data from multiple sources in a business friendly manner for easier insights and reporting. Data warehouses are typically used for business i{...}Databricks Runtime Databricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of {...}DataFrames What is a DataFrame?\nA DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are {...}Datasets Datasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recal{...}Deep Learning What is Deep Learning?\nDeep Learning is a subset of machine learning concerned with large amounts of data with algorithms that have been inspired by the structure and function of the human brain, which is why deep learning models are often referre{...}Demand Forecasting What is demand forecasting?\nDemand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.\nRet{...}Dense Tensor Dense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software prod{...}Digital Twin What is a Digital Twin?\nThe classical definition of of digital twin is; \"\"A digital twin is a virtual model designed to accurately reflect a physical object.\"\" \u2013 IBM[KVK4] For a discrete or continuous manufacturing process, a digital twin gathers {...}DNA Sequence What is a DNA Sequence?\nThe DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). &nbsp;Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine {...}Extract Transform Load (ETL) What is ETL?\nAs the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to pr{...}Feature Engineering Feature engineering for machine learning\nFeature engineering, also called data preprocessing, is the process of converting raw data into features that can be used to develop machine learning models. This topic describes the principal concepts of f{...}Genomics Genomics is an area within genetics that concerns the sequencing and analysis of an organism's genome. Its main task is to determine the entire sequence of DNA or the composition of the atoms that make up the DNA and the chemical bonds between the DN{...}Hadoop Cluster What Is a Hadoop Cluster?\nApache Hadoop is an open source, Java-based, software framework and parallel data processing engine. It enables big data analytics processing tasks to be broken down into smaller tasks that can be performed in parallel by{...}Hadoop Distributed File System (HDFS) HDFS\nHDFS (Hadoop Distributed File System) is the primary storage system used by Hadoop applications. This open source framework works by rapidly transferring data between nodes. It's often used by companies who need to handle and store big data. {...}Hadoop Ecosystem What is the Hadoop Ecosystem?\nApache Hadoop ecosystem refers to the various components of the Apache Hadoop software library; it includes open source projects as well as a complete range of complementary tools. Some of the most well-known tools of{...}Hash Buckets In computing, a hash table [hash map] is a data structure that provides virtually direct access to objects based on a key [a unique String or Integer]. A hash table uses a hash function to compute an index into an array of buckets or slots, from whic{...}Hive Date Function What is a Hive Date Function?\nHive provides many built-in functions to help us in the processing and querying of data. Some of the functionalities provided by these functions include string manipulation, date manipulation, type conversion, conditi{...}Hosted Spark What is Hosted Spark?\nApache Spark is a fast and general cluster computing system for Big Data built around speed, ease of use, and advanced analytics that was originally built in 2009 at UC Berkeley. It provides high-level APIs in Scala, Java, Py{...}Jupyter Notebook What is a Jupyter Notebook?\nA Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.\nWhat are Jupyter Notebooks used fo{...}Keras Model What is a Keras Model?\nKeras is a high-level library for deep learning, built on top of Theano and Tensorflow. It is written in Python and provides a clean and convenient way to create a range of deep learning models.&nbsp;Keras has become one of {...}Lakehouse for Retail What is Lakehouse for Retail?\nLakehouse for Retail is Databricks\u2019 first industry-specific Lakehouse. It helps retailers get up and running quickly through solution accelerators, data sharing capabilities, and a partner ecosystem.\nLakehouse fo{...}Lambda Architecture What is Lambda Architecture?\nLambda architecture is a way of processing massive quantities of data (i.e. \"Big Data\") that provides access to batch-processing and stream-processing methods with a hybrid approach. Lambda architecture is used to solv{...}Machine Learning Library (MLlib) Apache Spark\u2019s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and mod{...}Machine Learning Models What is a machine learning Model?\nA machine learning model is a program that can find patterns or make decisions from a previously unseen dataset. For example, in natural language processing, machine learning models can parse and correctly recogni{...}Managed Spark What is Managed Spark?\nA managed Spark service lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. By using such an automation you will be able to quickly create clusters on -demand, m{...}MapReduce What is MapReduce?\nMapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem.&nbsp; It takes away the complexity of distributed programming by exposing two processing steps that developers implement: 1) Map and {...}Materialized views Delta Pipelines \/ Materialized Views in Databricks Delta\nIntro\nDelta Pipelines provides a set of APIs and UI for managing the data pipeline lifecycle. This open-source framework helps data engineering teams simplify ETL development, improve dat{...}Medallion Architecture What is a medallion architecture?\nA medallion architecture is a data design pattern used to logically organize data in a lakehouse, with the goal of incrementally and progressively improving the structure and quality of data as it flows through ea{...}ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and c{...}MLOps What is MLOps?\nMLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. M{...}Model Risk Management Model risk management refers to the supervision of risks from the potential adverse consequences of decisions based on incorrect or misused models. The aim of model risk management is to employ techniques and practices that will identify, measure and{...}Neural Network What is a Neural Network?\nA neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an outpu{...}Open Banking What is Open Banking?\nOpen banking is a secure way to provide access to consumers' financial data, all contingent on customer consent.\u00b2 Driven by regulatory, technology, and competitive dynamics, Open Banking calls for the democratization of custo{...}Orchestration What is Orchestration?\nOrchestration is the coordination and management of multiple computer systems, applications and\/or services, stringing together multiple tasks in order to execute a larger workflow or process. These processes can consist of {...}Overall Equipment Effectiveness What is Overall Equipment Effectiveness?\nOverall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to{...}pandas DataFrame \nWhen it comes to data science, it's no exaggeration to say that you can transform the way your business works by using it to its full potential with pandas DataFrame. To do that, you'll need the right data structures. These will help you be as ef{...}Parquet What is Parquet?\nApache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in {...}Personalized Finance What is Personalized Finance?\nFinancial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remai{...}Predictive Analytics What is Predictive Analytics?\nPredictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.\nHow Does Predictive Analytics Work?\nPredictive analytics {...}Predictive Maintenance What is predictive maintenance?\nPredictive Maintenance, in a nutshell, is all about figuring out when an asset should be maintained, and what specific maintenance activities need to be performed, based on an asset\u2019s actual condition or state, rath{...}PyCharm PyCharm is an integrated development environment (IDE) used in computer programming, created for the Python programming language. When using PyCharm on Databricks, by default PyCharm creates a Python Virtual Environment, but you can configure to crea{...}PySpark What is PySpark?\nApache Spark is written in Scala programming language. PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface wi{...}Real-Time Retail What is real-time data for Retail?\nReal-time retail is real-time access to data. Moving from batch-oriented access, analysis and compute will allow data to be \u201calways on,\u201d therefore driving accurate, timely decisions and business intelligence. {...}Resilient Distributed Dataset (RDD) \nRDD was the primary user-facing API in Spark since its inception. At the core, an RDD is an immutable distributed collection of elements of your data, partitioned across nodes in your cluster that can be operated in parallel with a low-level API {...}Snowflake Schema What is a snowflake schema?\nA snowflake schema is a multi-dimensional data model that is an extension of a star schema, where dimension tables are broken down into subdimensions. Snowflake schemas are commonly used for business intelligence and re{...}Spark API If you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDs\nWhat are Resilient Distributed Datasets?\nRDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are {...}Spark Applications Spark Applications consist of a driver process and a set of executor processes. The driver process runs your main() function, sits on a node in the cluster, and is responsible for three things: maintaining information about the Spark Application; res{...}Spark Elasticsearch What is Spark Elasticsearch?\nSpark Elasticsearch is a NoSQL, distributed database that stores, retrieves, and manages document-oriented and semi-structured data. It is a GitHub open source, RESTful search engine built on top of Apache Lucene and r{...}Spark SQL Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can al{...}Spark Streaming Apache Spark Streaming is the previous generation of Apache Spark\u2019s streaming engine. There are no longer updates to Spark Streaming and it\u2019s a legacy project. There is a newer and easier to use streaming engine in Apache Spark called Structured Stre{...}Spark Tuning What is Spark Performance Tuning?\nSpark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also preven{...}Sparklyr What is Sparklyr?\nSparklyr is an open-source package that provides an interface between R and Apache Spark. You can now leverage Spark\u2019s capabilities in a modern R environment, due to Spark\u2019s ability to interact with distributed data with little l{...}SparkR SparkR is a tool for running R on Spark. It follows the same principles as all of Spark\u2019s other language bindings. To use SparkR, we simply import it into our environment and run our code. It\u2019s all very similar to the Python API except that it follow{...}Sparse Tensor Python offers an inbuilt library called numpy to manipulate multi-dimensional arrays. The organization and use of this library is a primary requirement for developing the pytensor library. Sptensor is a class that represents the sparse tensor. A spa{...}Star Schema What is a star schema?\nA star schema is a multi-dimensional data model used to organize data in a database so that it is easy to understand and analyze. Star schemas can be applied to data warehouses, databases, data marts, and other tools. The st{...}Streaming Analytics How Does Stream Analytics Work?\nStreaming analytics, also known as event stream processing, is the analysis of huge pools of current and \u201cin-motion\u201d data through the use of continuous queries, called event streams. These streams are triggered by a{...}Structured Streaming Structured Streaming is a high-level API for stream processing that became production-ready in Spark 2.2. Structured Streaming allows you to take the same operations that you perform in batch mode using Spark\u2019s structured APIs, and run them in a stre{...}Supply Chain Management What is supply chain management?\nSupply chain management is the process of planning, implementing and controlling operations of the supply chain with the goal of efficiently and effectively producing and delivering products and services to the end{...}TensorFlow In November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advant{...}Tensorflow Estimator API What is the Tensorflow Estimator API?\nEstimators represent a complete model but also look intuitive enough to less user. The Estimator API provides methods to train the model, to judge the model\u2019s accuracy, and to generate predictions. TensorFlow {...}Transformations What Are Transformations?\nIn Spark, the core data structures are immutable meaning they cannot be changed once created. This might seem like a strange concept at first, if you cannot change it, how are you supposed to use it? In order to \u201cchange\u201d {...}Tungsten What is the Tungsten Project?\nTungsten is the codename for the umbrella project to make changes to Apache Spark\u2019s execution engine that focuses on substantially improving the efficiency of memory and CPU for Spark applications, to push performance{...}Unified AI Framework Unified Artificial Intelligence or UAI was announced by Facebook during F8 this year. This brings together 2 specific deep learning frameworks that Facebook created and outsourced - PyTorch focused on research assuming access to large-scale compute r{...}Unified Data Analytics Unified Data Analytics is a new category of solutions that unify data processing with AI technologies, making AI much more achievable for enterprise organizations and enabling them to accelerate their AI initiatives. Unified Data Analytics makes it e{...}Unified Data Analytics Platform Databricks' Unified Data Analytics Platform&nbsp;helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at mass{...}Unified Data Warehouse What is a Unified Data Warehouse?\nA unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in {...}What Is Hadoop? Apache Hadoop is an open source, Java-based software platform that manages data processing and storage for big data applications. The platform works by distributing Hadoop big data and analytics jobs across nodes in a computing cluster, breaking them{...}ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"Pagina partner: Partner consulenti e integratori di sistemi| DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWProgramma partner consulenti e integratori (C&SI)Il Databricks Consulting and SI (C&SI) Partner Program \u00e8 guidato dal valore e favorisce una migliore collaborazione per raggiungere risultati migliori.IscrivitiUnisciti a un ecosistema globale di fornitori di servizi di gestione dei dati e AI che stanno trasformando i nostri clienti in imprese guidate dai dati. Come partner, avrai un ruolo centrale nel migliorare i seguenti aspetti:Impatto delle vendite\nInteragisci con i nostri team sul campo per vendere la visione del lakehouse e allargare il raggio d'azione di Databricks.Valore per il cliente\nForma il tuo team sulla piattaforma per sviluppare capacit\u00e0 e funzionalit\u00e0 specifiche per la tua attivit\u00e0 professionale.innovazione\nMostra la tua competenza sviluppando soluzioni replicabili per casi d'uso ad alto impatto.Ottieni benefici in fase di coinvolgimento e abilitazione per far crescere la tua attivit\u00e0 e costruire una partnership di successo.Formazione tecnica di DatabricksAccesso alla Databricks Lakehouse PlatformSupporto tecnico e alla venditaRegistrazione di opportunit\u00e0 e compensi per segnalazioniFondi di investimento per clientiAbilitazione e risorse per il go-to-marketPronto per cominciare?IscrivitiTrova un partnerProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=seoul%2C%20south%20korea","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/customers\/conde_nast","text":"Customer Story: Cond\u00e9 Nast | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYCreating a personalized experience with ML60%Reduction in processing times due to faster ETL pipelines50%Reduction in IT operational costsFastertime-to-insight led to a significant growth in businessWatch video INDUSTRY: Media and entertainment SOLUTION: Advertising effectiveness,customer retention,customer segmentation,recommendation engines PLATFORM USE CASE: Delta Lake,data science,machine learning,Databricks SQL,ETL CLOUD: AWS\u201cDatabricks has been an incredibly powerful end-to-end solution for us. It\u2019s allowed a variety of different team members from different backgrounds to quickly get in and utilize large volumes of data to make actionable business decisions.\u201d\n\u2013 Paul Fryzel, Principal Engineer of AI Infrastructure, Cond\u00e9 NastCond\u00e9 Nast, the publisher of iconic magazines such as Vogue, the New Yorker and Wired, uses data to reach over 1 billion people in print, online, on video, and on social media. With tremendous amounts of data to leverage, they struggled to manage infrastructure and enable data science productivity. With Databricks, cluster automation has eliminated unnecessary DevOps effort, Delta Lake has enabled them to build data pipelines that scale to 1 trillion data points per month, and data science innovation has been unlocked with a collaborative environment with MLflow to manage the entire ML lifecycle. This has allowed them to deliver personalized content across their brands to engage and retain customers.Inability to use customer data to improve content experienceAs a leading media publisher, Cond\u00e9 Nast manages over 20 brands in their portfolio. On a monthly basis, their web properties garner 100+ million visits and 800+ million page views producing a tremendous amount of data. The data team is focused on improving user engagement by using machine learning to provide personalized content recommendations and targeted ads. However, running vanilla Spark to power their data platform proved to be challenging:Infrastructure complexity: Building and managing Spark clusters required lots of setup and constant maintenance, pulling teams from higher value activities.Breaking down walls: Needed to find a common platform for teams to build data pipelines and advance analytics to better foster collaboration.Too much data: Data sets were outgrowing existing data lake solutions.Simplifying data pipelines and ML lifecyclesDatabricks provides Cond\u00e9 Nast with a fully managed cloud platform that simplifies operations, delivers superior performance, and enables data science innovation.Interactive Workspace:\u00a0Data scientists can collaborate, share, and track data and insights, fostering an environment of collaboration.Delta Lake:\u00a0As data sets grew in volume (over 1 trillion data points per month), Delta Lake can keep up and allow for more use cases, such as data rewrites and data merges.Managed MLflow:\u00a0With MLflow, Cond\u00e9 Nast can easily manage the entire machine learning lifecycle, from tracking experiments to monitoring production models.Delighting customers with personalized content powered by AIWith Databricks as the foundation for their data analytics and machine learning efforts, Cond\u00e9 Nast\u2019s newfound insights into their customers has transformed the way they drive engagement across their 20+ brands.Improved customer engagement:\u00a0With an improved data pipeline, Cond\u00e9 Nast can make better, faster, and more accurate content recommendations, improving the user experience.Unified approach:\u00a0Data engineering and data science teams are now solving problems together and collaborating to build new content products and experiences.Built for scale:\u00a0Data sets can no longer outgrow Cond\u00e9 Nast\u2019s capacity to process and glean insights.More models in production:\u00a0With MLflow, Cond\u00e9 Nast\u2019s data science teams can innovate their products faster. They have deployed over 1,200 models in production.Related ContentSessionTechnical Talk at Spark + AI Summit EU 2019Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/de\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWPreisaktion f\u00fcr Databricks SQL\u00a0\u2013 Mehr als 40\u00a0% sparenJetzt zugreifen: 15-monatige Aktion f\u00fcr SQL Serverless und das brandneue SQL ProMehr InformationenDatabricks SQLDas beste Data Warehouse ist ein LakehouseErste SchritteDemo ansehen\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks SQL (DB SQL) ist ein serverloses Data Warehouse auf der Databricks Lakehouse-Plattform, mit dem Sie alle Ihre SQL- und BI-Anwendungen in gro\u00dfem Ma\u00dfstab ausf\u00fchren k\u00f6nnen, mit einem bis zu 12-mal besseren Preis-\/Leistungsverh\u00e4ltnis, einem einheitlichen Governance-Modell, offenen Formaten und APIs sowie Tools Ihrer Wahl \u2013 ohne Lock-In.Bestes Preis-\/Leistungsverh\u00e4ltnisSenken Sie die Kosten, erzielen Sie das beste Preis-\/Leistungsverh\u00e4ltnis und machen Sie die Verwaltung, Konfiguration oder Skalierung der Cloud-Infrastruktur mit Serverless \u00fcberfl\u00fcssig.Integrierte GovernanceErstellen Sie eine einzige Kopie f\u00fcr alle Ihre Daten mithilfe offener Standards und eine einheitliche Governance-Ebene f\u00fcr alle Datenteams mit Standard-SQL.Umfangreiches \u00d6kosystemVerwenden Sie SQL und beliebige Tools wie Fivetran, dbt, Power BI oder Tableau zusammen mit Databricks, um all Ihre Daten aufzunehmen, zu transformieren und abzufragen.Trennung von Datenbest\u00e4nden beseitigenErm\u00f6glichen Sie jedem Analysten den schnelleren Zugriff auf die neuesten Daten f\u00fcr nachgelagerte Echtzeitanalysen und den m\u00fchelosen Zugriff von BI auf ML.Wie funktioniert es?Nahtlose Integration in das \u00d6kosystem\u00a0Anwenderfreundlichkeit\u00a0Leistung in der realen Welt\u00a0Zentralisierte Governance\u00a0Offener und zuverl\u00e4ssiger Data Lake als GrundlageDaten von \u00fcberall einfaches aufnehmen, transformieren und orchestrierenArbeiten Sie mit Ihren Daten, egal wo sie sich befinden. Dank schl\u00fcsselfertiger Funktionen k\u00f6nnen Analysten und Analysetechniker mithilfe von Fivetran problemlos Daten aus Cloud-Speicher in Unternehmensanwendungen wie Salesforce, Google Analytics oder Marketo \u00fcbertragen. Sie sind nur einen Klick entfernt. Verwalten Sie dann einfach Abh\u00e4ngigkeiten und transformieren Sie Daten direkt mit integrierten ETL-Funktionen im Lakehouse oder verwenden Sie Ihre bevorzugten Tools wie dbt auf Databricks SQL, um erstklassige Leistung zu erzielen.\u00a0\u201eDie Kombination von Databricks und Fivetran erm\u00f6glichte uns, in sehr kurzer Zeit eine stabile und moderne Datenpipeline aufzubauen. Fivetran hatte alle richtigen Konnektoren und Integrationen, die wir brauchten.\u201c\u2013 Justin Wille, Director of Insights and Analytics, Kreg ToolMehr InformationenModerne Analytics und BI mit Tools Ihrer WahlArbeiten Sie nahtlos mit den g\u00e4ngigsten BI-Tools wie Tableau, Power BI und Looker. Analysten k\u00f6nnen jetzt schnell die aktuellsten Daten mit ihren bevorzugten Tools visualisieren und analysieren, um neue Gesch\u00e4ftseinblicke in die vollst\u00e4ndigsten und aktuellsten Daten zu gewinnen. Databricks SQL erm\u00f6glicht es au\u00dferdem jedem Analysten, mit dem integrierten SQL-Editor Erkenntnisse, Visualisierungen und Dashboards abzufragen, zu finden und zu teilen.\u00a0\u201eMit den Daten, die uns auf einfache Weise zur Verf\u00fcgung stehen, sind wir viel zuversichtlicher, dass wir aktuelle und vollst\u00e4ndige Daten in unsere Power BI-Dashboards und -Berichte einflie\u00dfen lassen.\u201c\u2013 Jake Stone, Senior Manager, Business Analytics, ButcherBoxMehr InformationenRessourcenmanagement mit serverloser Datenverarbeitung eliminierenDatabricks SQL Serverless macht die Verwaltung, Konfiguration oder Skalierung der Cloud-Infrastruktur im Lakehouse \u00fcberfl\u00fcssig und gibt Ihrem Datenteam Zeit f\u00fcr das, was es am besten kann. Databricks SQL-Warehouses bieten sofortige, elastische SQL-Rechenleistung \u2013 vom Speicher entkoppelt \u2013 und werden automatisch skaliert, um unbegrenzte Parallelit\u00e4t ohne Unterbrechung f\u00fcr Anwendungsf\u00e4lle mit hoher Parallelit\u00e4t zu bieten.\u00a0\u201eMit Databricks SQL Serverless k\u00f6nnen wir die Leistungsf\u00e4higkeit von Databricks SQL nutzen und gleichzeitig unsere Infrastruktur viel effizienter zum Einsatz bringen.\u201c\u2013 R. Tyler Croy, Director of Platform Engineering, ScribdMehr InformationenVon Grund auf f\u00fcr erstklassige Leistung neu konzipiertDatabricks SQL umfasst Tausende von Optimierungen, um Ihnen maximale Leistung f\u00fcr alle Ihre Tools, Abfragetypen und Praxisanwendungen zu bieten. Dazu geh\u00f6rt die vektorisierte Abfrage-Engine Photon der n\u00e4chsten Generation, die zusammen mit SQL-Warehouses ein bis zu 12-mal besseres Preis-\/Leistungsverh\u00e4ltnis als andere Cloud Data Warehouses bietet.\u00a0\u201eMit der Lakehouse-Plattform von Databricks k\u00f6nnen wir Analysen durchf\u00fchren, die es uns erlauben, Erkenntnisse \u00fcber das Zuschauerverhalten innerhalb von Minuten statt Wochen zu gewinnen.\u2013 Stephane Caron, Sr. Director of Business Intelligence, CBC\/Radio-CanadaMehr InformationenAlle Ihre Daten zentral mit Standard-SQL speichern und verwaltenErstellen Sie eine einzelne Kopie all Ihrer Daten mit Delta Lake im offenen Format, um Daten-Lock-Ins zu vermeiden, und f\u00fchren Sie auf Ihrem Lakehouse direkte Analytics und ETL\/ELT durch \u2013 ohne Datenverlagerungen und Kopien in voneinander getrennten Systemen. Dann k\u00f6nnen Sie mit Databricks Unity Catalog auf einfache Weise all Ihre Daten mit fein abgestimmter Governance, Datenherkunft und Standard-SQL \u00fcber Clouds hinweg erkennen, sichern und verwalten.\u00a0\u201eDatabricks steht im Mittelpunkt unseres Gesch\u00e4fts, da uns seine Lakehouse-Architektur eine einheitliche M\u00f6glichkeit bietet, umsetzbare Erkenntnisse aus Daten abzurufen, zu speichern und zu teilen.\u201c\u2013 Jagan Mangalampalli, Director of Big Data, PunchhMehr InformationenAufbauend auf einer gemeinsamen Datenbasis, unterst\u00fctzt von der Lakehouse-PlattformDie Databricks Lakehouse-Plattform bietet die umfassendste End-to-End-Data-Warehousing-L\u00f6sung f\u00fcr all Ihre modernen Analytics-Anforderungen und vieles mehr. Erhalten Sie erstklassige Leistung zu einem Bruchteil der Kosten von Cloud Data Warehouses. Beschleunigen Sie die Zeit von Rohdaten bis hin zu verwertbaren Daten in gro\u00dfem Ma\u00dfstab \u2014 und vereinheitlichen Sie Batch und Streaming. Dar\u00fcber hinaus k\u00f6nnen Datenteams mit Lakehouse m\u00fchelos von deskriptiver zu pr\u00e4diktiver Analytics wechseln, um neue Einblicke zu gewinnen.\u00a0\u201eDatabricks hat unseren Daten- und Analyseteams eine Plattform bereitgestellt, mit der sie auf Daten von ABN AMRO zugreifen und diese gemeinsam nutzen k\u00f6nnen. Es bietet au\u00dferdem ML-basierte L\u00f6sungen, die die Automatisierung und Erkenntnisgewinnung im gesamten Unternehmen vorantreiben.\u201c\u2013 Stefan Groot, Head of Analytics Engineering, ABN AMROMehr InformationenZu Databricks migrierenSind die Datensilos, die langsame Leistung und die hohen Kosten f\u00fcr Altsysteme wie Hadoop und Enterprise Data Warehouses m\u00fcde? Holen Sie sich eine einzige moderne Plattform f\u00fcr alle Ihre Daten-, Analytics- und KI-Anwendungsf\u00e4lle.Zu Databricks migrierenIntegrationenNahtlose Integrationen mit dem \u00d6kosystem bedeuten maximale Flexibilit\u00e4t f\u00fcr Ihre Datenteams. Erfassen Sie gesch\u00e4ftskritische Daten mit Fivetran, wandeln Sie sie mit dbt direkt um und gewinnen Sie neue Erkenntnisse mit Power BI, Tableau oder Looker, ohne Ihre Daten in ein herk\u00f6mmliches Data Warehouse zu verschieben.Datenaufnahme und ETLData GovernanceBI und Dashboards+ jeder sonstige Apache Spark\u2122-kompatible Client\u201eUnternehmen brauchen heute mehr denn je eine Datenstrategie, die die f\u00fcr gesch\u00e4ftliche Flexibilit\u00e4t erforderliche Schnelligkeit und Agilit\u00e4t bietet. Da Unternehmen ihre Daten zunehmend in die Cloud verlagern, w\u00e4chst auch das Interesse an der Datenanalyse im Data Lake. Databricks SQL bietet Kunden eine v\u00f6llig neue Erfahrung: Sie k\u00f6nnen jetzt mit der erforderlichen Leistung, Zuverl\u00e4ssigkeit und Skalierbarkeit aus gigantischen Datenmengen Einblicke gewinnen. Wir sind stolz darauf, dieses Potenzial gemeinsam mit Databricks umzusetzen.\u201c\u2013 Francois ajenstat, Chief product officer, TableauKundenberichteMehr entdeckenDelta LakePartner ConnectUnity CatalogDelta Live Tables\u00c4hnliche Inhalte\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu den Vorteilen, die ein Lakehouse mit sich bringt.\nRessourcen erkundenE-Books\u201eErrichten eines Data Lakehouse\u201c von Bill Inmon, dem Vater des Data WarehouseWarum das Lakehouse Ihr n\u00e4chstes Data Warehouse sein wirdDaten, Analysen und KI-GovernanceDas gro\u00dfe Buch des Data EngineeringMigrieren von einem Data Warehouse zu einem Data Lakehouse f\u00fcr DummiesVeranstaltungenDas Innenleben des Lakehouse von Data + AI World TourWebinar \u00fcber Best Practices zur Leistungsoptimierung im Lakehouse \u2013 Einblick in das Leben einer AbfrageKostenlose Schulung f\u00fcr Databricks SQL \u2013 auf AbrufDas beste Data Warehouse ist ein LakehouseBlogsDatabricks stellt offiziellen Leistungsrekord f\u00fcr Data Warehousing aufAnk\u00fcndigung der allgemeinen Verf\u00fcgbarkeit von Databricks SQLEntwicklung der SQL-Sprache bei Databricks: ANSI-Standard by Default und leichtere Migrationen von Data WarehousesDer Einsatz von dbt in Databricks ist jetzt noch einfacherModellierungstechniken im Data Warehousing und ihre Implementierung auf der Databricks Lakehouse-PlattformSo erstellen Sie eine Marketing-Analytics-L\u00f6sung mit Fivetran und dbt im Databricks LakehouseM\u00f6chten Sie loslegen?Kostenlos testenMitglied der Community werdenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data-product-cta-freeTrial=","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/daniela-rus","text":"Daniela Rus - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MITBack to speakersDaniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. Rus\u2019s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering, and the American Academy for Arts and Science. She earned her PhD in Computer Science from Cornell University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/data-lakehouse","text":"Plateforme Data Lakehouse par Databricks \u2013 Planifiez une d\u00e9mo maintenant\u00a0! | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLa Plateforme Lakehouse de DatabricksRegroupez vos cas d'usage d'entreposage des donn\u00e9es et d'IA sur une plateforme uniqueEssai gratuit\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowSimple. Ouverte. Multicloud.La plateforme Lakehouse de Databricks combine le meilleur des data lakes et des data warehouses pour offrir la fiabilit\u00e9, la gouvernance renforc\u00e9e et les performances des data warehouses avec l'ouverture, la flexibilit\u00e9 et la prise en charge du machine learning des data lakes.Cette approche unifi\u00e9e simplifie votre pile de donn\u00e9es moderne en \u00e9liminant les silos qui s\u00e9parent et compliquent habituellement les domaines du data engineering, de l'analytique, de la BI, de la data science et du machine learning. Elle repose sur des standards ouverts et open source pour plus de flexibilit\u00e9. Par ailleurs, son approche commune de la gestion de donn\u00e9es, de la s\u00e9curit\u00e9 et de la gouvernance vous aide \u00e0 travailler plus efficacement et \u00e0 innover plus rapidement.SimpleL'approche unifi\u00e9e simplifie l'architecture de vos donn\u00e9es en \u00e9liminant les silos qui s\u00e9parent habituellement les domaines de l'analytique, de la BI, de la data science et du machine learning. Avec un lakehouse, vous pouvez \u00e9liminer la complexit\u00e9 et les d\u00e9penses qui vous emp\u00eachent d'atteindre tout le potentiel de vos projets en mati\u00e8re d'analytique et d'IA.OuvertDelta Lake constitue la base ouverte du lakehouse puisqu'il offre de la fiabilit\u00e9 et des performances records directement sur les donn\u00e9es du data lake. Elle vous permet d'\u00e9viter les \u00ab\u00a0walled gardens\u00a0\u00bb (jardins clos) propri\u00e9taires, de partager des donn\u00e9es facilement et de cr\u00e9er votre pile de donn\u00e9es moderne avec un acc\u00e8s illimit\u00e9 \u00e0 l'\u00e9cosyst\u00e8me de projets de donn\u00e9es open source et au vaste r\u00e9seau de partenaires Databricks.En savoir plus sur 450+ partenaires dans le paysage des donn\u00e9sPour en savoir plusMulti-cloudLa plateforme Lakehouse de Databricks vous offre une exp\u00e9rience de gestion, de s\u00e9curit\u00e9 et de gouvernance coh\u00e9rente sur tous les clouds. Pas besoin de r\u00e9inventer des processus pour chaque plateforme cloud que vous utilisez afin de prendre en charge vos projets de donn\u00e9es et d'IA. Au lieu de cela, vos \u00e9quipes data peuvent se concentrer sur la mise en \u0153uvre de toutes vos donn\u00e9es pour d\u00e9couvrir de nouveaux insights.Pour en savoir plusLib\u00e9rez le potentiel de vos donn\u00e9es et de vos \u00e9quipes de donn\u00e9esEn savoir plus sur la fa\u00e7on dont la plateforme Databricks Lakehouse permet vos charges de travail de donn\u00e9es et d\u2019IAData EngineeringDatabricks SQLMachine learningContenu associ\u00e9\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les atouts du data engineering sur Databricks.\nExplorer les ressourcesLakehouseQu'est-ce qu'un lakehouse\u00a0?Livre pour les nuls : Modern Cloud Data PlatformLa mont\u00e9e en puissance du paradigme du LakehouseRise of the Data Lakehouse par Bill Inmon, p\u00e8re de l\u2019entrep\u00f4t de donn\u00e9esDelta LakeLe Grand Livre du Data EngineeringDelta Lake : le guide ultime par O'ReillyLe guide complet du Delta LakeDelta Lake\u00a0: la fondation de votre LakehouseMachine learninge-Book\u00a0: standardiser le cycle de vie du Machine learning \u00c9v\u00e8nement virtuel\u00a0: cr\u00e9er des plateformes de Machine learningPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/abhishek-patel","text":"Abhishek Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAbhishek PatelHead of Databricks COE at LTIMindtreeBack to speakersAbhishek Patel heads the Databricks COE at LTIMindtree. He manages Databricks Strategy, Consulting and Tech initiatives for the COE. Abhishek Patel has over 22 years of experience helping customers build data platforms and analytical systems. He has played pivotal role in architecting and assisting customers with multiyear large-scale data modernization and migration projects to cloud data platforms like Azure and Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-databricks-runtime","text":"What is Databricks Runtime?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks RuntimeAll>Databricks RuntimeTry Databricks for freeGet StartedDatabricks Runtime is the set of software artifacts that run on the clusters of machines managed by Databricks. It includes Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of big data analytics. The primary differentiations are:Better Performance with DBIO:\u00a0The Databricks I\/O module, or DBIO, leverages the vertically integrated stack to significantly improve the performance of Spark in the cloud.Stronger Security with DBES:\u00a0The Databricks Enterprise Security, or DBES, module adds features such as data encryption at rest and in motion, fine-grained data access control, and auditing to satisfy standard compliance (e.g. HIPAA, SOC2) and the most stringent security requirements as one would expect of large enterprises.Significantly lower operational complexity:\u00a0With features such as auto-scaling of compute resources and local storage, we put Spark on \"autopilot\" and markedly reduce the operational complexity and management cost.Rapid releases and early access to new features:\u00a0Compared to upstream open source releases, Databricks' SaaS offering facilitates quicker release cycles, offering our customers the latest features and bug fixes that are not yet available in open source releases.DATABRICKS RUNTIME OUTPERFORMS OTHER COMPUTE ENGINESAdditional ResourcesDatabricks Runtime ProductDatabricks Runtime DocumentationA Technical Preview of Databricks Runtime 7 Including a Preview of Apache Spark 3.0Back to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/noam-bressler","text":"Noam Bressler - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNoam BresslerML Team Lead at DeepchecksBack to speakersNoam directs the development of algorithms and Machine Learning methodologies for validation of models and data at Deepchecks. Noam holds an MSc in physics and previously served as a Data Scientist and Algorithms Researcher, developing ML and analytical models in the domain of acoustic signal processing in the IDF.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/cloud-partners","text":"Databricks Cloud Service Provider Partner | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Cloud PartnersDatabricks Lakehouse runs on every major public cloud, tightly integrated with the security, compute, storage, analytics and AI services natively offered by the cloud providers. This provides the agility you need to leverage your cloud provider of choice, whenever and however you want.Azure Databricks is a jointly developed, first-party service from Databricks and Microsoft. Start with a single click in the Azure Portal and natively integrate with Azure security and data services.Learn moreDatabricks on AWS allows you to store and manage all your S3 data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes so you can unify all your analytics and AI workloads.Learn moreDatabricks on Google Cloud brings the open lakehouse platform to the open cloud to unify data engineering, data science and analytics, with tight integration to Google Cloud Storage, BigQuery and the Google Cloud AI Platform.Learn moreCloud regions\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/david-skinner\/#","text":"David Skinner - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid SkinnerChief Strategy Officer at AcxiomBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sai-ravuru\/#","text":"Sai Ravuru - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSai RavuruSenior Manager of Data Science & Analytics at JetBlueBack to speakersSai Ravuru is the Senior Manager of Data Science & Analytics at JetBlue architecting the AI & ML strategy for all of JetBlue. He manages a portfolio of Operations Data Science, Commercial Data Science, AI & ML engineering and Business Intelligence teams & products.\nSai Ravuru is a seasoned Data Scientist and aviation executive with over a decade of experience in empowering efficiencies in aviation using AI & ML. He started his career simulating hypersonic missiles on supercomputing clusters.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-kutay","text":"John Kutay - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn KutayDirector of Product Management at StriimBack to speakersJohn Kutay, Director of Product Management at Striim\nJohn Kutay is Director of Product Management at Striim with prior experience as a software engineer, product manager, and investor. His podcast \u201cWhat's New in Data\u201d best captures his ability to understand upcoming trends in the data space with thousands of listeners across the globe. In addition, John has over 10 years of experience in the streaming data space through academic research and his work at Striim.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/risha-ravindranath","text":"Risha Ravindranath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRisha RavindranathSr Manager, Data Governance at Comcast AdvertisingBack to speakersRisha Ravindranath brings 10+ years of experience in Data Governance and Business Analysis. She is a highly involved business analyst who expertly brings solutions together to drive end-to-end data governance programs integrated with technical solutions. Risha currently is a Senior Manager of Data Governance at Comcast Effectv.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/resources\/webinar\/goodbye-data-warehouse-hello-lakehouse?itm_data=unitycatalog-promocard-goodbyedwbigrock","text":"The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT \/ 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient \u2014 and unnecessary.\u00a0In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater.\u00a0Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we\u2019ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A.\u00a0Plus, you\u2019ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we\u2019ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.Jos\u00e9 Luis S\u00e1nchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy)\nEvent Co-sponsor: Fivetran (Fivetran Privacy Policy)\nEvent Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tomer-patel","text":"Tomer Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTomer PatelSoftware Engineering Manager at Akamai TechnologiesBack to speakersTomer Patel is an Engineering Manager at Akamai. He manages, builds, implements, and maintains scaled cyber security analytics applications on top of Azure and Databricks. \nHe currently manages 4 teams that focus on Data Engineering, Interactive Analytics product, and Devops.\nTomer has a Bachelor's degree in Computer Science from The Hebrew University of Jerusalem and a Master of Business Administration (MBA) from Bar-Ilan University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/federal-government","text":"Data Analytics und KI f\u00fcr Bundesbeh\u00f6rden | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWData Analytics und KI f\u00fcr Bundesbeh\u00f6rdenNutzen Sie Innovationen, um mit Daten und Machine Learning bessere \u00f6ffentliche Dienste anzubieten.Durch die Federal Data Strategy und AI Executive Order ist klar, dass sich die US-Regierung auf die Modernisierung ihrer Data-Analytics- und Warehousing-Funktionen konzentriert.Die Databricks Lakehouse Platform erm\u00f6glicht es Bundesbeh\u00f6rden, das volle Potenzial ihrer Daten auszusch\u00f6pfen, um ihre Ziele zu erreichen und B\u00fcrgern einen besseren Service zu bieten.Bef\u00e4higung von Bundesbeh\u00f6rden, Daten und KI\u00a0zu nutzen, um Missionsziele zu erreichenVon f\u00fchrenden Beh\u00f6rden des \u00f6ffentlichen Sektors als vertrauensw\u00fcrdig eingestuft+ jeder sonstige Apache Spark\u2122-kompatible ClientSehen Sie sich an, wie Branchenf\u00fchrer Databricks nutzen, um das Erlebnis f\u00fcr B\u00fcrger in allen \u00f6ffentlichen Diensten zu verbessern.Neueste Blogbeitr\u00e4ge, Webinare und FallstudienWarum Databricks f\u00fcr die Bundesbeh\u00f6rdenModernisieren Ihrer Data Analytics130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis f\u00fcr Patienten und \u00c4rzte mit der schnellsten DNAQSeq-Pipeline in gro\u00dfem Umfang.Effektive und effiziente Erbringung von Missionsergebnissen130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis f\u00fcr Patienten und \u00c4rzte mit der schnellsten DNAQSeq-Pipeline in gro\u00dfem Umfang.Schaffung besserer Erlebnisse f\u00fcr die B\u00fcrger130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis f\u00fcr Patienten und \u00c4rzte mit der schnellsten DNAQSeq-Pipeline in gro\u00dfem Umfang.Mehr InformationenUmfassende Compliance f\u00fcr eine schnelle und einfache Betriebserlaubnis (ATO)Databricks hat ATOs f\u00fcr die Regionen, Netzwerke und Konformit\u00e4tskontrollen erreicht, die Ihre Missionsziele unterst\u00fctzenCloudsC2S\nSC2S\nGovCloud\nPublic Cloud\nNetzwerke\u00d6ffentlich\nNIPR\nSIPR\nJWICS\nCompliance-KontrollenFedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICS-503\nWie Databricks Innovationen f\u00fcr die Bundesbeh\u00f6rden f\u00f6rdertGesundheitswesenVerbessern Sie die Lieferung und Qualit\u00e4t von Gesundheitsdiensten f\u00fcr die B\u00fcrger mit leistungsstarken Analysen und einer 360\u00b0-Ansicht der Patienten.\nPatient 360\u00a0\nOptimierung der Lieferkette\u00a0\nVersicherungsmanagement \u00a0Genomik\u00a0\nErforschung und Bereitstellung von MedikamentenVerteidigungNutzen Sie die M\u00f6glichkeiten der pr\u00e4diktiven Analytics f\u00fcr Geo-, IoT- und \u00dcberwachungsdaten, um den Betrieb zu verbessern und das Land zu sch\u00fctzen.\u00a0\nLogistik\nVorausschauende Wartung\u00a0\n\u00dcberwachung und Aufkl\u00e4rung\u00a0\nStrafverfolgung und BereitschaftHomeland SecurityErkennen und verhindern Sie kriminelle Aktivit\u00e4ten und nationale Bedrohungen mit Echtzeit-Analysen und datengesteuerten Entscheidungen.\u00a0\nZoll und Grenzschutz\u00a0\nEinwanderung und Staatsb\u00fcrgerschaft\u00a0\nTerrorismusbek\u00e4mpfung\u00a0\nVerwaltung der Nothilfe von Bundesbeh\u00f6rden\u00d6ffentliche Beh\u00f6rden\/HandelErkennen Sie Anomalien mit Machine Learning proaktiv, um Risiken zu mindern und betr\u00fcgerische Aktivit\u00e4ten zu verhindern.\nSteuerbetrug und -einzug\u00a0\nProzess- und Betriebsmanagement\u00a0\nVerwaltung von Finanzhilfen\u00a0\nKunde 360EnergieVerbessern Sie das Energiemanagement mit Dateneinblicken, die die Energieresilienz und Nachhaltigkeit sicherstellen.\u00a0\nSicherheit der Energieinfrastruktur\u00a0\nIntelligenteres Energiemanagement\u00a0\nEnergieexploration\u00a0\nZuverl\u00e4ssigkeit des StromnetzesGeheimdiensteNutzen Sie Echtzeiteinblicke, um fundierte Entscheidungen zu treffen, die sich auf die Sicherheit unserer B\u00fcrger und der Welt auswirken k\u00f6nnen.\u00a0\nBedrohungserkennung\u00a0\nNeutralisierung von Cyberangriffen\u00a0\nGeheimdienstliche \u00dcberwachung und Aufkl\u00e4rung\u00a0\nSocial Media AnalyticsRessourcenKundenberichteF\u00f6rderung der digitalen Transformation, damit Patienten bei CMS immer an oberster Stelle stehenBew\u00e4hrte Methoden der Data Governance \u2013 Lehren aus den Centers von Medicare und Medicaid ServicesLehren aus der Modernisierung der USCIS Data Analytics PlatformModernisierung der Air Force mit Big Data und KIWebinareSchnelle Reaktion im Krankenhausbetrieb mithilfe von Daten und KI w\u00e4hrend der COVID-19-PandemieGeodatenanalyse und KI im \u00f6ffentlichen SektorEine moderne Architektur zur Datenanalyse f\u00fcr RegierungenBessere Erkennung von Bedrohungen mit Big Data und KINeuigkeitenAzure Databricks erreicht FedRAMP High Authorization in Microsoft Azure Government (MAG)Sicherheit auf Regierungsniveau in der AWS CloudUnified Analytics f\u00fcr Regierungen und Beh\u00f6rdenSt\u00e4rkung der U.S. Intelligence Community durch missionskritische Analytics und KIGipfelgespr\u00e4cheAutomatisierung des systemweiten Informationsmanagements (SWIM) der Federal Aviation Administration (FAA) bei der Datenerfassung und -analyseGeospatial Analytics in gro\u00dfem Ma\u00dfstab: Analyse von Bewegungsmustern w\u00e4hrend einer PandemieM\u00f6chten Sie loslegen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.\u00a0Kostenlos testenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/try-databricks","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/events","text":"Databricks \uc774\ubca4\ud2b8 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks \uc774\ubca4\ud2b8\uc608\uc815\ub41c Databricks \ubaa8\uc784, \uc6e8\ube44\ub098, \ucee8\ud37c\ub7f0\uc2a4 \ub4f1\uc744 \uc0b4\ud3b4\ubcf4\uc138\uc694.Data + AI Summit 20236\uc6d4 26\uc77c ~ 29\uc77c\uacbd\ud5d8 \ubc29\uc2dd \uc120\ud0dd - \ud604\uc7a5\uc5d0 \uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \uae30\uc870 \uc5f0\uc124 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9ac\ubc0d\uc5d0 \uc628\ub77c\uc778\uc73c\ub85c \ucc38\uc11d\ud558\uace0 \ucc38\uc5ec\ud560 \uc138\uc158\uc744 \uc120\ud0dd\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30Loading...Browse All Upcoming Events\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bradley-axen\/#","text":"Bradley Axen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBradley AxenMachine Learning Engineer at BlockBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/john-thompson\/#","text":"John Thompson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn ThompsonGlobal Head, Artificial Intelligence at EYBack to speakersJohn is an international technology executive with over 35 years of experience in the fields of data, advanced analytics, and artificial intelligence (AI). He is currently the Global Head of AI at EY.\nJohn has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support, and product development organizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/#","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/product\/databricks-sql","text":"Databricks SQL | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPromotion Databricks SQL \u2013 \u00e9conomisez plus de 40\u00a0%Profitez de notre promotion de 15\u00a0mois sur SQL Serverless et le tout nouveau SQL ProEn savoir plusDatabricks SQLLe meilleur data warehouse est un lakehouseD\u00e9marrerRegarder la d\u00e9mo\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowDatabricks SQL (DB SQL) est un data warehouse serverless bas\u00e9 sur la plateforme Databricks Lakehouse. Capable d'ex\u00e9cuter toutes vos applications SQL et BI \u00e0 grande \u00e9chelle, il combine un rapport performance \/ prix jusqu'\u00e0 12\u00a0fois sup\u00e9rieur, un mod\u00e8le de gouvernance unifi\u00e9, des API et des formats ouverts ainsi que les outils de votre choix, sans vous lier \u00e0 aucun fournisseur.Meilleur rapport performance \/ prixR\u00e9duisez les co\u00fbts et obtenez le meilleur rapport performance \/ prix, tout en vous lib\u00e9rant de la gestion, de la configuration et de l'\u00e9volution de votre infrastructure cloud avec le serverless.Gouvernance int\u00e9gr\u00e9eCr\u00e9ez un exemplaire unique de toutes vos donn\u00e9es \u00e0 l'aide de normes ouvertes et appliquez une couche de gouvernance unifi\u00e9e \u00e0 toutes les \u00e9quipes de donn\u00e9es \u00e0 l'aide du SQL standard.Un \u00e9cosyst\u00e8me richeUtilisez SQL et des outils comme Fivetran, dbt, Power BI ou Tableau conjointement avec Databricks pour ing\u00e9rer, transformer et interroger toutes vos donn\u00e9es in situ.\u00c9liminez les silosDonnez \u00e0 tous vos analystes les moyens d'acc\u00e9der plus rapidement aux donn\u00e9es les plus r\u00e9centes \u00e0 des fins d'analytique en aval en temps r\u00e9el, et passez sans effort de la BI au ML.Comment \u00e7a marche\u00a0?Int\u00e9grations transparentes avec l\u2019\u00e9cosyst\u00e8me\u00a0Simplicit\u00e9 d'utilisation\u00a0Performant dans le monde r\u00e9el\u00a0Gouvernance centralis\u00e9e\u00a0Un lac de donn\u00e9es ouvert et fiable comme fondementIng\u00e9rez, transformez et orchestrez facilement les donn\u00e9es, quelle que soit leur sourceTravaillez avec vos donn\u00e9es, o\u00f9 qu'elles se trouvent. Les fonctionnalit\u00e9s cl\u00e9s en main permettent aux analystes et aux ing\u00e9nieurs analytiques d'ing\u00e9rer facilement des donn\u00e9es de tout type de source, du stockage cloud aux applications d'entreprise comme Salesforce, Google Analytics ou Marketo, \u00e0 l'aide de Fivetran. Tout est disponible en un clic. Ensuite, il vous suffit de g\u00e9rer les d\u00e9pendances et de transformer les donn\u00e9es in situ. Pour cela, vous pouvez utiliser les fonctionnalit\u00e9s ETL int\u00e9gr\u00e9es du Lakehouse ou vos outils pr\u00e9f\u00e9r\u00e9s comme dbt sur Databricks SQL pour des performances optimales.\u00a0\u00ab\u00a0En combinant Databricks et Fivetran, nous avons mis sur pied un pipeline de donn\u00e9es \u00e0 la fois robuste et moderne en un temps record. Fivetran offrait tous les connecteurs et toutes les int\u00e9grations dont nous avions besoin.\u00a0\u00bb\u2014 Justin Wille, Directeur Insights et Analytique, Kreg ToolEn savoir plusChoisissez vos outils d'analytique et de BITravaillez en toute transparence avec les outils de BI les plus populaires comme Tableau, Power BI et Looker. D\u00e9sormais, les analystes peuvent utiliser leurs outils favoris pour d\u00e9couvrir de nouveaux insights m\u00e9tier en s'appuyant sur les donn\u00e9es les plus compl\u00e8tes et les plus r\u00e9centes. Pour maximiser la collaboration, Databricks SQL permet \u00e9galement \u00e0 chaque analyste d'identifier et de partager rapidement de nouveaux insights gr\u00e2ce \u00e0 l'\u00e9diteur SQL int\u00e9gr\u00e9, aux visualisations et aux tableaux de bord.\u00a0\u00ab\u00a0Nous avons maintenant la certitude d'avoir \u00e0 port\u00e9e de main les donn\u00e9es les plus r\u00e9centes et les plus compl\u00e8tes pour alimenter nos tableaux de bord et nos rapports Power BI.\u00a0\u00bb\u2014 Jake Stone, Senior Manager, Business Analytics, ButcherBoxEn savoir plus\u00c9liminez la gestion des ressources gr\u00e2ce au calcul serverlessAvec Databricks SQL serverless, vous n'avez plus besoin de g\u00e9rer, configurer ou faire \u00e9voluer l'infrastructure cloud sur le Lakehouse. Votre \u00e9quipe de donn\u00e9es a ainsi davantage de temps \u00e0 consacrer \u00e0 son c\u0153ur de mission. Les warehouses SQL Databricks fournissent un calcul SQL instantan\u00e9 et \u00e9lastique, d\u00e9coupl\u00e9 du stockage. Convenant id\u00e9alement aux cas d\u2019usage \u00e0 forte concurrence, ils s\u2019adaptent automatiquement pour fournir une simultan\u00e9it\u00e9 illimit\u00e9e sans interruption.\u00a0\u00ab\u00a0Databricks SQL Serverless nous offre toute la puissance de Databricks SQL et permet une exploitation bien plus efficace de notre infrastructure.\u00a0\u00bb\u2014 R. Tyler Croy, Director of Platform Engineering, ScribdEn savoir plusInt\u00e9gralement con\u00e7u pour des performances optimalesDatabricks SQL a \u00e9t\u00e9 r\u00e9solument optimis\u00e9 pour vous offrir les meilleures performances pour tous les outils, types de requ\u00eates et applications du monde r\u00e9el. Cela inclut Photon \u2014 le moteur de requ\u00eate nouvelle g\u00e9n\u00e9ration \u2014 qui, combin\u00e9 aux warehouses SQL, offre un rapport performance \/ prix jusqu'\u00e0 12\u00a0fois sup\u00e9rieur \u00e0 celui des autres data warehouses dans le cloud.\u00a0\u00ab\u00a0Gr\u00e2ce aux analyses que nous effectuons sur la plateforme lakehouse Databricks, le temps n\u00e9cessaire pour produire des insights \u00e0 partir du comportement des audiences est pass\u00e9 de plusieurs semaines \u00e0 quelques minutes.\u00a0\u00bb\u2014 St\u00e9phane Caron, Directeur Business Intelligence, CBC\u00a0\/ Radio-CanadaEn savoir plusCentralisez le stockage et l'administration de toutes vos donn\u00e9es avec le SQL standardCr\u00e9ez un seul exemplaire de toutes vos donn\u00e9es \u00e0 l'aide du format ouvert de Delta Lake pour \u00e9viter le verrouillage des donn\u00e9es. Vous pouvez alors effectuer des analyses in situ et des op\u00e9rations ETL \/ ELT sur votre Lakehouse, sans d\u00e9placer ni copier des donn\u00e9es dispers\u00e9es dans diff\u00e9rents syst\u00e8mes. Gouvernance fine, data lineage et SQL standard\u00a0: ces outils facilitent la d\u00e9couverte, la s\u00e9curisation et la gestion de toutes vos donn\u00e9es sur l'ensemble des clouds avec le Unity Catalog de Databricks.\u00a0\u00ab\u00a0Databricks joue un r\u00f4le essentiel dans nos activit\u00e9s. Son architecture de lakehouse nous offre en effet un moyen unifi\u00e9 de stocker, consulter et partager des donn\u00e9es exploitables.\u00a0\u00bb\u2014 Jagan Mangalampalli, Directeur Big Data, PunchhEn savoir plusB\u00e2ti sur une fondation de donn\u00e9es commune, aliment\u00e9 par la plateforme LakehouseLa plate-forme Databricks Lakehouse fournit la solution de data warehouse la plus compl\u00e8te de bout en bout pour tous vos besoins d\u2019analytique moderne, et bien plus encore. Obtenez des performances de classe mondiale pour un co\u00fbt bien inf\u00e9rieur \u00e0 celui des data warehouses cloud. R\u00e9duisez le d\u00e9lai entre l'acquisition des donn\u00e9es brutes et les renseignements exploitables \u00e0 grande \u00e9chelle, et unifiez donn\u00e9es en lot et en streaming. De plus, le Lakehouse permet aux \u00e9quipes de donn\u00e9es de passer sans effort de la description \u00e0 l'analyse pr\u00e9dictive pour d\u00e9couvrir de nouveaux insights.\u00a0\u00ab\u00a0Databricks met \u00e0 la disposition de nos \u00e9quipes de donn\u00e9es et d'analytique une plateforme unique pour consulter les donn\u00e9es et les partager au sein d'ABN AMRO. Elles peuvent ainsi d\u00e9livrer des solutions ML qui facilitent l'automatisation et g\u00e9n\u00e8rent des insights \u00e0 l'\u00e9chelle de l'entreprise.\u00a0\u00bb\u2014 Stefan Groot, Directeur Ing\u00e9nierie analytique, ABN AMROEn savoir plusMigrer vers DatabricksVous en avez assez des silos de donn\u00e9es, de la lenteur des performances et des co\u00fbts \u00e9lev\u00e9s associ\u00e9s aux anciens syst\u00e8mes comme Hadoop et aux entrep\u00f4ts de donn\u00e9es d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de donn\u00e9es, d'analyses et d'IA.Migrer vers DatabricksInt\u00e9grationsDes int\u00e9grations fluides avec l'\u00e9cosyst\u00e8me offrent une flexibilit\u00e9 maximale \u00e0 vos \u00e9quipes data. Int\u00e9grez les donn\u00e9es critiques de l'entreprise avec Fivetran, transformez-les sur place avec dbt et d\u00e9couvrez de nouveaux insights avec Power BI, Tableau ou Looker, le tout sans d\u00e9placer vos donn\u00e9es dans un data warehouse existant.Ingestion de donn\u00e9es et ETLGouvernance des donn\u00e9esBI et tableaux de bord+ tout autre client compatible Apache Spark\u2122\u00ab\u00a0Aujourd'hui, plus que jamais, les organisations ont besoin d'une strat\u00e9gie de donn\u00e9es offrant rapidit\u00e9 et agilit\u00e9 pour \u00eatre adaptables. Alors que les entreprises migrent rapidement leurs donn\u00e9es vers le cloud, nous constatons un int\u00e9r\u00eat croissant pour l'analytique dans le datalake. Databricks SQL offre une toute nouvelle exp\u00e9rience permettant aux clients d'exploiter des insights provenant de volumes massifs de donn\u00e9es, avec les performances, la fiabilit\u00e9 et l'\u00e9volutivit\u00e9 dont ils ont besoin. Nous sommes fiers de nous associer \u00e0 Databricks pour concr\u00e9tiser cette opportunit\u00e9.\u00a0\u00bb- Francois Ajenstat, chef de produit, TableauT\u00e9moignages de clientsEn savoir plusDelta LakeContact partenairesUnity CatalogDelta\u00a0Live\u00a0tablesContenu associ\u00e9\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les avantages du lakehouse.\nExplorer les ressourcesEbooksCr\u00e9er le Data Lakehouse par Bill Inmon, p\u00e8re du data warehousePourquoi le lakehouse est votre prochain data warehouseDonn\u00e9es, analyses et gouvernance de l'IALe Grand Livre du Data EngineeringLa migration d'un data warehouse vers un data lakehouse en quelques mots\u00c9v\u00e9nementsTravaux internes du Lakehouse sur le Data + AI World TourWebinaire sur les bonnes pratiques en mati\u00e8re d'optimisation des performances sur le Lakehouse \u2013 Dans la vie d'une requ\u00eateFormation gratuite Databricks SQL \u2013 \u00c0 la demandeLe meilleur data warehouse est un lakehouseBlogsDatabricks \u00e9tablit un record officiel de performance pour l'entreposage des donn\u00e9esAnnonce de la disponibilit\u00e9 g\u00e9n\u00e9rale de Databricks SQL\u00c9volution du langage SQL chez Databricks\u00a0: standard Ansi par d\u00e9faut et migrations plus faciles \u00e0 partir des Data WarehousesIl n'a jamais \u00e9t\u00e9 aussi simple de d\u00e9ployer dbt sur DatabricksTechniques de mod\u00e9lisation de data warehouse et mise en \u0153uvre sur la plateforme de lakehouse DatabricksComment cr\u00e9er une solution d'analyse marketing avec Fivetran et dbt sur le lakehouse DatabricksPr\u00eat \u00e0 vous lancer\u00a0?Essai gratuitRejoignez la communaut\u00e9ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lakhan-prajapati\/#","text":"Lakhan Prajapati - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLakhan PrajapatiDirector of Architecture and Engineering at ZS associatesBack to speakersTechnology Enthusiast, Loves solving complex tech problems for the enterprise. Expertise in the field of cloud, data warehousing, and enterprise architectureLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/the-delta-lake-series","text":"The Definitive Guide to Delta Lake Series | DatabricksSeriesBring fast analytics to your data lakeImprove quality, security and performance in your data lake.In \u201cThe Delta Lake Series\u201d, we will explore how Delta Lake brings quality, reliability, security and performance to your data lake to enable a lakehouse architecture. Download this eBook series to understand the unique capabilities of Delta Lake, explore common use cases like streaming and learn how Delta Lake delivers substantial performance improvements for our customers.The eBook series breaks out into the following chapters:Chapter 01 \u2014 Fundamentals and PerformanceChapter 02 \u2014 FeaturesChapter 03 \u2014 LakehouseChapter 04 \u2014 StreamingChapter 05 \u2014 Customer Use CasesGet the SeriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#9dedeff4ebfcfee4ddf9fce9fcffeff4fef6eeb3fef2f0","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c3ca7bcb282c6\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/awards-and-recognition","text":"Prix et distinctions | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWPrix et distinctionsD\u00e9couvrez toutes les raisons pour lesquelles Databricks est r\u00e9compens\u00e9 par les leaders du secteur.Leader du Magic Quadrant 2022pour les syst\u00e8mes de gestion des bases de donn\u00e9es cloudCustomer Choice Award 2022 pour les syst\u00e8mes de gestion des bases de donn\u00e9es cloudLeader du Magic Quadrant 2021 pour les syst\u00e8mes de gestion des bases de donn\u00e9es cloudLeader du Magic Quadrant 2021 pour la Data Science et le Machine learningLakehouse \u2013 Hype Cycle sur les solutions de gestion des donn\u00e9es, 2022Les entreprises \u00e0 suivre en 2023Entreprises les plus innovantes en data scienceCloud 100AI 50America\u2019s Best Startup EmployersMeilleurs lieux de travail dans le secteur des technologiesMeilleurs lieux de travail de la r\u00e9gion de la Baie de San FranciscoMeilleurs lieux de travail pour les MillennialsCNBC Disruptor 50Meilleurs lieux de travail en 2022Vous voulez en savoir plus\u00a0?Nous serions ravis de conna\u00eetre vos objectifs commerciaux. Notre \u00e9quipe de services fera tout son possible pour vous aider \u00e0 r\u00e9ussir.ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/tathagata-das","text":"Tathagata Das - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTathagata Das DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/pouya-barrach-yousefi\/#","text":"Pouya Barrach-Yousefi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPouya Barrach-YousefiData Pro and Director Strategic Accounts at ProphecyBack to speakersIn the 6 years at IQVIA prior to joining Prophecy, Pouya was a Data Science Developer and tech lead for the Analytics Center of Excellence, then joined the global Data Science & Advanced Analytics team as an Associate Data Science Director to focus on delivering commercial AIML solutions for pharma clients, and finally as Director of Enterprise AIML Strategy he led data, data science, and machine learning improvements across IQVIA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/deepak-sekar\/#","text":"Deepak Sekar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeepak SekarSr. Solution Architect at DatabricksBack to speakersA Data & AI enthusiast from the down under! Extensive experience in building Enterprise\/ SMB Data & AI solutions in ASEAN and Australia\/NZ across Energy & Utilities\/ Oil & Gas\/ Telecommunication\/ Retail. I love guiding organizations to embrace data & unlock the never-ending value that data brings to them. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/customers?itm_data=hp-promo-customerlogos-seeallcustomers","text":"Kunden von\u2028Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWKunden von DatabricksEntdecken Sie, wie innovative Unternehmen aus allen Branchen die Databricks Lakehouse-Plattform f\u00fcr ihren Erfolg nutzenEmpfehlungen\n\n\nKundenbericht\n\nModernisierung von Finanzdienstleistungen mit Daten und KI\nTrotz der steigenden Akzeptanz von Big Data und KI sehen sich die meisten Finanzdienstleister immer noch mit erheblichen Herausforderungen bei Datentypen, Datenschutz und Umfang konfrontiert.\n\nWeiterlesen\n\n\nKundenbericht\n\nVorhersagen und Steigern des Customer Lifetime Value mit ML\nKolibri Games befindet sich im Herzen Berlins und ist bekannt f\u00fcr seinen erfrischenden, von Spielern gef\u00fchrten Ansatz. Kolibri Games ist ein aufgehender Stern in der Szene der Spiele f\u00fcr Mobilger\u00e4te. Die Hittitel Idle Miner Tycoon und Idle Factory Tycoon ziehen monatlich \u00fcber 10\u00a0Millionen aktive Benutzer an.\n\nWeiterlesen\n\n\nKundenbericht\n\nShell f\u00fchrt innovative Energiel\u00f6sungen f\u00fcr eine sauberere Welt ein\nDatabricks Lakehouse tr\u00e4gt dazu bei, Daten zu demokratisieren und Abl\u00e4ufe weltweit zu modernisieren\n\nWeiterlesen\n\n\nKundenbericht\n\nDigitalisierung der Solaranlagen zur F\u00f6rderung der betrieblichen Exzellenz\nSolytic, ein Unternehmen, das Solaranlagen \u00fcberwacht und deren Daten analysiert, hat ein Ziel: die Nutzung von Solarenergie f\u00fcr jedermann zu vereinfachen.\n\nWeiterlesen\n\n\nKundenbericht\n\nVerbinden Sie Millionen von Kunden mit dem gr\u00f6\u00dften 5G-Netzwerk\nAls einer der bekanntesten Mobilfunkanbieter in den USA hat sich T-Mobile zum Ziel gesetzt, das gr\u00f6\u00dfte und schnellste 5G-Netz bereitzustellen.\n\nWeiterlesen\n\n\nKundenbericht\n\nAufbau einer energieeffizienten Welt\nDa die weltweite Nachfrage nach energieeffizienten L\u00f6sungen weiter steigt\u00a0\u2013 von Klimasystemen \u00fcber Solarmodule bis hin zu Windturbinen und Elektroautos\u00a0\u2013 kann die Bedeutung von Daten f\u00fcr einen intelligenteren Betrieb nicht hoch genug eingesch\u00e4tzt werden.\u00a0\n\nWeiterlesenAlle Kunden erkundenDer Daten-Team EffektDatenteams bilden eine vereinte Streitmacht, wenn es darum geht, die schwierigsten Probleme der Welt zu l\u00f6sen.Erfahren Sie, wie \u2192Ist Ihr Unternehmen die n\u00e4chste Erfolgsgeschichte?KontaktRessourcenKundenberichtSo stellt Cond\u00e9 Nast seinen Kunden mithilfe von Databricks personalisierte Inhalte bereit.Mehr InformationenKundenberichtFinden Sie heraus, wie Apple und Disney+ mit Unified Analytics und KI riesige Erfolge feiernMehr InformationenKundenberichtErfahren Sie von Slawek Kierner, SVP, Chief Data & Analytics Officer bei Humana, mehr \u00fcber die Rolle von Daten und KI im GesundheitswesenAnsehenM\u00f6chten Sie loslegen?Kostenlos testenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/fr\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/tredence-predictive-supply-risk-management","text":"Predictive Supply Risk Management by Tredence and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionPredictive Supply Risk Management by TredenceIndustry-specific solution developed by Tredence and powered by the Databricks Lakehouse PlatformContact usPower your supply risk decisionsCustomers today are faced with multiple supply risks including lack of in-transit visibility, disruptions caused by weather, and local events, among others. Tredence\u2019s Predictive Supply Risk Management solution, built on the Databricks Lakehouse Platform, helps businesses meet supply risk challenges by providing a scalable, cloud-based solution that can be tailored to the specific needs of each organization. The platform\u2019s flexibility and scalability allow businesses to keep pace with changing regulations and customer demands, and its comprehensive suite of tools helps identify and mitigate risks across the enterprise. Benefits of the Tredence Predictive Supply Risk Management solution are:Predicts order delays, identifies root causes and quantifies supply chain impactProvides real-time visibility with delay alerts using external and internal data\u00a0Delivers prescriptive models and simulation to mitigate risksContact usResourcesWhitepaperLearn moreBlogLearn moreExplainer VideoLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/aman-kapoor\/#","text":"Aman Kapoor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAman KapoorHead of Data Platform at PetronasBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/suneel-konidala\/#","text":"Suneel Konidala - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuneel KonidalaSr. Manager at AccentureBack to speakersSuneel is an accomplished leader in Data space for more than two decades. He is a lead partner champion at Accenture's Databricks practice. Suneel is well versed in multiple data and cloud technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/beinan-wang","text":"Beinan Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeinan WangSenior Staff Software Engineer at AlluxioBack to speakersDr. Beinan Wang is a Senior Staff Software Engineer from Alluxio and is the committer of PrestoDB. He is leading the engineer efforts of the next generation distributed cache. Prior to Alluxio, he was the Tech Lead of the Presto team in Twitter and he built large-scale distributed SQL systems for Twitter\u2019s data platform. He has twelve-year experience of working on performance optimization. He received his Ph.D. in computer engineering from Syracuse University on distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?location=washington%2C%20D.C.","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vinit-doshi","text":"Vinit Doshi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVinit DoshiSenior Manager at TredenceBack to speakersVinit Doshi leads the MLOps delivery practice at Tredence, He has over 14 years of experience in building and managing ML solutions with a focus on building scalable MLOPs practices for clients over the past 3 years.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alexander-booth","text":"Alexander Booth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlexander BoothAssistant Director of Research & Development at Texas Rangers Baseball Club, LLCBack to speakersAlexander is a data scientist, data engineer, and application developer with extensive experience in using machine learning and artificial intelligence techniques, based on insights from big data, to communicate actionable decisions to management to help generate a competitive advantage. He specializes in Sports Analytics with a particular passion for learning how innovation and new technology can shape the game of baseball.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/pricing\/serverless-realtime-inference","text":"Model Serving Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWModel Serving PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorModel ServingMake live predictions in your apps and websites.Select planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudSelect regionSelectLoading...Model Serving pricing examples\u00a0Notes:1. The simple examples above are baseline configurations. Example 2 requires launch charge from cold start.2. Users may also select \u201cscale to zero\u201d or \u201cvery latency sensitive\u201d options, which would change DBU emissions.FAQHow much memory is provided per concurrent request?4 GB per concurrent requestWhy are there regionalized prices?Our regional prices are based on the regional cost of infrastructure supporting our serverless productsHow do DBUs and concurrency work for model serving?Total queries\/total time determines # of concurrent requests required per hour\n1 DBU\/hr provides 1 concurrent request\/hr; minimum of 4 DBU\/hr\nWhat is Model Execution time?Model Execution Time refers to the time required for running a machine learning model on Model Serving. To estimate execution time, you can check the latency chart on the endpoint page or conduct load testing. Feel free to contact our team for guidance on load testing.What is the minimum charge if Scale to Zero is not selected and there is no traffic ?If the 'scale to zero' is not selected, the minimum charge will depend on the minimum provisioned concurrency specified by the chosen concurrency range.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erika-ehrli\/#","text":"Erika Ehrli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErika EhrliSenior Director of Product Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/don-scott\/#","text":"Don Scott - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon ScottVP, New Product Development at Hitachi Solutions AmericaBack to speakersDon, is the VP of New Product Development at Hitachi Solutions. With 10 years in emerging technology, and a background in high-performance compute, he currently drives success for clients by leading the Empower Analytics Platform. Passionate about cloud solutions, Don's mission is to address historic labor shortages through automation in the data and AI space.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/nadine-farah","text":"Nadine Farah - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNadine FarahHead of Dev Rel at OnehouseBack to speakersNadine Farah is head of dev rel at Onehouse and an Apache Hudi contributor. She's passionate about bridging engineering, product & marketing to help drive product adoption. She previously lead Rockset's developer initiatives where she focused on building technical content to drive developer adoption for real-time analytics. At Bose, she contributed to the watchOS SDK & worked with partners to embrace spatial audio in the music and gaming industries.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lindsay-mico","text":"Lindsay Mico - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLindsay MicoHead of Data Science at Providence HealthBack to speakersLindsay Mico is the Head of Data Science for Providence, with a focus on enterprise scale AI solutions and cloud native architectures. Originally trained as a cognitive neuroscientist and statistician, he has worked across industries including natural resource management, telecom, and healthcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/lakehouse-for-manufacturing\/lakehouse-for-manufacturing#page=1","text":"\n\n\n\n\n\n\n\nExplore the Lakehouse for Manufacturing\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/craig-wiley","text":"Craig Wiley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCraig WileySr. Director of Product, Lakehouse AI at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/diversity","text":"Diversit\u00e0 e inclusione | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWIl futuro dei dati \u00e8 aperto a tuttiDiversit\u00e0, equit\u00e0 e inclusione in DatabricksGuidati dai dati. Supportati dalle persone.La nostra missione \u00e8 diversificare i Big Data... a partire dal nostro team. Crediamo che estrazioni, esperienze, prospettive e competenze diverse alimentino l'innovazione e consolidino i rapporti fra di noi e con i nostri clienti. Puntiamo a coltivare una cultura di appartenenza in cui tutti siano messi nelle condizioni di svolgere il loro lavoro nel modo migliore. Dalla garanzia di parit\u00e0 salariale a parit\u00e0 di lavoro, alla definizione di programmi che celebrano, educano e fanno crescere il nostro team, i concetti di Diversit\u00e0, Equit\u00e0 e Inclusione (DEI) sono \"intrecciati\" in tutto ci\u00f2 che facciamo.Posto di lavoro certificato per l'equit\u00e0 salariale\nSiamo orgogliosi di essere fra le prime sei organizzazioni certificate da Fair Pay Workplace. Nell'ambito del suo impegno a raggiungere la parit\u00e0 salariale, Databricks ha effettuato una rigorosa valutazione dei dati e dei processi retributivi, impegnandosi alla massima trasparenza con analisi continue dell'equit\u00e0 salariale.Gaingels e Flucas Ventures\nIl nostro impegno per la diversit\u00e0, l'equit\u00e0 e l'inclusione abbraccia tutto il nostro team, dalle persone che lavorano con noi a quelle che investono su di noi. Per questo siamo fieri di collaborare con una serie di investitori di caratura mondiale, fra cui Gaingels e Flucas Ventures, specializzati nel finanziamento di aziende che dimostrano grande attenzione in ambito DEI.\u201cSappiamo che pi\u00f9 sono i dati in nostro possesso, pi\u00f9 approfondite sono le nostre informazioni. Lo stesso vale per diversit\u00e0 e inclusione: Databricks cresce includendo la pi\u00f9 ampia variet\u00e0 di estrazioni, esperienze e punti di vista\u201d.\u2014 Ali Ghodsi, Cofondatore e CEO, DatabricksLe nostre comunit\u00e0Crediamo che mettere i nostri dipendenti nelle migliori condizioni di lavoro sia la chiave per sfruttare appieno il loro potenziale. I nostri vivaci Employee Resource Group (ERG) sono collettivi gestiti dai dipendenti che svolgono un ruolo chiave nel creare un ambiente inclusivo e favorevole in Databricks. Queste diverse comunit\u00e0 di dipendenti e partner creano spazi di interazione e svago, oltre ad aumentare la consapevolezza rispetto a questioni importanti.Queeries Network\nVeterans Network\nBlack Employee Network\nWomen\u2019s Network\nLatinX Network\nAsian Employee Network\nLe nostre esperienze\u201cIn Databricks costruisco team dei quali vorrei far parte. Questo significa avere la sicurezza di essere me stessa e offrire la stessa comfort zone a tutti quelli che mi circondano. L'attenzione che mostriamo l'uno per l'altro e la nostra dedizione all'inclusione hanno un forte impatto sull'intera comunit\u00e0\u201d.\u2014 Stacy Kerkela, Director of EngineeringMaggiori informazioni\u201cLa rete LatinX di Databricks rafforza il mio senso di appartenenza alla comunit\u00e0, una comunit\u00e0 aperta, perch\u00e9 gli Employee Resource Group di Databricks accolgono e formano tutte le persone, qualunque sia il loro background\u201d.\u2014 Miguel Peralvo, Senior Solutions ArchitectMaggiori informazioni\u201cMolte aziende sono attente a promuovere la diversit\u00e0 di genere, ma \u00e8 bello far parte di un'azienda che compie azioni concrete per spostare l'ago della bilancia\u201d.\u2014 Allie Emrich, Program Management, ProductMaggiori informazioniIniziative di inclusioneReportCollaborazioni con ColorStack e Rewriting the CodeIl nostro team di reclutamento universitario collabora con ColorStack e Rewriting the Code per aiutare pi\u00f9 donne e pi\u00f9 studenti neri e latinoamericani a fare carriera nel settore della tecnologia.Maggiori informazioniReportProgramma di mentoring Women in TechIn Databricks riconosciamo l'importanza di offrire opportunit\u00e0 di crescita e avanzamento professionale a comunit\u00e0 storicamente sottorappresentate.Maggiori informazioniReport2021 InHerSight AwardSiamo entusiasti di essere considerati una delle aziende di software che favorisce maggiormente il lavoro delle donne, dalle donne stesse. Visita il profilo di InHerSight per saperne di pi\u00f9.Maggiori informazioniCostruiamo il futuro dei dati insiemeLa nostra missione \u00e8 semplificare e democratizzare dati e AI, e non possiamo riuscirci senza il tuo contributo.Scopri le opportunit\u00e0ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/br\/solutions\/industries\/federal-government","text":"An\u00e1lise de dados e IA para org\u00e3os governamentais | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWAn\u00e1lise de dados e IA para org\u00e3os governamentaisLibere a inova\u00e7\u00e3o para oferecer melhores servi\u00e7os p\u00fablicos por meio de dados e machine learningDa estrat\u00e9gia federal de dados \u00e0 ordem executiva de IA, o governo federal dos EUA est\u00e1 apostando na moderniza\u00e7\u00e3o de seus recursos de an\u00e1lise e armazenamento de dados.A Databricks Lakehouse Platform permite que as ag\u00eancias federais liberem todo o potencial de seus dados para atingir seus objetivos de miss\u00e3o e atender melhor os cidad\u00e3os.Capacita\u00e7\u00e3o de org\u00e3os governamentais para alavancar dados\u00a0e IA para cumprir os objetivos da miss\u00e3oUsado pelas principais ag\u00eancias do setor p\u00fablico+ qualquer outro cliente compat\u00edvel com Apache Spark\u2122Saiba como os l\u00edderes do setor est\u00e3o usando o Databricks para melhorar a experi\u00eancia dos cidad\u00e3os em todos os servi\u00e7os p\u00fablicos\u00daltimos posts de blog, webinars e estudos de casoPor que Databricks para o org\u00e3os governamentais?Modernize sua an\u00e1lise de dados130 caracteres. Modernize sua pilha de tecnologia para melhorar a experi\u00eancia de pacientes e m\u00e9dicos com o pipeline DNAQSeq mais r\u00e1pido em escala.Alcance os resultados da miss\u00e3o de forma eficaz e eficiente130 caracteres. Modernize sua pilha de tecnologia para melhorar a experi\u00eancia de pacientes e m\u00e9dicos com o pipeline DNAQSeq mais r\u00e1pido em escala.Crie experi\u00eancias melhores para os cidad\u00e3os130 caracteres. Modernize sua pilha de tecnologia para melhorar a experi\u00eancia de pacientes e m\u00e9dicos com o pipeline DNAQSeq mais r\u00e1pido em escala.Saiba maisConformidade extensa para aprova\u00e7\u00e3o r\u00e1pida e f\u00e1cil para operar (ATO)A Databricks obteve ATOs em regi\u00f5es, redes e controles de conformidade que suportam seus objetivos de miss\u00e3oNuvensC2S\nSC2S\nGovCloud\nNuvem p\u00fablica\nRedesP\u00fablico\nNIPR\nSIPR\nJWICS\nControles de conformidadeFedRAMP\nFedRAMP-High\nFISMA\nIL5\nIL6\nICS-503\nComo a Databricks impulsiona a inova\u00e7\u00e3o para o governo federalCuidados de sa\u00fadeMelhore a presta\u00e7\u00e3o e a qualidade dos servi\u00e7os de sa\u00fade para os cidad\u00e3os com an\u00e1lises poderosas e uma vis\u00e3o de 360\u00b0 dos pacientes.\nPatient 360\u00a0\nOtimiza\u00e7\u00e3o da cadeia de suprimentos\u00a0\nGest\u00e3o de seguros\u00a0Gen\u00f4mica\nDescoberta e entrega de medicamentosDefesaAplique os benef\u00edcios da an\u00e1lise preditiva aos dados geoespaciais, de IoT e de vigil\u00e2ncia para melhorar as opera\u00e7\u00f5es e proteger o pa\u00eds.\u00a0\nLog\u00edstica\nManuten\u00e7\u00e3o preditiva\u00a0\nVigil\u00e2ncia e reconhecimento\u00a0\nAplica\u00e7\u00e3o da lei e disponibilidade operacionalSeguran\u00e7a nacionalDetecte e evite atividades criminosas e amea\u00e7as em n\u00edvel nacional com an\u00e1lises em tempo real e tomada de decis\u00e3o orientada por dados.\u00a0\nAlf\u00e2ndega e prote\u00e7\u00e3o de fronteiras\u00a0\nImigra\u00e7\u00e3o e cidadania\u00a0\nCombate ao terrorismo\u00a0\nGest\u00e3o do aux\u00edlio emergencial federalAutoridade p\u00fablica\/com\u00e9rcioDetecte irregularidades proativamente usando machine learning para reduzir riscos e evitar atividades fraudulentas.\u00a0\nFraude e cobran\u00e7a fiscais\u00a0\nGerenciamento de processos e opera\u00e7\u00f5es\u00a0\nGerenciamento de concess\u00f5es\u00a0\nCustomer 360EnergiaMelhore a gest\u00e3o de energia com insights de dados que garantem resili\u00eancia e sustentabilidade energ\u00e9tica.\u00a0\nSeguran\u00e7a da infraestrutura energ\u00e9tica\u00a0\nGest\u00e3o de energia mais inteligente\u00a0\nExplora\u00e7\u00e3o de energia\u00a0\nConfiabilidade da rede el\u00e9tricaComunidade de intelig\u00eanciaAproveite insights em tempo real para tomar decis\u00f5es informadas que podem afetar a seguran\u00e7a dos nossos cidad\u00e3os e do mundo.\u00a0\nDetec\u00e7\u00e3o de amea\u00e7as\u00a0\nNeutralizar ataques cibern\u00e9ticos\u00a0\nVigil\u00e2ncia e reconhecimento da intelig\u00eancia\u00a0\nAn\u00e1lise de m\u00eddia socialRecursosHist\u00f3ria de clienteImpulsionando a transforma\u00e7\u00e3o digital para colocar os pacientes em primeiro lugar no CMSPr\u00e1ticas recomendadas de governan\u00e7a de dados \u2014 Li\u00e7\u00f5es aprendidas com os centros de servi\u00e7os Medicare e MedicaidLi\u00e7\u00f5es aprendidas com a moderniza\u00e7\u00e3o da plataforma de an\u00e1lise de dados do USCISModernizar or\u00e7a a\u00e9rea com Big Data e IAWebinarsResposta r\u00e1pida \u00e0s opera\u00e7\u00f5es hospitalares usando dados e IA durante a pandemia de COVID-19An\u00e1lise geoespacial e IA no setor p\u00fablicoArquitetura moderna de an\u00e1lise de dados para o governoMelhorar a detec\u00e7\u00e3o de amea\u00e7as com Big Data e IANot\u00edciasAzure Databricks obt\u00e9m autoriza\u00e7\u00e3o elevada FedRAMP no Microsoft Azure Government (MAG)Seguran\u00e7a de n\u00edvel governamental na nuvem AWSAn\u00e1lises unificadas para clientes do governoCapacitar a comunidade de intelig\u00eancia dos EUA com an\u00e1lise de miss\u00e3o cr\u00edtica e IADiscuss\u00f5es do SummitAutomatizar a ingest\u00e3o e an\u00e1lise de dados do System-Wide Information Management (SWIM) da Federal Aviation Administration (FAA)An\u00e1lise geoespacial em escala: An\u00e1lise de padr\u00f5es de movimento humano durante uma pandemiaTudo pronto para come\u00e7ar?Adorar\u00edamos saber sobre seus objetivos de neg\u00f3cios. Nossa equipe de servi\u00e7os far\u00e1 todo o poss\u00edvel para ajudar sua empresa a ter sucesso.\u00a0Experimente gratuitamenteEntre em contatoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/legal\/privacynotice#dbadditionalinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amrinder-singh-oberai\/#","text":"Amrinder Singh Oberai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmrinder Singh OberaiEMR Migrations Lead at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/krishti-bikal","text":"Krishti Bikal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKrishti BikalSenior Executive - Director BI & Analytics at EmeraldBack to speakersKrishti is a Senior technical Executive at EmeraldX, where he is currently leading various Data Analytics projects. One of them is implementation of ThoughtSpot Everywhere for Emerald's Customer Hub. He has over 15 years of industry experience in Data Engineering and Analytics.\nHe holds B. Tech in Mechanical Engineering from NIT Patna, India and Masters in MIS from University of Illinois, USA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/11\/11\/10-powerful-features-to-simplify-semi-structured-data-management-in-the-databricks-lakehouse.html","text":"10 Powerful Features to Simplify Semi-structured Data Management in the Databricks Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic Sector10 Powerful Features to Simplify Semi-structured Data Management in the Databricks LakehouseIngest and query complex JSON data like a pro with Delta Lake and SQLby John O'Dwyer and Emma LiuNovember 11, 2021 in Engineering BlogShare this postHassle Free Data Ingestion\nDiscover how Databricks simplifies semi-structured data ingestion into Delta Lake with detailed use cases, a demo, and live Q&A.WATCH NOW\u00a0Ingesting and querying JSON with semi-structured data can be tedious and time-consuming, but Auto Loader and Delta Lake make it easy. JSON data is very flexible, which makes it powerful, but also difficult to ingest and query. The biggest challenges include:It\u2019s a tedious and fragile process to define a schema of the JSON file being ingested.The schema can change over time, and you need to be able to handle those changes automatically.Software does not always pick the correct schema for your data, and you may need to hint at the correct format. For example, the number 32 could be interpreted as either an integer or a long.Often data engineers have no control of upstream data sources generating the semi-structured data. For example, the column name may be upper or lower case but denotes the same column, or the data type sometimes changes, and you may not want to completely rewrite the already ingested data in Delta Lake.You may not want to do the upfront work of flattening out JSON documents and extracting every single column, and doing so may make the data very hard to use.Querying semi-structured data in SQL is hard. You need to be able to query this data in a manner that is easy to understand.In this blog and the accompanying notebook, we will show what built-in features make working with JSON simple at scale in the Databricks Lakehouse. Below is an incremental ETL architecture. The left-hand side represents continuous and scheduled ingest, and we will discuss how to do both types of ingest with Auto Loader. After the JSON file is ingested into a bronze Delta Lake table, we will discuss the features that make it easy to query complex and semi-structured data types that are common in JSON data.In the accompanying notebook, we used sales order data to demonstrate how to easily ingest JSON. The nested JSON sales order datasets get complex very quickly.\u00a0Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.Hassle-free JSON ingestion with Auto LoaderAuto Loader provides Python and Scala interfaces to ingest new data from a folder location in object storage (S3, ADLS, GCS) into a Delta Lake table. Auto Loader makes ingestion easy and hassle-free by enabling data ingestion into Delta Lake tables directly from object storage in either a continuous or scheduled way.Before discussing the general features of Auto Loader, let\u2019s dig into the features that make ingesting the JSON extremely easy. Below is an example of how to ingest very complex JSON data.\n df = spark.readStream.format(\"cloudFiles\") \\\n  .option(\"cloudFiles.schemaLocation\", schemaLocation) \\\n  .option(\"cloudFiles.format\", \"json\") \\\n  .option(\"cloudFiles.inferColumnTypes\", \"true\") \\\n  .option(\"cloudFiles.schemaEvolutionMode\", \"addNewColumns\") \\\n  .option(\"cloudFiles.schemaHints\", schemaHints) \\\n  .load(landingZoneLocation)\nFlexibility and ease of defining the schema: In the code above, we use two features of Auto Loader to easily define the schema while giving guardrails for problematic data. The two useful features are cloudFiles.inferColumnTypes and cloudFiles.schemaHints. Let\u2019s take a closer look at the definitions:Feature 1 - Use cloudFiles.inferColumnTypes for automatically inferring data types during the schema inference process: The default value for cloudFiles.inferColumnTypes is false because, in most cases, it is better to have the top-level columns be strings for schema evolution robustness and avoid issues such as numeric type mismatches(integers, longs, floats) during the schema evolution process.Feature 2 - Use cloudFiles.schemaHints for specifying the desired data type to complement schema inference: Schema hints are used only if you do not provide a schema to Auto Loader. You can use schema hints whether cloudFiles.inferColumnTypes is enabled or disabled. More details can be found here.In this use case (notebook), we actually set cloudFiles.inferColumnTypes to true since we want the columns and the complex data types to be inferred, instead of Auto Loader\u2019s default inferred data type of string. Inferring most columns will give the fidelity of this complex JSON and provide flexibility for querying later. In addition, while inferring the column types is very convenient, we also know there are problematic columns ingested. This is where cloudFiles.schemaHints comes into play, working together with cloudFiles.inferColumnTypes. The combination of the two options allows for inferring most columns\u2019 complex data types while specifying the desired data type (string in this example) for only two of the columns.Let\u2019s take a closer look at the two problematic columns. From the semi-structured JSON data we use in the notebook, we have identified two columns of problematic data: \u201cordered_products.element.promotion_info\u201d and \u201cclicked_items\u201d. Hence, we hint that they should come in as strings (see data snippets for one of the columns above: \u201cordered_products.element.promotion_info\u201d). For these columns, we can easily query the semi-structured JSON in SQL, which we will discuss later. You can see that one of the hints is on a nested column inside an array, which makes this feature really functional on complex schemas!Feature 3 - Use Schema Evolution to handle schema changes over time make the ingest and data more resilient: Like schema inference, schema evolution is simple to implement with Auto Loader. All you have to do is set cloudFiles.schemaLocation, which saves the schema to that location in the object storage, and then the schema evolution can be accommodated over time. To clarify, schema evolution is when the schema of the ingested data changes and the schema of the Delta Lake table changes accordingly.For example, in the accompanying notebook, an extra column named fulfillment_days is added to the data ingested by Auto Loader. This column is identified by Auto Loader and applied automatically to the Delta Lake table. Per the documentation, you can change the schema evolution mode to your liking. Here is a quick overview of the supported modes for Auto Loader\u2019s option cloudFiles.schemaEvolutionMode:addNewColumns: The default mode when a schema is not provided to Auto Loader. New columns are added to the schema. Existing columns do not evolve data types.failOnNewColumns: If Auto Loader detects a new column, the stream will fail. It will not restart unless the provided schema is updated or the offending data file is removed.rescue: The stream runs with the very first inferred or provided schema. Any data type changes or new columns are automatically saved in the rescued data column as _rescued_data in your stream\u2019s schema. In this mode, your stream will not fail due to schema changes.none: The default mode when a schema is provided to Auto Loader. It does not evolve the schema. New columns are ignored, and data is not rescued unless the rescued data column is provided separately as an option.The example above (also in the notebook) does not include a schema, hence we use the default option .option(\"cloudFiles.schemaEvolutionMode\", \"addNewColumns\") on readStream to accommodate schema evolution.Feature 4 - Use rescued data column to capture bad data in an extra column, so nothing is lost: The rescued data column is where all unparsed data is kept, which ensures that you never lose data during ETL. If data doesn\u2019t adhere to the current schema and can\u2019t go into its required column, the data won\u2019t be lost with the rescued data column. In this use case (notebook), we did not use this option. To turn on this option, you can specify the following: .option(\"cloudFiles.schemaEvolutionMode\", \"rescue\"). Please see more information here.Now that we have explored the Auto Loader features that make it great for JSON data and tackled challenges mentioned at the beginning, let\u2019s look at some of the features that make it hassle-free for all ingest:\ndf.writeStream \\\n  .format(\"delta\") \\\n  .trigger(once=True) \\\n  .option(\"mergeSchema\", \"true\") \\\n  .option(\"checkpointLocation\", bronzeCheckPointLocation) \\\n  .start(bronzeTableLocation)\nFeature 5 - Use Trigger Once and Trigger AvailableNow for continuous vs. scheduled ingest: While Auto Loader is an Apache Spark\u2122 Structured Streaming source, it does not have to run continuously. You can use the trigger once option to turn it into a scheduled job that turns itself off when all files have been ingested. This comes in handy when you don\u2019t have the need for continuously running ingest. Yet, it also gives you the ability to drop the cadence of the schedule over time and then eventually go to continuously running ingest without changing the code. In DBR 10.1 and later, we have introduced Trigger.AvailableNow, which provides the same data processing semantics as trigger once, but can also perform rate limiting to ensure that your data processing can scale to very large amounts of data.Feature 6 - Use Checkpoints to handle state: State is the information needed to start up where the ingestion process left off if the process is stopped. For example, with Auto Loader, the state would include the set of files already ingested. Checkpoints save the state if the ETL is stopped at any point, whether on purpose or due to failure. By leveraging checkpoints, Auto Loader can run continuously and also be a part of a periodic or scheduled job. In the example above, the checkpoint is saved in the option checkpointLocation . If the Auto Loader is terminated and then restarted, it will use the checkpoint to return to its latest state and will not reprocess files that have already been processed.Querying semi-structured and complex structured dataNow that we have our JSON data in a Delta Lake table, let's explore the powerful ways you can query semi-structured and complex structured data. Let\u2019s tackle the last challenge of querying semi-structured data.Until this point, we have used Auto Loader to write a Delta Table to a particular location. We can access this table by location in SQL, but for readability, we point an external table to the location using the following SQL code.\nCREATE TABLE autoloaderBronzeTable\nLOCATION '${c.bronzeTablePath}';\nEasily access top level and nested data in semi-structured JSON columns using syntax for casting values:\nSELECT fulfillment_days, fulfillment_days:picking,\n  fulfillment_days:packing::double, fulfillment_days:shipping.days\nFROM autoloaderBronzeTable\nWHERE fulfillment_days IS NOT NULL\nWhen ingesting data, you may need to keep it in a JSON string, and some data may not be in the correct data type. In those cases, syntax in the above example makes querying parts of the semi-structured data simple and easy to read. To double click on this example, let\u2019s look at data in the column filfillment_days, which is a JSON string column:Feature 7 - Use single colon (:) to extract the top-level of a JSON string column: For example, filfillment_days:picking returns the value 0.32 for the first row above.Feature 8 - Use Dot Notation to access nested fields: For example, fulfillment_days:shipping.days returns the value 3.7 for the first row above.Feature 9 -  Use double colon (::) to specify the desired data type to return for casting value:\nFor example, fulfillment_days:packing::double returns the double data type value 1.99 for the string value of packing for the first row above.Extracting values from semi-structured arrays even when the data is ill-formed: \nSELECT *, reduce(all_click_count_array, 0, (acc, value) -> acc + value) as\nsum\nFROM (\n SELECT order_number, clicked_items:[*][1] as all_click_counts,\n   from_json(clicked_items:[*][1], 'ARRAY<string>')::ARRAY<int> as all_click_count_array\n FROM autoloaderBronzeTable\n)\n<\/int><\/string>Unfortunately, not all data comes to us in a usable structure. For example, the column clicked_items is a confusing array of arrays in which the count comes in as a string. Below is a snippet of the data in the column clicked_items:Feature 10 - Extracting Values From Arrays: Use an asterisk (*) to extract all values in a JSON array string. For the specific array indices, use a 0-based value. For example, SQL clicked_items:[*][1]returns the string value of [\"54\",\"85\"].Casting complex array values: After extracting the correct values for the array of arrays, we can use from_json and ::ARRAY to cast the array into a format that can be summed using reduce. In the end, the first row returns the summed value of 139 (54 + 89). It\u2019s pretty amazing how easily we can sum values from ill-formed JSON in SQL!Aggregations in SQL with complex structured data: Accessing complex structured data, as well as moving between structured and semi-structured data, has been available for quite some time in Databricks.\nSELECT order_date, ordered_products_explode.name  as product_name,\n SUM(ordered_products_explode.qty) as quantity\nFROM (\n SELECT DATE(from_unixtime(order_datetime)) as order_date,\n   EXPLODE(ordered_products) as ordered_products_explode\n FROM autoloaderBronzeTable\n WHERE DATE(from_unixtime(order_datetime)) is not null\n )\nGROUP BY order_date, ordered_products_explode.name\nORDER BY order_date, ordered_products_explode.name\nIn the SQL query above, we explored how to access and aggregate data from the complex structured data in the column ordered_products. To show the data complexity, below is an example of one row of the column ordered_products, and our goal here is to find the quantity of each product sold on a daily basis. As you can see, both the product and quantity are nested in an array.Accessing array elements as rows: Use explode on the ordered_products column so that each element is its own row, as seen below.Accessing nested fields: Use the dot notation to access nested fields in the same manner as semi-structured JSON. For example, ordered_products_explode.qty returns the value 1 for the first row above. We can then group and sum the quantities by date and the product name.Additional Resources: we have covered many topics on querying structured and semi-structured JSON data, but you can find more information here:Documentation on querying semi-structured JSON in SQL.A blog on working complex structured and semi-structured data. The specific use case is working with complex data while streaming.ConclusionAt Databricks, we strive to make the impossible possible and the hard easy. Auto Loader makes ingesting complex JSON use cases at scale easy and possible. The SQL syntax for semi-structured and complex data makes manipulating data easy. Let\u2019s recap the 10 features:Feature 1 - Infer Column Types for inferring data types during schema inferenceFeature 2 - Schema Hints for specifying desired data types to complement schema inferenceFeature 3 - Schema Evolution for handling schema changes in ingested data over timeFeature 4 - Rescued Data Column for capturing bad data in an extra column, so nothing is lostFeature 5 - Trigger Once and Trigger AvailableNow for continuous and scheduled ingest for large amounts of dataFeature 6 - Checkpoints for handling the state of the ingestion processFeature 7 - Extract JSON Columns for accessing top-level columns in JSON fileFeature 8 - Dot Notation for accessing nested fieldsFeature 9 - Casting Values for converting values to specified data typesFeature 10 - Extracting Values From Arrays for accessing arrays and structs within arraysNow that you know how to ingest and query complex JSON with Auto Loader and SQL, we can\u2019t wait to see what you build with them.Try the notebook Try Databricks for freeGet StartedRelated posts10 Powerful Features to Simplify Semi-structured Data Management in the Databricks LakehouseNovember 11, 2021 by John O'Dwyer and Emma Liu in Engineering Blog\nHassle Free Data Ingestion Discover how Databricks simplifies semi-structured data ingestion into Delta Lake with detailed use cases, a demo, and live Q&A...\nSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/albert-hu","text":"Albert Hu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlbert HuSenior Analytics Engineer at Rec RoomBack to speakersAlbert is a Senior Analytics Engineer at Rec Room, a social UGC app you can play on multiple platforms. In this role, he is responsible for building out the infrastructure to enable analysis, experimentation, and product features. Prior to Rec Room, Albert held various roles in both startups and Fortune 500 companies including Head of Analytics at Ribbon and Data Product roles at Walmart. He holds a B.A., Economics and Mathematics from Northwestern University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners","text":"\ud30c\ud2b8\ub108 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c 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\uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks \ud30c\ud2b8\ub108Databricks\ub294 \uc138\uacc4 \uac01\uc9c0\uc5d0 1200+\uc5ec \uacf3\uc758 \ud30c\ud2b8\ub108 \uc5c5\uccb4\ub97c \ubcf4\uc720\ud558\uace0 \uc788\uc73c\uba70, Databricks\uc640 \ud568\uaed8 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uc774\uc6a9\ud558\uc5ec\n\uace0\uac1d\uc5d0\uac8c \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uc194\ub8e8\uc158\uacfc \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.\n\uc774\ub7ec\ud55c \ud30c\ud2b8\ub108 \uc5c5\uccb4\uc5d0\uc11c\ub294 \uace0\uac1d\uc774 Databricks\ub97c \ud65c\uc6a9\ud574 \uace0\uac1d\uc774 \ubcf4\uc720\ud55c \ub370\uc774\ud130\uc640 AI \uc6cc\ud06c\ub85c\ub4dc\ub97c \ubaa8\ub450 \ud1b5\ud569\ud558\uc5ec \uc880 \ub354 \uc758\ubbf8 \uc788\ub294 \uc778\uc0ac\uc774\ud2b8\ub97c \ud655\ubcf4\ud558\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4.\u201cDatabricks\ub294 \ub370\uc774\ud130 \ubcfc\ub968\uc744 \uc81c\uacf5\ud558\uace0 Tableau\ub294 \ube60\ub978 \uc2dc\uac01\ud654\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774\ub4e4 \uc194\ub8e8\uc158\uc774 \uc6b0\ub9ac \ud50c\ub7ab\ud3fc\uc758 \ud575\uc2ec\uc5d0\uc11c \ub098\ub780\ud788 \uc791\ub3d9\ud558\uba70 \uc6b0\ub9ac \uace0\uac1d\uc774 \ucca8\ub2e8 \uc790\uc728 \uc8fc\ud589 \ucc28\ub7c9 \uae30\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 \ub370 \ud544\uc694\ud55c \uc131\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\"\u2014 Patrick McAuliffe, Lead Engineer, Incite\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108Databricks\ub294 AWS, Microsoft Azure, Google Cloud \ubc0f Alibaba Cloud\uc5d0\uc11c \uc218\ud589\ub418\uba70 \uac01 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4 \uc81c\uacf5\uc790\uc758 \uc778\ud504\ub77c, \ub370\uc774\ud130 \u0000\u0000\ubc0f AI \uc11c\ube44\uc2a4\uc5d0 \uae4a\uc774 \uc788\uac8c \ud1b5\ud569\ub418\uc5b4 \uc788\uc74c\uae30\uc220 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108\ub294 \uc790\uc0ac \uc194\ub8e8\uc158\uc744 Databricks \uc194\ub8e8\uc158\uacfc \ud1b5\ud569\ud558\uc5ec ETL, \ub370\uc774\ud130 \uc218\uc9d1, BI, ML \ubc0f \uac70\ubc84\ub10c\uc2a4 \ub4f1\uc5d0 \ubcf4\uc644\uc801 \uae30\ub2a5 \uc81c\uacf5\ucee8\uc124\ud305 \ud30c\ud2b8\ub108\ucee8\uc124\ud305 \ud30c\ud2b8\ub108\ub294 Databricks\uc640 \ud568\uaed8\n\uace0\uac1d\uc774 \ub370\uc774\ud130, \ubd84\uc11d\uacfc AI \uc774\ub2c8\uc154\ud2f0\ube0c \uc804\ub7b5 \uc218\u0000\u0000\ub9bd, \uad6c\ud604 \ubc0f \ud655\uc7a5\uc744 \ucd94\uc9c4\ud558\ub3c4\ub85d \ub3d5\uae30\n\uc720\ub9ac\ud55c \ub3c5\ubcf4\uc801\uc778 \uc704\uce58\ub97c \uc810\ud55c \uc804\ubb38\uac00\ud30c\ud2b8\ub108 \ub418\uae30Databricks \ud30c\ud2b8\ub108\ub294 \ub2f9\uc0ac\uc640 \ud611\ub825\ud558\uc5ec \uace0\uac1d\uc744 \uc704\ud574 \ud601\uc2e0\uc801\uc778 \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud558\uc5ec \uc81c\uacf5\ud569\ub2c8\ub2e4. Databricks \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\uc5d0 \ucc38\uc5ec\ud558\uc5ec \uac01\uc885 \uc804\uc6a9 \ud234, \uad50\uc721, \uc194\ub8e8\uc158\uc988 \uc561\uc140\ub7ec\ub808\uc774\ud130 \ubc0f GTM \ud504\ub85c\uadf8\ub7a8\uc744 \ud65c\uc6a9\ud558\uc138\uc694.\uc790\uc138\ud788\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\u0000\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-bell\/#","text":"Scott Bell - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott BellPrincipal Consultant and Databricks SME at RapidDataBack to speakersScott is currently a Principal Consultant & Databricks SME with RapidData focusing on the Azure Data Platforms, Data Architecture, Integration Engineering and Analytics. Previously, he was a senior consultant and UK&I Databricks SME at Avanade a top global partner with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/neural-network","text":"What is a Neural Network?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNeural NetworkAll>Neural NetworkTry Databricks for freeGet StartedWhat is a Neural Network?A neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an output function. Neural networks are made of input and output layers\/dimensions, and in most cases, they also have a hidden layer consisting of units that transform the input into something that the output layer can use.Types of Neural Network Architectures:Neural networks, also known as Artificial Neural network use different deep learning algorithms. Here are some the most common types of neural networks:Feed-Forward Neural Network:This is the most basic and common type of architecture; here the information travels in only one direction from input to output. It consists of an input layer; an output layer and in between, we have some hidden layers. If the hidden layer is more than one then that network is called a deep neural network.Recurrent Neural Network (RNNs)This is a more complex type of network; this artificial neural network is commonly used in speech recognition and natural language processing (NLP). RNNs perform the same task for every element of a sequence, with the output being depended on the previous computations.Convolutional Neural Network (ConvNets or CNNs)A CNN has several layers through which data is filtered into categories. CNNs have proven to be very effective in areas such as image recognition, text language processing, and classification. A convolutional neural network is made of an input layer, an output layer and a hidden layer that includes multiple convolutional layers, pooling layers, fully connected layers, and normalization layers.There are at least a dozen other kinds of neural network such as symmetrically connected network: Boltzmann machine networks, Hopfield networks,and many other types. Choosing the right network depends on the data you have to train it with, as well as on the specific application you have in mind.Additional ResourcesA Convolutional Neural Network Implementation For Car ClassificationIntroduction to Neural NetworksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stan-lin","text":"Stan Lin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStan LinSenior Software Engineer at Microsoft CorporationBack to speakersTech lead at Microsoft, MSAI. Experience in large-scale machine learning, graph intelligence, performant web services and compliance. Building the large-scale ML platform powering Microsoft 365 knowledge mining, search and recommendation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/05\/26\/introducing-databricks-unity-catalog-fine-grained-governance-for-data-and-ai-on-the-lakehouse.html","text":"Introducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the Lakehouseby Matei Zaharia, Todd Greenstein and Cyrielle SimeoneMay 26, 2021 in AnnouncementsShare this postUpdate:\u00a0Unity Catalog is now generally available on AWS, Azure, and GCP.Data lake systems such as S3, ADLS, and GCS store the majority of data in today\u2019s enterprises thanks to their scalability, low cost, and open interfaces. Over time, these systems have also become an attractive place to process data thanks to lakehouse technologies such as Delta Lake that enable ACID transactions and fast queries. However, one area where data lakes have remained harder to manage than traditional databases is governance; so far, these systems have only offered tools to manage permissions at the file level (e.g. S3 and ADLS ACLs), using cloud-specific concepts like IAM roles that are unfamiliar to most data professionals.That\u2019s why we\u2019re thrilled to announce our Unity Catalog, which brings fine-grained governance and security to lakehouse data using a familiar, open interface. Unity Catalog lets organizations manage fine-grained data permissions using standard ANSI SQL or a simple UI, enabling them to safely open their lakehouse for broad internal consumption. It works uniformly across clouds and data types. Finally, it goes beyond managing tables to govern other types of data assets, such as ML models and files. Thus, enterprises get a simple way to govern all their data and AI assets:What\u2019s hard with data lake governance tools today?Although all cloud storage systems (e.g. S3, ADLS and GCS) offer security controls today, these tools are file-oriented and cloud-specific, both of which cause problems as organizations scale up. We\u2019ve often seen customers run into four problems:Lack of fine-grained (row, column and view level) security: Cloud data lakes can generally only set permissions at the file or directory level, making it hard to share just a subset of a table with particular users. This makes it tedious to onboard enterprise users who should not have access to the whole table.Governance tied to physical data layout: Because governance controls are at the file level, data teams must carefully structure their data layout to support the desired policies. For example, a team might partition data into different directories by country and give access to each directory to different groups. But what should the team do when governance rules change? If different states inside one country adopt different data regulations, the organization may need to restructure all its data.Nonstandard, cloud-specific interfaces: Cloud governance APIs such as IAM are unfamiliar to data professionals (e.g., database administrators), and different across clouds. Today, enterprises increasingly have to store data in multiple clouds, (e.g., to satisfy privacy regulations), so they need to be able to manage data across clouds.No support for other asset types: Data lake governance APIs work for files in the lake, but modern enterprise workflows produce a wide range of other types of data assets. For example, SQL workflows often revolve around views, data science workloads produce ML models, and many workloads connect to data sources other than the lake (e.g., databases). In the modern compliance landscape, all of these assets need to be governed the same way if they contain sensitive data. Thus, data teams have to reimplement the same security policies in many different systems.Unity Catalog's approachUnity Catalog solves these problems by implementing a fine-grained approach to data governance based on open standards that works across data asset types and clouds. It is designed around four key principles:Fine-grained permissions: Unity Catalog can enforce permissions for data at the row, column or view level instead of the file level, so that you can always share just part of your data with a new user without copying it.An open, standard interface: Unity Catalog\u2019s permission model is based on ANSI SQL, making it instantly familiar to any database professional. We\u2019ve also built a UI to make governance easy for data stewards, and we\u2019ve extended the SQL model to support attribute-based access control, allowing you to tag many objects with the same attribute (e.g., \u201cPII data\u201d) and apply one policy to all of them. Finally, the same SQL based interface can be used to manage ML models and external data sources.Central control: Unity Catalog can work across multiple Databricks workspaces, geographic regions and clouds, allowing you to manage all enterprise data centrally. This central position also enables it to track lineage and audit all accesses.Secure access from any platform: Although we love the Databricks platform, we know that many customers will also access the data from other platforms and that they\u2019d like their governance rules to work across them. Unity Catalog enforces security permissions from any client that connects through JDBC\/ODBC or through Delta Sharing, the open protocol we\u2019ve launched to exchange large datasets between a wide range of platforms.Let\u2019s look at how the Unity Catalog can be used to implement common governance tasks.Easily manage permissions using ANSI SQLUnity Catalog brings fine-grained centralized governance to all data assets across clouds through the open standard ANSI SQL Data Control Language (DCL). This means administrators can easily grant permission to arbitrary user-specific subsets of the data using familiar SQL -- no need to learn an arcane, cloud-specific interface. We\u2019ve also added a powerful tagging feature that lets you control access to multiple data items at once based on attributes to further simplify governance at scale.Below are a few examples of how you can use SQL grant statements with the Unity Catalog to add permissions to existing data stored on your data lake.First, you can create tables in the catalog either from scratch or by pointing to existing data in a cloud storage system, such as S3, accessed with cloud-specific credentials:\nCREATE EXTERNAL TABLE iot_events LOCATION s3:\/...\n  WITH CREDENTIAL iot_iam_roleYou can now simply use SQL standard GRANT statements to set permissions, as in any database. Below is an example of how to grant permissions to iot_events to an entire group such as engineers, or to just the date and country columns to the marketing group:\nGRANT SELECT ON iot_events TO engineers\nGRANT SELECT(date, country) ON iot_events TO marketingThe Unity Catalog also understands SQL views. This allows you to create SQL views to aggregate data in a complex way. Here is how you can use View-Based Access Control to grant access to only an aggregate version of the data for business_analysts:\n\nCREATE VIEW aggregate_data AS\n  SELECT date, country, COUNT(*) AS num_events FROM iot_events\n  GROUP BY date, country\n\nGRANT SELECT ON aggregate_data TO business_analystsIn addition, the Unity Catalog allows you to set policies across many items at once using attributes (Attribute-Based Access Control), a powerful way to simplify governance at scale. For example, you can tag multiple columns as PII and manage access to all columns tagged as PII in a single rule:\nALTER TABLE iot_events ADD ATTRIBUTE pii ON email\nALTER TABLE users ADD ATTRIBUTE pii ON phone\n\nGRANT SELECT ON DATABASE iot_data\n  HAVING ATTRIBUTE NOT IN (pii)\n  TO product_managersFinally, the same attribute system lets you easily govern MLflow models and other objects in a consistent way with your raw data:\nGRANT EXECUTE ON MODELS HAVING ATTRIBUTE (eu_data)\n  TO eu_product_managersDiscover and govern data assets in the UIUnity Catalog's UI makes it easy to discover, describe, audit and govern data assets in one place. Data stewards can set or review all permissions visually, and the catalog captures audit and lineage information that shows you how each data asset was produced and accessed. The UI is designed for collaboration so that data users can document each asset and see who uses it.and secure data access to meet compliance and privacy needs, directly on the lakehouse.Share data across organizations with Delta SharingEvery organization needs to share data with customers, partners and suppliers to collaborate. Unity Catalog implements the open source Delta Sharing standard to let you securely share data across organizations, regardless of which computing platform or cloud they run on (any Delta Sharing client can connect to the data).Open interfaces for easy accessUnity Catalog works with your existing catalogs, data, storage and computing systems so you can leverage your existing investments and build a future-proof governance model. It can mount existing data in Apache Hive Metastores or cloud storage systems such as S3, ADLS and GCS without moving it. It also connects with governance platforms like Privacera and Immuta to let you define custom workflows for managing access to data. Finally, we designed Unity Catalog so that you can also access it from computing platforms other than Databricks: ODBC\/JDBC interfaces and high-throughput access via Delta Sharing allow you to securely query your data any computing system.\u00a0Try Databricks for freeGet StartedRelated postsIntroducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the LakehouseMay 26, 2021 by Matei Zaharia, Todd Greenstein and Cyrielle Simeone in Announcements\nUpdate: Unity Catalog is now generally available on AWS, Azure, and GCP. Data lake systems such as S3, ADLS, and GCS store the...\nSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/events-policy\/","text":"Events Policy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEvents PolicyPaymentsIn-person conference tickets and both in-person and virtual training will be assessed a fee and must be purchased with a credit card. Payment will be accepted in US dollars only. All registration fees must be paid in full prior to attending the conference. You will receive a payment confirmation and receipt via email once your credit card is processed and payment is complete. In order to receive the prices listed online you must complete and submit the online registration form by midnight (PST) on the deadline date. 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All requests for substitutions must be received no later than 5:00 p.m. (Pacific) on June 23, 2023. \u00a0 Onsite substitutions will incur a US $50 processing fee.\n\u00a0\nCancellations\nThe Databricks Registration Team must receive all cancellation requests in writing via email at [email\u00a0protected] by June 21, 2023.\n\u00a0\nPayment Information\nPayment accepted in US dollars only.\n\u00a0\nRefunds\nAll paid items (such as training or in person registration packages) will be refunded to the original form of payment.\n\u00a0\nWe will issue a full refund, less a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PT.\u00a0 Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PT, will be issued a 50% refund, less a 10% cancellation fee.\u00a0 No refunds will be offered for paid items after May 26, 2023.\n\u00a0\nRefunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record.\u00a0 If you have not received a refund by July 1, 2023, please contact the Databricks Registration Team at [email\u00a0protected]\n\u00a0\nPlease note: Any requests to change the payment method used for a completed registration will incur a $50 change fee. If you need to make a change, please contact the Databricks Registration Team at: [email\u00a0protected]\u00a0 Databricks reserves the right to deny registration to any individual or entity for any reason, in Databricks\u2019s sole discretion, including for past or present failure to meet Databricks\u2019s standards of conduct (including, but not limited to, engaging in violent, illegal, threatening, or discriminatory conduct).\u00a0 \u00a0 Payment terms are Net 30.\u00a0 Payment must be received in full to print attendee badge on-site.\nRegistration ConfirmationRegistration will be confirmed by email. You\u2019ll receive a message as soon as payment has been received and your registration has been processed.\nSpeakers & SessionsThe speakers listed on this website are leading professionals in their respective fields. Should a speaker be unable to attend the conference, all efforts will be made to replace him or her with one of comparable experience and qualifications. We are constantly working on improving the quality of our conference products. If the opportunity arises we may, at our discretion, add conference sessions and workshops to the posted line-up to enhance the schedule.\nPhoto Release & Privacy InformationFrom time to time Databricks may choose to photograph and record certain portions of the conference and may capture conference participants. Databricks may choose such photographs and recordings in our promotional materials. By virtue of your attendance at Data + AI Summit you consent to, Databricks\u2019 use of your likeness in such materials and you hereby waive \u201cmoral rights\u201d in such photos, recordings, or other digital content. You agree that any personal data you provide us will be handled in accordance with this Event Policy and our Privacy Policy.\n\u00a0\nYou may not record any sessions or sessions at Data + AI Summit without prior approval from Databricks.\n\nTerms of Use. Privacy Policy. 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/madalina-tanasie","text":"Madalina Tanasie - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMadalina TanasieChief Technology Officer at CollibraBack to speakersAs Collibra\u2019s Chief Technology Officer, Madalina oversees Software Engineering, Architecture, Production Engineering, Test Engineering and Security. With over 18 years of software engineering leadership experience, her expertise includes service oriented architecture, cloud-native distributed systems and product operations with a focus on engineering practices, scale and operational excellence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/learn","text":"\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 PT\n\u3055\u3088\u3046\u306a\u3089\u3001\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u3002\u3053\u3093\u306b\u3061\u306f\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3002\n\u30c7\u30fc\u30bf\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u304c\u6700\u65b0\u306e\u30c7\u30fc\u30bf\u30b9\u30bf\u30c3\u30af\u306b\u3069\u306e\u3088\u3046\u306b\u9069\u5408\u3059\u308b\u304b\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u51fa\u5e2d\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\u4eca\u3059\u3050\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c5\u67089\u65e5 |\u5348\u524d8\u6642(\u592a\u5e73\u6d0b\u6a19\u6e96\u6642)\n\u00a0\n\u88fd\u9020\u696d\u306e\u305f\u3081\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u767a\u898b\u3059\u308b\n\u30b3\u30fc\u30cb\u30f3\u30b0\u304c\u3001\u624b\u4f5c\u696d\u306b\u3088\u308b\u691c\u67fb\u3092\u6700\u5c0f\u9650\u306b\u6291\u3048\u3001\u8f38\u9001\u30b3\u30b9\u30c8\u3092\u524a\u6e1b\u3057\u3001\u9867\u5ba2\u6e80\u8db3\u5ea6\u3092\u9ad8\u3081\u308b\u91cd\u8981\u306a\u610f\u601d\u6c7a\u5b9a\u3092\u3069\u306e\u3088\u3046\u306b\u884c\u3063\u3066\u3044\u308b\u304b\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u4eca\u3059\u3050\u767b\u9332\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeacons2023\u5e746\u670826\u65e5\uff5e29\u65e5\n\n\u76f4\u63a5\u53c2\u52a0\u3059\u308b\u304b\u3001\u57fa\u8abf\u8b1b\u6f14\u306e\u30e9\u30a4\u30d6\u30b9\u30c8\u30ea\u30fc\u30e0\u306b\u53c2\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3054\u767b\u9332\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks 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\u30b5\u30df\u30c3\u30c8\u696d\u754c\u3001\u7814\u7a76\u6a5f\u95a2\u3001\u5b66\u8853\u754c\u306e\u30a8\u30ad\u30b9\u30d1\u30fc\u30c8\u306b\u3088\u308b\u57fa\u8abf\u8b1b\u6f14\u3001\u88fd\u54c1\u767a\u8868\u306a\u3069\u3001200 \u3092\u8d85\u3048\u308b\u6280\u8853\u30bb\u30c3\u30b7\u30e7\u30f3\u3092\u8996\u8074\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u30b0\u30ed\u30fc\u30d0\u30eb\u30a4\u30d9\u30f3\u30c8\u30b0\u30ed\u30fc\u30d0\u30eb\u30fb\u5730\u57df\u5225\u30ab\u30f3\u30d5\u30a1\u30ec\u30f3\u30b9\u3001\u88fd\u54c1\u306e\u30c7\u30e2\u3001Web \u30bb\u30df\u30ca\u30fc\u3001\u30d1\u30fc\u30c8\u30ca\u30fc\u4e3b\u50ac\u306e\u30a4\u30d9\u30f3\u30c8\u3001\u30df\u30fc\u30c8\u30a2\u30c3\u30d7\u306a\u3069\u3001\u5404\u7a2e\u30a4\u30d9\u30f3\u30c8\u3092\u3054\u7528\u610f\u3057\u3066\u3044\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308bDATA+AI \u30aa\u30f3\u30e9\u30a4\u30f3\u30df\u30fc\u30c8\u30a2\u30c3\u30d7\u30aa\u30f3\u30e9\u30a4\u30f3\u958b\u50ac\u306e Databricks Meetup \u3067\u306f\u3001\u4e16\u754c\u4e2d\u306e Databricks \u30e6\u30fc\u30b6\u30fc\u3068\u306e\u4ea4\u6d41\u3092\u901a\u3058\u3066\u6700\u65b0\u60c5\u5831\u3092\u5165\u624b\u3067\u304d\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308bBeacons\u30c7\u30fc\u30bf\u3068 AI \u306e\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u306e\u5145\u5b9f\u306b\u5411\u3051\u3066\u5c3d\u529b\u3059\u308b Databricks Beacons \u306e\u30e1\u30f3\u30d0\u30fc\u3092\u3054\u7d39\u4ecb\u3057\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u5927\u5b66\u3068\u306e\u9023\u643aDatabricks \u3067\u306f\u3001Databricks \u3092\u6559\u80b2\u306b\u53d6\u308a\u5165\u308c\u308b\u3053\u3068\u3092\u5e0c\u671b\u3059\u308b\u5927\u5b66\u30fb\u6559\u80b2\u8005\u5411\u3051\u306b\u3001\u30ea\u30bd\u30fc\u30b9\u3092\u7121\u6599\u3067\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308bData Brew \u52d5\u753b\u30dd\u30c3\u30c9\u30ad\u30e3\u30b9\u30c8Data+AI \u3092\u30b9\u30da\u30b7\u30e3\u30ea\u30b9\u30c8\u3068\u63a2\u7d22Brook Wenig and Denny Lee\u52d5\u753b\u30b7\u30ea\u30fc\u30ba\u30c6\u30c3\u30af\u30c8\u30fc\u30af\u3068\u30df\u30fc\u30c8\u30a2\u30c3\u30d7Brook Wenig and Denny Lee\u30c6\u30c3\u30af\u30c8\u30fc\u30afMLflow \u306b\u3088\u308b ML \u30e9\u30a4\u30d5\u30b5\u30a4\u30af\u30eb\u7ba1\u7406\u30b8\u30e5\u30fc\u30eb\u30fb\u30c0\u30e0\u30b8\u30c6\u30c3\u30af\u30c8\u30fc\u30afDelta Lake \u5165\u9580Denny Lee\u30c6\u30c3\u30af\u30c8\u30fc\u30afDelta Lake \u4e0a\u7d1a\u7de8Denny LeeDatabricks Demo Hub \uff08\u88fd\u54c1\u30c7\u30e2\uff09DATA+AI \u306e\u7814\u7a76Matei Zaharia\u5171\u540c\u5275\u696d\u8005\u517c CTODatabricksReynold Xin\u5171\u540c\u5275\u696d\u8005\u517c\u30c1\u30fc\u30d5\u30a2\u30fc\u30ad\u30c6\u30af\u30c8Databricks\u30b9\u30fc\u30fb\u30a2\u30f3\u30fb\u30db\u30f3\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30a8\u30f3\u30b8\u30cb\u30a2DatabricksDatabricks 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\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/don-bosco-durai","text":"Don Bosco Durai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon Bosco DuraiCofounder and CTO at PrivaceraBack to speakersBosco is an enterprise security thought leader. Bosco co-founded XASecure which reinvented security at scale for Big Data which later became Apache Ranger. Bosco is currently co-founder and CTO at Privacera addressing data security & access governance challenges in the Cloud. He is also actively involved in the Open-Source communities as a committer in open source projects like Apache Ranger, Ambari, and HAWQ.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/?itm_data=mainnav-promo-dais2022","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions\/capgemini-revenue-growth-management","text":"Capgemini Revenue Growth Management | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionRevenue Growth Management by CapgeminiIndustry-specific solution developed by Capgemini and powered by the Databricks Lakehouse Platform\nGet startedBuild a better recommendation engineIn today\u2019s dynamic environment, knowing what a customer purchased three months ago does not always tell you what they will purchase tomorrow. To establish fine-grained and accurate demand-sensing patterns, you need to incorporate externalities like dynamic market data, indices and social media. Capgemini\u2019s revenue growth management engine leverages the Databricks Lakehouse for Retail to rapidly perform analysis of invoice data, external market data, indices, news and web scraping data to explore patterns. This improves on all aspects of the selling and marketing cycle, including acquisition, conversion and retention. With Capgemini Revenue Growth Management, you can:Preconfigure a visual interface and filter to display revenue growthPre-populate PySpark code and notebooks within Databricks for migrationsUtilize frameworks for initial product backlog structure and model selection criteriaGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases.\u00a0See our full library of solutions \u279eProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rafi-kurlansik\/#","text":"Rafi Kurlansik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRafi KurlansikLead Solutions Architect at DatabricksBack to speakersRafi is a Lead Solutions Architect at Databricks where he specializes in Data Science, Machine Learning and the Developer Experience. He has also helped many customers scale their R workloads with Spark. In his spare time he enjoys gardening with native plants, cooking up a storm, and long video game sessions with his three children.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jeff-mroz\/#","text":"Jeff Mroz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeff MrozTechnical SME for Cloud and Big Data at Woolpert \/ US Army Corps of EngineersBack to speakersJeff Mroz is a Woolpert technical Cloud SME working for government clients on Azure cloud data modernization and architecture, CI\/CD pipeline development, Geospatial Big Data and Lake House workflows, and cloud R&D projects in secure government clouds.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/greg-nelson\/#","text":"Greg Nelson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGreg NelsonVP of Data Operations at Highmark HealthBack to speakersGreg Nelson, MMCi, CPHIMS, FACHE serves as the Vice President, of Data Operations and is a key member of the executive leadership team for the Enterprise Data and Analytics organization at Highmark Health. \nBefore joining Highmark, Greg held leadership roles at Intermountain Healthcare and ECU Health (formerly Vidant Health.) Greg was also the founder and CEO of ThotWave, a healthcare analytics advisory firm specializing in helping organizations mature their analytics maturity. \nGreg serves as an expert for the International Institute for Analytics (IIA) and as adjunct faculty at Duke University, where he teaches advanced analytics to master\u2019s level students in both the School of Nursing and the Fuqua School of Business.\nAn author with over 200 papers and publications, Mr. Nelson is a regular speaker and keynote presenter at national and international events as well as is also an educator and futurist for industry and association events. As an analytics evangelist and futurist, Greg has brought his 20+ years of analytics advisory work to bear through a recently published book addressing the people and process sides of analytics entitled The Analytics Lifecycle Toolkit (Wiley, 2018). Through this pragmatic treatment of the analytics lifecycle, Greg speaks to both the practical and human-centeredness of analytics in a way that is accessible and useful for all.\nMr. Nelson earned his bachelor\u2019s degree in Psychology from the University of California, Santa Cruz, a Master of Management in Clinical Informatics from Duke University, and conducted Ph.D. level work (ABD) in Social and Cognitive Psychology and Quantitative Methods from the University of Georgia. \nYou can connect with Greg on Twitter @gregorysnelson or LinkedIn at www.linkedin.com\/in\/gregorysnelson\/Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/category\/platform\/announcements","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/roie-schwaber-cohen\/#","text":"Roie Schwaber-Cohen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRoie Schwaber-CohenStaff Developer Advocate at PineconeBack to speakersRoie Schwaber-Cohen is a staff developer advocate at Pinecone. He has 15 years of software engineering experience and has worked in a variety of startups across industries. Roie is a musician, playing piano and flute. He lives in Seattle with my wife and daughter, along with our two dogs and cat.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/awards-and-recognition","text":"Premi e riconoscimenti | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPremi e riconoscimentiScopri i riconoscimenti che Databricks ha ricevuto dai leader di settore.Leader nel 2022 Magic Quadrant for Cloud Database Management Systems2022 Customer Choice Award for Cloud Database Management SystemsLeader nel 2021 Magic Quadrant for Cloud Database Management SystemsLeader nel 2021 Magic Quadrant for Data Science and Machine LearningLakehouse \u2014 Hype Cycle for Data Management, 2022Aziende da tenere d'occhio nel 2023Le aziende pi\u00f9 innovative nella data scienceThe Cloud 100The AI 50Le migliori startup americane in cui lavorareLe migliori aziende tecnologiche in cui lavorareLe migliori aziende in cui lavorare nella Baia di San FranciscoLe migliori aziende in cui lavorare per i millennialCNBC Disruptor 50Le migliori aziende in cui lavorare nel 2022Pronto per saperne di pi\u00f9?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/08\/06\/5-key-steps-to-successfully-migrate-from-hadoop-to-the-lakehouse-architecture.html","text":"5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architecture - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic Sector5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architectureby Harsh NarulaAugust 6, 2021 in Data StrategyShare this postThe decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision. In a previous blog, we dug into the reasons why every organization must re-evaluate its relationship with Hadoop. Once stakeholders from technology, data, and the business make the decision to move the enterprise off of Hadoop, there are several considerations that need to be taken into account before starting the actual transition. In this blog, we\u2019ll specifically focus on the actual migration process itself. You\u2019ll learn about the key steps for a successful migration and the role the lakehouse architecture plays in sparking the next wave of data-driven innovation.The migration stepsLet's call it like it is. Migrations are never easy. However, migrations can be structured to minimize adverse impact, ensure business continuity and manage costs effectively. To do this, we suggest breaking your migration off of Hadoop down into these five key steps:AdministrationData MigrationData ProcessingSecurity and GovernanceSQL and BI LayerStep 1: AdministrationLet\u2019s review some of the essential concepts in Hadoop from an administration perspective, and how they compare and contrast with Databricks.Hadoop is essentially a monolithic distributed storage and compute platform. It consists of multiple nodes and servers, each with their own storage, CPU and memory. Work is distributed across all these nodes. Resource Management is done via YARN, which attempts best efforts to ensure that workloads get their share of compute.Hadoop also consists of metadata information. There is a Hive metastore, which contains structured information around your assets that are stored in HDFS. You can leverage Sentry or Ranger for controlling access to the data. From a data access perspective, users and applications can either access data directly through HDFS (or the corresponding CLI\/API\u2019s) or via a SQL type interface. The SQL interface, in turn, can be over a JDBC\/ODBC connection using Hive for generic SQL (or in some cases ETL Scripts) or Hive on Impala or Tez for interactive queries. Hadoop also provides an HBase API and related data source services. More on the Hadoop ecosystem here.Next, let\u2019s discuss how these services are mapped to or dealt with in the\u00a0 Databricks Lakehouse Platform. In Databricks, one of the first differences to note is that you\u2019re looking at multiple clusters in a Databricks environment. Each cluster could be used for a specific use case, a specific project, business unit, team or development group. More importantly, these clusters are meant to be ephemeral. For job clusters, the clusters\u2019 life span is meant to last for the duration of the workflow. It will execute the workflow, and once it\u2019s complete, the environment is torn down automatically. Likewise, if you think of an interactive use case, where you have a compute environment that\u2019s shared across developers, this environment can be spun up at the beginning of the workday, with developers running their code throughout the day. During periods of inactivity, Databricks will automatically tear it down via the (configurable) auto-terminate functionality that\u2019s built into the platform.Unlike Hadoop, Databricks does not provide data storage services like HBase or SOLR. Your data resides in your file storage, within object storage. A lot of the services like HBase or SOLR have alternatives or equivalent technology offerings in the cloud. It might be a cloud-native or an ISV solution.As you can see in the diagram above, each cluster node in Databricks corresponds to either Spark driver or a worker. The key thing here is that the different Databricks clusters are completely isolated from each other. This allows you to ensure that strict SLAs can be met for specific projects and use cases. You can truly isolate streaming or real-time use cases from other, batch oriented workloads, and you don\u2019t have to worry about manually isolating long running jobs that could hog cluster resources for a long time. You can just spin up new clusters as compute for different use cases. Databricks also decouples storage from compute, and allows you to leverage existing cloud storage such as AWS S3, Azure Blob Storage and Azure Data Lake Store (ADLS).Databricks also has a default managed Hive metastore, which stores structured information about data assets that reside in cloud storage. It also supports using an external metastore, such as AWS Glue, Azure SQL Server or Azure Purview. You can also specify security control such as Table ACLs within Databricks, as well as object storage permissions.When it comes to data access, Databricks offer similar capabilities to Hadoop in terms of how your users interact with the data. Data stored in cloud storage, can be accessed through multiple paths in the Databricks environment. Users can use SQL Endpoints and Databricks SQL for interactive queries and analytics. They can also use the Databricks notebooks for Data Engineering and Machine Learning capabilities on the data stored in cloud storage. HBase in Hadoop maps to Azure CosmosDB, or AWS DynamoDB\/Keyspaces, which can be leveraged as a serving layer for downstream applications.Step 2:\u00a0 Data migrationComing from a Hadoop background, I\u2019ll assume most of the audience would already be familiar with HDFS. HDFS is the storage file system used with Hadoop deployments that leverages disks on the nodes of the Hadoop cluster. So, when you scale HDFS, you need to add capacity to the cluster as a whole (i.e. you need to scale compute and storage together). If this involves procurement and installation of additional hardware, there can be a significant amount of time and effort involved.In the cloud, you have nearly limitless storage capacity in the form of cloud storage such as AWS S3, Azure Data Lake Storage or Blob Storage or Google Storage. There are no maintenance or health checks needed, and it offers built-in redundancy and high levels of durability and availability from the moment it is deployed. We recommend using native cloud services to migrate your data, and to ease the migration there are several partners\/ISVs.So, how do you get started? The most commonly recommended route is to start with a dual ingestion strategy (i.e. add a feed that uploads data into cloud storage in addition to your on-premise environment). This allows you to get started with new use cases (that leverage new data) in the cloud without impacting your existing setup. If you\u2019re looking for buy-in from other groups within the organization, you can position this as a backup strategy to begin with. HDFS traditionally has been a challenge to back up due to the sheer size and effort involved, so backing up data into the cloud can be a productive initiative anyway.In most cases, you can leverage existing data delivery tools to fork the feed and write not just to Hadoop but to cloud storage as well. For example, if you\u2019re using tools\/frameworks like Informatica and Talend to process and write data to Hadoop, it\u2019s very easy to add the additional step and have them write to cloud storage. Once the data is in the cloud, there are many ways to work with that data.In terms of data direction, the data either be pulled from on-premise to the cloud, or pushed to the cloud from on-premise. Some of the tools that can be leveraged to push the data into the cloud are cloud native solutions (Azure Data Box, AWS Snow Family, etc.), DistCP (a Hadoop tool), other third party tools, as well as any in-house frameworks. The push option is usually easier in terms of getting the required approvals from the security teams.For pulling the data to the cloud, you can use Spark\/Kafka Streaming or Batch ingestion pipelines that are triggered from the cloud. For batch, you can either ingest files directly or use JDBC connectors to connect to the relevant upstream technology platforms and pull the data. There are, of course, third party tools available for this as well. The push option is the more widely accepted and understood of the two, so let\u2019s dive a little bit deeper into the pull approach.The first thing you\u2019ll need is to set up connectivity between your on-premises environment and the cloud. This can be achieved with an internet connection and a gateway. You can also leverage dedicated connectivity options such as AWS Direct Connect, Azure ExpressRoute, etc. In some cases, if your organization is not new to the cloud, this may have already been set up so you can reuse it for your Hadoop migration project.Another consideration is the security within the Hadoop environment. If it is a Kerberized environment, it can be accommodated from the Databricks side. You can configure Databricks initialization scripts that run on cluster startup, install and configure the necessary kerberos client, access the krb5.conf and keytab files, which are stored in a cloud storage location, and ultimately execute the kinit() function, which will allow the Databricks cluster to interact directly with your Hadoop environment.Finally, you will also need an external shared metastore. While Databricks does have a metastore service that is deployed by default, it also supports using an external one. The external metastore will be shared by Hadoop and Databricks, and can be deployed either on-premises (in your Hadoop environment) or the cloud. For example, if you have existing ETL processes running in Hadoop and you cannot migrate them to Databricks yet, you can leverage this setup with the existing on-premises metastore, to have Databricks consume the final curated dataset from Hadoop.Step 3: Data ProcessingThe main thing to keep in mind is that from a data processing perspective, everything in Databricks leverages Apache Spark. All Hadoop programming languages, such as MapReduce, Pig, Hive QL and Java, can be converted to run on Spark, whether it be via Pyspark, Scala, Spark SQL or even R. With regards to the code and IDE, both Apache Zeppelin and Jupyter notebooks can be converted to Databricks notebooks, but it\u2019s a bit easier to import Jupyter notebooks. Zeppelin notebooks will need to be converted to Jupyter or Ipython before they can be imported. If your data science team would like to continue to code in Zeppelin or Jupyter, they can use Databricks Connect, which allows you to leverage your local IDE (Jupyter, Zeppelin or even IntelliJ, VScode, RStudio, etc.) to run code on Databricks.When it comes to migrating Apache Spark\u2122 jobs, the biggest consideration is Spark versions. Your on-premises Hadoop cluster may be running an older version of Spark, and you can use the Spark migration guide to identify what changes were made to see any impacts on your code. Another area to consider is converting RDDs to dataframes. RDDs were commonly used with Spark versions up to 2.x, and while they can still be used with Spark 3.x, doing so can prevent you from leveraging the full capabilities of the Spark optimizer. We recommend that you change your RDDs to dataframes wherever possible.Last but not least, one of the common gotchas we\u2019ve come across with customers during migration is hard-coded references to the local Hadoop environment. These will, of course, need to be updated, without which the code will break in the new setup.Next, let\u2019s talk about converting non-Spark workloads, which for the most part involve rewriting code. For MapReduce, in some cases, if you\u2019re using shared logic in the form of a Java library, the code can be leveraged by Spark. However, you may still need to re-write some parts of the code to run in a Spark environment as opposed to MapReduce. Sqoop is relatively easy to migrate since in the new environments you\u2019re running a set of Spark commands(as opposed to MapReduce commands) using a JDBC source. You can specify parameters in Spark code in the same way that you specify them in Sqoop. For Flume, most of the use cases we\u2019ve seen are around consuming data from Kafka and writing to HDFS. This is a task that can be easily accomplished using Spark streaming. The main task with migrating Flume is that you have to convert the config file-based approach into a more programmatic approach in Spark. Lastly, we have Nifi, which is mostly used outside Hadoop, mostly as a drag and drop, self-service ingestion tool. Nifi can be leveraged in the cloud as well, but we see many customers using the opportunity to migrate to the cloud to replace Nifi with other, newer tools available in the cloud.Migrating HiveQL is perhaps the easiest task of all. There is a high degree of compatibility between Hive and Spark SQL, and most queries should be able to run on Spark SQL as-is. There are some minor changes in DDL between HiveQL and Spark SQL, such as the fact that Spark SQL uses the \u201cUSING\u201d clause vs HiveQL\u2019s \u201cFORMAT\u201d clause. We do recommend changing the code to use the Spark SQL format, as it allows the optimizer to prepare the best possible execution plan for your code in Databricks. You can still leverage Hive Serdes and UDFs, which makes life even easier when it comes to migrating HiveQL to Databricks.With respect to workflow orchestration, you have to consider potential changes to how your jobs will be submitted. You can continue to leverage Spark submit semantics, but there are also other, faster and more seamlessly integrated options available. You can leverage Databricks jobs and Delta Live Tables for code-free ETL to replace Oozie jobs, and define end-to-end data pipelines within Databricks. For workflows involving external processing dependencies, you\u2019ll have to create the equivalent workflows\/pipelines in technologies like Apache Airflow, Azure Data Factory, etc. for automation\/scheduling. With Databricks\u2019 REST APIs, nearly any scheduling platform can be integrated and configured to work with Databricks.There is also an automated tool called MLens (created by KnowledgeLens), which can help migrate your workloads from Hadoop to Databricks. MLens can help migrate PySpark code and HiveQL, including translation of some of the Hive specifics into Spark SQL so that you can take advantage of the full functionality and performance benefits of the Spark SQL optimizer. They are also planning to soon support migrating Oozie workflows to Airflow, Azure Data Factory, etc.Step 4: Security and governanceLet\u2019s take a look at security and governance. In the Hadoop world, we have LDAP integration for connectivity to admin consoles like Ambari or Cloudera Manager, or even Impala or Solr. Hadoop also has Kerberos, which is used for authentication with other services. From an authorization perspective, Ranger and Sentry are the most commonly used tools.With Databricks, Single Sign On (SSO) integration is available with any Identity Provider that supports SAML 2.0. This includes Azure Active Directory, Google Workspace SSO, AWS SSO and Microsoft Active Directory. For Authorization, Databricks provides ACLs (Access Control Lists) for Databricks objects, which allows you to set permissions on entities like notebooks, jobs, clusters. For data permissions and access control, you can define table ACLs and views to limit column and row access, as well as leverage something like credential passthrough, with which Databricks passes on your workspace login credentials to the storage layer (S3, ADLS, Blob Storage.) to determine if you are authorized to access the data. If you need capabilities like attribute-based controls or data masking, you can leverage partner tools like Immuta and Privacera. From an enterprise governance perspective, you can connect Databricks to an enterprise data catalog such as AWS Glue, Informatica Data Catalog, Alation and Collibra.Step 5: SQL & BI layerIn Hadoop, as discussed earlier, you have Hive and Impala as interfaces to do ETL as well as ad-hoc queries and analytics. In Databricks, you have similar capabilities via Databricks SQL. Databricks SQL also offers extreme performance via the Delta engine, as well as support for high-concurrency use cases with auto-scaling clusters. Delta engine also includes Photon, which is a new MPP engine built from scratch in C++ and is vectorized to exploit both data level and instruction-level parallelism.Databricks provides native integration with BI tools such as Tableau, PowerBI, Qlik andlooker, as well as highly-optimized JDBC\/ODBC connectors that can be leveraged by those tools. The new JDBC\/ODBC drivers have a very small overhead (\u00bc sec) and a 50% higher transfer rate using Apache Arrow, as well as several metadata operations that support significantly faster metadata retrieval operations. Databricks also supports SSO for PowerBI, with support for SSO with other BI\/dashboarding tools coming soon.Databricks has a built-in SQL UX in addition to the notebook experience mentioned above, which gives your SQL users their own lens with a SQL workbench, as well as light dashboarding and alerting capabilities. This allows for SQL-based data transformations and exploratory analytics on data within the data lake, without the need to move it downstream to a data warehouse or other platforms.Next stepsAs you think about your migration journey to a modern cloud architecture like the lakehouse architecture, here are two things to remember:Remember to bring the key business stakeholders along on the journey. This is as much of a technology decision as it is a business decision and you need your business stakeholders bought into the journey and its end state.Also, remember you\u2019re not alone, and there are skilled resources across Databricks and our partners who have done this enough to build out repeatable best practices, saving organizations, time, money, resources, and reducing overall stress.Download the Hadoop to Databricks Technical Migration guide for step-by-step guidance, notebooks, and code to begin your migration.To learn more about how Databricks increases business value and start planning your migration off of Hadoop, visit databricks.com\/migration.Migration Guide: Hadoop to Databricks\nUnlock the full potential of your data with this self-guided playbook.Download NowTry Databricks for freeGet StartedRelated posts5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse ArchitectureAugust 6, 2021 by Harsh Narula in Data Strategy\nThe decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision...\nSee all Data Strategy postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/events","text":"Databricks \u306e\u30a4\u30d9\u30f3\u30c8 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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{"source":"https:\/\/www.databricks.com\/fr\/product\/delta-lake-on-databricks","text":"Delta Lake sur Databricks \u2013 Planifiez une d\u00e9mo d\u00e8s maintenant\u00a0!Skip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWDelta LakeFiabilit\u00e9, s\u00e9curit\u00e9 et performance\nde votre data\u00a0lakeEssai gratuitregarder une d\u00e9moQu'est-ce que Delta\u00a0Lake\u00a0?Delta\u00a0Lake est une couche de stockage au format ouvert qui offre fiabilit\u00e9, s\u00e9curit\u00e9 et performances \u00e0 votre data\u00a0lake, pour les op\u00e9rations de streaming mais aussi de batch. En rempla\u00e7ant les silos par un emplacement unique d\u00e9di\u00e9 aux donn\u00e9es structur\u00e9es, semi-structur\u00e9es et non structur\u00e9es, Delta\u00a0Lake constitue la base d'un lake\u00a0house rentable et hautement \u00e9volutif.Des donn\u00e9es fiables et de haute qualit\u00e9Proposez une source de v\u00e9rit\u00e9 unique et fiable pour toutes vos donn\u00e9es, y compris pour les flux en\u00a0temps r\u00e9el. Vos \u00e9quipes data travailleront ainsi toujours avec les bases les plus r\u00e9centes. Gr\u00e2ce \u00e0 la prise en charge des transactions ACID et \u00e0 la validation des sch\u00e9mas, Delta\u00a0Lake offre la fiabilit\u00e9 qui manque aux data\u00a0lakes traditionnels. Cela vous permet de d\u00e9ployer des insights fiables dans toute votre organisation et de lancer des analyses et d'autres projets li\u00e9s aux donn\u00e9es directement depuis votre data\u00a0lake, dans un temps jusqu'\u00e0\u00a050 fois plus court.Partage de donn\u00e9es ouvert et s\u00e9curis\u00e9Delta Sharing\u00a0est le premier protocole ouvert pour le partage s\u00e9curis\u00e9 des donn\u00e9es. Il permet d'\u00e9changer facilement des donn\u00e9es avec d'autres organisations, quel que soit l'endroit o\u00f9 elles se trouvent. L'int\u00e9gration native avec le\u00a0Unity Catalog\u00a0vous permet de g\u00e9rer et d'auditer les donn\u00e9es partag\u00e9es dans toutes les organisations, de fa\u00e7on centralis\u00e9e. Cela vous permet \u00e9galement de partager en toute confiance des actifs de donn\u00e9es avec vos fournisseurs et partenaires pour une meilleure coordination de votre activit\u00e9, tout en r\u00e9pondant aux crit\u00e8res de s\u00e9curit\u00e9 et de conformit\u00e9. Les int\u00e9grations avec les principaux outils et plateformes facilitent en outre la visualisation, l'interrogation, l'enrichissement et le contr\u00f4le des donn\u00e9es partag\u00e9es \u00e0 partir des outils de votre choix.Des performances rapides comme l'\u00e9clairB\u00e2ti sur le moteur Apache Spark\u2122, Delta\u00a0Lake offre des performances exceptionnelles en termes de vitesse et d'\u00e9chelle. Gr\u00e2ce \u00e0 des fonctionnalit\u00e9s qui optimisent ses performances comme l'indexation, Delta\u00a0Lake permet \u00e0 ses clients de traiter des charges ETL avec une vitesse d'ex\u00e9cution jusqu'\u00e0 48\u00a0fois sup\u00e9rieure.Ouvert et agileToutes les donn\u00e9es de Delta\u00a0Lake sont stock\u00e9es au format ouvert Apache\u00a0Parquet. Elles sont donc lisibles par n'importe quel lecteur adapt\u00e9. Les API sont ouvertes et compatibles avec Apache\u00a0Spark. Avec Delta\u00a0Lake pour Databricks, vous acc\u00e9dez \u00e0 un vaste \u00e9cosyst\u00e8me open\u00a0source, \u00e9vitant ainsi tout verrouillage des donn\u00e9es dans des formats propri\u00e9taires.Data engineering automatis\u00e9 et fiableSimplifiez votre data\u00a0engineering avec Delta\u00a0Live\u00a0Tables. Ce framework vous permet de construire et de g\u00e9rer facilement des pipelines de donn\u00e9es afin d'obtenir des donn\u00e9es fra\u00eeches et de grande qualit\u00e9 sur Delta\u00a0Lake. En aidant les \u00e9quipes de data\u00a0engineering \u00e0 simplifier le d\u00e9veloppement et la gestion de l'ETL, gr\u00e2ce \u00e0 la cr\u00e9ation de pipelines d\u00e9claratifs, \u00e0 l'am\u00e9lioration de la fiabilit\u00e9 des donn\u00e9es et la mise en place d'op\u00e9rations de production \u00e0 l'\u00e9chelle du Cloud, Delta\u00a0Live\u00a0Tables facilite la construction des fondations de Lakehouse.S\u00e9curit\u00e9 et gouvernance \u00e0 l'\u00e9chelleDelta\u00a0Lake r\u00e9duit les risques gr\u00e2ce \u00e0 une gouvernance des donn\u00e9es reposant sur la finesse des contr\u00f4les d'acc\u00e8s, ce qui n'est en principe pas possible avec les data\u00a0lakes. Vous pouvez mettre \u00e0 jour rapidement et avec pr\u00e9cision les donn\u00e9es de votre data\u00a0lake pour vous conformer \u00e0 des r\u00e9glementations telles que le RGPD, et maintenir une meilleure gouvernance des donn\u00e9es gr\u00e2ce \u00e0 la journalisation des audits. Ces fonctionnalit\u00e9s sont nativement int\u00e9gr\u00e9es et am\u00e9lior\u00e9es pour Databricks dans le cadre du Unity Catalog, le premier catalogue de donn\u00e9es multicloud pour le Lakehouse.Cas d\u2019utilisationLa BI sur vos donn\u00e9esMettez \u00e0 disposition de vos analystes de nouvelles donn\u00e9es en temps r\u00e9el et obtenez des insights imm\u00e9diats sur votre entreprise gr\u00e2ce \u00e0 des t\u00e2ches de Business\u00a0Intelligence directement ex\u00e9cut\u00e9es sur votre datalake. Delta\u00a0Lake vous permet d'exploiter une architecture lakehouse multicloud qui offre des performances d'entreposage de donn\u00e9es \u00e0 des co\u00fbts proches de ceux des data\u00a0lakes, pour un rapport prix \/ performance jusqu'\u00e0 quatre fois meilleur pour les t\u00e2ches SQL que les data warehouses classiques dans le Cloud.En savoir plusUnifier batch et streamingEx\u00e9cutez des op\u00e9rations de streaming et de batch sur une architecture simplifi\u00e9e, en \u00e9vitant les syst\u00e8mes complexes et redondants, ainsi que les difficult\u00e9s op\u00e9rationnelles. Dans Delta Lake, une table est \u00e0 la fois une table batch mais aussi une source de streaming et un puits de donn\u00e9es. L'ingestion de donn\u00e9es en streaming, le remplissage historique par batch et les requ\u00eates interactives fonctionnent sans aucun effort suppl\u00e9mentaire, s'int\u00e9grant directement \u00e0 Spark Structured Streaming.R\u00e9pondre aux exigences r\u00e9glementairesDelta\u00a0Lake \u00e9limine les probl\u00e8mes li\u00e9s \u00e0 l'ingestion de donn\u00e9es erron\u00e9es, \u00e0 la suppression des donn\u00e9es pour des raisons de conformit\u00e9 et aux changements dans la capture de donn\u00e9es modifi\u00e9es (Change Data Capture). Gr\u00e2ce \u00e0 la prise en charge des transactions ACID dans votre data\u00a0lake, Delta\u00a0Lake garantit que chaque op\u00e9ration est enti\u00e8rement men\u00e9e \u00e0 bien ou abandonn\u00e9e en vue de nouvelles tentatives ult\u00e9rieures, sans n\u00e9cessiter la cr\u00e9ation de nouveaux pipelines de donn\u00e9es. D'autre part, Delta\u00a0Lake enregistre toutes les transactions pr\u00e9c\u00e9dentes sur votre data\u00a0lake, facilitant ainsi l'acc\u00e8s aux versions ant\u00e9rieures de vos donn\u00e9es pour r\u00e9pondre de mani\u00e8re fiable aux normes de conformit\u00e9 telles que le RGPD et le CCPA.R\u00e9seau d'ingestion de donn\u00e9esDes connecteurs natifs pour faciliter une ingestion fiable et rapide des donn\u00e9es dans Delta\u00a0Lake, depuis tous vos stockages de fichiers, applications et bases de donn\u00e9es.Clients\u00ab\u00a0Databricks nous a fourni les analyses, les d\u00e9lais de mise sur le march\u00e9 et le coup de pouce op\u00e9rationnel dont nous avions besoin pour r\u00e9pondre aux nouvelles exigences du secteur de la sant\u00e9.\u00a0\u00bb \u2013 Peter James, Architecte en chef, Healthdirect AustraliaEn savoir plus\u00ab\u00a0En exploitant Databricks et Delta Lake, nous avons d\u00e9j\u00e0 pu d\u00e9mocratiser les donn\u00e9es \u00e0 l'\u00e9chelle, tout en r\u00e9duisant de 60\u00a0% le co\u00fbt d'ex\u00e9cution des t\u00e2ches de production, ce qui nous fait \u00e9conomiser des millions de dollars.\u00a0\u00bb\n- Steve Pulec, Directeur technique, YipitDataEn savoir plus\u00ab\u00a0\u00bbDelta\u00a0Lake offre des fonctionnalit\u00e9s ACID qui simplifient les op\u00e9rations de pipeline de donn\u00e9es afin d'am\u00e9liorer la fiabilit\u00e9 et la coh\u00e9rence des donn\u00e9es. Parall\u00e8lement, des fonctionnalit\u00e9s telles que la mise en cache et l'indexation automatique permettent un acc\u00e8s efficace et performant aux donn\u00e9es.\u00a0\u00bb\n- Lara Minor, Senior Enterprise Data Manager, Columbia SportswearEn savoir plus\u00ab\u00a0Delta\u00a0Lake a cr\u00e9\u00e9 une approche simplifi\u00e9e de la gestion des pipelines de donn\u00e9es. Nous avons ainsi pu r\u00e9duire les co\u00fbts op\u00e9rationnels tout en acc\u00e9l\u00e9rant la production d'analyses et les processus de data\u00a0science.\u00a0\u00bb\n- Parijat Dey, Vice-pr\u00e9sident adjoint, en charge de la transformation num\u00e9rique et de la technologie, Viacom18En savoir plusRessources\nToutes les ressources dont vous avez besoin. R\u00e9unies au m\u00eame endroit.\nExplorez notre biblioth\u00e8que de ressources\u00a0: vous y trouverez des ebooks et des vid\u00e9os sur les atouts du data engineering sur Databricks.\nExplorer les ressourcesEbooksLe Grand Livre des cas d'usage du data engineeringDonn\u00e9es, analyses et gouvernance de l'IAD\u00e9couvrez les Fondamentaux de la gestion des donn\u00e9esCr\u00e9er le Data Lakehouse par Bill Inmon, p\u00e8re du data warehouseConf\u00e9rences et formations technologiquesD\u00e9marrer avec Delta Lake \u2013 S\u00e9rie de Tech TalksWebinairesLe bon, la brute et le truandPlongez dans le lakehouse avec Delta LakePr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSDocumentation Delta\u00a0LakeProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/product\/spark","text":"Spark on Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark on DatabricksThe best platform to run your Spark workloads, from the original creators of Apache Spark\u2122Simplicity, best-in-class operational excellence and price\/performance benefits make the Databricks Lakehouse Platform the best place to run your\u00a0Apache Spark\u2122\u00a0workloadsBest-in-class operational excellenceWe help thousands of customers launch millions of VMs every day to run their Spark applications. And we support the latest\u00a0developer tools and guidance, ensuring that you can develop and deploy your Spark applications with confidence and ease.Run your Spark applications individually or deploy them with ease on\u00a0Databricks WorkflowsRun Spark notebooks with other task types for declarative data pipelines on fully managed compute resourcesWorkflow monitoring allows you to easily track the performance of your Spark applications over time and diagnosis problems within a few clicksBest price\/performance for Spark workloadsRunning your Spark workloads on the Databricks Lakehouse Platform means you benefit from\u00a0Photon\u00a0\u2013 a fast C++, vectorized execution engine for Spark and SQL workloads that runs behind Spark\u2019s existing programming interfaces. Photon provides\u00a0record-breaking\u00a0query performance at low cost while leveraging the latest in modern hardware architectures such as AWS\u00a0Graviton.In addition to lightning-fast performance, Spark on Databricks achieves lower overall TCO through capabilities such as dynamic autoscaling, so you only pay for what you use. Databricks also offers GPU and spot instances.End-to-end analytics and unified governance with the Databricks Lakehouse PlatformWhile other platforms require you to integrate multiple tools and manage different governance models, Databricks unifies data warehouse, data lake and data streaming in one simple Lakehouse Platform to handle all your\u00a0data engineering, analytics and AI use cases end-to-end. It\u2019s built on an\u00a0open and reliable data foundation\u00a0that efficiently handles all data types, unifies batch and streaming, and applies\u00a0one common security and governance model\u00a0across all your data and cloud platforms.Continued innovationThe 2022 SIGMOD Systems Award\u00a0recognized Spark as an innovative, widely used, open source, unified data processing system encompassing relational, streaming and machine learning workloads.And the innovation continues. Recently we introduced\u00a0Spark Connect\u00a0and\u00a0Project Lightspeed.Spark Connect decouples the client and server for better stability and allows for Spark applications everywhere.Project Lightspeed, the next generation of Spark Structured Streaming, further delivers on predictable low latency and enhanced functionality for processing events.Ready to get started?Try Spark on Databricks todayProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/avinash-sooriyarachchi","text":"Avinash Sooriyarachchi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAvinash SooriyarachchiSenior Solutions Architect at DatabricksBack to speakersAvinash Sooriyarachchi is a Solutions Architect at Databricks. His current work involves working with large Retail and Consumer Packaged Goods organizations across the United States and enabling them to build Machine Learning based systems. His specific interests include streaming machine learning systems and building applications leveraging foundation models. Avi holds a Master\u2019s degree in Mechanical Engineering and Applied Mechanics from the University of Pennsylvania.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/06\/28\/introducing-databricks-marketplace-an-open-marketplace-for-all-data-and-ai-assets.html","text":"Introducing Databricks Marketplace, an Open Marketplace for Data Solutions - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks MarketplaceAn open marketplace for data solutionsby Matei Zaharia, Zaheera Valani, Jay Bhankharia, Sachin Thakur, Itai Weiss and Steve MahoneyJune 28, 2022 in AnnouncementsShare this postWe're pleased to announce Databricks Marketplace, an open marketplace for exchanging data products such as datasets, notebooks, dashboards, and machine learning models. To accelerate insights, data consumers can discover, evaluate, and access more data products from third-party vendors than ever before. Providers can now commercialize new offerings and shorten sales cycles by providing value-added services on top of their data. Databricks Marketplace is powered by Delta Sharing allowing consumers to access data products without having to be on the Databricks platform. This open approach allows data providers to broaden their addressable market without forcing consumers into vendor lock-in.\n Databricks MarketplaceThis blog will discuss the key limitations of the existing data marketplaces and our vision for an open marketplace on the Databricks Lakehouse platform\nExisting data marketplaces fail to maximize business value for data providers and data consumersThe demand for 3rd party data to make data-driven innovations is greater than ever and data marketplaces act as a bridge between data providers and data consumers to help facilitate the discovery and delivery of datasets. However, as organizations continue leveraging more third party data, the value these platforms provide has not kept up with the needs of both providers and consumers.\nChallenges for data consumersData consumers value ease of data discovery and frictionless data evaluation from a data marketplace.\nHowever, existing data marketplaces that provide only datasets miss out on one of the key considerations for data consumers which is the context around the data. In most of the current data marketplaces, consumers receive a brief overview of the datasets, and maybe a few sample queries. This often leads to frustration as consumers have to spend time understanding the data model and going back and forth with the data provider's support teams before they are able to determine if it is the right fit for their analytic needs.\nAdditionally, most current marketplaces work in walled garden environments. Data exchange can only be done on their closed platforms and sometimes only within their proprietary data formats. There are limited options to access the data from 3rd party tools or platforms seamlessly and the data consumers are forced to be on the platform, creating lock-in.\nChallenges for data providersFrom the data providers' perspectives, two important measures of success are an increase in sales and a lowering in operational cost. However, most data marketplaces fall short on both of these measures.\nWith existing data marketplaces, data providers can only package and distribute datasets. And most marketplaces limit providers to only offering a brief write-up or out-of-context query examples to augment their dataset product profiles. Data consumers end up incurring significant effort and downstream costs to evaluate these datasets. This results in cumbersome onboarding, unnecessary long sales cycles, and eventually lost revenue opportunities.\nAdditionally, many data marketplaces require data providers to load data into their proprietary format, leverage their compute, and replicate data into different clouds and regions in which their customers operate. This quickly increases compute costs and operational burden as more and more moving parts are added to the system to maintain parity across cloud providers\/regions. As the number of datasets and their volume grows, data providers must consider these costs and trade-off decisions. Some data providers may be left with the decision to deprioritize potentially valuable datasets as the cost to commercialize them grows.\nUnlock business value with Databricks MarketplaceThe vision behind Databricks Marketplace is to address these problems and help. consumers and providers achieve their business objectives.\nBenefits for Data ConsumersFaster time to insightsWith the Databricks marketplace, Data consumers can get access not only to just datasets but other data assets including dashboards, notebooks, and ML models. This provides data consumers an easy way to evaluate data and accelerate time to insights. For example, data consumers can leverage a starter notebook to do exploratory data analysis or a machine learning model that helps predict future rankings of the dataset. Before requesting access to the data, Databricks hosted dashboards enable customers to explore the data live without any additional cost. All of this helps speed up the evaluation, acquisition, and analysis cycle and get more value from the data.\nAn open marketplacePowered by Delta Sharing, Databricks Marketplace allows data consumers to seamlessly access the data products without the need to be on the Databricks platform. There is no lock-in, and it provides consumers options to maximize the data value from the tools of their choice.\nBenefits for Data ProvidersDistribute and monetize a wide array of data productsWith the Databricks Marketplace, providers can market and distribute not only just datasets, but also their other data products such as notebooks, dashboards, and models that are essential to help consumers realize the full value of a dataset.\nLets say a provider is selling Environmental Social and Governance (ESG) data. The provider can package a notebook along with the data to show how the data can be utilized for NLP analysis, a dashboard that provides a visualization of the worst polluting companies, and a model that will show how the shared ESG data can provide recommendations on when a company's ESG ranking will change. With the existing data marketplaces, there is no easy way for providers to share all these highly valuable assets.\nBroaden the reach of the data productsWith Databricks Marketplace,data providers can expand their addressable market beyond the consumers who are on the Databricks Platform. This helps data providers increase the revenue potential of their data products.\nNo replication of data productsDatabricks Marketplace allows data providers to share their data products without having to move or replicate the data products from their cloud storage. This allows providers to deliver data products to other clouds, tools, and platforms from a single source. Providers may choose to replicate data products as desired, but they have the option to choose versus being forced to do so and incurring additional costs.\nWhat Databricks Partners are saying:\"Databricks Marketplace is a compelling platform for us. We like the fact that it is open and provides us a way to reach existing and new types of personas for our data offerings. We see the platform as a key enabler to accelerate value with our data offerings to our customers\"- Chris Anderson, CTO Intellectual Property Solutions, LexisNexis\"Customers need solutions, not only raw data. Being able to package raw data along with the code and analytics on top of it is how we see customers consuming raw data in the future\" - Ross Epstein, VP New Projects, Safegraph\"Facteus is extremely excited to be part of the inception of the Databricks Marketplace. A marketplace built on their Delta Share protocol is a huge step forward in democratizing and simplifying data access.\" - Jonathan Chin, Co-Founder Head of Data and Growth, Facteus\"With more than 1.2B non-identified patient records, IQVIA has unparalleled healthcare data and is focused on advancing innovation for a healthier world. We are looking forward to the upcoming launch of Databricks' Delta Sharing Marketplace to enable seamless data sharing with our customers, which will accelerate time to insights and value across the ecosystem.\" - Avinob Roy, VP & GM Product Management, IQVIASIGN UP TO BE A DATA PROVIDERTry Databricks for freeGet StartedRelated postsNow Generally Available: Introducing Databricks Partner Connect to Discover and Connect Popular Data and AI Tools to the LakehouseNovember 18, 2021 by Hiral Jasani and Himanshu Raja in Platform Blog\nDatabricks is thrilled to announce Partner Connect, a one-stop portal for customers to quickly discover a broad set of validated data, analytics, and...\nBuild Your Business on Databricks With Partner ConnectNovember 18, 2021 by Dave Eyler, Pankaj Dugar and Zaheera Valani in Platform Blog\nAt Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and...\nDatabricks\u2019 2022 Global Partner AwardsJune 27, 2022 by Kori O'Brien and Roger Murff in Company Blog\nDatabricks has a partner ecosystem with over 600 partners globally that are critical to building and delivering the best data and AI solutions...\nSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2021\/03\/23\/introducing-databricks-on-google-cloud-now-in-public-preview.html","text":"Introducing Databricks on Google Cloud - Now in Public Preview - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks on Google Cloud - Now in Public Previewby Hiral JasaniMarch 23, 2021 in AnnouncementsShare this postLast month, we announced Databricks on Google Cloud, a jointly-developed service that allows data teams (data engineering, data science, analytics, and ML professionals) to store data in a simple, open lakehouse platform for all data, AI and analytics workloads. Today, we are launching the public preview of Databricks on Google Cloud.\nWhen speaking to our customers, one thing is clear: they want to build modern data architectures to drive real business impact, whether that\u2019s by personalizing customer experiences with ML, improving in-product gaming experience or delivering life-saving medical supplies (just to name a few). But many find themselves bogged down with unmanageable amounts of data across data types \u2013 structured, unstructured, and semi-structured data \u2013 while simultaneously dealing with a variety of applications. For just the day-to-day work, data teams must stitch together various open source libraries and tools for further analytics. Multiple handoffs between data science, ML engineering and deployment teams slow down development. Complexity and cost of transferring data between multiple disparate data systems and challenges managing multiple copies of data and security models add to the overhead.\nWith these pain points in mind, we believe the way to build a best-in-class Lakehouse platform is to build with open standards. Open standards, open APIs, open platform -- it gives customers the choice to build their modern data architecture based on services with a simple, collaborative experience. Google Cloud shares this \u201cvision of openness\u201d with an open cloud service, meaning our joint customers have the choice to choose the right set of tools to solve any problem.\nOpen data lake with Delta Lake and Google Cloud StorageThe open technology that allows us to unify analytics and artificial intelligence (AI) with a lakehouse on top of your existing data lake is Delta Lake. Data lakes are an affordable way to store large amounts of raw data (structured, unstructured, video, text, audio), often in open source formats such as the widely-used Apache Parquet. Yet, many companies struggle to run their analytics and AI applications in production as they face many of the challenges listed below.\nDelta Lake is an open format storage layer that delivers reliability, performance and governance to solve these data lake challenges. Databricks on Google Cloud is based on Delta Lake and the Parquet format, so you can keep all your data in Google Cloud Storage (GCS) without having to move it or copy it in several places. This allows you to store and manage all your data for analytics on your data lake.\nFaster experimentation with easy-to-use ML & AI servicesOnce you have an open data lake, you have laid the foundation for your data science teams to develop and train their machine learning models. With the availability of Databricks on Google Cloud, data scientists and ML engineers can use our collaborative data science and managed MLflow capabilities with the data in Google Cloud Storage or BigQuery Storage.\nDatabricks on Google Cloud is also integrated with Google Cloud\u2019s suite of AI services. For example, you can deploy MLflow models to AI Platform Predictions for online serving or use AI Platform\u2019s pre-trained ML APIs and AutoML for vision, video, translation and natural language processing.\nConclusionDatabricks on Google Cloud brings a shared vision to combine the open platform with the open cloud for simplified data engineering, data science and data analytics. Want to learn more about how this joint solution unifies all your analytics and AI workloads? Register for our launch event with Databricks CEO & Co-founder Ali Ghodsi and Google Cloud CEO Thomas Kurian for a deep dive into the benefits of an open Lakehouse platform and how Databricks on Google Cloud drive data team collaboration.\nGET STARTED FOR FREETry Databricks for freeGet StartedSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/chunxu-tang\/#","text":"Chunxu Tang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChunxu TangResearch Scientist at AlluxioBack to speakersDr. Chunxu Tang is a Research Scientist at Alluxio and a committer of PrestoDB. Prior to Alluxio, he served as a Senior Software Engineer in Twitter\u2019s data platform team, where he gained extensive experience with a wide range of data systems, including Presto, Zeppelin, BigQuery, and Druid. He received his Ph.D. from Syracuse University, where he conducted research on distributed collaboration systems and machine learning applications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/br\/resources\/whitepaper\/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025","text":"Vis\u00e3o de CIOs para 2025: Preenchendo a lacuna entre BI e AI - DatabricksRelat\u00f3rioVis\u00e3o de CIOs para 2025Preenchendo a lacuna entre BI e AIPesquisa global de CIOs sobre ado\u00e7\u00e3o de IA orientada para o valor de neg\u00f3cioVeja como as principais empresas e organiza\u00e7\u00f5es est\u00e3o superando seus maiores desafios de dados para dominar a IA. No novo relat\u00f3rio de pesquisa do MIT Technology Review, voc\u00ea ter\u00e1 informa\u00e7\u00f5es de 600 CIOs em 18 pa\u00edses e 14 setores.Como os CIOs priorizam a ado\u00e7\u00e3o da IA? Como eles est\u00e3o investindo em melhorias em sua estrat\u00e9gia de dados?Obtenha respostas de entrevistas detalhadas com executivos C-level da Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global, Marks & Spencer e muito mais.Explore as principais descobertas sobre as perspectivas do CIO:72% dizem que os dados s\u00e3o o maior desafio para IA e 68% dizem que unificar sua plataforma de dados para analytics e IA \u00e9 crucial94% dizem que j\u00e1 est\u00e3o usando IA em LOBs e mais da metade espera que a IA seja difundida at\u00e9 202572% acreditam que a multicloud \u00e9 cr\u00edtica e muitos oferecem suporte a padr\u00f5es abertos para preservar a flexibilidade estrat\u00e9gicaBaixe o relat\u00f3rioProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anindya-saha\/#","text":"Anindya Saha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnindya SahaML Platform Software Engineer at nullBack to speakersAnindya Saha is a Machine Learning Platform Engineer, focusing on enabling distributed computing solutions for machine learning and data engineering. He has led implementation of Spark on Kubernetes support on ml platform for feature engineering at scale. He also worked on enabling multi gpus multi nodes distributed model training on machine learning platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/david-skinner","text":"David Skinner - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid SkinnerChief Strategy Officer at AcxiomBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/dna-sequence","text":"What is a DNA Sequence?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDNA SequenceAll>DNA SequenceTry Databricks for freeGet StartedWhat is a DNA Sequence?The DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid). \u00a0Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine also known as bases, occur within the DNA molecule. The first methods for sequencing DNA were developed in the middle 1970s by Fred Sanger, and by Walter Gilbert and Allan Maxam. The first DNA fragment that has been sequenced belonged to a \u00a0virus named T4 bacteriophage that specifically infects the Escherichia coli bacteria. Since the completion of the Human Genome Project, a number of new methods were being developed for large-scale sequencing. The technological improvements and automation have reached a point where labs can sequence well over 100,000 billion bases per year. A number of new methods have been developed for large-scale sequencing; these new methods can target large numbers of short DNA fragments or even entire chromosomes.DNA Sequencing MethodsThere are two main types of DNA sequencing: The Sanger method, also known as dideoxy, which is the classical chain termination method. This method is still being used for determining the sequences of relatively long stretches of DNA, at low volumes. However, if a large number of molecules has to be quickly sequenced it will not be the best choice mainly due to its high costs and laborious work.The High-Throughput Sequencing (HTS) method also known as the Next-Generation Sequencing (NGS) technique. NGS is characterized by improved accuracy and speed, but also reduced manpower and cost.The implementation of the High-Throughput Sequencing method has expanded the applications for genomics. DNA sequencing is now being used as an integral part of basic science, translational research, medical diagnostics, and forensics. \u00a0Additional ResourcesData Analytics and Machine Learning for the Life Sciences IndustryGenome Sequencing in a NutshellPractical Genomics with Apache SparkBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/atiyah-curmally\/#","text":"Atiyah Curmally - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAtiyah CurmallyPrincipal Environmental Specialist at International Finance CorporationBack to speakersAtiyah Curmally's career centers on a passion for sustainable impact investing in emerging markets. At the International Finance Corporation, she focuses on providing insights, guidance, and practical solutions to investors, enabling them to assess risks and make decisions through the environmental, social, and governance (ESG) lens. Atiyah leads the ESG innovation and data science portfolio, including conception and development of an artificial intelligence (AI) solution called MALENA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/supply-chain-distribution-optimization","text":"Supply Chain Distribution Optimization | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorSupply Chain Distribution OptimizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook\nGet startedOptimize transportation costs and improve distribution network performanceThe delivery of goods across a global distribution network is highly costly and logistically complex. Manufacturers can use data and AI to address these operational challenges to maintain competitiveness and profitability in the marketplace. With the Databricks Lakehouse for Manufacturing, organizations can:Use linear programming (LP) to optimize product distribution at scaleTrain models to predict supply and demand of productsLeverage Apache SparkTM to easily speed up model training on Pandas DataFramesDownload notebookResourceseBookRead nowVideoWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit?itm_data=menu-learn-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/contact?contactReason=Request%20a%20Demo","text":"Contact Us - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContact usNeed assistance with training or support? See these additional resources.DocumentationRead technical documentation for Databricks on AWS, Azure or Google CloudDatabricks CommunityDiscuss, share and network with Databricks users and expertsTrainingMaster the Databricks Lakehouse Platform with instructor-led and self-paced training or become a certified developerSupportAlready a customer? Click here if you are encountering a technical or payment issueOur office locationsSee all our office locations globally and get in touchKnowledge baseFind quick answers to the most frequently asked questions about Databricks products and servicesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/collaborative-notebooks?itm_data=product-link-collaborativeNotebooks","text":"Databricks Notebooks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks NotebooksCollaborative data science with familiar languages and toolsTry for freeSchedule a demoWork across engineering, data science and machine learning teams in one workspace. Use multiple languages, built-in data visualizations and automatic versioning, all within Notebooks.BenefitsWork togetherShare Notebooks and work with peers across teams in multiple languages (R, Python, SQL and Scala) and libraries of your choice. Real-time coauthoring, commenting and automated versioning simplify collaboration while providing control.Share insightsQuickly discover new insights with built-in interactive visualizations, or leverage libraries such as Matplotlib and ggplot. Export results and Notebooks in HTML or IPYNB format, or build and share dashboards that always stay up to date.Production at scaleSchedule Notebooks to automatically run machine learning and data pipelines at scale. Create multistage pipelines using Databricks Workflows. Set up alerts and quickly access audit logs for easy monitoring and troubleshooting.FeaturesData AccessQuickly access available data sets or connect to any data source, on-premises or in the cloud.DashboardsShare insights with your colleagues and customers, or let them run interactive queries with Spark-powered dashboards.Multi-language supportExplore data using interactive notebooks with support for multiple programming languages within the same notebook, including R, Python, Scala and SQL.Run Notebooks as JobsTurn notebooks or JARs into resilient production jobs with a click or an API call.Interactive VisualizationsVisualize insights through a wide assortment of point-and-click visualizations. Or use powerful scriptable options like Matplotlib, ggplot and D3.Jobs SchedulerExecute jobs for production pipelines on a specific schedule.Real-Time CoauthoringWork on the same notebook in real time while tracking changes with detailed revision history.Notebook WorkflowsCreate multistage pipelines with the control structures of the source programming language.CommentsLeave a comment and notify colleagues from within shared Notebooks.Notifications and LogsSet up alerts and quickly access audit logs for easy monitoring and troubleshooting.Automatic VersioningAutomatic change-tracking and versioning to help you pick up where you left off.Permissions ManagementQuickly manage access to each individual notebook, or a collection of Notebooks, and experiments, with one common security model.Git-based ReposSimplified Git-based collaboration, reproducibility and CI\/CD workflows.ClustersQuickly attach Notebooks to auto-managed clusters to efficiently and cost-effectively scale up compute.Runs SidebarAutomatically log experiments, parameters and results from Notebooks directly to MLflow as runs, and quickly see and load previous runs and code versions from the sidebar.IntegrationsConnect to Tableau, Looker, Power BI, RStudio, Snowflake and also through your favorite IDEs such as VS Code \u2014 allowing data scientists and engineers to use their tools of choice.How it worksShared and interactive Notebooks, experiments and extended files support allow data scientist teams to organize, share and manage complex data science projects more effectively throughout the lifecycle. APIs and Job Scheduler allow data engineering teams to quickly automate complex pipelines, while business analysts can directly access results via interactive dashboards.Overview of collaborative featuresVisualize your dataManage, schedule, and scale nodesCustomersResourcesDocumentationNotebooksJobseBooks and WebinarsThe Big Book of Data Science Use CasesThe Big Book of Machine Learning Use CasesAutoML Rapid, simplified machine learning for everyoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningThe Data Scientist\u2019s Guide to Apache Spark\u2122The Apache Spark\u2122 CollectionMLOps Virtual EventManaging the Complete Machine Learning LifecycleProduct DemoCollaboration in DatabricksVisualizations in DatabricksCase StudyHPNielsenReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/company\/founders","text":"Founders | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLeadershipWith a long-term vision, our leadership team leverages decades of experience to chart a new course for data and AIMeet our teamExecutive teamFoundersBoard of directorsAli GhodsiCo-founder and Chief Executive OfficerIon StoicaCo\u2013founder and Executive ChairmanMatei ZahariaCo\u2013founder and Chief TechnologistPatrick WendellCo\u2013founder and VP of EngineeringReynold XinCo\u2013founder and Chief ArchitectAndy KonwinskiCo\u2013founder and VP of Product ManagementArsalan Tavakoli-ShirajiCo-founder and SVP of Field EngineeringProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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\u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29REGISTER NOW\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u3092\u6d3b\u7528\u3059\u308b\u6a5f\u68b0\u5b66\u7fd2\u3067\nAI \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u52a0\u901f\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u30ea\u30af\u30a8\u30b9\u30c8\nHelly Dolly :\u30aa\u30fc\u30d7\u30f3\u306a\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb(LLM) \u3092\u81ea\u8eab\u3067\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\n2023\u5e745\u670818\u65e5\uff08\u6728\uff09\u5348\u5f8c4\u664200\u5206 (JST)\n\u3054\u767b\u9332Databricks \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3067\u6a5f\u68b0\u5b66\u7fd2\u3092\u5c55\u958b\u30de\u30cd\u30fc\u30b8\u30c9 MLflow\u30e2\u30c7\u30eb\u30ec\u30b8\u30b9\u30c8\u30eaML \u30e9\u30f3\u30bf\u30a4\u30e0\u30b3\u30e9\u30dc\u30ec\u30fc\u30b7\u30e7\u30f3\u578b Notebook\u7279\u5fb4\u91cf\u30b9\u30c8\u30a2\uff08Feature 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\u4e0a\u306b\u69cb\u7bc9\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30a8\u30f3\u30bf\u30fc\u30d7\u30e9\u30a4\u30ba\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u3001\u4fe1\u983c\u6027\u3001\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3067\u3001 ML 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/xiao-li\/#","text":"Xiao Li - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingXiao LiSenior Engineering Manager at DatabricksBack to speakersXiao Li is a senior engineering manager, Apache Spark Committer and PMC member at Databricks. His main interests are on Spark and database engine. Previously, he was an IBM master inventor and an expert on asynchronous database replication and consistency verification. He received his Ph.D. from University of Florida in 2011.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/\/ce-termsofuse","text":"Databricks Community Edition | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. 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The effective date of these Terms is the earliest to occur of the date you explicitly accept these Terms, or the date you first access or use the Community Edition Services.BY CLICKING TO ACCEPT THESE TERMS OR USING THE COMMUNITY EDITION SERVICES, YOU ARE REPRESENTING THAT YOU HAVE CAREFULLY READ, UNDERSTOOD AND AGREE TO BE BOUND BY THESE TERMS, INCLUDING WITHOUT LIMITATION THE ACCEPTABLE USE POLICY, THE SECTION TITLED \u201cYOUR DATA AND USE OF COMMUNITY EDITION - RESTRICTIONS APPLY\u201d AND THE SECTION REGARDING MANDATORY, BINDING ARBITRATION OF DISPUTES ENTITLED \u201cDISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVER\u201d.YOUR DATA AND USE OF COMMUNITY EDITION \u2013 RESTRICTIONS APPLYThere Are Strict Limits On What Your Data Can Include. \u00a0In order for us to provide the Community Edition Services to you at no charge, we have implemented certain cost saving elements within the architecture of the Community Edition Services including, among other things, the use of a multi-tenant environment with limited data security protections. \u00a0In addition, Databricks personnel have generally unrestricted access to your account (\u201cYour Account\u201d) and any data used or exposed to the Community Edition Services for the purposes of monitoring and improving the quality of the service. \u00a0Therefore, you should have no expectation of privacy regarding the data you submit or otherwise make available in any way to the Community Edition Services (collectively, \u201cYour Data\u201d) or the notebooks you create within or upload to the Community Edition Services (\u201cYour Notebooks\u201d, and collectively with Your Data, \u201cYour Content\u201d) and you must limit Your Content to only that data and other information that you can afford to lose, or have accessed, obtained or disseminated by other parties.Without limiting the foregoing, under no circumstances are you permitted to use with or make available to the Community Edition Services (such data, \u201cProhibited Data\u201d):any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by this Agreement;any data with respect to which your use and provision to Databricks pursuant to this Agreement would breach any agreement between you and any third party;any data that includes pornography, incitements to violence, terrorism or other wrongdoing, or obscene, illicit or deceptive materials of any kind;any data with respect to which its usage as contemplated herein would violate any applicable local, state, federal or other laws, regulations, orders or rules, including without limitation any privacy laws;any (w) bank, credit card or other financial account numbers or login credentials, (x) social security, tax, driver\u2019s license or other government-issued identification numbers, (y) health information identifiable to a particular individual; or (z) any data that would constitute \u201cspecial categories of data,\u201d \u201csensitive personal data,\u201d or any similar concept under applicable law; orany data that is prohibited by the Acceptable Use Policy.You Must Protect Access to Your Account and to Your Content. \u00a0You are responsible for safeguarding your password and you must make sure no one else has access to it. \u00a0Additionally, in order to facilitate the sharing and widespread use of the Community Edition Services, we enable you, at your discretion, to share with others access to Your Content. \u00a0You bear sole responsibility for protecting access to Your Content and for any and all liabilities that may result from the misuse of any sharing privileges granted by you to others. You agree and acknowledge Databricks has a passive role in the transmission, reception and use of Your Content, and Databricks does not take any initiative in the transmission, reception, or use of Your Content. Moreover, as between you and Databricks, you agree and acknowledge that you are solely responsible for your use of Your Content and that Databricks cannot supervise, control, direct, choose, verify, investigate, or evaluate Your Content or your actions with respect to Your Content that you transmit or receive using the Community Edition Services. You acknowledge that we may (but are not obligated to) remove or disable access to any of Your Content, or interrupt any or all services, at any time at our own discretion. You understand and acknowledge that we have the right (but no obligation) to do so if we believe, or are notified, that you have breached any provision of this Agreement (including copyright breach), or if we discontinue or restrict the service that enables you to transmit or receive Your Content.Limits Apply to How You Can Use the Community Edition Services. \u00a0You agree that your use of the Community Edition Services is subject to the Acceptable Use Policy.DATABRICKS\u2019 LEGAL PROTECTIONS & OTHER PROVISIONSDatabricks Intellectual Property Rights. \u00a0The Community Edition Services are protected in various ways by copyright, trademark, and other laws of the United States and other countries. \u00a0These Terms don\u2019t grant you any rights to use of Databricks\u2019 intellectual property, including trademarks, logos and other brand features, except those rights necessary for you to use the Community Edition Services as contemplated under these Terms. \u00a0Databricks welcomes your feedback but please note that we may use your comments and suggestions freely to improve the Community Edition Services or any of our other products or services, and accordingly you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Community Edition Services or otherwise use any feedback Databricks receives from you.The Community Edition Services are Provided \u201cAs Is\u201d With No Warranty. \u00a0Databricks cannot provide guarantees regarding the Community Edition Services. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, DATABRICKS MAKES NO WARRANTIES, EXPRESS OR IMPLIED, ABOUT THE SERVICES, WHICH ARE PROVIDED \u201cAS IS.\u201d \u00a0WE DISCLAIM ALL WARRANTIES OF ANY KIND, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, NON-INTERRUPTION, ACCURACY OR DATA SECURITY. \u00a0Some jurisdictions don\u2019t allow certain of these disclaimers, so they may not apply to you.We Require Your Indemnification. \u00a0You understand and agree that Databricks bears no liability whatsoever in the event you violate the restrictions and obligations imposed by these Terms regarding your use of the Community Edition Services or for the loss of, or unauthorized access to, Your Data, and that Databricks\u2019 willingness and ability to provide access to you to the Community Edition Services at no charge is contingent upon this understanding, and upon your accepting and adhering to all other provisions of these Terms. \u00a0You agree to indemnify, defend and hold harmless each of Databricks and its investors, directors, officers, employees, representatives and affiliates from any claims, costs, damages, liabilities or expenses (including reasonable attorneys\u2019 fees) arising out of any third party claim alleging that Your Data or your use of our services infringes the rights of, or has caused harm to, any party, or violates any law or regulation.Limitation on Liability. \u00a0TO THE FULLEST EXTENT PERMITTED BY LAW, IN NO EVENT WILL DATABRICKS BE LIABLE FOR ANY INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE, EXEMPLARY OR CONSEQUENTIAL DAMAGES OR ANY LOSS OF USE, DATA, BUSINESS OR PROFITS, REGARDLESS OF LEGAL THEORY, REGARDLESS OF WHETHER DATABRICKS HAS BEEN WARNED OF THE POSSIBILITY OF SUCH DAMAGES, AND EVEN IF A REMEDY FAILS OF ITS ESSENTIAL PURPOSE. \u00a0ADDITIONALLY, DATABRICKS\u2019 AGGREGATE LIABILITY TO YOU FOR ALL CLAIMS RELATING TO THE SERVICES SHALL NOT EXCEED THE GREATER OF THE TOTAL OF ANY AMOUNTS YOU MAY HAVE PAID US IN FEES FOR ANY SERVICE IN THE SIX MONTHS IMMEDIATELY PRIOR TO THE EVENT FIRST GIVING RISE TO ANY SUCH LIABILITY OR $500 (FIVE HUNDRED DOLLARS). THE FOREGOING LIMITATIONS AND EXCLUSIONS SHALL NOT APPLY WITH RESPECT TO ANY LIABILITY ARISING UNDER FRAUD, FRAUDULENT MISREPRESENTATION, GROSS NEGLIGENCE, OR ANY OTHER LIABILITY THAT CANNOT BE LIMITED OR EXCLUDED BY LAW. Some jurisdictions don\u2019t allow the types of limitations in this paragraph, so they may not apply to you. \u00a0IN THESE JURISDICTIONS, EACH PARTY\u2019S LIABILITY WILL BE FURTHER LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW. You agree that this limitation of liability section is intended to allocate the risks between the parties, and that but for this limitation of liability, Databricks would not make available the Community Edition Services.Entire Agreement; No Third Party Rights. These Terms constitute the entire agreement between you and Databricks concerning the Community Edition Services and these Terms create no third party beneficiary rights.Termination, Modification, Waiver & Assignment. \u00a0Either of us may suspend or terminate your use of the Community Edition Services or delete Your Account or Your Content at any time and for any reason (including without limitation for any suspected violations of the Acceptable Use Policy); however, obligations of these Terms that by their nature should survive termination shall so survive. \u00a0In addition, we may revise these Terms from time to time, and will always post the most current version on our website. \u00a0If we elect to terminate your access to the Community Edition Services or delete Your Account or Your Content, or if a revision of these Terms meaningfully reduces your rights, we will make a reasonable attempt to notify you (by, for example, sending a message to the email address associated with your account or posting for a reasonable time period a message to the login page of the Community Edition Services) unless Databricks deems it necessary to suspend or terminate Your Account without notice. \u00a0By continuing to use or access the Community Edition Services after the revisions come into effect, you agree to be bound by the revised Terms. Databricks' failure to enforce a provision of these Terms is not a waiver of its right to do so later. If a provision of these Terms is found unenforceable, the remaining provisions of the Terms will remain in full effect and an enforceable term will be substituted reflecting our intent as closely as possible, provided that questions of unenforceability regarding the Arbitration Agreement shall be resolved according to the Severability Section of the Arbitration Agreement. \u00a0You may not assign or transfer any of your rights under these Terms, and any such attempt will be void. Databricks may assign these Terms and\/or its rights under these Terms to any of its affiliates or to any successor in interest.DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVERInformal Resolution. You agree with us that, if either of us has concerns, we must first work together to resolve any dispute informally without resorting to legal action. \u00a0You agree to contact us at [email\u00a0protected] in the event you have a dispute prior to bringing a formal claim against Databricks. \u00a0If the dispute is not resolved within 30 calendar days from the notice date, either of us may bring a claim subject to the procedures set forth below. You and Databricks agree to the jurisdiction of the Northern District of California to resolve any dispute, claim, or controversy that relates to or arises in connection with these Terms (and any non-contractual disputes\/claims relating to or arising in connection with them) and is not subject to mandatory arbitration as set forth below (the \u201cArbitration Agreement\u201d). \u00a0Any disputes not subject to mandatory arbitration are subject to the laws of the state of California, without regard to choice or conflicts of law principles.Arbitration Agreement. \u00a0If you are located within the United States, you and Databricks agree that any dispute, claim, or controversy between you and Databricks arising in connection with or relating in any way to these Terms or to your relationship with Databricks as a user of the Community Edition Services (whether based in contract, tort, statute, fraud, misrepresentation, or any other legal theory, and whether the claims arise during or after the termination of these Terms) will be determined by mandatory binding individual (not class) arbitration. You and Databricks further agree that the arbitrator shall have the exclusive power to rule on his or her own jurisdiction, including any objections with respect to the existence, scope or validity of the Arbitration Agreement or to the arbitrability of any claim or counterclaim. The Arbitration Agreement will survive termination of the Terms. \u00a0You and Databricks agree that the Federal Arbitration Act applies and governs the interpretation and enforcement of the Arbitration Agreement (despite the choice of law provision above).Exceptions to Arbitration. Notwithstanding the prior clause, you and Databricks both agree that nothing in this Arbitration Agreement will be deemed to waive, preclude, or otherwise limit either of our rights, at any time, to (1) bring an individual action in a U.S. small claims court or (2) bring an individual action seeking only temporary or preliminary individualized injunctive relief in a court of law, pending a final ruling from the arbitrator. In addition, this Arbitration Agreement doesn\u2019t stop you or us from bringing issues to the attention of federal, state, or local agencies. Such agencies can, if the law allows, seek relief against us on your behalf (or vice versa).Prohibition of Class and Representative Actions and Non-Individualized Relief. You and Databricks agree that each of us may bring claims against the other only on an individual basis and not as a plaintiff or class member in any purported class or representative action or proceeding. \u00a0Unless both you and Databricks agree otherwise, the arbitrator(s) may not consolidate or join more than one person\u2019s or party\u2019s claims and may not otherwise preside over any form of a consolidated, representative or class proceeding. \u00a0Also, the arbitrator(s) may award relief (including monetary, injunctive and declaratory relief) only in favor of the individual party seeking relief and only to the extent necessary to provide relief necessitated by that party\u2019s individual claim(s). \u00a0Any relief awarded cannot affect other Databricks customers.Arbitration Procedures. Arbitration is more informal than a lawsuit in court. \u00a0Arbitration uses a neutral arbitrator or arbitrators instead of a judge or jury, and court review of an arbitration award is very limited. \u00a0However, the arbitrator(s) can award the same damages and relief on an individual basis that a court can award to an individual. The arbitrator(s) also must follow the terms of these Terms as a court would. \u00a0The arbitration will be conducted by the American Arbitration Association (referred to as the \"AAA\") under its rules and procedures, including the AAA's Consumer Arbitration Rules (as applicable), unless you have accepted these Terms as a representative of a business entity, in which case AAA\u2019s Commercial Arbitration Rules shall govern (as applicable), in each case as modified by this Arbitration Agreement. \u00a0The AAA's rules and forms to commence arbitration are available at www.adr.org. A party who intends to seek arbitration must first send the other party, if to Databricks, by certified mail, a completed Demand for Arbitration. You should send this notice to Databricks at: Databricks, Inc., Attn: Legal Department, Re: Demand for Arbitration, 160 Spear St., Ste. 1300, San Francisco, CA 94105 USA (with a copy to [email\u00a0protected]). \u00a0Databricks will send any notice to you to the address we have on file associated with your Databricks account (which may solely be at your account email address); it is your responsibility to keep your address up to date. All information called for in the notice must be provided including a description of the nature and basis of the claims the party is asserting and the relief sought. The arbitration shall be held in the county in which you reside or at another mutually agreed location. \u00a0If the value of the relief sought is $10,000 or less, you or Databricks may elect to have the arbitration conducted by telephone or based solely on written submissions, which election shall be binding on you and Databricks subject to the discretion of the arbitrator(s) to require an in-person hearing, if the circumstances warrant. In cases where an in-person hearing is held, you and\/or Databricks may attend by telephone, unless the arbitrator(s) require otherwise. Any settlement offer made by you or Databricks shall not be disclosed to the arbitrator(s). The arbitrator(s) will decide the substance of all claims in accordance with applicable law, including recognized principles of equity, and will honor all claims of privilege recognized by law. \u00a0The arbitrator(s) shall not be bound by rulings in prior arbitrations involving different Databricks customers, but is\/are bound by rulings in prior arbitrations involving the same Databricks customer to the extent required by applicable law. The award of the arbitrator(s) shall be final and binding, and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof.Costs of Arbitration. Payment of all filing, administration, and arbitrator fees will be governed by the AAA's rules (either Consumer or Commercial, as applicable), unless otherwise stated in this Arbitration Agreement. \u00a0If the value of the relief sought by an individual is $10,000 or less, at your request, Databricks will pay all filing, administration, and arbitrator fees associated with the arbitration. Any request for payment of fees by Databricks should be submitted by mail to the AAA along with your Demand for Arbitration and Databricks will make arrangements to pay all necessary fees directly to the AAA. \u00a0If the value of the relief sought by an individual is more than $10,000 and you are able to demonstrate that the costs of accessing arbitration will be prohibitive as compared to the costs of accessing a court for purposes of pursuing litigation on an individual basis, Databricks will pay as much of the filing, administration, and arbitrator fees as the arbitrator(s) deem necessary to prevent the cost of accessing the arbitration from being prohibitive. \u00a0In the event the arbitrator(s) determine the claim(s) you assert in the arbitration to be frivolous, you agree to reimburse Databricks for all fees associated with the arbitration paid by Databricks on your behalf that you otherwise would be obligated to pay under the AAA's rules.Severability. With the exception of any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above, if a court decides that any part of this Arbitration Agreement is invalid or unenforceable, the other parts of this Arbitration Agreement shall still apply. If a court decides that any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above is invalid or unenforceable because it would prevent the exercise of a non-waivable right to pursue public injunctive relief, then any dispute regarding the entitlement to such relief (and only that relief) must be severed from arbitration and may be litigated in court; in such case you irrevocably consent to the personal jurisdiction of the state and federal courts in the Northern District of California and such dispute shall be governed by the laws of the state of California, without regard to choice or conflicts of law principles. All other disputes subject to arbitration under the terms of the Arbitration Agreement shall be arbitrated under its terms.Amendments to Arbitration Agreement. Notwithstanding any provision in the Terms to the contrary, you and we agree that if we make any amendment to this Arbitration Agreement (other than an amendment to any notice address or website link provided herein) in the future, that amendment shall not apply to any claim that was filed in a legal proceeding against Databricks prior to the effective date of the amendment. \u00a0The amendment shall apply to all other disputes or claims governed by this Arbitration Agreement that have arisen or may arise between you and Databricks. We will notify you of amendments to this Arbitration Agreement by posting the amended terms on https:\/\/www.databricks.com\/legal\/ce-termsofuse at least 30 days before the effective date of the amendments and by providing notice through email where possible. \u00a0If you do not agree to these amended terms, you may close Your Account within the 30-day period and you will not be bound by the amended terms.Last Updated April 9, 2019ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/hari-shankar","text":"Hari Shankar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHari ShankarSenior Director, R&D at VizioBack to speakersHari Shankar is the Senior Director of R&D, Data Engineering, for Vizio, the connected home and entertainment leader. At Vizio, Hari was responsible for leading their Databricks and lakehouse migration, as well as managing their AdTech platform strategy. Prior to Vizio, Hari worked at Samsung, NetApp, and Sun Microsystems in technical leadership roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-are-datasets","text":"What are Datasets?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatasetsAll>DatasetsTry Databricks for freeGet StartedDatasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recall that DataFrames are a distributed collection of objects of type Row, which can hold various types of tabular data. The Dataset API allows users to assign a Java class to the records inside a DataFrame, and manipulate it as a collection of typed objects, similar to a Java ArrayList or Scala Seq. The APIs available on Datasets are type-safe, meaning that you cannot accidentally view the objects in a Dataset as being of another class than the class you put in initially. This makes Datasets especially attractive for writing large applications where multiple software engineers must interact through well-defined interfaces. The Dataset class is parametrized with the type of object contained inside: Dataset in Java and Dataset[T] in Scala. As of Spark 2.0, the types T supported are all classes following the JavaBean pattern in Java, and case classes in Scala. These types are restricted because Spark needs to be able to automatically analyze the type T and create an appropriate schema for the tabular data inside your Dataset. Additional ResourcesDatabricks Datasets DocumentationCOVID-19 Datasets Now Available on DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/industries\/manufacturing-industry-solutions","text":"L\u00f6sungen f\u00fcr das verarbeitende Gewerbe \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse f\u00fcr FertigungsunternehmenSenken Sie Kosten, steigern Sie die Produktivit\u00e4t und vereinheitlichen Sie Ihr Daten\u00f6kosystem auf der einzigen Datenplattform, die speziell f\u00fcr die Verwendung von Daten in Fertigungsunternehmen entwickelt wurde.RegistrierenKontaktGeringere Gesamtbetriebskosten. Bessere Performance. Gr\u00f6\u00dfere Skalierbarkeit.Lakehouse f\u00fcr FertigungsunternehmenWenn Sie Ihre Daten-, Analytics- und KI-Workloads mit integrierter Freigabe und Governance vereinheitlichen, k\u00f6nnen interne und externe Teams bei Bedarf auf die n\u00f6tigen Daten zugreifen.Wirkung \u00fcber die gesamte Wertsch\u00f6pfungsketteKundenbindungPr\u00e4zise Ergebnisse und reibungslose Interaktionen f\u00fcr KundenMit einer 360-Grad-Sicht auf Kunden, Betrieb und Anlagen k\u00f6nnen Sie \u00fcber den gesamten Produktlebenszyklus hinweg h\u00f6chste Betriebszeit, Servicequalit\u00e4t und wirtschaftlichen Wert bieten und so die Personalisierung f\u00fcr Kunden, proaktiven Au\u00dfendienst und differenzierte unternehmenskritische L\u00f6sungen f\u00f6rdern.BetriebseffizienzMitarbeiterproduktivit\u00e4tProduktinnovationFertigungsl\u00f6sungen und PartnerKompromisslose Datenanalyse- und KI-L\u00f6sungen, die speziell f\u00fcr Fertigungsunternehmen entwickelt wurdenDatabricks Solution Accelerators sind speziell entwickelte Leitf\u00e4den\u00a0\u2013 voll funktionsf\u00e4hige Notebooks und Best Practices\u00a0\u2013 f\u00fcr schnellere Ergebnisse in der Fertigungsbranche. Sparen Sie Zeit beim Entdecken, Entwerfen, Entwickeln und Testen in Anwendungsf\u00e4llen wie digitalen Zwillingen, Gesamtanlageneffektivit\u00e4t, Prognosen und mehr.Monitoring der Gesamtanlageneffektivit\u00e4t und KPIsEine leistungsf\u00e4hige und skalierbare End-to-End-Ger\u00e4te\u00fcberwachung erzielen\nErfassen und verarbeiten Sie schrittweise Daten von Sensor-\/IoT-Ger\u00e4ten in einer Vielzahl von Formaten und berechnen Sie KPIs und Metriken, um wertvolle Erkenntnisse zu gewinnen.Erste SchrittePrognosen auf TeileebeneDen Bedarf auf Teileebene f\u00fcr eine optimierte Fertigung prognostizieren\nPrognostizieren Sie Ihren Bedarf auf Teileebene statt auf aggregierter Ebene, um Unterbrechungen in Ihrer Lieferkette zu minimieren und den Umsatz zu steigern.Erste SchritteDigitale ZwillingeDie betriebliche Effizienz steigern und die Entscheidungsfindung verbessern\nVerarbeiten Sie reale Daten in Echtzeit, beziehen Sie erkenntnisreiche Informationen durch umfassende Datenanalysen, liefern Sie sie an mehrere nachgelagerte Anwendungen und optimieren Sie den Anlagenbetrieb mit datengesteuerten Entscheidungen.Erste SchritteAccelerators f\u00fcr Fertigungsunternehmen erkundenWir sind eine Partnerschaft mit f\u00fchrenden Beratungsunternehmen eingegangen, um innovative, branchenspezifische L\u00f6sungen zu liefern. Databricks Brickbuilder Solutions helfen Ihnen, Kosten zu senken und den Wert Ihrer Daten zu steigern. Gest\u00fctzt auf jahrzehntelange Branchenkenntnis \u2013 und entwickelt f\u00fcr die Databricks Lakehouse-Plattform \u2013 sind die Brickbuilder Solutions genau auf Ihre Bed\u00fcrfnisse zugeschnitten.Intelligente Fertigung Nutzen Sie Ihre Daten, f\u00f6rdern Sie die Interoperabilit\u00e4t und stellen Sie mithilfe von Analysen und KI umfassende Informationen in gro\u00dfem Ma\u00dfstab bereit.Mehr InformationenQualit\u00e4tspr\u00fcfungenAutomatisieren Sie Ihre Qualit\u00e4tskontrolle mit Computer Vision, um Defekte, Fremdk\u00f6rper, Anomalien oder falsche Einstellungen zu erkennen.Mehr InformationenVorausschauendes Management von LieferrisikenVerbessern Sie die Sichtbarkeit der n-ten Ebene in Auftragsabl\u00e4ufen und bei der Lieferantenperformance, um die Effizienz zu steigern, Ausnahmen zu verwalten und die Ausfallsicherheit zu verbessern.Mehr InformationenAlle Partnerl\u00f6sungen anzeigen\u201eDatabricks Lakehouse versetzt uns in die Lage, die Eintrittsbarriere f\u00fcr den Datenzugriff in unserem gesamten Unternehmen zu senken, damit wir die innovativsten und zuverl\u00e4ssigsten Elektrofahrzeuge der Welt bauen k\u00f6nnen.\u201c\n\u2013 Wassym Bensaid, Vice President of Software Development, Rivian\n\u201eDie Verwendung von Databricks hat sich im Laufe der Jahre erheblich ausgeweitet. Anfangs haben wir Databricks als Big Data- und KI-Plattform genutzt, aber der Anwendungsbereich hat sich ausgeweitet. Wir haben eine v\u00f6llig andere Klasse von Citizen Engineers und Data Scientists, die Databricks als modernes Business-Intelligence-Tool verwenden, um intelligentere Gesch\u00e4ftsentscheidungen zu treffen.\u201c\n\u2013 Daniel Jeavons, General Manager, Advanced Analytics CoE, Shell\n\u201eDie Databricks-Plattform hat uns geholfen, Risiken f\u00fcr die Triebwerksverf\u00fcgbarkeit zu minimieren, Vorlaufzeiten f\u00fcr Ersatzteile zu verk\u00fcrzen und die Lagerumschlagszeiten effizienter zu gestalten\u00a0\u2013 all dies erm\u00f6glicht es uns, TotalCare, das f\u00fchrende PBH-Wartungsprogramm (Power-by-the-Hour) der Luftfahrtbranche, bereitzustellen.\u201c\n\u2013 Stuart Hughes, Chief Information and Digital Officer, Rolls-Royce Civil Aerospace\nRessourcenE-BookERP-Daten nutzbringend einsetzenWebinareVerbesserung der vorausschauenden Wartung f\u00fcr Unternehmen des verarbeitenden Gewerbes mit Daten und KIE-BookVier Kr\u00e4fte, die die intelligente Fertigung vorantreibenM\u00f6chten Sie loslegen?Wir w\u00fcrden uns freuen, Ihre Gesch\u00e4ftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/siddharth-bhai","text":"Siddharth Bhai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSiddharth BhaiSr. Manager, Product Management at DatabricksBack to speakersSiddharth Bhai is a product management leader at Databricks, with 15+ years of experience, including long stints at Google and Microsoft. He has deep experience in identity, security, provisioning, and cloud computing. He has spoken at major industry conferences, including Hybrid Identity Protection, Directory Experts Conference, Microsoft TechEd, and Google Cloud Next. This summer, he\u2019s interested in hearing about how teams in the real world are using Databricks. Come say hi if you see him!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/legal\/security-addendum","text":"Security Addendum | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesSecurity AddendumThis Security Addendum is incorporated into and made a part of the written agreement between Databricks, Inc. (\u201cDatabricks\u201d) and Customer that references this Security Addendum (\u201cAgreement\u201d). Databricks maintains a comprehensive documented security program that is based on industry standard security frameworks including ISO 27001 and ISO 27018 (the \u201cSecurity Program\u201d). Pursuant to the Security Program, Databricks implements and maintains administrative, physical, and technical security measures to protect the Platform Services and Support Services and the security and confidentiality of Customer Content (including any Customer Personal Data that may be contained therein) (each as defined in the Agreement) under Databricks\u2019 control that is processed by Databricks in its provisioning of the Platform Services or Support Services (the \u201cSecurity Measures\u201d). Databricks\u2019 compliance with this Addendum shall be deemed to satisfy any more general measures included within any Agreement, including the Service Specific Terms. In accordance with its Security Program, Databricks will, when any Customer Content is under its control: (i) comply with the Security Measures identified below with respect to such Customer Content, and (ii) where relevant, keep documentation of such Security Measures. Databricks regularly tests and evaluates its Security Program, and may review and update this Security Addendum at any time without notice, provided that such updates are equivalent (or enhance) security and do not materially diminish the level of protection afforded to Customer Content by these Security Measures.Deployment ModelShared Responsibility. Databricks operates in a shared responsibility model, where both Databricks and the Customer maintain security responsibilities. This is covered in more detail in our Documentation.Architecture. Databricks is a hybrid platform-as-a-service offering. The components responsible for managing and controlling the Platform Services are referred to as the \u2018Databricks Control Plane\u2019 and are hosted within a Databricks Cloud Service Provider account. The compute resources that perform data processing operations are referred to as the \u201cData Plane\u201d. For certain Cloud Service Providers, the Data Plane may either be deployed in the Customer\u2019s Cloud Service Provider account (known as the \u2018Customer Data Plane\u2019) or, for Databricks Serverless Compute, in a Databricks-controlled Cloud Service Provider account (known as the \u2018Databricks Data Plane\u2019).\u00a0 Data Plane shall refer to both Customer Data Plane and Databricks Data Plane unless otherwise specified.Compute Resources. Compute resources are created and coordinated by the Databricks Control Plane and deployed into the Data Plane. Compute resources are launched as new virtual machines that leverage the latest base image and Databricks source code and do not have data from previous machines. When compute resources terminate, the data on their local hard drives is overwritten by Databricks or by the Cloud Service Provider.Data Storage of Customer Content.\nCustomer Data and Customer Results.\nCustomer Control. Most Customer Data is stored within the Customer\u2019s own Cloud Service Provider account at rest (e.g., within Customer\u2019s AWS S3 bucket) or within other Systems under Customer\u2019s control.\u00a0 Customer may choose where this Customer Data resides (other than the DBFS root, which is deployed into a storage bucket within the applicable Cloud Service Provider in the region in which the Data Plane is deployed). Please see the Documentation for more details.Databricks Control.\u00a0 Small amounts of Customer Data may be stored within the Databricks Control Plane, including Customer Results and metadata about Customer Data (e.g., contained within the metastore). Databricks offers Customers options regarding the storage of certain Customer Content within the Platform Services (e.g., the location of Customer Results created by the use of interactive notebooks). Please see the Documentation for more details.Customer Instructional Input. Customer Instructional Input is stored at rest within the Databricks Control Plane.Deployment Region. Customers may specify the region(s) where their Platform Services Workspaces are deployed. Customers can choose to deploy the Data Plane into any supported Databricks region. The Databricks Control Plane is deployed into the same region. Databricks will not, without Customers\u2019 permission, move a Customer Workspace into a different region. See the Documentation for details specific to Customer\u2019s Cloud Service Provider.Databricks\u2019 Audits & Certifications. Databricks uses independent third-party auditors to assess the Databricks Security Program at least annually, as described in the following audits, regulatory standards, and certifications:\nSOC 2 Type II (report available under NDA)ISO 27001ISO 27018HIPAA (AWS, for HIPAA-compliant deployments)PCI DSS (AWS, for PCI-compliant deployments)Administrative ControlsGovernance. Databricks\u2019 Chief Security Officer leads the Databricks\u2019 Information Security Program and develops, reviews, and approves (together with other stakeholders, such as Legal, Human Resources, Finance, and Engineering) Databricks\u2019 Security Policies (as defined below).Change Management. Databricks maintains a documented change management policy, reviewed annually, which includes but is not limited to, evaluating changes of or relating to systems authentication.ISMS; Policies and Procedures. Databricks has implemented a formal Information Security Management System (\u201cISMS\u201d) in order to protect the confidentiality, integrity, authenticity, and availability of Databricks' data and information systems, and to ensure the effectiveness of security controls over data and information systems that support operations. The Databricks Security Program implemented under the ISMS includes a comprehensive set of privacy and security policies and procedures developed and maintained by the security, legal, privacy, and information security teams (\u201cSecurity Policies\u201d). The Security Policies are aligned with information security standards (such as ISO 27001) and cover topics including but not limited to: security controls when accessing Customer Workspaces; confidentiality of Customer Content; acceptable use of company technology, systems and data; processes for reporting security incidents; and privacy and security best practices. The Security Policies are reviewed and updated annually.Personnel Training. Personnel receive comprehensive training on the Security Policies upon hire and refresher trainings are given annually. Personnel are required to certify and agree to the Security Policies and personnel who violate the Security Policies are subject to disciplinary action, including warnings, suspension and up to (and including) termination.Personnel Screening and Evaluation. All personnel undergo background checks prior to onboarding (as permitted by local law), which may include, but are not limited to, criminal record checks, employment history verification, education verification, and global sanctions and enforcement checks. Databricks uses a third-party provider to conduct screenings, which vary by jurisdiction and comply with applicable local law. Personnel are required to sign confidentiality agreements.Monitoring & Logging. Databricks employs monitoring and logging technology to help detect and prevent unauthorized access attempts to its network and equipment.Access Review. Active users with access to the Platform Services are reviewed at least quarterly and are promptly removed upon termination of employment. As part of the personnel offboarding process, all accesses are revoked and data assets are securely wiped.Third Party Risk Management. Databricks assesses the security compliance of applicable third parties, including vendors and subprocessors, in order to measure and manage risk. This includes, but is not limited to, conducting a security risk assessment and due diligence prior to engagement and reviewing external audit reports from critical vendors at least annually. In addition, applicable vendors and subprocessors are required to sign a data processing agreement that includes compliance with applicable data protection laws, as well as confidentiality requirements.Physical and Environmental ControlsDatabricks Corporate Offices. Databricks has implemented administrative, physical, and technical safeguards for its corporate offices. These include, but are not limited to, the below:\nVisitors are required to sign in, acknowledge and accept an NDA, wear an identification badge, and be escorted by Databricks personnel while on premisesDatabricks personnel badge into the officesBadges are not shared or loaned to others without authorizationPhysical entry points to office premises are recorded by CCTV and have an access card verification system at every door, allowing only authorized employees to enter the office premisesEquipment and other Databricks-issued assets are inventoried and trackedOffice Wi-Fi networks are protected with encryption, wireless rogue detection, and Network Access ControlCloud Service Provider Data Centers. Databricks regularly reviews Cloud Service Provider audits conducted in compliance with ISO 27001, SOC 1, SOC 2, and PCI-DSS. Security controls include, but are not limited to the list below:\nBiometric facility access controlsVisitor facility access policies and procedures24-hour armed physical securityCCTV at ingress and egressIntrusion detectionBusiness continuity and disaster recovery plansSmoke detection sensors and fire suppression equipmentMechanisms to control temperature, humidity and water leaksPower redundancy with backup power supplySystems & Network SecurityPlatform Controls.\nIsolation. Databricks leverages multiple layers of network security controls, including network-level isolation, for separation between the Databricks Control Plane and Customer Data Plane, and between Workspaces within the Databricks Data Plane. See documentation on Serverless Compute for more details on the difference between Serverless Compute and non-Serverless Compute.Firewalls & Security Groups. Firewalls are implemented as network access control lists or security groups within the Cloud Service Provider's account. Databricks also configures local firewalls or security groups within the Customer Data Plane.Hardening.Databricks employs industry standards to harden images and operating systems under its control that are deployed within the Platform Services, including deploying baseline images with hardened security configuration such as disabled remote root login, isolation of user code, and images are regularly updated and refreshed.For Systems under Databricks control supporting the production data processing environment, Databricks tracks security configurations against industry standard baselines such as CIS and STIG.EncryptionEncryption of data-in-transit. Customer Content is encrypted using cryptographically secure protocols (TLS v.1.2 or higher) in transit between (1) Customer and the Databricks Control Plane and (2) the Databricks Control Plane and the Data Plane.\u00a0 Additionally, depending on functionality provided by the Cloud Service Provider, Customers may optionally encrypt communications between clusters within the Data Plane (e.g., by utilizing appropriate AWS Nitro instances).Encryption of data-at-rest. Customer Content is encrypted using cryptographically secure protocols (AES-128 bit, or the equivalent or better) while at rest within the Databricks Control Plane.\u00a0 Additionally, depending on functionality provided by the Cloud Service Provider, Customers may optionally encrypt at rest Customer Content within the Data Plane. See Documentation on \u2018local disk encryption\u2019 for more details.Review. Cryptographic standards are periodically reviewed and selected technologies and ciphers are updated in accordance with assessed risk and market acceptance of new standards.Customer Options; Responsibilities. Customers may choose to leverage additional encryption options for data in transit within the Customer Data Plane or Databricks Data Plane as described in the Documentation (e.g., Customer may utilize AWS Nitro EC2 instances within the Customer Data Plane to provide additional encryption in transit). Customer shall, based on the sensitivity of the Customer Content, configure the Platform Services and Customer Systems to encrypt Customer Content where appropriate (e.g., by enabling encryption at rest for data stored within AWS S3).Monitoring & LoggingIntrusion Detection Systems. Databricks leverages security capabilities provided natively by Cloud Service Providers for security detection.Audit Logs.\nGeneration. Databricks generates audit logs from Customer\u2019s use of the Platform Services. The logs are designed to store information about material events within the Platform Services.Delivery. Customer may, depending on the entitlement tier of the Platform Services, enable delivery of audit logs.\u00a0 It is Customer\u2019s responsibility to configure this option.Integrity.\u00a0 Databricks stores audit logs in a manner designed to protect the audit logs from tampering.Retention. Databricks stores audit logs for at least one year.Penetration Testing. Databricks conducts third-party penetration tests at least annually, employs in-house offensive security personnel, and also maintains a public bug bounty program.Vulnerability Management & Remediation. Databricks regularly runs authenticated scans against representative hosts in the SDLC pipeline to identify vulnerabilities and emerging security threats that may impact the Data Plane and Databricks Control Plane. Databricks will use commercially reasonable efforts to address critical vulnerabilities within 14 days, high severity within 30 days, and medium severity within 60 days measured from, with respect to publicly declared third party vulnerabilities, the date of availability of a compatible, vendor-supplied patch, or for internal vulnerabilities, from the date such vulnerability is confirmed. Databricks leverages the National Vulnerability Database\u2019s Common Vulnerability Scoring System (CVSS), or where applicable, the U.S.-Cert rating, combined with an internal analysis of contextual risk to determine criticality.Patching.\nControl Plane. Databricks deploys new code to the Databricks Control on an ongoing basis.Data Plane. New Data Plane virtual machines use the latest applicable source code and system images upon launch and do not require Databricks to patch live systems. Customers are encouraged to restart always-on clusters on a periodic basis to take advantage of security patches.Databricks Personnel Login to Customer Workspaces.\u00a0 Databricks utilizes an internal technical and organizational control tool called \u2018Genie\u2019 that permits Databricks personnel to log in to a Customer Workspace to provide support to our Customers and permits limited Databricks engineering personnel to log in to certain Platform Services infrastructure.\u00a0 Customer may optionally configure certain limitations on the ability for Databricks personnel to access Customer Workspaces. Please see Documentation on \u2018Genie\u2019 for more details, including on which Cloud Service Providers this is offered.Corporate Controls.Access ControlsAuthentication. Databricks personnel are authenticated through single sign-on (SSO), 802.1x (or similar) where applicable, and use a unique user ID and password combination and multi-factor authentication. Privileges are consistent with least privilege principles. Security Policies prohibits personnel from sharing or reusing credentials, passwords, IDs, or other authentication information. If your identity provider supports the SAML 2.0 protocol, you can use Databricks\u2019 SSO to integrate with your identity provider.Role-Based Access Controls (RBACs). Only authorized roles are allowed to access systems processing customer and personal data. Databricks enforces RBACs (based on security groups and access control lists), and restricts access to Customer Content based on the principle of 'least privilege' and segregation of responsibilities and duties.Pseudonymization. Information stored in activity logs and databases are protected where appropriate using a unique randomized user identifier to mitigate risk of re-identification of data subjects.Workstation Controls: Databricks enforces certain security controls on its workstations used by personnel, including:\nFull-disk encryptionAnti-malware softwareAutomatic screen lock after 15 minutes of inactivitySecure VPNIncident Detection & ResponseDetection & Investigation. Databricks\u2019 dedicated Detection engineering team deploys and develops intrusion detection monitoring across its computing resources, with alert notifications sent to the Security Incident Response Team (SIRT) for triage and response. The SIRT employs an incident response framework to manage and minimize the effects of unplanned security events.Security Incidents; Security Breaches. \u201cSecurity Breach\u201d means a breach of security leading to any accidental or unlawful destruction, loss, alteration, unauthorized disclosure of, or access to Customer Data under Databricks control. A \u201cSecurity Incident\u201d is any actual or attempted breach of security that does not rise to the level of a Security Breach. A Security Breach shall not include an unsuccessful attempt or activity that does not compromise the security of Customer Data, including (without limitation) pings and other broadcast attacks of firewalls or edge servers, port scans, unsuccessful log-on attempts, denial of service attacks, packet sniffing (or other unauthorized access to traffic data that does not result in access beyond headers) or similar incidents. Databricks maintains a record of known Security Incidents and Security Breaches that includes description, dates and times of relevant activities, and incident disposition. Suspected and confirmed Security Incidents are investigated by security, operations, or support personnel; and appropriate resolution steps are identified and documented. For any confirmed Security Incidents, Databricks will take appropriate, reasonable steps to minimize product and Customer damage or unauthorized disclosure. All incidents are logged in an incident tracking system that is subject to auditing on an annual basis.Communications & Cooperation. In accordance with applicable data protection laws, Databricks will notify Customer of a Security Breach for which that Customer is impacted without undue delay after becoming aware of the Security Breach, and take appropriate measures to address the Security Breach, including measures to mitigate any adverse effects resulting from the Security Breach.Backups, Business Continuity, and Disaster RecoveryBusiness Continuity and Disaster Recovery. Databricks Business Continuity (BC) and Disaster Recovery (DR) plans are reviewed and drills are conducted annually.Data Resiliency. Databricks performs backups for the Databricks Control Plane (including any Customer Instructional Input stored therein), generally managed by the Cloud Service Provider capabilities, for data resiliency purposes in the case of a critical systems failure. While Databricks backs up Customer notebooks that persist in the Databricks Control Plane as part of its systems resiliency, those backups are maintained only for emergency recovery purposes and are not available for Customers to use on request for recovery purposes.No Data Restoration. Due to the hybrid nature of the Databricks Platform, Databricks does not provide backup for Customer Content, and Databricks is unable to restore an individual Customer\u2019s Instructional Input upon request. To assist Customers in backing up Customer Instructional Input, Databricks provides certain features within the Platform Services (like the ability to synchronize notebooks via a customer\u2019s Github or Bitbucket account).Self-service Access. Databricks makes available certain features within the Platform Services that permit customers to access, export and delete certain Customer Content (e.g., notebooks) contained within the Databricks Control Plane. Please see the Documentation related to \u2018manage workspace storage\u2019.Customer Managed Backups. Customers retain ownership of their Customer Content and must manage their own backups, including to the extent applicable, enabling backup within the Systems in which the Customer Data is stored.Data Deletion.\nDuring Use. The Platform Services provide Customers with functionality that permit Customers to delete Customer Content under Databricks\u2019 control.Upon Workspace Cancellation. Customer Content contained within a Customer Workspace is permanently deleted within thirty (30) days following cancellation of the Workspace.Secure Software Development Lifecycle (\u201cSDLC\u201d)Security Champions. Databricks Engineering and the security organization co-run a Security Champions program, in which senior engineers are trained and socialized as virtual members of the security team. Security Champions are available to all engineering staff for design or code review.Security Design Review. Feature designs are assessed by security personnel for their security impact to the Databricks Platform, for example, additions or modifications to access controls, data flows, and logging.Security Training. Engineers are required to take Secure SDLC training, including but not limited to, content provided by OWASP.Peer Code Review. All production code must be approved through a peer code review process.Change Control. Databricks\u2019 controls are designed to securely manage assets, configurations, and changes throughout the SDLC.Code Scanning. Static and dynamic code scans are regularly run and reviewed.Penetration Testing. As part of the Security Design Review process, certain features are identified and subjected to penetration testing prior to release.Code Approval. Functional owners are required to approve code in their area of responsibility prior to the code being merged for production.Multi-Factor Authentication. Accessing the Databricks code repository requires Multi-Factor Authentication.Code Deployment. Production code is deployed via automated continuous integration \/ continuous deployment (CI\/CD) pipeline processes.\u00a0 The release management teams are separated from the engineering teams that build the product.Production Separation. Databricks separates production Platform Services Systems from testing and development Platform Services Systems.Last Revised September 25, 2021.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
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Try adjusting the filters or start a new search.reset the list\u696d\u7a2e\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u767a\u6848\u304b\u3089 PoC \u307e\u3067\u3092 2 \u9031\u9593\u3067\u5b8c\u4e86Databricks \u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u306f\u3001\u6210\u679c\u5275\u51fa\u3092\u52a0\u901f\u3059\u308b\u30d5\u30eb\u6a5f\u80fd\u306e Notebook \u3084\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u3092\u542b\u3080\u76ee\u7684\u306b\u6cbf\u3063\u305f\u30ac\u30a4\u30c9\u3067\u3059\u3002\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u767a\u898b\u3001\u8a2d\u8a08\u3001\u958b\u767a\u3001\u30c6\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593\u3092\u77ed\u7e2e\u3067\u304d\u3001\u591a\u304f\u306e\u304a\u5ba2\u69d8\u306f\u3001\u767a\u6848\u304b\u3089 PoC \u307e\u3067\u3092\u308f\u305a\u304b 2 \u9031\u9593\u3067\u5b8c\u4e86\u3055\u305b\u3066\u3044\u307e\u3059\u3002\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u3092\u898b\u308b\u3055\u3063\u305d\u304f\u8a66\u3057\u3066\u307f\u307e\u305b\u3093\u304b\uff1f\u307e\u305a\u306f\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u3067 Databricks \u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u304a\u8a66\u3057\u304f\u3060\u3055\u3044\u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/blog\/category\/platform\/solutions","text":"The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lewis-mbae","text":"Lewis Mbae - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLewis MbaeHead of Customer Engineering at RudderStackBack to speakersLewis leads Customer Engineering at RudderStack. His team's core focus is to be the trusted technical advisor for all RudderStack customers throughout their journey on the platform. Prior to RudderStack he spent 7 years at Fastly where he held senior roles in Sales Engineering. On the personal side, he grew up in Kenya and moved to the United States to attend college. He has a MS in Computer Science from Columbia as well as a BS in Electrical Engineering from StanfordLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jim-hibbard","text":"Jim Hibbard - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJim HibbardSenior Developer Advocate at DatabricksBack to speakersJim Hibbard is a Developer Advocate at Databricks. Prior to that, he worked at Seattle Children\u2019s Hospital where he developed frameworks and methods for integrating medical records with multi-omics datasets to improve care. He is currently working on improving machine learning infrastructure and model management as part of the extended MLflow team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2019\/11\/21\/a-day-at-the-2019-women-in-product-conference.html","text":"A Day at the 2019 Women in Product ConferenceSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorA Day at the 2019 Women in Product Conferenceby Anna Shrestinian, Allie Emrich, Julia Han and Rebecca LiNovember 21, 2019 in Company BlogShare this postFrom left to right: Shveta, Julia, Yardley Pohl (a WIP board member and co-founder), Anna, Allie, Cyrielle, and Rani at the Databricks boothDatabricks was a proud sponsor of the 2019 Women In Product conference which focuses on empowering women in product management and advocating for equal representation. We had a booth and happy hour where attendees could network with our product team, and learn more about our open roles. Read more about what this experience meant to the team members that attended below!\nWhat led you to your current position at Databricks?Anna Shrestinian, Senior Product Manager\nI am a product manager on identity and data security at Databricks. I work to solve our customers\u2019 challenges with securing data at an enterprise scale.\nRebecca Li, Staff Product Manager, Pricing and Portfolio\nI am a product manager on pricing, cost management, and usage visibility. I work to design a packaging & pricing model that drives Databricks\u2019 adoption in the market; and optimizes the long-term revenue of the company. At the same time, I work to make sure customers have the right tools to closely monitor their usage and cost.\nAllie Emrich, Senior Program Manager, Product\nI\u2019m a program manager on the product team who\u2019s in charge of coordinating and communicating much of our roadmap and the updates that occur throughout the quarter. Program management is a funny position because it doesn\u2019t necessarily have a conventional path. I started out working on the customer success side, and really enjoyed cross-departmental projects focusing on product launches. When I saw the role at Databricks that leveraged my skill set on the CS side, but allowed me to grow operationally on the product side, I knew it was an opportunity I couldn\u2019t pass up.\nCyrielle Simeone, Senior Product Marketing Manager, Data Science and Machine Learning\nI'm a product marketing manager for data science and machine learning at Databricks. My role primarily consists of developing deep domain and audience understanding, product messaging collateral, as well as go-to-market strategies and campaigns. It's funny, I didn\u2019t originally plan on becoming a PMM, but I\u2019m so glad I did. I graduated from a French generalist engineering school in 2006 with a specialization in image and signal processing. While curious and fascinated by math and science, I realized early on in my career that I was more interested in enabling people with technology and learning how they solved problems rather than becoming a specialist myself. The PMM role at Databricks is perfect for me in the sense that it sits at the intersection of product, customers, and sales, and gives me the opportunity to collaborate with extremely talented people across functions to bring to market ML products with a fantastic community fit, like MLflow. It allows me to stay abreast of practitioner needs and challenges, industry trends, and use cases across industries. It is a very diverse and demanding role, that can be very rewarding when executed well.\nJulia Han, Engineering Program Manager\nI\u2019m an engineering program manager on the technical program management team. The technical program management team works on ensuring that there is alignment between the engineering and product management orgs. I work on reducing engineering overhead for project management and ensuring that proper coordination and communication is in place to facilitate execution for the engineering teams.\nKeynote Session with Diane von Furstenberg at the conferenceWhat did sponsoring the Women in Product conference mean to you?Anna Shrestinian, Senior Product Manager\nThe energy at the Women in Product conference was invigorating. It was amazing to be surrounded by leaders in the field and hear their insights on Product skills as well as their inspiring stories. I am proud to see Databricks\u2019 name alongside best-in-class organizations as a Gold Sponsor. It shows me our commitment to diversity and inclusion.\nRebecca Li, Staff Product Manager, Pricing and Portfolio\nI was pleasantly surprised by the diversity of industries, experiences, and career trajectories of our guest speakers. Each of them shed light on a different area of expertise, and shared their unique story of how they became who they are today. It was very inspiring and encouraging to understand their mindset, their struggles and how they overcome them to build their unique character. The crowd was very energetic and engaging. You can tell the message resonates with the audience deeply, and it is a community of women in product that can help each other grow. It was a great experience and there needs to be more of them!\nAllie Emrich, Senior Program Manager, Product\nMany companies are focused on increasing gender diversity, but it\u2019s great to be part of a company who is visibly taking action to help move the needle. The atmosphere at the conference was vivacious and contagious-full of attendees who were so excited to be there and connect with one another. Getting our name out there, and teaching people about what Databricks is all about was an experience for the books!\nCyrielle Simeone, Senior Product Marketing Manager\nIt was very exciting and humbling to be part of this initiative, and represent Databricks at the Women in Product conference. It demonstrates real commitment and initiatives towards more diversity and inclusion for us as we continue to scale, which is key. As a woman in tech, it was fantastic to get to meet and connect with the community, hear the experiences and aspirations of many women throughout the day, and introduce them to Databricks. The energy was vibrant and very communicative, I look forward to the next one!\nJulia Han, Engineering Program Manager\nAs a woman in tech myself, it\u2019s always eye opening to be able to hear and learn about the experiences of other women who are in tech. As Databricks scales, we want to see gender diversity make progress across the board by learning from other companies on their efforts and vice versa. It\u2019s exciting to be part of a company that supports women who are seeking to connect and search for growth opportunities.\nWe are so excited to be a part of a team that promotes growth and development and fosters us to learn from other subject matter experts in the field. Interested in working with our product teams here at Databricks? Check out our Careers Page!Learn More about Databricks Involvement with Women in Tech:https:\/\/www.databricks.com\/sparkaisummit\/north-america\/women-in-uaTry Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/vicky-andonova\/#","text":"Vicky Andonova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVicky AndonovaManager, Applied Machine Learning at AnomaloBack to speakersVicky is a founding team member and the manager of the Applied Machine Learning team at Anomalo. Her team is responsible for building Anomalo\u2019s machine-learning models and translating them into actionable insights for customers. Before Anomalo, Vicky worked at Instacart as a senior data scientist. There, she built Instacart\u2019s experimentation platform and was the lead data scientist on a company initiative to improve grocery delivery quality. Vicky graduated with a BSEE from Columbia University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/company\/contact","text":"Nous contacter - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWNous contacterAvez-vous besoin d'assistance ou d'aide vis-\u00e0-vis de la formation\u00a0? Veuillez consulter ces ressources suppl\u00e9mentaires.DocumentationLire la documentation technique pour Databricks sur AWS, Azure ou Google CloudCommunaut\u00e9 DatabricksDiscutez, partagez et interagissez avec les utilisateurs et les experts de DatabricksFormationDevenez un expert de la plateforme Lakehouse de Databricks gr\u00e2ce \u00e0 des sessions dispens\u00e9es par des formateurs ou que vous suivez \u00e0 votre propre rythme. Ou devenez d\u00e9veloppeur certifi\u00e9.AideD\u00e9j\u00e0 client\u00a0? Cliquez ici si vous rencontrez un probl\u00e8me technique ou li\u00e9 au paiementSites des bureauxD\u00e9couvrez tous nos bureaux dans le monde et contactez-nous.Base de connaissancesTrouvez des r\u00e9ponses rapides aux questions les plus fr\u00e9quemment pos\u00e9es sur les produits et services de DatabricksProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/pricing\/#","text":"Pricing - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPricingConference\n\n\n\n\n\n\n\n\n\n\n\nFull Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1795 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nGroup DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1295 IN-PERSONEACH\n\n\n\n\n\n\n\n\n\n\n\nGOV\/EDU\/NFPDiscounted pass for Government\/Education\/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.\n$1395 IN-PERSON\n\n\n\n\n\n\n\n\n\n\n\n\nVirtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event.\n $0 VIRTUALTraining\n\n\n\n\n\n\n\n\n\n\nTwo-Day CourseThis includes a two-day course and the certification exam.\n$1125 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nFull-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic.\n$750 IN-PERSON\n\n\n\n\n\n\n\n\n\n\nHalf-Day TrainingA 4-hour, in-depth session covering your chosen topic.\n$375 IN-PERSONCertification\n\n\n\n\n\n\n\n\n\n\n\nCertification ExamRegister for training and take a certification exam onsite for free.\n$0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/anomaly-detection","text":"What is Anomaly Detection?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAnomaly DetectionAll>Anomaly DetectionTry Databricks for freeGet StartedAnomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such \u201canomalous\u201d behavior typically translates to some kind of a problem like credit card fraud, a failing machine, or a cyber attack. In finance, with thousands or millions of transactions to watch, anomaly detection can help point out where an error is occurring, enhancing root cause analysis and quickly getting support on the issue. Anomaly detection helps the monitoring cause of chaos engineering by detecting outliers and informing the responsible parties to act. Machine Learning and AI are increasingly being used for anomaly detection for fraud detection and Anti-Money Laundering (AML).Additional ResourcesSmarter risk and compliance with data and AIIdentify Fraud With Geospatial Analytics and AIHow to build: Rule-based AI models to combat financial fraudAnti-Money Laundering Solutions at Scale Using Databricks Lakehouse PlatformBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/michael-sanky\/#","text":"Michael Sanky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael SankyRVP, Industry Solutions, Healthcare and Life Sciences at DatabricksBack to speakersBusiness leader focusing on strategy, products, and business development in the intersection of science and IT. Helping Life Sciences companies accelerate and improve discovery by combining Technology and Human Ingenuity to enable Collaboration, Data Science, Digital Twins, AI, and Analytics in the Cloud.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Databricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30 | DatabricksDatabricks \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud558\uae30AWS, Microsoft Azure \ub610\ub294 Google Cloud \uc911 \uc6d0\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc \uc11c\ube44\uc2a4\uc5d0\uc11c 14\uc77c \ub3d9\uc548 Databricks \ud50c\ub7ab\ud3fc \uc804\uccb4\ub97c \ubb34\ub8cc\ub85c \uccb4\ud5d8\ud574 \ubcf4\uc138\uc694.\ub370\uc774\ud130 \uc218\uc9d1 \ub2e8\uc21c\ud654 \ubc0f ETL \uc790\ub3d9\ud654\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uc218\ubc31 \uac1c\uc758 \uc18c\uc2a4\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud574 \ubcf4\uc138\uc694. \uac04\ub2e8\ud55c \ubc29\uc2dd\uc73c\ub85c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc2e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc6d0\ud558\ub294 \uc5b8\uc5b4\ub85c \ud611\uc5c5\uc774 \uac00\ub2a5\ud569\ub2c8\ub2e4.\uacf5\ub3d9 \uc800\uc791, \uc790\ub3d9 \ubc84\uc804 \uad00\ub9ac, Git \ud1b5\ud569, RBAC\ub97c \ud65c\uc6a9\ud558\uc5ec Python, R, Scala \ubc0f SQL\ub85c \ucf54\ub529\ud558\uc138\uc694.\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\ubcf4\ub2e4 12\ubc30 \ub354 \uc6b0\uc218\ud55c \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc804 \uc138\uacc4 7,000\uac1c \uace0\uac1d\uc0ac\uac00 BI\ubd80\ud130 AI\uc5d0 \uc774\ub974\ub294 \ubaa8\ub4e0 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc704\ud574\uc11c Databricks \ub97c \uc120\ud0dd\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.Databricks \uacc4\uc815 \uc0dd\uc131\ud558\uae301\/2\uc774\ub984\uc131\ud68c\uc0ac \uc774\uba54\uc77c\ud68c\uc0ac\uc9c1\ud568\uc804\ud654\ubc88\ud638(\uc120\ud0dd\uc0ac\ud56d)\ubcf4\uae30 \uc911\uc5d0\uc11c \uc120\ud0dd\ud558\uc138\uc694\uad6d\uac00\uacc4\uc18d\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0(\uc5c5\ub370\uc774\ud2b8\ub428)\uc774\uc6a9\uc57d\uad00\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/shir-chorev\/#","text":"Shir Chorev - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShir ChorevCTO at DeepchecksBack to speakersShir is the co-founder and CTO of Deepchecks, an MLOps startup for continuous validation of ML models and data. Previously, Shir worked at the Prime Minister\u2019s Office and at Unit 8200, conducting and leading research in various Machine Learning and Cybersecurity related challenges. Shir has a B.Sc. in Physics from the Hebrew University, which she obtained as part of the Talpiot excellence program, and an M.Sc. in Electrical Engineering from Tel Aviv University. Shir was selected as a featured honoree in the Forbes Europe 30 under 30 class of 2021.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ganesh-deivarayan","text":"Ganesh Deivarayan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGanesh DeivarayanSr Manager at American AirlinesBack to speakersCurrently leading the TechOps Data Strategy \nand Cloud Engineering StrategyLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marianna-cervino\/#","text":"Marianna Cervino - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarianna CervinoGlobal Data Scientist at GucciBack to speakersMarianna holds a Master Degree in Physics from University of Bari. She is a Data Scientist experienced in Time Series Forecasting methodologies and has worked on business problems of diverse industries in the past years. She joined Gucci in 2021, where she works in collaboration with the Media Department.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/discover\/beacons","text":"Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing \u2013 all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark\u2122, Delta Lake, MLflow and others. Don\u2019t hesitate to reach out to them on social to see what they\u2019re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.\n\u00a0UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark\u2122 committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark\u2122, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark\u2122 adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI\/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark\u2122.POLANDMaciej SzymkiewiczMaciej is an Apache Spark\u2122 committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark\u2122 committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark\u2122, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select\nDatabricks eventsSponsorship and swag for meetupsNominate a peerWe\u2019d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone \u2014 including customers, partners, Databricks employees or even a current Beacon \u2014 is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/product\/data-lakehouse","text":"Data Lakehouse Platform da Databricks - Agende uma demonstra\u00e7\u00e3o!Skip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernan\u00e7a de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePre\u00e7osMarketplaceTecnologia de c\u00f3digo abertoCentro de seguran\u00e7a e confian\u00e7aWEBINAR Maio 18 \/ 8 AM PT\nAdeus, Data Warehouse. Ol\u00e1, Lakehouse.\nParticipe para entender como um data lakehouse se encaixa em sua pilha de dados moderna.\nInscreva-se agoraSolu\u00e7\u00f5esSolu\u00e7\u00f5es por setorServi\u00e7os financeirosSa\u00fade e ci\u00eancias da vidaProdu\u00e7\u00e3o industrialComunica\u00e7\u00f5es, m\u00eddia e entretenimentoSetor p\u00fablicoVarejoVer todos os setoresSolu\u00e7\u00f5es por caso de usoAceleradores de solu\u00e7\u00e3oServi\u00e7os profissionaisNeg\u00f3cios nativos digitaisMigra\u00e7\u00e3o da plataforma de dados9 de maio | 8h PT\n\u00a0\nDescubra a Lakehouse para Manufatura\nSaiba como a Corning est\u00e1 tomando decis\u00f5es cr\u00edticas que minimizam as inspe\u00e7\u00f5es manuais, reduzem os custos de envio e aumentam a satisfa\u00e7\u00e3o do cliente.Inscreva-se hojeAprenderDocumenta\u00e7\u00e3oTreinamento e certifica\u00e7\u00e3oDemosRecursosComunidade onlineAlian\u00e7a com universidadesEventosData+AI SummitBlogLaborat\u00f3riosBeaconsA maior confer\u00eancia de dados, an\u00e1lises e IA do mundo retorna a S\u00e3o Francisco, de 26 a 29 de junho.\u00a0ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConex\u00e3o de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSolu\u00e7\u00f5es para parceirosConecte-se com apenas alguns cliques a solu\u00e7\u00f5es de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de Administra\u00e7\u00e3oBlog da empresaImprensaDatabricks VenturesPr\u00eamios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como l\u00edder pelo segundo ano consecutivoObtenha o relat\u00f3rioExperimente DatabricksAssista \u00e0s DemosEntre em contatoIn\u00edcio de sess\u00e3oJUNE 26-29REGISTER NOWPlataforma Databricks LakehouseCombine seu data warehousing e casos de uso de IA em uma \u00fanica plataformaExperimente gratuitamenteAgendar uma demonstra\u00e7\u00e3o\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowSimples. Aberta. Multicloud.A Plataforma Databricks Lakehouse combina o melhor dos data lakes e data warehouses para entregar a confiabilidade, governan\u00e7a refor\u00e7ada e desempenho de data warehouses com a abertura, flexibilidade e suporte a machine learning de data lakes.Essa abordagem unificada simplifica sua stack de dados moderna ao acabar com silos que tradicionalmente separam e complicam as \u00e1reas de engenharia de dados, an\u00e1lise, BI, data science e a machine learning. Ela \u00e9 baseada em padr\u00f5es abertos e c\u00f3digo aberto para maior flexibilidade. Esta estrat\u00e9gia comum para gerenciamento de dados, seguran\u00e7a e governan\u00e7a ajuda voc\u00ea a operar com mais efici\u00eancia e inovar mais rapidamente.SimplesA abordagem unificada simplifica sua arquitetura de dados ao acabar com silos que tradicionalmente separam as \u00e1reas de an\u00e1lise, BI, data science e machine learning. Com um lakehouse, \u00e9 poss\u00edvel eliminar a complexidade e as despesas que impedem voc\u00ea de atingir todo o potencial das suas iniciativas de an\u00e1lise e IA.AbertaO Delta Lake\u00a0\u00e9 a funda\u00e7\u00e3o aberta do lakehouse, entregando confiabilidade e\u00a0desempenho recordes\u00a0diretamente nos dados no data lake. Ele permite evitar estruturas propriet\u00e1rias, compartilhar dados facilmente e criar sua stack de dados moderna com acesso irrestrito ao ecossistema de projetos de dados de c\u00f3digo aberto e \u00e0 ampla rede de parceiros da Databricks.Saiba mais sobre mais de 450 parceiros em todo o cen\u00e1rio de dadosSaiba MaisMulticloudA Plataforma Databricks Lakehouse oferece uma experi\u00eancia consistente de gerenciamento, seguran\u00e7a e governan\u00e7a em todas as nuvens. N\u00e3o h\u00e1 necessidade investir e de reinventar processos para cada plataforma de nuvem que voc\u00ea usa para suportar seus projetos de dados e IA. Em vez disso, suas equipes de dados podem se concentrar em colocar todos os seus dados para trabalhar e descobrir novos insights.Saiba MaisSblocca il potenziale dei tuoi dati e dei tuoi team di datiScopri di pi\u00f9 su come Databricks Lakehouse Platform abilita i tuoi carichi di lavoro di dati e intelligenza artificialeData EngineeringDatabricks SQLMachine leaningConte\u00fado relacionado\nTodos os recursos de que voc\u00ea precisa. Reunidos em um s\u00f3 lugar.\nExplore nossa biblioteca de recursos: voc\u00ea encontrar\u00e1 e-books e v\u00eddeos sobre os benef\u00edcios de utilizar Databricks para data engineering .\nExplorar recursosLakehouseO que \u00e9 lakehouse?Livro para leigos: The Modern Cloud Data PlatformA ascens\u00e3o do paradigma lakehouseAscens\u00e3o do Data Lakehouse por Bill Inmon, pai do data warehouseDelta Lakee-book: The Big Book of Data EngineeringDelta Lake: O Guia Definitivo por O'ReillyGuia definitivo do Delta LakeDelta Lake: a funda\u00e7\u00e3o do seu lakehouseMachine leaninge-book: Standardizing the ML LifecycleEvento virtual: Cria\u00e7\u00e3o de plataformas de machine learningTudo pronto para come\u00e7ar?Experimente o Databricks gratuitamenteProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoProdutoVis\u00e3o geral da plataformaPre\u00e7osTecnologia de c\u00f3digo abertoExperimente DatabricksDemoAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineAprendizagem e suporteDocumenta\u00e7\u00e3oGloss\u00e1rioTreinamento e certifica\u00e7\u00e3oCentral de ajudaInforma\u00e7\u00f5es legaisComunidade onlineSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisSolu\u00e7\u00f5esPor setorServi\u00e7os profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclus\u00e3oBlog da empresaEntre em contatoSee Careers\nat DatabricksMundialEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas op\u00e7\u00f5es de privacidade|Seus direitos de privacidade na Calif\u00f3rnia"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/yali-sassoon","text":"Yali Sassoon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYali SassoonCPO at SnowplowBack to speakersYali is passionate about the transformative impact of data. Yali Sassoon co-founded Snowplow to help companies realize the possibilities the behavioral data creates to build deep understanding of individuals in real-time. Prior to Snowplow Yali spent his career in data, as a consultant (operational and strategic) and in house at OpenX. Yali has an MPhil in History and Philosophy of Science and a BA in Natural Sciences, both from the University of Cambridge.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit?itm_data=events-hp-nav-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alon-gubkin","text":"Alon Gubkin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlon GubkinCo-Founder & CTO at AporiaBack to speakersWriting code from the age of 7, Alon has a fairly healthy obsession with programming. He\u2019s also an avid fan of all things machine learning, software architecture, video games, and biology. At the age of 17, Alon created his first successful open source project, a video chat platform for mobile. Before joining Aporia, Alon served as an R&D Lead in the elite 81 intelligence unit of the Israel Defense Forces.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr#yourprivacychoices","text":"Architecture de data lakehouse et IA \u2013 DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWLe meilleur data warehouse est un lakehouseUnifiez vos donn\u00e9es, votre analytique\net votre IA sur une seule plateformeEssayer gratuitementEn savoir plusR\u00e9duisez les co\u0000\u00fbts et acc\u00e9l\u00e9rez l'innovation avec la plateforme lakehouseEn savoir plusUnifi\u00e9eUne seule plateforme pour toutes vos donn\u00e9es, r\u00e9gies par une gouvernance coh\u00e9rente et disponibles pour toutes vos t\u00e2ches d'analyse et d'IAOuvertB\u00e2tie sur des standards ouvertes, int\u00e9gr\u00e9e \u00e0 tous les clouds pour une harmonie parfaite avec votre pile de donn\u00e9es moderne\u00c9volutiveUne \u00e9volutivit\u00e9 efficace pour toutes les charges de travail, des simples pipelines de donn\u00e9es aux LLM de grande envergure.Les organisations data-driven choisissent Lakehouse\nVoir tous les clients\nLe lakehouse unifie vos \u00e9quipes dataGestion des donn\u00e9es et Data EngineeringRationalisez l'ingestion et la gestion de vos donn\u00e9esAvec un ETL automatis\u00e9 et fiable, un partage de donn\u00e9es ouvert et s\u00e9curis\u00e9 et des performances rapides comme l'\u00e9clair, Delta Lake envoie toutes vos donn\u00e9es structur\u00e9es, semi-structur\u00e9es et non structur\u00e9es vers votre datalake.En savoir plus Regarder la d\u00e9moEntreposage des donn\u00e9esObtenez de nouveaux insights \u00e0 partir des donn\u00e9es les plus compl\u00e8tesGr\u00e2ce \u00e0 l'acc\u00e8s imm\u00e9diat aux donn\u00e9es les plus r\u00e9centes et compl\u00e8tes et \u00e0 la puissance de Databricks SQL \u2014\u00a0dont le rapport prix \/ performance est jusqu'\u00e0 douze fois sup\u00e9rieur \u00e0 celui des data warehouses Cloud traditionnels\u00a0\u2014 les analystes et data scientists peuvent d\u00e9sormais b\u00e9n\u00e9ficier rapidement de nouveaux insights.En savoir plus Regarder la d\u00e9moData Science et Machine LearningAcc\u00e9l\u00e9rer le ML sur l'ensemble du cycle de vieLe lakehouse constitue la base de Databricks Machine Learning, une solution collaborative et native en mati\u00e8re de donn\u00e9es pour l'ensemble du cycle de vie du Machine Learning, de la mise en forme \u00e0 la production. Combin\u00e9 \u00e0 des pipelines de donn\u00e9es de haute qualit\u00e9 et hautement performants, le lakehouse acc\u00e9l\u00e8re le Machine Learning et la productivit\u00e9 des \u00e9quipes.En savoir plus Regarder la d\u00e9moGouvernance et partage des donn\u00e9esDonn\u00e9es, analytique et IA\u00a0: conjuguez gouvernance et partageAvec Databricks, vous b\u00e9n\u00e9ficiez d'un mod\u00e8le commun de s\u00e9curit\u00e9 et de gouvernance pour l'ensemble de vos assets de donn\u00e9es, d'analytique et d'IA au sein de votre lakehouse, quel que soit le cloud. D\u00e9couvrez et partagez les donn\u00e9es de l'ensemble de vos plateformes, cloud ou r\u00e9gions, sans les r\u00e9pliquer ni \u00eatre tributaire d'un fournisseur. Vous pouvez m\u00eame distribuer des produits de donn\u00e9es sur une marketplace ouverte.En savoir plus Regarder la d\u00e9moLe data warehouse est de l'histoire ancienne. D\u00e9couvrez pourquoi le lakehouse constitue l'architecture moderne pour les donn\u00e9es et l'IA.Discover LakehouseLe catalogue de sessions est disponibleRejoignez-nous \u00e0 San Francisco pour explorer l'\u00e9cosyst\u00e8me du lakehouse et d\u00e9couvrir les nouvelles avanc\u00e9es des technologies open sourceParcourez les sessionsD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutive.Obtenir le rapport600 DSI. 14 secteurs. 18 pays.Une nouvelle \u00e9tude r\u00e9v\u00e8le que la strat\u00e9gie de donn\u00e9es joue un r\u00f4le crucial dans le succ\u00e8s de l'IA. D\u00e9couvrez les perspectives d'autres DSI.Obtenir le rapportUne lecture incontournable pour les ing\u00e9nieurs ML et les data scientists qui veulent optimiser leur pratique MLOpsObtenir l'e-bookPr\u00eat \u00e0 vous lancer\u00a0?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=field%20engineering","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-del-balso\/#","text":"Mike Del Balso - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike Del BalsoCo-founder + CEO at TectonBack to speakersMike Del Balso is the co-founder of Tecton, where he is building next-generation data infrastructure for Real-Time ML. Before Tecton, Mike was the PM lead for the Uber's Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power Google\u2019s Search Ads business.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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\ub370\uc774\ud130\ub97c \uc2e0\uc18d\ud558\uac8c \uc218\uc9d1, \ucc98\ub9ac\ud558\uc5ec \uc2e4\uc2dc\uac04 \ubd84\uc11d\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \uac00\uc6a9 \ubcd1\uc0c1 \uad00\ub9ac\uc5d0\uc11c\ubd80\ud130 \uc81c\uc870 \ucd5c\uc801\ud654, \uc57d\ubb3c \uc720\ud1b5\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0 \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.ML \uae30\ubc18 \uc57d\ubb3c \ud0d0\uc0c9 \ubc0f \ud658\uc790 \uce58\ub8cc\n\uba38\uc2e0 \ub7ec\ub2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uc9c8\ubcd1\uc5d0 \ub300\ud55c \uc774\ud574\ub3c4\ub97c \ub192\uc774\uace0 \uc758\ub8cc \uc694\uad6c \uc0ac\ud56d\uc744 \uc608\uce21\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubaa8\ub4e0 \ub370\uc774\ud130\ub294 \ubaa8\ub4e0 \ud611\uc5c5 \ub3c4\uad6c\uc640 \ub9e4\ub044\ub7fd\uac8c \uc5f0\uacb0\ud558\uc5ec \uace0\uae09 \ubd84\uc11d\uc744 \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.eBook \ub2e4\uc6b4\ub85c\ub4dc\ud30c\ud2b8\ub108 \ubc0f \uc194\ub8e8\uc158\uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ubd84\uc57c\uc758 \ub2e4\uc591\ud55c \ub370\uc774\ud130, \ubd84\uc11d \uc194\ub8e8\uc158, \ud15c\ud50c\ub9bf \uc0ac\uc6a9\ud574 \ubcf4\uae30\uc9c0\ub2a5\ud615 \uac74\uac15 \uad00\ub9ac\uac1c\uc778 \ub9de\ucda4\ud615 \ud658\uc790 \uce58\ub8cc \uc5ec\uc815\uacfc \uce58\ub8cc \uc811\uadfc\uc131\uc744 \ud1b5\ud574 \ud658\uc790 \uacbd\ud5d8\uacfc \uce58\ub8cc \ud6a8\uacfc\ub97c \uac1c\uc120\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30PrecisionView\u2122\uae30\ub2a5\uc744 \ud655\uc7a5\ud558\uace0, \uc5ed\ub7c9\uc744 \ub192\uc774\uace0, \uc758\ub8cc\uc640 \uc0dd\uba85\uacf5\ud559\uc5d0 \ub300\ud55c \ub0b4\ubd80 \ud611\uc5c5\uc744 \ubcf4\uac15\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\uac74\uac15 \ub370\uc774\ud130 \uc0c1\ud638\uc6b4\uc6a9\uc131\uc2a4\ud2b8\ub9ac\ubc0d FHIR \ubc88\ub4e4\uc744 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc790\ub3d9 \uc218\uc9d1\ud558\uc5ec \ub2e4\uc6b4\uc2a4\ud2b8\ub9bc \ud658\uc790\ub97c \ub300\uaddc\ubaa8\ub85c \ubd84\uc11d\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\uc2dc\uc791\ud558\uae30\uc0dd\ubb3c\uc758\ud559 \uc5f0\uad6c\ub97c \uc704\ud55c \uc9c0\ub2a5\uc801 \ub370\uc774\ud130 \uad00\ub9ac\uc804\uccb4\uc801 \uac00\uce58 \uc0ac\uc2ac\uc744 \uad6c\ud604\ud568\uc73c\ub85c\uc368 \uacfc\ud559\uc801 \ub370\uc774\ud130\ub97c \uc5d4\ud130\ud504\ub77c\uc774\uc988 \uc790\uc0b0\uc73c\ub85c \uc804\ud658\ud569\ub2c8\ub2e4.\uc2dc\uc791\ud558\uae30\ubaa8\ub4e0 \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158 \ubcf4\uae30\ub370\uc774\ud130 \ubaa8\ub378 \ubc0f \ucf54\ud638\ud2b8 \uad6c\ucd95: OMOP \ubc0f \uc131\ud5a5 \uc810\uc218 \ub9e4\uce6d\uc2e4\uc81c \ub370\uc774\ud130\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uac04\ud3b8\ud558\uac8c \uc218\uc9d1\ud558\uc5ec \ud45c\uc900\ud654\ud558\uace0, \ub300\uaddc\ubaa8 \uad00\ucc30 \ubd84\uc11d \uc81c\uacf5\uc2dc\uc791\ud558\uae30\uc0c1\ud638\uc6b4\uc6a9\uc131: HL7V2 \uba54\uc2dc\uc9c0 \uc218\uc9d1\uc2a4\ud2b8\ub9ac\ubc0d HL7V2 \uba54\uc2dc\uc9c0\ub97c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \uc790\ub3d9 \uc218\uc9d1\ud558\uc5ec \uc2e4\uc2dc\uac04 \ubd84\uc11d\uc2dc\uc791\ud558\uae30\uc0c1\ud638\uc6b4\uc6a9\uc131: FHIR \ubc88\ub4e4 \uc218\uc9d1\uc2a4\ud2b8\ub9ac\ubc0d FHIR \ubc88\ub4e4\uc744 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc790\ub3d9 \uc218\uc9d1\ud558\uc5ec \ub2e4\uc6b4\uc2a4\ud2b8\ub9bc \ud658\uc790 \ubd84\uc11d\uc2dc\uc791\ud558\uae30\uc774\ubbf8\uc9c0: \ub514\uc9c0\ud138 \ubcd1\ub9ac\ud559 \ubd84\ub958\ub514\uc9c0\ud138 \ubcd1\ub9ac\ud559 \uc2ac\ub77c\uc774\ub4dc\uc5d0\uc11c \uc804\uc774\ub97c \ucc3e\uc544\ub0c4\uc73c\ub85c\uc368 \ub525 \ub7ec\ub2dd\uc73c\ub85c \uc9c4\ub2e8 \uc6cc\ud06c\ud50c\ub85c \uac15\ud654\uc2dc\uc791\ud558\uae30R&D: \uc57d\ubb3c \ud0c0\uac9f \uc2dd\ubcc4\ub300\uaddc\ubaa8\ub85c \uc720\uc804\uc801 \uad00\uacc4\ub97c \ubd84\uc11d\ud558\uc5ec R&D \ud300\uc774 \uc0c8\ub85c\uc6b4 \uc57d\ubb3c \ud0c0\uac9f\uc744 \ucc3e\uc544\ub0b4\ub3c4\ub85d \uc9c0\uc6d0\uc2dc\uc791\ud558\uae30\uc778\ub958 \uac74\uac15: \uc9c8\ubcd1 \uc704\ud5d8 \uc608\uce21\uc9c8\ubcd1 \uc704\ud5d8 \uc608\uce21 \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uc5ec \uce58\ub8cc \uad00\ub9ac \ud504\ub85c\uadf8\ub7a8 \uac1c\uc120\uc2dc\uc791\ud558\uae30NLP: \uc774\uc0c1 \ubc18\uc751 \ud0d0\uc9c0John Snow Labs\uc640 \uc758 \uacf5\ub3d9 NLP \uc194\ub8e8\uc158\uc744 \uc0ac\uc6a9\ud55c \uc774\uc0c1 \ubc18\uc751 \ud0d0\uc9c0\ub97c \ud1b5\ud574 \uc57d\ubb3c \uc548\uc804\uc131 \ubaa8\ub2c8\ud130\ub9c1 \uac1c\uc120\uc2dc\uc791\ud558\uae30NLP: \uc2e4\uc81c \uc885\uc591\ud559 \ub370\uc774\ud130 \ucd94\ucd9c\ube44\uad6c\uc870\uc801 \uc885\uc591\ud559 \uc18c\uacac\uc744 John Snow Labs\uc640\uc758 \uacf5\ub3d9 NLP \uc194\ub8e8\uc158\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc0c8\ub85c\uc6b4 \ud658\uc790 \uc778\uc0ac\uc774\ud2b8\ub85c \ucd94\ucd9c\uc2dc\uc791\ud558\uae30NLP: PHI \uc81c\uac70 \uc790\ub3d9\ud654John Snow Labs\uc640\uc758 \uacf5\ub3d9 NLP \uc194\ub8e8\uc158\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc5d0\uc11c \ubbfc\uac10\ud55c \ud658\uc790 \uc815\ubcf4\ub97c \uc790\ub3d9 \uc81c\uac70\uc2dc\uc791\ud558\uae30\ubaa8\ub4e0 \uc194\ub8e8\uc158 \ubcf4\uae30\uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ub370\ubaa8\uc790\uc138\ud55c \uc815\ubcf4\uac00 \ud544\uc694\ud558\uc2e0\uac00\uc694?\uc758\ub8cc \uc11c\ube44\uc2a4\n\ub370\uc774\ud130\uc640 AI\uc758 \ud798\uc73c\ub85c \ud658\uc790 \uc911\uc2ec \uc758\ub8cc \uc81c\uacf5\uc0dd\uba85 \uacfc\ud559\n\ub370\uc774\ud130 \ubd84\uc11d\uacfc AI\ub85c \ub3c4\uc6c0\uc774 \uc808\uc2e4\ud55c \ud658\uc790\uc5d0\uac8c \uc0c8\ub85c\uc6b4 \uce58\ub8cc \uc81c\uacf5\ub370\uc774\ud130 \ubc0f AI\ub85c \uce58\ub8cc \ud6a8\uacfc \uac1c\uc120eBook \ub2e4\uc6b4\ub85c\ub4dc \u2192\ub9ac\uc18c\uc2a4\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc5d0\uc11c \uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc744 \uc704\ud55c \ub370\uc774\ud130 \ubc0f AI ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ucc3e\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uce58\ub8cc \ud6a8\uacfc \uac1c\uc120\ub300\uaddc\ubaa8 \uc790\uc5f0 \uc5b8\uc5b4 \ucc98\ub9ac\ub85c \uc0c8\ub85c\uc6b4 \ud658\uc790 \uc778\uc0ac\uc774\ud2b8 \ubc1c\uacac\ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc2e4\uc81c \ub370\uc774\ud130\uc758 \uc7a0\uc7ac\ub825 \uad6c\ud604\uc194\ub8e8\uc158 \uc2dc\ud2b8: \uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc18c\uac1c\uc6e8\ube44\ub098\uc6cc\ud06c\uc20d: \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub97c \ud1b5\ud55c FHIR \uae30\ubc18 \uc2e4\uc2dc\uac04 \ud658\uc790 \ubd84\uc11d\uc6e8\ube44\ub098: Chesapeake Regional Information System\uc744 \ud1b5\ud574 \ud658\uc790\ub97c \uc704\ud55c \uc758\ub8cc \ud601\uc2e0\uc6cc\ud06c\uc20d: OMOP\ub97c \uc0ac\uc6a9\ud55c \ub370\uc774\u0000\u0000\ud130 \ud45c\uc900\ud654\uc640 ML\uc744 \ud65c\uc6a9\ud55c \uc9c8\ubcd1 \uc704\ud5d8 \uc608\uce21\uc6cc\ud06c\uc20d: NLP\ub85c \uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \ucd94\ucd9c\uc6cc\ud06c\uc20d: \uc2e4\uc81c \ub370\uc774\ud130 + AI\ub85c R&D \uac00\uc18d\ud654\ube14\ub85c\uadf8Amgen, \uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub85c \uc57d\ubb3c \uac1c\ubc1c \ubc0f \uc804\ub2ec \uac00\uc18d\ud654\uc758\ub8cc \ubc0f \uc0dd\uba85 \uacf5\ud559 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ucd9c\uc2dcNLP\ub97c \uc0ac\uc6a9\ud55c \uc774\uc0c1 \ubc18\uc751 \ud0d0\uc9c0\ub85c \uc57d\ubb3c \uc548\uc804\uc131 \uac1c\uc120Databricks\uc758 \uc624\ud508 \uc18c\uc2a4 \uc720\uc804\uccb4 \ud234\ud0b7\uc774 \uc720\uba85 \ub3c4\uad6c\ubcf4\ub2e4 \uc6b0\uc218\ud55c \uc131\ub2a5\uc744 \uc790\ub791NLP\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc2e4\uc81c \uc784\uc0c1 \ub370\uc774\ud130\uc5d0\uc11c \uc885\uc591\ud559 \uc778\uc0ac\uc774\ud2b8 \ucd94\ucd9c\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uadc0\uc0ac\uc758 \ube44\uc988\ub2c8\uc2a4 \ubaa9\ud45c\ub97c \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uace0 \uc11c\ube44\uc2a4 \ud300\uc5d0\uc11c \uadc0\uc0ac\uc758 \uc131\uacf5\uc744 \ub3c4\uc6b8 \ubc29\ubc95\uc744 \ud568\uaed8 \uc54c\uc544\ubcf4\uace0\uc790 \ud569\ub2c8\ub2e4.Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\ub370\ubaa8 \uc608\uc57d\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/jp\/professional-services","text":"Databricks \u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9 | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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\u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks \u30d6\u30ed\u30b0\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u0000\u0000\u63a1\u7528\u60c5\u5831\u8a00\u8a9e\u5730\u57dfEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/company\/contact?contactReason=Have%20Sales%20Contact%20Me&message=I%20would%20need%20information%20about%20AWS%20pricing","text":"Contact Us - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContact usNeed assistance with training or support? See these additional resources.DocumentationRead technical documentation for Databricks on AWS, Azure or Google CloudDatabricks CommunityDiscuss, share and network with Databricks users and expertsTrainingMaster the Databricks Lakehouse Platform with instructor-led and self-paced training or become a certified developerSupportAlready a customer? Click here if you are encountering a technical or payment issueOur office locationsSee all our office locations globally and get in touchKnowledge baseFind quick answers to the most frequently asked questions about Databricks products and servicesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ketan-ganatra\/#","text":"Ketan Ganatra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKetan GanatraSolution Architect at DatabricksBack to speakersAs a Solution Architect working with Databrick's SI partners, Ketan helps them build competencies and products around the Lakehouse platform. Ketan acts as a SME on ML topics. Prior to joining Databricks, he led development and production roll-out of the first ever Enterprise ML use case in the Department of Defense. Ketan Has 20+ years of IT experience and degrees in Electronics Engg and MBA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/young-bang\/#","text":"Young Bang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and Technology at U.S. ArmyBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/training-services-schedule","text":"Training Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTraining Services ScheduleThis Schedule sets forth terms related to the Training Services and is incorporated as part of the Master Cloud Services Agreement (\u201cMCSA\u201c). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Other Schedules do not apply to the services ordered under this Schedule unless expressly referenced as being applicable. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Additional Definitions.\u201cCourse\u201d means an instance of either Instructor-Led Training Services or Self-Paced Training Services\u201cCourse Materials\u201d means the training materials and other information and content provided by Databricks in conducting the Training ServicesGenerally. Databricks may provide, as set forth in an Order, certain Training Services, delivered (i) by instructors (\u201cInstructor-led Training Services\u201d), either in person or online-only; or (ii) as a self-paced online training course (\u201cSelf-Paced Training Services\u201d). If we have agreed to provide you with Training Services, we will provide qualified training personnel and\/or suitable training materials. You will make available to Databricks any materials Databricks reasonably requires to perform the Training Services, but unless agreed between the parties in writing, you will not provide Databricks any Customer Content for use with the Training Services.Instructor-led Training Services. If we have agreed to provide you with Instructor-led Training Services, except as otherwise mutually agreed upon by the parties, you will, as reasonably applicable: (i) provide qualified personnel to assist in coordinating and implementing the Instructor-led Training Services; (ii) provide Databricks with access to your sites and facilities (or temporary off-site facilities) during normal business hours and as otherwise reasonably required by Databricks to perform the Instructor-led Training Services; (iii) provide Databricks with such working space and office support as Databricks may reasonably request; and (iv) perform such tasks as may be reasonably required to permit Databricks to perform the Instructor-led Training Services.Self-Paced Training Services. Databricks may make available certain Self-Paced Training Services. Unless otherwise set forth in an Order or when signing up for a Self-Paced Training Service, the Self-Paced Training Services will expire 12 months from the earlier of purchase or activation and are licensed on a per-user basis.Course Materials.Ownership of Course Materials. Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Course Materials. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Course Materials as delivered to you. You agree that the Course Materials are provided on a non-exclusive basis and not sold. You further acknowledge and agree that portions of the Course Materials, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Course Materials License. Databricks grants a limited, non-sublicensable, non-transferable, license to the Course Materials, solely for the internal educational use by individuals who attend a training course (\u201cStudents\u201d). Unless indicated by a Databricks instructor, Students are permitted to retain any Course Materials provided during the Course for continued learning following the conclusion of the Course. For the avoidance of doubt, Course Materials may not be used other than by the Students who received them, and may not be shared with individuals who did not attend a Course.Expenses. Customer will reimburse Databricks for reasonable travel expenses. Customer is responsible for all training venue expenses.Compliance with your Onsite Access Policies. If, in the course of providing Databricks Services, Databricks personnel go onsite at your premises, Databricks will require such personnel to comply with your commercially reasonable onsite access policies that have been provided by you to such personnel reasonably in advance. For the avoidance of doubt, no such policies will be deemed to modify the terms of the Agreement.Use of Workspace during Performance of Training Services. You may be required to use a Workspace in order to receive the benefit of the Training Services. Your use of the Workspace constitutes acceptance of the Platform Services terms of the MCSA unless the Workspace is provided as part of a Databricks Powered Service. If the Workspace is created for you by Databricks, it may be terminated following the conclusion of the Training Services without prior notice or any liability to you unless you enter into an Order with Databricks for its continued use.\u00a0Last Updated August 12, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).\u00a0ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mostafa-mokhtar\/#","text":"Mostafa Mokhtar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMostafa MokhtarPrincipal Software Engineer at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/product\/delta-lake-on-databricks","text":"Databricks \uae30\ubc18 Delta Lake - \uc9c0\uae08 \ub370\ubaa8\ub97c \uc608\uc57d\ud558\uc138\uc694!Skip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \u0000\uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDelta Lake\ub370\uc774\ud130 \ub808\uc774\ud06c\n\uc548\uc815\uc131, \ubcf4\uc548\uacfc \uc131\ub2a5\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30Delta Lake\ub780\n\ubb34\uc5c7\uc778\uac00\uc694?Delta Lake\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c \uc548\uc815\uc131, \ubcf4\uc548\uacfc \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 \uc624\ud508 \ud615\uc2dd \uc2a4\ud1a0\ub9ac\uc9c0 \uacc4\uce35\uc785\ub2c8\ub2e4. \uc2a4\ud2b8\ub9ac\ubc0d \uc791\uc5c5\uacfc \ubc30\uce58 \uc791\uc5c5 \ub458 \ub2e4\uc5d0 \uc801\ud569\ud569\ub2c8\ub2e4. Delta Lake\ub294 \ub370\uc774\ud130 \uc0ac\uc77c\ub85c\ub97c \uad6c\uc870\uc801, \ubc18\uad6c\uc870\uc801, \ube44\uad6c\uc870\uc801 \ub370\uc774\ud130\ub97c \ubaa8\ub450 \ub2f4\uc740 \ub2e8 \ud558\ub098\uc758 \ud648\uc73c\ub85c \ub300\uccb4\ud558\ubbc0\ub85c \ube44\uc6a9 \ud6a8\uc728\uc801\uc774\uace0 \uace0\ub3c4\ub85c \ud655\uc7a5 \uac00\ub2a5\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ubcf8 \ud1a0\ub300\uac00 \ub418\uc5b4\uc90d\ub2c8\ub2e4.\uc591\uc9c8\uc758 \uc548\uc815\uc801\uc778 \ub370\uc774\ud130\uc2e4\uc2dc\uac04 \uc2a4\ud2b8\ub9bc\uae4c\uc9c0 \ud3ec\ud568\ud574 \ub370\uc774\ud130 \uc804\uccb4\uc5d0 \ubbff\uc744 \uc218 \uc788\ub294 \ub2e8\uc77c \uc815\ubcf4 \ucd9c\ucc98(Single Source of Truth, SSOT)\ub97c \uc81c\uacf5\ud558\ubbc0\ub85c \ub370\uc774\ud130 \ud300\uc774 \ud56d\uc0c1 \ucd5c\uc2e0 \ub370\uc774\ud130\ub97c \ub2e4\ub8e8\ub3c4\ub85d \ubcf4\uc7a5\ub429\ub2c8\ub2e4. Delta Lake\ub294 ACID \ud2b8\ub79c\uc7ad\uc158\uacfc \uc2a4\ud0a4\ub9c8 \uc801\uc6a9\uc744 \uc9c0\uc6d0\ud558\uc5ec \uae30\uc874 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0 \ubbf8\ud761\ud588\ub358 \uc548\uc815\uc131\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774 \ub54c\ubb38\uc5d0 \uc804\uc0ac\uc801\uc73c\ub85c \ubbff\uc744 \uc218 \uc788\ub294 \ub370\uc774\ud130 \uc778\uc0ac\uc774\ud2b8\ub97c \ud655\uc7a5\ud558\uace0, \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c \uc9c1\uc811 \ubd84\uc11d \ubc0f \uc5ec\ud0c0 \ub370\uc774\ud130 \ud504\ub85c\uc81d\ud2b8\ub97c \uc2e4\ud589\ud558\uba74\uc11c\ub3c4 \uc778\uc0ac\uc774\ud2b8 \ub3c4\ucd9c \uc2dc\uac04\uc744 \ucd5c\ub300 50\ubc30\ub098 \ub2e8\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc548\uc804\ud55c \uc624\ud508 \ub370\uc774\ud130 \uacf5\uc720Delta Sharing\uc740 \uc548\uc804\ud55c \ub370\uc774\ud130 \uacf5\uc720\ub97c \uc704\ud55c \uc5c5\uacc4 \ucd5c\ucd08\uc758 \uc624\ud508 \ud504\ub85c\ud1a0\ucf5c\ub85c, \ub370\uc774\ud130 \uc704\uce58\uc5d0 \uad6c\uc560\ubc1b\uc9c0 \uc54a\uace0 \ub2e4\ub978 \uc870\uc9c1\uacfc \uac04\ud3b8\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4. Unity Catalog\uc640 \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569\ub418\uae30 \ub54c\ubb38\uc5d0 \uc804\uc0ac\uc801\uc73c\ub85c \uacf5\uc720 \ub370\uc774\ud130\ub97c \uc911\uc559\uc5d0\uc11c \uad00\ub9ac\ud558\uace0 \uac10\uc0ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74 \uacf5\uae09\uc790, \ud611\ub825\uc5c5\uccb4\uc640 \uc2e0\ub8b0\ub97c \ubc14\ud0d5\uc73c\ub85c \ub370\uc774\ud130 \uc790\uc0b0\uc744 \uacf5\uc720\ud560 \uc218 \uc788\uc5b4 \ube44\uc988\ub2c8\uc2a4 \uc870\uc728\uc5d0 \ub3c4\uc6c0\uc774 \ub418\uace0, \ub3d9\uc2dc\uc5d0 \ubcf4\uc548\uacfc \uaddc\uc815 \uc900\uc218 \uc694\uad6c \uc0ac\ud56d\uc5d0\ub3c4 \ubd80\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc8fc\uc694 \ud234, \ud50c\ub7ab\ud3fc\uacfc \ud1b5\ud569\ub418\ubbc0\ub85c \uc0ac\uc6a9\uc790\uac00 \uc120\ud0dd\ud55c \ud234\uc5d0\uc11c \uacf5\uc720 \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654, \ucffc\ub9ac, \ubcf4\uac15\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ucd08\uace0\uc18d \uc131\ub2a5Delta Lake\ub294 Apache Spark\u2122 \uae30\ubc18\uc73c\ub85c, \ub6f0\uc5b4\ub09c \ud655\uc7a5\uc131\uacfc \uc18d\ub3c4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ub610\ud55c \uc778\ub371\uc2f1\uacfc \uac19\uc740 \uc131\ub2a5 \uae30\ub2a5\uc744 \uc5fc\ub450\uc5d0 \ub450\uace0 \ucd5c\uc801\ud654\ud558\uc600\uae30 \ub54c\ubb38\uc5d0 Delta Lake\ub97c \uc774\uc6a9\ud574\ubcf8 \uace0\uac1d\uc740 \ucd5c\ub300 48%\uae4c\uc9c0 ETL \uc6cc\ud06c\ub85c\ub4dc \uc2e4\ud589 \uc18d\ub3c4\uac00 \ube68\ub77c\uc9c0\ub294 \ud6a8\uacfc\ub97c \uccb4\ud5d8\ud588\uc2b5\ub2c8\ub2e4.\uc624\ud508, \uc560\uc790\uc77cDelta Lake \ub0b4 \ubaa8\ub4e0 \ub370\uc774\ud130\ub294 \uc624\ud508 Apache Parquet \ud615\uc2dd\uc73c\ub85c \uc800\uc7a5\ub418\ubbc0\ub85c, \ud638\ud658\ub418\ub294 \ub9ac\ub354\ub77c\uba74 \ubb34\uc5c7\uc774\ub4e0 \uc885\ub958\uc640 \uad00\uacc4\uc5c6\uc774 \ub370\uc774\ud130\ub97c \uc77d\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. API\ub3c4 \uc624\ud508 \ud615\uc2dd\uc774\uace0 Apache Spark\uc640 \ud638\ud658\ub429\ub2c8\ub2e4. Databricks\uc758 Delta Lake\ub97c \uc774\uc6a9\ud558\uba74 \uad11\ubc94\uc704\ud55c \uc624\ud508 \uc18c\uc2a4 \uc5d0\ucf54 \uc2dc\uc2a4\ud15c\uc73c\ub85c \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc73c\ubbc0\ub85c \ud2b9\uc815 \ubca4\ub354\uc758 \ub370\uc774\ud130 \ud3ec\uba67\uc5d0 \ub77d\uc778(lock-in)\ub418\ub294 \ubb38\uc81c\ub97c \ubc29\uc9c0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\ub3d9\ud654\ub418\uace0 \uc2e0\ub8b0\ud560 \uc218 \uc788\ub294\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1Delta Live Table\uacfc \ud568\uaed8\ub77c\uba74 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc774 \uac04\ub2e8\ud574\uc9d1\ub2c8\ub2e4. Delta Lake\uc5d0\uc11c \ucd5c\uc2e0 \uace0\ud488\uc9c8 \ub370\uc774\ud130\uc5d0 \uc801\ud569\ud55c \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \ube4c\ub4dc\ud558\uc5ec \uad00\ub9ac\ud560 \uc190\uc26c\uc6b4 \ubc29\ubc95\uc744 \uc18c\uac1c\ud569\ub2c8\ub2e4. \uc774 \ud14c\uc774\ube14\uc740 \uc120\uc5b8\uc801 \ud30c\uc774\ud504\ub77c\uc778 \uac1c\ubc1c, \ub370\uc774\ud130 \uc548\uc815\uc131 \uac1c\uc120 \ubc0f \ud074\ub77c\uc6b0\ub4dc \uaddc\ubaa8 \ud504\ub85c\ub355\uc158 \uc791\uc5c5\uc744 \ud1b5\ud574 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \uae30\ucd08\ub97c \uad6c\ucd95\ud558\ub3c4\ub85d \ub3c4\uc640 ETL \uac1c\ubc1c\uacfc \uad00\ub9ac\ub97c \uac04\uc18c\ud654\ud558\uc5ec \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ud300\uc5d0 \ud070 \ub3c4\uc6c0\uc774 \ub418\uc5b4\uc90d\ub2c8\ub2e4.\ub300\uaddc\ubaa8 \ubcf4\uc548 \ubc0f \uac70\ubc84\ub10c\uc2a4Delta Lake\ub294 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4, \uae30\ub2a5\uc5d0 \uc138\ubd84\ud654\ub41c \uc561\uc138\uc2a4 \uad00\ub9ac\ub97c \ud65c\uc6a9\ud558\uc5ec \ub9ac\uc2a4\ud06c\ub97c \uc904\uc785\ub2c8\ub2e4. \uc774\uac83\uc740 \ubcf4\ud1b5 \ub370\uc774\ud130 \ub808\uc774\ud06c\ub85c\ub294 \ubd88\uac00\ub2a5\ud55c \uc77c\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0 \ubcf4\uad00\ub41c \ub370\uc774\ud130\ub97c \ube60\ub974\uace0 \uc815\ud655\ud558\uac8c \uc5c5\ub370\uc774\ud2b8\ud558\uc5ec GDPR\uacfc \uac19\uc740 \uaddc\uc81c\ub97c \uc900\uc218\ud560 \uc218 \uc788\uace0, \uac10\uc0ac \ub85c\uae45\uc744 \ud1b5\ud574 \uac1c\uc120\ub41c \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub97c \uc720\uc9c0\uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \uae30\ub2a5\uc740 Databricks\uc5d0\uc11c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc6a9 \ucd5c\ucd08\uc758 \uba40\ud2f0\ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uce74\ud0c8\ub85c\uadf8\uc778 Unity Catalog\uc758 \uc77c\ubd80\ubd84\uc73c\ub85c \uae30\ubcf8 \ud1b5\ud569 \ubc0f \uac15\ud654\ub429\ub2c8\ub2e4.\uc0ac\uc6a9 \uc0ac\ub840\uae30\uc874 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud55c BI\ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c \uc9c1\uc811 \ube44\uc988\ub2c8\uc2a4 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc2e4\ud589\ud558\uc5ec \ube44\uc988\ub2c8\uc2a4\uc5d0 \uc989\uac01\uc801\uc778 \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\ub3c4\ub85d \ucd5c\uc2e0 \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\ub97c \ub370\uc774\ud130 \uc560\ub110\ub9ac\uc2a4\ud2b8\uac00 \ucffc\ub9ac\ud560 \uc218 \uc788\ub294 \uc0c1\ud0dc\ub85c, \ubc14\ub85c \uc774\uc6a9\ud560 \uc218 \uc788\uac8c \uc81c\uacf5\ud569\ub2c8\ub2e4. Delta Lake\ub97c \uc0ac\uc6a9\ud558\uba74 \ub370\uc774\ud130 \ub808\uc774\ud06c \uc218\uc900\uc758 \ube44\uc6a9\uc73c\ub85c \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5 \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\ub294 \uba40\ud2f0\ud074\ub77c\uc6b0\ub4dc \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98\ub97c \uc6b4\uc601\ud574 \uae30\uc874 \ud074\ub77c\uc6b0\ub4dc \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4 \ub300\ube44 \ucd5c\ub300 6\ubc30 \ub354 \ub098\uc740 \uac00\uaca9\/\uc131\ub2a5\uc73c\ub85c SQL \uc6cc\ud06c\ub85c\ub4dc\ub97c \ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ubc30\uce58\uc640 \uc2a4\ud2b8\ub9ac\ubc0d \ud1b5\ud569\uac04\uacb0\ud55c \ub2e8\uc77c \uc544\ud0a4\ud14d\ucc98\uc5d0\uc11c \ubc30\uce58\uc640 \uc2a4\ud2b8\ub9ac\ubc0d \uc791\uc5c5\uc744 \ubaa8\ub450 \uc2e4\ud589\ud568\uc73c\ub85c\uc368 \ubcf5\uc7a1\ud558\uace0 \uc911\ubcf5\ub41c \uc2dc\uc2a4\ud15c\uacfc \uc6b4\uc601\uc0c1\uc758 \ubb38\uc81c\ub97c \ud53c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Delta Lake\uc758 \uacbd\uc6b0 \ud14c\uc774\ube14 \ud558\ub098\uac00 \ubc30\uce58 \ud14c\uc774\ube14\uacfc \uc2a4\ud2b8\ub9ac\ubc0d \uc18c\uc2a4 \ubc0f \uc2f1\ud06c\ub97c \uacb8\ud569\ub2c8\ub2e4. \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \uc218\uc9d1, \uacfc\uac70 \ubc31\ud544(backfill)) \ubc30\uce58 \ucc98\ub9ac\uc640 \ub300\ud654\ud615 \ucffc\ub9ac \ubaa8\ub450 \ubc14\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc73c\uba70 Spark Structured Streaming\uacfc \uc9c1\uc811 \ud1b5\ud569\ub429\ub2c8\ub2e4.\uaddc\uc81c \uc694\uad6c\uc0ac\ud56d\uc5d0 \ubd80\ud569Delta Lake\ub294 \ud615\uc2dd\uc774 \uc798\ubabb\ub41c \ub370\uc774\ud130 \uc218\uc9d1 \ubb38\uc81c\ub97c \uc5c6\uc560\uace0 \uaddc\uc81c \uc900\uc218\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc0ad\uc81c\uc758 \uc5b4\ub824\uc6c0\uc744 \uc644\ud654\ud558\uba70 \ubcc0\uacbd \ub370\uc774\ud130 \ucea1\ucc98\ub97c \uc704\ud55c \ub370\uc774\ud130 \uc218\uc815 \ubb38\uc81c\ub3c4 \uc5c6\uc560\uc90d\ub2c8\ub2e4. Delta Lake\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c ACID \ud2b8\ub79c\uc7ad\uc158\uc744 \uc9c0\uc6d0\ud558\uc5ec \ubaa8\ub4e0 \uc791\uc5c5\uc774 \uc644\uc804\ud788 \uc131\uacf5\ud558\uac70\ub098 \ub098\uc911\uc5d0 \ub2e4\uc2dc \uc2dc\ub3c4\ud560 \uc218 \uc788\uac8c \uc644\uc804\ud788 \uc911\ub2e8\ub418\ub3c4\ub85d \ubcf4\uc7a5\ud569\ub2c8\ub2e4.\uc774\ub97c \uc704\ud574 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uc0c8\ub85c \ub9cc\ub4e4 \ud544\uc694\ub3c4 \uc5c6\uc2b5\ub2c8\ub2e4. \ub610\ud55c Delta lake\ub294 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0 \uacfc\uac70 \ud2b8\ub79c\uc7ad\uc158\uc744 \ubaa8\ub450 \uae30\ub85d\ud558\ubbc0\ub85c GDPR\uacfc CCPA \ub4f1\uc758 \uaddc\uc815 \uc900\uc218 \ud45c\uc900\uc5d0 \uc548\uc815\uc801\uc73c\ub85c \ubd80\ud569\ud558\uae30 \uc704\ud574 \ub370\uc774\ud130\uc758 \uae30\uc874 \ubc84\uc804\uc5d0 \uc561\uc138\uc2a4\ud558\uc5ec \uc774\ub97c \ud65c\uc6a9\ud558\uae30\ub3c4 \uac04\ud3b8\ud569\ub2c8\ub2e4.\ub370\uc774\ud130 \uc218\uc9d1 \ub124\ud2b8\uc6cc\ud06c\ub124\uc774\ud2f0\ube0c \ucee4\ub125\ud130\ub85c \uac01\uc885 \uc560\ud50c\ub9ac\ucf00\uc774\uc158, \ub370\uc774\ud130\ubca0\uc774\uc2a4\uc640 \ud30c\uc77c \uc2a4\ud1a0\ub9ac\uc9c0\uc5d0\uc11c \ube60\ub974\uace0 \uc548\uc815\uc801\uc73c\ub85c \ub370\uc774\ud130\ub97c \uc190\uc27d\uac8c \uc218\uc9d1\ud574 Delta Lake\uc5d0 \ubcf4\uad00\ud569\ub2c8\ub2e4.\uace0\uac1d\"Databricks\ub294 \uc758\ub8cc \uc11c\ube44\uc2a4 \ubd80\ubb38\uc758 \uc0c8\ub85c\uc6b4 \uc218\uc694\uc5d0 \ubd80\ud569\ud558\uae30 \uc704\ud574 \uaf2d \ud544\uc694\ud588\ub358 \ubd84\uc11d\uacfc \uc6b4\uc601\uc131 \uac1c\uc120\uc740 \ubb3c\ub860 \ucd9c\uc2dc \uc2dc\uac04 \ub2e8\ucd95\uc774\ub77c\ub294 \ud6a8\uacfc\uae4c\uc9c0 \ub2ec\uc131\ud588\uc2b5\ub2c8\ub2e4.\"\n\u2013 Healthdirect Australia\uc758 Chief Architect, Peter James\uc790\uc138\ud788\"Databricks\uc640 Delta Lake\ub97c \ud65c\uc6a9\ud558\uba74\uc11c \uc774\ubbf8 \ub300\uaddc\ubaa8\ub85c \ub370\uc774\ud130\ub97c \ubbfc\uc8fc\ud654(democratize)\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uace0, \ub3d9\uc2dc\uc5d0 \ud504\ub85c\ub355\uc158 \uc6cc\ud06c\ub85c\ub4dc \uc2e4\ud589 \ube44\uc6a9\uc744 60% \uc904\uc5ec\uc11c \uc218\ubc31\ub9cc \ub2ec\ub7ec\ub97c \uc808\uac10\ud558\ub294 \ud6a8\uacfc\ub97c \uac70\ub450\uc5c8\uc2b5\ub2c8\ub2e4.\"\n\u2014 YipitData \ucd5c\uace0 \uae30\uc220 \ucc45\uc784\uc790(CTO) Steve Pulec\uc790\uc138\ud788\"Delta Lake\ub294 ACID \uae30\ub2a5\uc744 \uc81c\uacf5\ud574 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778 \uc6b4\uc601\uc744 \uac04\uc18c\ud654\ud558\uae30\n\ub54c\ubb38\uc5d0 \ud30c\uc774\ud504\ub77c\uc778 \uc548\uc815\uc131\uacfc \ub370\uc774\ud130 \uc77c\uad00\uc131\uc774 \uc88b\uc544\uc9d1\ub2c8\ub2e4. \ub3d9\uc2dc\uc5d0 \uce90\uc2f1\uc774\ub098 \uc790\ub3d9 \uc778\ub371\uc2f1\uacfc \uac19\uc740 \uae30\ub2a5\uc744 \uc774\uc6a9\ud558\uba74 \ub370\uc774\ud130\uc5d0 \ud6a8\uc728\uc801\uc73c\ub85c, \uc131\ub2a5 \uc218\uc900\uc5d0 \ub9de\ucdb0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\"\n\u2014 Columbia Sportswear \uc120\uc784 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uad00\ub9ac\uc790 Lara Minor\uc790\uc138\ud788\"Delta Lake \ub355\ubd84\uc5d0 \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778 \uad00\ub9ac\uc5d0 \uac04\uc18c\ud55c \ubc29\uc2dd\uc73c\ub85c \uc811\uadfc\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc774 \ub355\ubd84\uc5d0 \uc6b4\uc601 \ube44\uc6a9\uc740 \uc808\uac10\ud558\uba74\uc11c \ub3d9\uc2dc\uc5d0 \ub2e4\uc6b4\uc2a4\ud2b8\ub9bc \ubd84\uc11d\uacfc \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uc758 \uc778\uc0ac\uc774\ud2b8 \ub3c4\ucd9c \uc2dc\uac04(time-to-insight)\uc740 \uc9e7\uc544\uc84c\uc5b4\uc694.\"\n\u2014 Viacom18 \ub514\uc9c0\ud138 \ubcc0\ud601 \ubc0f \uae30\uc220 \uc0ac\uc5c5\ubd80 AVP(Assistant Vice President) Parijat Dey\uc790\uc138\ud788\ub9ac\uc18c\uc2a4\n\uc5ec\ub7ec\ubd84\uc5d0\uac8c \ud544\uc694\ud55c \ubaa8\ub4e0 \ub9ac\uc18c\uc2a4\uac00 \ud55c \uacf3\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.\n\ub9ac\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 ebook\uacfc \ub3d9\uc601\uc0c1\uc744 \ud1b5\ud574 Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc744 \ud65c\uc6a9\ud558\ub294 \uc7a5\uc810\uc5d0 \ub300\ud574 \uc54c\uc544\ubcf4\uc138\uc694.\n\ub9ac\uc18c\uc2a4 \ub458\ub7ec\ubcf4\uae30eBook\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uc0ac\uc6a9 \uc0ac\ub840 Big Book\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uad00\ub9ac \uae30\ucd08 \uc0b4\ud3b4\ubcf4\uae30\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0 Bill Inmon\uc774 \uad6c\ucd95\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4Tech Talks \ubc0f \uad50\uc721Delta Lake \uc2dc\uc791\ud558\uae30 \u2013 Tech Talk \uc2dc\ub9ac\uc988\uc6e8\ube44\ub098\uc88b\uc740 \ub188, \ub098\uc05c \ub188, \ud749\ud55c \ub188(The Good The Bad The Ugly)Delta Lake\ub85c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc790\uc138\ud788 \uc0b4\ud3b4\ubcf4\uae30\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30Delta Lake \uad00\ub828 \ubb38\uc11c\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mike-tang","text":"Mike Tang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMike TangAssociate Director, Responsible AI at VerizonBack to speakersXuning (Mike) Tang has more than a decade of academic and industrial experience in machine learning, natural language processing, and big data technologies. He is enthusiastic about applied research and solving complex business problems with cutting-edge technologies. He has managed large teams to build advanced analytics solutions for major manufacturing, hospitality, and banking companies, as well as Am Law 100 law firms. Before joining Verizon, Mike was the leader of Berkeley Research Group (BRG)\u2019s Artificial Intelligence & Machine Learning practice, where he initiated BRG\u2019s ethical AI market offering. Prior to that, he worked for Deloitte and Fannie Mae.\nMike earned his Ph.D. from Drexel University in the College of Computing and Informatics. He has filed multiple patents and inventions and published more than 40 peer-reviewed research papers in top computer science journals and international conferences. He also serves as an associate editor and reviewer for multiple flagship journals in Artificial Intelligence and Machine Learning.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cyrielle-simeone\/#","text":"Cyrielle Simeone - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCyrielle SimeonePrincipal Product Marketing Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lin-qiao","text":"Lin Qiao - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLin QiaoCo-creator of PyTorch, Co-founder and CEO at FireworksBack to speakersLin Qiao is the co-founder and CEO of Fireworks, which is on a mission to accelerate the transition to AI-powered business via interactive experimentation and a production platform centered around PyTorch technologies and state-of-the-art models built using PyTorch. She led the development of PyTorch, AI compilers and on-device AI platforms at Meta for the past half-decade. She drove AI research to production innovations across hardware acceleration, enabling model exploration and large and complex model scaling, building production ecosystems and platforms for all Meta\u2019s AI use cases. She received a Ph.D. in computer science, started her career as a researcher in Almaden Research Lab, and later moved to the industry as an engineer. Prior to Meta, she worked on a broad range of distributed and data processing domains, from high-performance columnar databases, OLTP systems, streaming processing systems, data warehouse systems, and logging and metrics platforms.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/google-cloud","text":"Databricks Google Cloud Platform (GCP) | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks on Google CloudOpen lakehouse platform meets open cloud to unify data engineering, data science and analyticsGet startedDatabricks on Google Cloud is a jointly developed service that allows you to store all your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all your analytics and AI workloads. Tight integration with Google Cloud Storage, BigQuery and the Google Cloud AI Platform enables Databricks to work seamlessly across data and AI services on Google Cloud.\nReliable data engineeringSQL analytics on all your dataCollaborative data scienceProduction machine learning\nWhy Databricks on Google Cloud?OpenBuilt on open standards, open APIs and open infrastructure so you can access, process and analyze data on your terms.OptimizedDeploy Databricks on Google Kubernetes Engine, the first Kubernetes-based Databricks runtime on any cloud, to get insights faster.IntegratedGet one-click access to Databricks from the Google Cloud Console, with integrated security, billing and management.Learn more from these customers\n\u201cDatabricks on Google Cloud simplifies the process of driving any number of use cases on a scalable compute platform, reducing the planning cycles that are needed to deliver a solution for each business question or problem statement that we use.\u201d\u2014 Harish Kumar, the Global Data Science Director at ReckittStreamlined integration with Google CloudGoogle Cloud StorageGoogle Cloud StorageEnable seamless read\/write access for data in Google Cloud Storage (GCS) and leverage the Delta Lake open format to add powerful reliability and performance capabilities within Databricks.Google Kubernetes EngineBigQueryBig Cloud IdentityGoogle Cloud AI PlatformGoogle Cloud BillingLookerPartner ecosystemResourcesVirtual EventsVirtual Workshop: The Open Data LakeNewsDatabricks Partners With Google Cloud to Deliver Its Platform to Global BusinessesBlogs and ReportsAnnouncing the Launch of Databricks on Google CloudIntroducing Databricks on Google Cloud \u2013 Now in Public PreviewDatabricks on Google Cloud DatasheetDatabricks on Google Cloud Now Generally AvailableData Engineering, Data Science and Analytics With Databricks on Google CloudReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/wassym-bensaid","text":"Wassym Bensaid - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWassym BensaidSr. Vice President, Software Development at RivianBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/product\/delta-sharing","text":"Delta-Freigabe | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDelta-FreigabeEin offener Standard f\u00fcr die sichere Freigabe von Daten-AssetsErste SchritteDemo ansehenDatabricks Delta Sharing bietet eine offene L\u00f6sung zum sicheren Freigeben von Live-Daten aus Ihrem Lakehouse an jede beliebige Computerplattform.Die wichtigsten VorteileOffene plattform\u00fcbergreifende FreigabeGeben Sie ganz einfach vorhandene Daten in den Formaten Delta Lake und Apache Parquet f\u00fcr jede Computing-Plattform frei.Live-Daten ohne Replikation freigebenGeben Sie Live-Daten frei, ohne sie zu replizieren oder in ein anderes System zu kopieren.Zentralisierte GovernanceVerwalten, kontrollieren, pr\u00fcfen und verfolgen Sie die Nutzung der freigegebenen Daten zentral auf einer Plattform.Marktplatz f\u00fcr DatenprodukteErstellen und paketieren Sie Datenprodukte, einschlie\u00dflich Datens\u00e4tze, ML-Modelle und Notebooks, einmalig und verteilen Sie sie \u00fcberall \u00fcber einen zentralen Marktplatz.Datenschutzsichere Datenreinr\u00e4umeArbeiten Sie einfach mit Ihren Kunden und Partnern in jeder Cloud \u00fcber eine sichere, gehostete Umgebung zusammen und sorgen Sie gleichzeitig f\u00fcr den Datenschutz.Wie es funktioniertNative Integration mit der Databricks-PlattformDie native Integration mit dem Unity-Katalog gestattet organisations\u00fcbergreifend das zentrale Verwalten und Auditing freigegebener Daten. So k\u00f6nnen Sie Datenbest\u00e4nde vertrauensvoll mit Lieferanten und Partnern teilen, damit Unternehmensabl\u00e4ufe besser koordiniert und Sicherheits- und Compliance-Anforderungen zuverl\u00e4ssig erf\u00fcllt werden.Freigaben einfach verwaltenErstellen und verwalten Sie Anbieter, Empf\u00e4nger und Freigaben mit einer benutzerfreundlichen Benutzeroberfl\u00e4che, SQL-Befehlen oder REST-APIs mit vollst\u00e4ndiger CLI- und Terraform-Unterst\u00fctzungDatenprodukte erkunden und \u00fcber einen offenen Marktplatz darauf zugreifenFinden, bewerten und erhalten Sie von \u00fcberall aus Zugriff auf Datenprodukte wie Datens\u00e4tze, Modelle f\u00fcr Machine Learning, Dashboards und Notebooks, ohne dass Sie auf der Databricks-Plattform sein m\u00fcssen.Datenschutzsichere Datenreinr\u00e4umeArbeiten Sie mit Ihren Kunden und Partnern in jeder Cloud in einer datenschutzsicheren Umgebung zusammen. Geben Sie Daten aus Ihren Data Lakes sicher ohne Datenreplikation frei. Arbeiten Sie mit Beteiligten in ihrer bevorzugten Cloud zusammen und bieten Sie ihnen die Flexibilit\u00e4t, komplexe Berechnungen und Workloads in jeder Sprache auszuf\u00fchren \u2013 SQL, R, Scala, Java und Python. F\u00fchren Sie Mitarbeiter mithilfe vordefinierter Vorlagen, Notebooks und Dashboards durch g\u00e4ngige Anwendungsf\u00e4lle und verk\u00fcrzen Sie so die Zeit bis zur Erkenntnisgewinnung.Anwendungsf\u00e4lleInterne Freigabe innerhalb des Gesch\u00e4ftsbereichsErstellen Sie Data Mesh mit Delta Sharing, um Daten sicher zwischen Gesch\u00e4ftsbereichen und Tochtergesellschaften auszutauschen.B2B-FreigabeDatenmonetarisierungKunden\u201eDelta Sharing hat uns geholfen, unseren Datenbereitstellungsprozess f\u00fcr gro\u00dfe Datenmengen zu optimieren. So k\u00f6nnen unsere Kunden ihre eigene Rechenumgebung nutzen, um frisch kuratierte Daten mit wenig bis gar keiner Integrationsarbeit zu lesen, und wir konnten unseren Katalog einzigartiger, hochwertiger Datenprodukte erweitern.\u201c\u2013 William Dague, Head of Alternative Data\u201eAls Datenunternehmen ist es von entscheidender Bedeutung, unseren Kunden Zugriff auf unsere Datens\u00e4tze zu geben. Die Databricks Lakehouse-Plattform mit Delta Sharing rationalisiert diesen Prozess wirklich und erm\u00f6glicht es uns, unabh\u00e4ngig von Cloud oder Plattform sicher eine viel breitere Benutzerbasis zu erreichen.\u201c\u2013 Felix Cheung, VP of Engineering\u201eDie Nutzung der leistungsstarken Funktionen von Delta Sharing von Databricks erm\u00f6glicht Pumpjack Dataworks ein schnelleres Onboarding-Erlebnis, sodass der Export, Import und die Remodellierung von Daten \u00fcberfl\u00fcssig werden, was unseren Kunden einen sofortigen Mehrwert bietet. Schnellere Ergebnisse bieten unseren Kunden und ihren Partnern gr\u00f6\u00dfere Gesch\u00e4ftschancen.\u201c\u2013 Corey Zwart, Head of Engineering\u201eMit Delta Sharing k\u00f6nnen unsere Kunden fast sofort auf kuratierte Datens\u00e4tze zugreifen und sie in Analytics-Tools ihrer Wahl integrieren. Der Dialog mit unseren Kunden verlagert sich von einem geringwertigen, kleinlichen Hin und Her bei der Aufnahme zu einer hochwertigen analytischen Diskussion, in der wir erfolgreiche Kundenerlebnisse f\u00f6rdern. W\u00e4hrend sich unsere Kundenbeziehungen weiterentwickeln, k\u00f6nnen wir \u00fcber Delta Sharing nahtlos neue Datens\u00e4tze bereitstellen und bestehende aktualisieren, um Kunden \u00fcber die wichtigsten Trends in ihren Branchen auf dem Laufenden zu halten.\u201c\u2013 Anup Segu, Data Engineering Tech LeadEin offenes \u00d6kosystemGreifen Sie direkt vom Anbieter in benutzerfreundlichen SQL-, Python- oder BI-Tools auf die neueste ver\u00f6ffentlichte Version zu.RessourcenKeynote und Webinar[Keynote]Data Governance and sharing on the lakehouse beim Data + AI Summit 2022[On-Demand-Webinar]Beschleunigen Sie den Gesch\u00e4ftswert mit Delta-SharingBlogsAnk\u00fcndigung der allgemeinen Verf\u00fcgbarkeit von Delta-SharingDelta Sharing: Ein offener Standard f\u00fcr sicheren DatenaustauschDie drei wichtigsten Anwendungsf\u00e4lle f\u00fcr den Datenaustausch mit Delta SharingL\u00f6sungs\u00fcbersicht und E-Book[E-Book] Die neue Delta-Sharing-L\u00f6sung erkundenDelta Sharing: Ein offener Standard f\u00fcr sicheren DatenaustauschRise of the Data Lakehouse von Bill Inmon, dem Vater des Data WarehouseBereit f\u00fcr Ihre ersten Schritte mit Databricks?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/us-pub-sector-services","text":"Public Sector Services Schedule | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPublic Sector Services ScheduleThis Schedule sets forth terms related to use by Public Sector Customers of Databricks Services and is incorporated as part of the\u00a0Master Cloud Services Agreement\u00a0(the \u201cMCSA\u201d). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Contracting Entity and Order of Precedence.\u00a0If an Order identifies the Databricks contracting party as Databricks Federal, LLC (\u201cDBF\u201d), then any references in the Agreement to Databricks, including those contained in this Schedule, will be deemed to refer to DBF. Orders referencing DBF or any Order between Databricks and a Public Sector Customer will be deemed to incorporate this Schedule. In the event of a conflict between this Schedule and the MCSA or another Schedule thereto, this Schedule will be deemed to control solely for such DBF Order or other Public Sector Order.Databricks Services.\u00a0This Schedule establishes the terms and conditions enabling Databricks to provide Databricks Services to Public Sector Customers. For the purposes of this Schedule, references to \u201cCustomer\u201d in an Order, the MCSA or any Schedule thereto will be deemed to refer to Public Sector Customer or Customer Representative, as applicable. This Schedule does not grant you access to the Databricks Services without mutual agreement to an Order and applicable Databricks Services Schedule.Additional Definitions.\u201cCustomer Information\u201d\u00a0means Customer Content (if\u00a0you are purchasing Platform Services) and \/ or Customer Materials (if you are purchasing Advisory Services).\u201cCustomer Representative\u201d\u00a0means an organization authorized on behalf of a Public Sector Customer to purchase Databricks Services on its behalf, as designated in an applicable Order.\u201cFederal Customer\u201d\u00a0means any United States federal government branch or agency Customer of Databricks Services subject to this Schedule, including agencies and departments from the Executive Branch, the Congress, or the Military.\u201cPublic Sector Customer\u201d\u00a0means any Federal Customer or other United States state or local government, or entity, authority, agency, or body exercising executive, legislative, judicial, regulatory or administrative functions of any such government, who purchases Databricks Services subject to this Schedule. Public Sector Customer(s) may include public universities and hospitals.Modification.\u00a0Notwithstanding anything contained in the MCSA or any other Schedule, you agree as follows:\nU.S. Government License Rights.\u00a0If Customer is a Federal Customer, or the Agreement otherwise become subject to the Federal Acquisition Regulation (FAR), Customer acknowledges and agrees that the Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation constitute \u201ccommercial computer software\u201d and \u201ccommercial computer software documentation\u201d, respectively, provided as \u201cCommercial Items\u201d as defined in FAR 2.101. The Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation have been developed solely at private expense, and as set forth in FAR 12.212 and DFARS Section 227.7202, any use, modification, reproduction release, performance, display or disclosure thereof shall be solely in accordance with the terms of the MCSA as modified by this Schedule.Customer Representative Obligations.\u00a0Customer Representative will have no rights to the Databricks Services if purchasing Databricks Services on behalf of a Public Sector Customer except to the extent that a Public Sector Customer provides access to Customer Representative as its Authorized User. Customer Representative agrees to bind Public Sector Customer to the terms of the Agreement, including this Schedule, and will ensure that Databricks will be a third party beneficiary to such agreement. Customer Representative acknowledges that submission of a purchase order or Order will be deemed to be a representation to Databricks that the applicable Public Sector Customer has assented to the terms of the Agreement. Customer Representative will use commercially reasonable efforts to enforce the terms of the Agreement in the event it becomes aware that the Public Sector Customer has breached any terms and conditions of the Agreement where such breach adversely affects Databricks\u2019 rights or contractual protections. Customer Representative will notify Databricks promptly upon learning of any such breach.Acceptance.\u00a0Any Advisory Services or Training Services provided under the MCSA shall be deemed accepted upon delivery.Confidentiality.\u00a0Any provisions contained in the Agreement that require a Public Sector Customer to keep certain information confidential may be subject to the Freedom of Information Act, 5 U.S.C. \u00a7552 or similar applicable state or local state law, and any order by a United States Federal Court or court of appropriate jurisdiction.Equitable Relief.\u00a0Orders entered into directly with Databricks by a Federal Customer subject to this Schedule will only allow equitable relief when explicitly provided by statute (e.g., Prompt Payment Act or Equal Access to Justice Act).Auto Renewal, Customer Responsibility, and Indemnification.\u00a0If you are a Federal Customer subject to the Anti-Deficiency Act or similar limitations on fees or payment absent approved allocation of funding, any auto-renewal of Databricks Services, penalty fees or interest accrual associated with late payment, or Customer indemnification obligations in the Agreement will be deemed inapplicable. Federal Customer agrees to be responsible to Databricks for any claim (i) by a third party alleging that Customer Information or its use with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights; and \/ or (ii) arising from or related to your use of the Databricks Services allegedly in violation of any applicable law or the Agreement. Any clause in the Agreement requiring Databricks to defend or indemnify a Public Sector Customer is hereby amended solely to the extent that (a) the U.S. Department of Justice has the sole right to represent the Federal Customers in any such action in accordance with 28 U.S.C. 516, and (b) representation on behalf of Public Sector Customers may lie solely with the applicable state attorney general\u2019s office if you are a state or local government entity.Governing Law.\u00a0Orders entered into directly by a Federal Customer subject to this Schedule, the MCSA and any other applicable Schedules will be governed by and construed in accordance with the laws of the United States, and venue and jurisdiction of any dispute will be determined by applicable federal statute. If the federal laws of the United States are not dispositive, then to the extent permitted by federal law, the Agreement will be governed by the laws of the State of California, excluding its conflict of law principles. If you are a state or local government entity, the Agreement is governed by the laws of your state, excluding its conflict of laws principles. In the event the Uniform Computer Information Transactions Act (UCITA) or any similar laws or regulations are enacted, to the extent allowed by law, such law or regulation will not apply to the Agreement, and the governing law will remain as if such law or regulation had not been enacted. The Agreement does not affect statutory rights that cannot be waived or changed by contract.Disputes.\u00a0Notwithstanding any other provision in the Agreement, any dispute between Databricks and any Federal Customer arising under or related to the Agreement will be resolved exclusively under the terms and procedures of the Contract Disputes Act (41 U.S.C. Chapter 71).Assignment.\u00a0If you are a Federal Customer purchasing directly from Databricks, then except to the extent transfer may not be legally restricted, you may not assign the Agreement, any Order, or any right or obligation under the Agreement, or delegate any performance, without Databricks\u2019 prior written consent, which consent will not be unreasonably withheld. Databricks may assign its right to receive payment in accordance with the Assignment of Claims Act (31 U.S.C. 3727) and FAR 52.212-4(b), and may assign the Agreement to the extent not prohibited by the Anti-Assignment Act (41 U.S.C. 15). Subject to the requirements of FAR 42.12 (Novation and Change-of-Name Agreements), you agree to recognize Databricks\u2019 successor in interest following a transfer of assets or a change in name. Any attempted assignment or transfer in violation of the foregoing will be void. Subject to the foregoing, the Agreement will be binding upon and will inure to the benefit of the parties and their respective successors and assigns.Taxes.\u00a0References to taxes payable by Customer will not apply to your purchases of Databricks Services to the extent You are exempt from such taxes, provided that you agree to provide documentation reasonably acceptable to Databricks evidencing your tax-exempt status.Last Updated August 12, 2022. For earlier versions, please send a request to\u00a0[email\u00a0protected]\u00a0(with \u201cTOS Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/gidon-gershinsky\/#","text":"Gidon Gershinsky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGidon GershinskyLead Systems Architect at AppleBack to speakersGidon Gershinsky designs and builds Data Security solutions at Apple. He plays a leading role in the Apache Parquet community work on big data encryption and integrity verification technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/the-modern-cloud-data-platform-dummies","text":"\n\n\n\n\n\n\n\nModern Cloud Platform for Dummies\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n \n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/worldtour\/","text":"World Tour 2022 Homepage - Data + AI Summit 2022 | DatabricksThis site works best with JavaScript enabled.HomepageFind My LocationOn demandSpeakersTrainingsSpecial EventsSponsorsHealthFAQDestination LakehouseFind Your LocationData + AI World Tour brings the data lakehouse to the global data community. With content, customers and speakers tailored to each region, the tour showcases how and why the data lakehouse is quickly becoming the cloud data architecture of today\u2019s most data-driven companies.Featured SpeakersTony ChanSenior Data Science ManagerOctopus CardMichael CamarriPhD, Head of Data Science for APACCognizantRaela WangHead of Field EngineeringDatabricksScott SunPartner, Digital Analytics ServiceDeloitteVeronica HoHead of Data Analytics & InsightsSwire PropertiesOlivier KuzinerGeneral ManagerEkimetricsJia Woei LingManaging Director, North AsiaDatabricks Wang YiField Engineering ManagerDatabricksGerman ChungData Engineering LeadLi & Fung | LFXArnab MaulikAssociate Head of Beta LabsLane Crawford Joyce GroupEd LentaSVP and GM, Asia Pacific & JapanDatabricksSun Yoke KuanRegional DirectorASEANTrirat SuwanprateebChief Executive OfficerSCB TechWanlapa LinlawanChief Operating OfficerDataXPedro Uria-RecioChief Analytics & AI OfficerTrue DigitalPaul HoweGroup Chief Information OfficerMakroKramol PulkesExecutive Vice President, Data and Analytics HeadKASIKORNBANKChris D'AgostinoGlobal Field CTODatabricksLeo LiuChief Digital OfficerLi & Fung | LFXGary LamChief Technology OfficerLivi BankAlex WuChief ArchitectLivi BankNicholas EayrsVice President, Field EngineeringDatabricksThomas QianWholesale Chief Data Science Architect & Analytical Platform LeadHSBCJack NgDirector of TechnologyLane Crawford Joyce GroupTony ChanSenior Data Science ManagerOctopus CardMichael CamarriPhD, Head of Data Science for APACCognizantRaela WangHead of Field EngineeringDatabricksScott SunPartner, Digital Analytics ServiceDeloitteVeronica HoHead of Data Analytics & InsightsSwire PropertiesOlivier KuzinerGeneral ManagerEkimetricsJia Woei LingManaging Director, North AsiaDatabricks Wang YiField Engineering ManagerDatabricksGerman ChungData Engineering LeadLi & Fung | LFXArnab MaulikAssociate Head of Beta LabsLane Crawford Joyce GroupEd LentaSVP and GM, Asia Pacific & JapanDatabricksSun Yoke KuanRegional DirectorASEANTrirat SuwanprateebChief Executive OfficerSCB TechWanlapa LinlawanChief Operating OfficerDataXPedro Uria-RecioChief Analytics & AI OfficerTrue DigitalPaul HoweGroup Chief Information OfficerMakroKramol PulkesExecutive Vice President, Data and Analytics HeadKASIKORNBANKChris D'AgostinoGlobal Field CTODatabricksLeo LiuChief Digital OfficerLi & Fung | LFXGary LamChief Technology OfficerLivi BankJoin the World TourBangkok30 MarRegister NowHong Kong20 AprRegister NowSeoul25 AprRegister NowBangalore5 MayRegister NowPast EventsLondonNov 2nd 2022\nAmsterdam VirtualDec 13th 2022\nJapan VirtualDec 6th 2022\nKorea VirtualDec 7th 2022\nAPAC VirtualDec 1st 2022\nEMEA VirtualNov 2nd 2022\nSydneyNov 18th 2022\nNew YorkDec 13th 2022\nMunichNov 15th 2022\nParisNov 8th 2022\nHomepageLONDONPARISMUNICHSYDNEYNEW YORK CITYEMEA VIRTUALASIA-PACIFIC VIRTUALJAPAN VIRTUALKOREA VIRTUALAMERICAS VIRTUALPrivacy NoticeTerms of useYour Privacy ChoicesYour California Privacy Rights\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/miranda-luna","text":"Miranda Luna - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMiranda LunaProduct Management at DatabricksBack to speakersMiranda focuses on making all aspects of the Databricks SQL experience delightful. She resides in Seattle where outside of work she can usually be found skiing or golfing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/steve-mahoney","text":"Steve Mahoney - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSteve MahoneySr Manager, Product Management at DatabricksBack to speakersSteve has spent the past 18 years building platform-driven businesses in the data analytics and infrastructure space as a founding engineer and leading product. He brings his healthy obsession for analytics, visualization, and data-driven storytelling as the product leader for Databricks' collaboration products including Delta Sharing, Databricks Marketplace, Clean Rooms, and OEMs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/praveen-vemulapalli\/#","text":"Praveen Vemulapalli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPraveen VemulapalliDirector- Technology at AT&TBack to speakersPraveen is the Director-Technology for Chief Data Office at AT&T. He oversees and manages AT&T's Network Traffic Data and Artificial Intelligence platforms. Responsible for 5G Analytics\/AI Research & Development (R&D). He also leads the on-premise to cloud transformation of the Core Network Usage platforms. Leading a strong team of Data Engineers, Data Scientists, ML\/AI Ops Engineers and Solution Architects.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/dataaisummit","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/itai-yaffe\/#","text":"Itai Yaffe - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingItai YaffeSenior Big Data Architect at AkamaiBack to speakersItai Yaffe is a Senior Big Data Architect at Akamai.\nPrior to Akamai, Itai was a Senior Solutions Architect at Databricks, a Principal Solutions Architect at Imply, and a big data tech lead at Nielsen Identity, where he dealt with big data challenges using tools like Spark, Druid, Kafka, and others.\nHe is also a part of the Israeli chapter's core team of Women in Big Data. Itai is keen on sharing his knowledge and has presented his real-life experience in various forums in the past.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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IN NO EVENT WILL DATABRICKS OR ANY OF ITS DIRECTORS, EMPLOYEES, AGENTS OR SUPPLIERS BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, EXEMPLARY, CONSEQUENTIAL OR PUNITIVE DAMAGES OF ANY KIND (INCLUDING, BUT NOT LIMITED TO, LOSS OF USE, LOSS OF BUSINESS, LOSS OF PROFITS, LOSS OF DATA, LOSS OF GOODWILL, SERVICE INTERRUPTION, COMPUTER DAMAGE, SYSTEM FAILURE OR THE COST OF SUBSTITUTE PRODUCTS OR SERVICES) ARISING OUT OF OR IN CONNECTION WITH THE SITES, AND ANY CONTENT, SERVICES OR PRODUCTS INCLUDED ON OR OTHERWISE MADE AVAILABLE THROUGH THE SITES, REGARDLESS OF THE FORM OF ACTION (WHETHER IN CONTRACT, TORT, STRICT LIABILITY, EQUITY OR OTHERWISE) AND EVEN IF WE ARE AWARE OF OR HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.\n\u00a0IN NO EVENT WILL OUR TOTAL CUMULATIVE LIABILITY TO YOU ARISING OUT OF OR IN CONNECTION WITH THESE TERMS, OR FROM THE USE OF OR INABILITY TO USE THE SITES, INCLUDING ANY CONTENT, OR FROM THE USE OF OR EXPOSURE TO ANY SUBMISSIONS, EXCEED ONE HUNDRED DOLLARS ($100.00). 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YOU ACKNOWLEDGE THAT THE LIMITATIONS OF LIABILITY SET FORTH IN THIS SECTION 7 SHALL SURVIVE ANY TERMINATION OR EXPIRATION OF THESE TERMS OR YOUR USE OF THE SITES.INDEMNIFICATION\nTo the fullest extent permitted by law, you agree to indemnify, defend and hold harmless Databricks, its officers, directors, shareholders, successors in interest, employees, agents, subsidiaries and affiliates, from and against any and all actual or threatened third party claims (groundless or otherwise), demands, losses, damages, costs and liability, proceedings (at law or in equity) and expenses (including reasonable attorneys\u2019 and expert fees and costs of investigation) arising out of or in connection with (a) your use of the Sites, including without limitation any of your Submissions, (b) your breach of these Terms, including your breach of any covenant, representation, warranty, term, or condition set forth herein, including, without limitation, the obligations set forth in Section 3 (Information Submitted Through Our Sites) and Section 4 (Required Conduct While Using Our Sites), (c) your violation of any law or regulation or of any third party rights, including infringement, libel, misappropriation, or other violation of any third party\u2019s intellectual property or other legal rights or (d) the disclosure, solicitation or use of any personal information by you, whether with or without your knowledge or consent. 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Databricks shall not be liable to you or any third party for any termination of your access to any part of the Sites. The rights and obligations of these Terms which by their nature should survive, shall so survive any termination of your use of the Sites.CONTACT\nQuestions or comments about the Terms or about the Sites may be directed to Databricks at the email address [email\u00a0protected] You may also email us at that address if you would like to report what you believe to be a violation of these Terms. However, please note that we do not accept any responsibility to maintain the confidentiality of any report of a violation you may submit to us, including your identity, nor do we commit to providing a personal reply to any report you submit, nor are we obligated to take action in response to your report.CLAIMS OF COPYRIGHT INFRINGEMENT\nDatabricks respects the intellectual property rights of others and we request that the people who use the Sites do the same. The Digital Millennium Copyright Act of 1998 (the \u201cDMCA\u201d) provides recourse for copyright owners who believe that material appearing on the Internet infringes their rights under U.S. copyright law. If you believe in good faith that materials available on the Sites infringe your copyright, you (or your agent) may send Databricks a notice requesting that we remove the material or block access to it. If you believe in good faith that someone has wrongly filed a notice of copyright infringement against you, you may send a counter-notice to Databricks under applicable provisions of the DMCA. Please note that substantial penalties under U.S. copyright law may be levied against any filer of a false counter-notice. Notices and counter-notices must meet the then-current statutory requirements imposed by the DMCA. See 17 U.S.C. \u00a7 512(c)(3), available at https:\/\/www.copyright.gov\/title17\/92chap5.html for details. 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We encourage you to consult your legal advisor before filing a notice or counter-notice.In accordance with the DMCA and other applicable law, Databricks may at our discretion limit access to the Sites and\/or terminate the accounts of any users who infringe any intellectual property rights of others, whether or not there is any repeat infringement.GENERAL\nThe Terms and the relationship between each user and Databricks shall be governed by the laws of the State of California without regard to its conflict of law provisions and each party shall submit to the personal and exclusive jurisdiction of the courts located in San Francisco, California. The application of the United Nations Convention on Contracts for the International Sale of Goods is expressly excluded. 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Databricks\u2019 failure to insist on or enforce strict performance of these Terms shall not be construed as a waiver by Databricks of any provision or any right it has to enforce these Terms, nor shall any course of conduct between Databricks and you or any other party be deemed to modify any provision of these Terms. The headings of the sections of these Terms are for convenience of reference only and are not intended to restrict, affect or be of any weight in the interpretation or construction of the provisions of such sections.\n\u00a0None of your rights or duties under these Terms may be transferred, assigned or delegated by you without our prior written consent, and any attempted transfer, assignment or delegation without such consent will be void and without effect. We may freely transfer, assign or delegate any of our rights or duties under these Terms. Subject to the foregoing, these Terms will be binding upon and will inure to the benefit of the parties and their respective representatives, heirs, administrators, successors and permitted assigns. No provision of these Terms is intended for the benefit of any third party, and the parties do not intend that any provision should be enforceable by a third party. Our relationship is an independent contractor relationship, and neither these Terms nor any actions by either party may be interpreted as creating an agency or partnership relationship. Nothing in these Terms shall be construed to obligate Databricks to enter into or engage with you on any commercial transaction.If you are provided access to any Software, you acknowledge that such Software may be subject to regulation by local laws and United States government agencies which prohibit export or diversion of certain products or information about products to certain countries and certain persons. 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{"source":"https:\/\/www.databricks.com\/terms-of-use","text":"Terms of Use | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (\u201cTerms\u201d) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than *.cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the \u201cSites\u201d). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the \u201cPlatform Services\u201d), which are subject to the\u00a0Databricks Terms of Service\u00a0(or with respect to the Community Edition, the\u00a0Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (\u201cDatabricks\u201d) and our subscribers (\u201cSubscribers\u201d) (any such agreement, a \u201cServices Agreement\u201d).PLEASE READ CAREFULLY THESE TERMS AND THE\u00a0DATABRICKS PRIVACY POLICY\u00a0(\u201cPRIVACY POLICY\u201d) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. BY ACCESSING OR USING ANY OF THE SITES, YOU REPRESENT THAT YOU ARE AT LEAST 18 YEARS OLD, YOU ACKNOWLEDGE AND AGREE THAT YOU HAVE READ AND UNDERSTOOD THESE TERMS, AND YOU AGREE TO BE LEGALLY BOUND BY ALL OF THESE TERMS. IF YOU DO NOT AGREE TO ALL OF THESE TERMS, DO NOT ACCESS OR USE THE SITES. WE SUGGEST YOU PRINT A COPY OF THESE TERMS FOR YOUR RECORDS.Throughout the Terms, \u201cwe,\u201d \u201cus,\u201d \u201cour\u201d and \u201cours\u201d refer to Databricks, and \u201cyou,\u201d \u201cyour\u201d or \u201cyours\u201d refer to you personally (i.e., the individual who reads and agrees to be bound by these Terms) and, if you access the Sites on behalf of a legal entity, to that entity. If you are using the Sites on behalf of any entity you represent and warrant that you are authorized to accept these Terms on such entity\u2019s behalf and, by accepting these Terms, you are hereby binding such entity to the Terms.Subject to your compliance with these Terms, solely for so long as you are permitted by Databricks to access and use the Sites, and provided that you keep intact all copyright and other proprietary notices, you may view Content and you may download and print the materials that Databricks specifically makes available for downloading from the Sites (such as white papers or user documentation), in each case solely for informational purposes and solely for personal or internal business use.ACCEPTANCE OF TERMS\nDatabricks provides the Sites to you conditioned upon your accepting all of the Terms, without modification. Your use of the Sites constitutes your agreement with such Terms. We reserve the right to change, modify, add to, or remove portions of these Terms in our sole discretion at any time and we will, at our sole discretion, either post the modification on\u00a0https:\/\/www.databricks.com\/terms-of-use\u00a0or provide you with email notice of the modification. You should check these Terms periodically for changes and you can determine when these Terms were last revised by referring to the \u201cLast Updated\u201d reference at the top of these Terms. Any modification shall be effective immediately upon the uploading of modified Terms. You indicate your agreement to comply with, and be bound by, any such modification by continuing to use or access the Sites after modified Terms are posted. If the modified Terms are not acceptable to you, your sole recourse is to discontinue your use of the Sites.\n\u00a0If you have registered for and opened an account through the Sites (an \u201cAccount\u201d), you are entirely responsible for maintaining the confidentiality of your Account information, including your password, and for any and all activity that occurs under your Account. You agree to notify Databricks immediately of any unauthorized use of your Account or password, or any other breach of security. However, you will remain responsible for losses incurred by Databricks or by any other party due to your knowingly or inadvertently permitting unauthorized use of your Account or your Account information. You may not use anyone else\u2019s ID, password or account at any time unless we expressly pre-approve such use, or unless expressly permitted under a Services Agreement. Databricks cannot and will not be liable for any loss or damage arising from your failure to comply with these obligations. Registration for any account is void where the user lacks the requisite eligibility for registration or if such registration is otherwise prohibited.Software (\u201cSoftware\u201d) or the Platform Services may be made available to you through the Sites. Your rights to access and use the Platform Services, including any Software will be subject to your agreement to the applicable Services Agreement governing your use of the Platform Services and to any terms and conditions of any applicable third party software license agreement (\u201cSoftware License\u201d) identified in the Software or on the web page providing access to the Software. You may not use any Software unless you agree to be bound by all terms and conditions of any applicable Software License. If there is a conflict between any Services Agreement and any Software License, the conflicting term of the Software License shall control but only to the extent necessary to eliminate the conflict.LICENSE GRANT AND PROPRIETARY RIGHTS\nProvided that you fully comply at all times with these Terms and any other policies or restrictions posted on or transmitted through the Sites, Databricks grants you a limited, non-exclusive, non-transferable, revocable license to access and use the Sites. Except as otherwise specifically noted in these Terms or on the Sites, the Software, Submissions (as later defined), and all other information, content, user interfaces, graphics, registered or unregistered trademarks, logos, images, artwork, videos, and documents, and the design, structure, selection, coordination, expression, \u201clook and feel\u201d and arrangement of such materials, made available through the Sites (collectively, the \u201cContent\u201d), regardless of its source or creation, is owned, controlled or licensed by or to Databricks, and is protected by trade dress, copyright, patent and trademark laws, and various other intellectual property rights and unfair competition laws, and Databricks reserves and retains all rights in and to such Content. Any reproduction, redistribution or other use or exploitation of Software in violation of any applicable Software License or in violation of any license granted under these Terms or, if applicable, under a Services Agreement, is expressly prohibited by law, and may result in civil and criminal penalties.\n\u00a0\u201cApache\u201d and \u201cSpark\u201d are trademarks of the Apache Software Foundation. Any other third party trademarks, service marks, logos, trade names or other proprietary designations, that are or may become present within the Sites, including within any Content, are the registered or unregistered trademarks of the respective parties.Except solely as necessary for you to access the Sites for the intended purpose pursuant to these Terms, you may not copy, collect, modify, create derivative works or uses of, translate, distribute, transmit, publish, re-publish, perform, display, post, download, upload, sublicense, transfer, dispose of, resell or sell the Content or any other part of the Services. Except as expressly set forth in these Terms, these Terms do not grant to you any license to any intellectual property rights or other proprietary rights, including any implied licenses or licenses granted by estoppel or otherwise.INFORMATION SUBMITTED THROUGH OR TO OUR SITES\nAt our sole discretion, you may be permitted to provide Submissions (as defined in the next sentence) to the Sites (e.g., through our forums). \u201cSubmissions\u201d are defined to include: any messages, emails, text, graphics, code, questions, suggestions, comments, feedback, ideas, plans, notes, drawings, sample data, sound, images, video, original or creative materials, and other items or materials that you may provide to discussion forums, blogs, or other interactive features or areas of the Services where you or other users can create, post, transmit or store Content. Unless otherwise specifically agreed to by you and Databricks, by uploading, e-mailing, posting, publishing or otherwise transmitting any Submission, you hereby acknowledge that such Submission is non-confidential and you automatically grant (or warrant that the owner of such rights has expressly granted) to Databricks a perpetual, irrevocable, worldwide, non-exclusive, sub-licensable, fully paid-up and royalty-free license to use, make, have made, offer for sale, sell, copy, distribute, perform, display (whether publicly or otherwise), modify, adapt, publish, transmit and otherwise exploit such Submission, by means of any form, medium, or technology now known or later developed, and to grant to others rights to do any of the foregoing. In addition, you warrant that all so-called moral rights in such Submission have been waived.\n\u00a0For each Submission, you represent and warrant that you have all rights necessary for you to grant the license granted in the prior paragraph, and that such Submission, and your provision thereof to and through the Sites, does not violate any privacy, publicity, contractual, intellectual property, or other right or rights of any person or entity or otherwise violate any applicable laws, rules or regulations. You acknowledge that Databricks may have ideas or materials already under consideration or development that are or may be similar to your Submissions and that you are not entitled to any form of compensation or reimbursement from Databricks in connection with your Submissions. You agree to be fully responsible for, and to pay any and all royalties, fees, damages, and any other monies owing any person or entity by reason of, any Submission you provide to the Sites. We reserve the right to terminate access to all or any part of the Sites for anyone we suspect to be an infringer of our or any third party\u2019s intellectual property rights of any kind whatsoever.You agree that you will not, and will not allow or authorize any third party to, post Submissions containing:Anything that is or may be (a) threatening, harassing, degrading, abusive or hateful; (b) an incitement to violence, terrorism or other wrongdoing; (c) defamatory or libelous; (d) invasive of privacy rights; (e) fraudulent, deceptive, impersonating of any person or entity, or misrepresentative of your affiliation with any person or entity; (f) obscene, pornographic, indecent, grotesque or otherwise objectionable; or (g) protected by copyright, trademark, confidentiality obligations, or other proprietary or privacy right without the express prior written consent of the owner of such right.Any material, the posting or usage of which would give rise to criminal or civil liability, or cause violation of any rules or regulations, or that encourages conduct that constitutes a criminal offense.Any virus, worm, Trojan horse or other computer code, file, data or program that is harmful, disruptive, corrupted, or invasive, or may be or is intended to damage or hijack the operation of any hardware or software.Any information identifiable to a particular individual, including but not limited to addresses, phone numbers, email addresses, birthdates, Social Security numbers and other government-issued identification numbers, payment card and other financial account numbers or login credentials, and health information.Any unsolicited or unauthorized advertising, promotional materials, junk mail, spam, chain letter, pyramid scheme, political campaign message, offering of an investment opportunity, or any other form of solicitation.Any material with respect to which you do not have all rights, power and authority necessary for its collection, use and processing, or where your use and provision to the Sites would breach any agreement between you and any third party.Databricks generally does not pre-screen or monitor Submissions (but reserves the right to do so) and does not control Submissions. Therefore, Databricks does not guarantee the accuracy, quality or appropriateness of Submissions and disclaims any responsibility for Submissions, including any liability for errors or omissions, or for any loss or damage of any kind incurred as a result of their use. However, Databricks reserves the right at its sole discretion to refuse, delete, screen or edit Submissions, provided that even if we do remove or alter any Submission, we shall have no obligation to stop our other uses of such Submission or any other Submission as permitted above. We have no obligation to store any of your Submissions. We have no responsibility or liability for the deletion or failure to store, transmit or receive your Submissions, nor do we have any responsibility for the security, privacy, storage or transmission of other communications originating with or involving your use of the Sites, except as may be expressly stated in these Terms or in the Privacy Policy. You are solely responsible for creating backup copies of and replacing any Submissions at your sole cost and expense. Our Privacy Policy governs your Submissions.By accepting these Terms, you agree to our collection, use, and disclosure of your information as described in the Privacy Policy. No one under age 18 may register for an Account or provide any personal information to Databricks or to the Sites. If we learn that we have collected personal information from or about anyone under age 18, we will delete that information as quickly as possible. If you believe that we might have any information from or about a child under 18, please contact us at\u00a0[email\u00a0protected]\u00a0with the subject \u201cChild Data\u201c.Databricks reserves the right to disclose any Submissions, and the circumstances surrounding their transmission, to any third party to operate the Sites, to protect Databricks or its suppliers or representatives, to protect users of the Sites, to comply with legal or regulatory obligations, to enforce these Terms, or for any other reason. Databricks is not responsible or liable for the conduct of, or your interactions with, any other users of the Sites (whether online or offline), or for any associated loss, damage, injury or harm. By using the Site, you may be exposed to Submissions that are offensive, indecent or objectionable and you agree that Databricks bears no liability for such exposure.REQUIRED CONDUCT WHILE USING OUR SITES\nWhile using the Sites you will comply with all applicable laws, rules and regulations. In addition, Databricks expects users of the Sites to respect the rights and dignity of others. Your use of the Sites is conditioned on your compliance with the rules of conduct set forth in this Section; any failure to comply may also result in termination of your access to the Sites pursuant to Section 9 (Suspension or Termination of Access to Our Sites). 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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/erika-ehrli","text":"Erika Ehrli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErika EhrliSenior Director of Product Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jacob-renn\/#","text":"Jacob Renn - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJacob RennChief Technologist at AI Squared, IncBack to speakersDr. Jacob Renn is co-founder and Chief Technologist of AI Squared, a seed-stage startup located in the Washington, DC area. At AI Squared, Jacob leads the company\u2019s R&D efforts. Jacob is the lead developer of DLite, a family of large language models developed by AI Squared, and he is also the creator of the BeyondML project. Jacob also serves as adjunct faculty at Capitol Technology University, where he completed his PhD in Technology with a focus in Explainable Artificial Intelligence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/jackie-brosamer","text":"Jackie Brosamer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJackie BrosamerDirector of Software Engineering at BlockBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/01\/17\/improving-drug-safety-with-adverse-event-detection-using-nlp.html","text":"Improving Drug Safety With Adverse Event Detection Using NLP -Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorImproving Drug Safety With Adverse Event Detection Using NLPby Amir Kermany, Michael Ortega, Moritz Steller, David Talby and Michael SankyJanuary 17, 2022 in Engineering BlogShare this postDon't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution accelerator for adverse drug event detection.The World Health Organization defines pharmacovigilance as \"the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine\/vaccine-related problem.\" In other words, drug safety.Pharmacovigilance: drug safety monitoring in the real-worldWhile all medicines and vaccines undergo rigorous testing for safety and efficacy in clinical trials, certain side effects may only emerge once these products are used by a larger and more diverse patient population, including people with other concurrent diseases.To support ongoing drug safety, biopharmaceutical manufacturers must report adverse drug events (ADEs) to regulatory agencies, such as the US Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in the EU. Adverse drug reactions or events are medical problems that occur during treatment with a drug or therapy. Of note, ADEs do not necessarily have a casual relationship with the treatment. But in aggregate, the proactive reporting of adverse events is a key part of the signal detection system used to ensure drug safety.Adverse event detection requires the right data foundationMonitoring patient safety is becoming more complex as more data is collected. In fact, less than 5% of ADEs are reported via official channels and the vast majority are captured in free-text channels: emails and phone calls to patient support centers, social media posts, sales conversations between clinicians and pharma sales reps, online patient forums, and so on.Robust drug safety monitoring requires manufacturers, pharmaceutical companies and drug safety groups to monitor and analyze unstructured medical text from a variety of jargons, formats, channels and languages. To do this effectively, organizations need a modern, scalable data and AI platform that can provide scientifically rigorous, near real-time insights.The path forward begins with the Databricks Lakehouse, a modern data platform that combines the best elements of a data warehouse with the low-cost, flexibility and scale of a cloud data lake. This new, simplified architecture enables healthcare providers and life sciences organizations to bring together all their data\u2014structured (like diagnoses and procedure codes found in EMRs), semi-structured (like clinical notes) and unstructured (like images)\u2014 into a single, high-performance platform for both traditional analytics and data science.Building on these capabilities, Databricks has partnered with John Snow Labs, the leader in healthcare natural language process (NLP), to provide a robust set of NLP tools tailored for healthcare text. This is critical, as much of the data used for adverse event detection is text-based. You can learn more about our partnership with John Snow in our previous blog, Applying Natural Language Processing to Health Text at Scale.Solution accelerator for adverse drug event detectionTo help organizations monitor drug safety issues, Databricks and John Snow Labs built a solution accelerator notebook for ADE using NLP. As demonstrated in our previous blog, by leveraging the Databricks Lakehouse Platform, we can use pre-trained NLP models to extract highly-specialized structures from unstructured text and build powerful analytics and dashboards for different personas. In this solution accelerator, we show how to use pre-trained models to process conversational text, extract adverse events and drug information and build a Lakehouse for pharmacovigilance that powers various downstream use cases.The solution accelerator follows 4 basic steps:Ingest unstructured medical text at scale.Use pre-trained NLP models to extract useful information such as adverse events (e.g., renal damage), drug names and timing of the events in near real-time.Correlate adverse events with drug entities to establish a relationship.Measure frequency of events to determine significance.Below is a brief summary of the workflow contained within the notebook.Overview of the adverse drug event detection workflowStarting with raw text data, we use a corpus of 20,000 texts with known ADE status (4,200 texts containing ADE) and apply a pre-trained biobert model to detect ADE status and assess the specificity and sensitivity of the model based on the ground truth and the confidence level in accuracy of the assignment. In addition, we extract ADE status and drug entities from the conversational texts by using a combination of ner_ade_clinical and ner_posology models.By simply adding a stage in the pipeline, we can detect the assertion status of the ADE (present, absence, occured in the past, etc).To infer the relationship status of an ADE with a clinical entity, we use a pre-trained model (re_ade_clinical), which detects the relationships between a clinical entity (in this case drug) and the inferred ADE.The sparknlp_display library has the ability to show relations on the raw text and their linguistic relationships and dependencies as demonstrated below.After the ADE and drug entity data has been processed and correlated, we can build powerful dashboards to monitor the frequency of ADE and drug entity pairs in real time.Get started analyzing adverse drug events with NLP on DatabricksWith this solution accelerator, Databricks and John Snow Labs make it easy to analyze large volumes of text data to help with real-time drug signal detection and safety monitoring. To use this solution accelerator, you can preview the notebooks online and import them directly into your Databricks account. The notebooks include guidance for installing the related John Snow Labs NLP libraries and license keys.You can also visit our industry pages to learn more about our Healthcare and Life Sciences solutions.Try Databricks for freeGet StartedSee all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=deltalake-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/product\/machine-learning-runtime","text":"ML Runtime \u2013 DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWMachine Learning RuntimeReady-to-use and optimized machine learning environmentTry for freeSchedule a demoThe Machine Learning Runtime (MLR) provides data scientists and ML practitioners with scalable clusters that include popular frameworks, built-in AutoML and optimizations for unmatched performance.BenefitsFrameworks of ChoiceML Frameworks are evolving at a frenetic pace and practitioners need to manage on average 8 libraries. The ML Runtime provides one-click access to a reliable and performant distribution of the most popular ML frameworks, and custom ML environments via pre-built containers.Augmented Machine LearningAccelerate machine learning from data prep to inference with built-in AutoML capabilities including hyperparameter tuning and model search using Hyperopt and MLflow.Simplified ScalingGo from small to big data effortlessly with an auto-managed and scalable cluster infrastructure. The Machine Learning Runtime also includes unique performance improvements for the most popular algorithms as well as HorovodRunner, a simple API for distributed deep learning.FeaturesFrameworks of ChoiceML Frameworks: The most popular ML libraries and frameworks are provided out-of-the-box including TensorFlow, Keras, PyTorch, MLflow, Horovod, GraphFrames, scikit-learn, XGboost, numpy, MLeap, and Pandas.Augmented MLAutomated Experiments Tracking:\u00a0Track, compare, and visualize hundreds of thousands of experiments using open source or Managed MLflow and the parallel coordinates plot feature.Automated Model Search (for Single-node ML):\u00a0Optimized and distributed conditional hyperparameter search across multiple model architectures with enhanced Hyperopt and automated tracking to MLflow.Automated Hyperparameter Tuning for Single-node Machine Learning:\u00a0Optimized and distributed hyperparameter search with enhanced Hyperopt and automated tracking to MLflow.Automated Hyperparameter Tuning for Distributed Machine Learning:\u00a0Deep integration with PySpark MLlib\u2019s Cross Validation to automatically track MLlib experiments in MLflow.Optimized for simplified scalingOptimized TensorFlow:\u00a0Benefit from TensorFlow CUDA-optimized version on GPU clusters for maximum performance.HorovodRunner:\u00a0Quickly migrate your single node deep learning training code to run on a Databricks cluster with HorovodRunner, a simple API that abstracts complications faced when using Horovod for distributed training.Optimized MLlib Logistic Regression and Tree Classifiers:\u00a0The most popular estimators have been optimized as part of the Databricks Runtime for ML to provide you with up to 40% speed-up compared to Apache Spark 2.4.0.Optimized GraphFrames:\u00a0Run GraphFrames 2-4 times faster and benefit from up to 100 times speed-up for Graph queries, depending on the workloads and data skew.Optimized Storage for Deep Learning Workloads:\u00a0Leverage high-performance solutions on\u00a0Azure,\u00a0AWS, and\u00a0GCP\u00a0for data loading and model checkpointing, both of which are critical to deep learning training workloads.How it worksThe Machine Learning Runtime is built on top and updated with every Databricks Runtime release. It is generally available across all Databricks product offerings including: Azure Databricks, AWS cloud, GPU clusters and CPU clusters.To use the ML Runtime, simply select the ML version of the runtime when you create your cluster.Databricks Runtime for Machine LearningCustomer StoryResourcesBlogsProductionizing Machine Learning: From Deployment to Drift DetectionDetecting Bias with SHAPHyperparameter Tuning with MLflow, Apache Spark MLlib and HyperoptIntroducing HorovodRunner for Distributed Deep Learning TrainingLoan Risk Analysis with XGBoost and Databricks Runtime for Machine LearningeBooksThe Big Book of Machine Learning Use CasesWebinarsAutoML Rapid, simplified machine learning for everyoneMLOps Virtual Event - Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningMLOps Virtual EventAutomated Hyperparameter Tuning, Scaling and Tracking on DatabricksSimple Steps to Distributed Deep LearningAccelerating Machine Learning on DatabricksNotebooksUse Keras with TensorFlow on a single node on DatabricksFrom single node to distributed training with PyTorch on DatabricksSimple Steps to Distributed Deep Learning Demo NotebookDocumentationDatabricks Runtime for Machine LearningApache Spark MLlibAutoMLDeep LearningHorovodRunner: Distributed Deep Learning with HorovodReady to get started?Follow the Quickstart GuideProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators?filters=retail","text":"Databricks Solution Accelerators - Deliver Data & AI Value Faster - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWIndustry SolutionsDeliver the data and AI-driven outcomes that matter most \u2014 fasterStart your free trialDatabricks Solution AcceleratorsSave hours of discovery, design, development and testing with Databricks Solution Accelerators. Our purpose-built guides \u2014 fully functional notebooks and best practices \u2014 speed up results across your most common and high-impact use cases. Go from idea to proof of concept (PoC) in as little as two weeks.\n\u00a0\nStart using Solution Accelerators with your free Databricks trial or your existing account.\n\u00a0\nStart your free trial todayBrowse AcceleratorssearchHide filtersIndustrySortDatabricksToxicity Detection in GamingfeaturedDatabricksOn-Shelf AvailabilityfeaturedDatabricksFine-Grained Demand Forecastingfeatured\ud83d\udd25DatabricksAutomated PHI RemovalfeaturednewDatabricksAbstracting Real-World Data for OncologyDatabricksAnti-Money LaunderingDatabricksCohort Building with Knowledge GraphsDatabricksComputer Vision FoundationsDatabricksCustomer Entity ResolutionDatabricksCustomer Lifetime Value\ud83d\udd25DatabricksCustomer SegmentationSplunkCyber Analytics (Splunk Connector)DatabricksDetecting Adverse Drug EventsnewDatabricksDigital Pathology Image AnalysisDatabricksDigital TwinsDatabricksESG Performance Analytics\ud83d\udd25DatabricksFHIR Interoperability with dbigniteDatabricksFuzzy Item MatchingDatabricksGenome-Wide Association StudiesDatabricksGeospatial Analytics to Identify FraudDatabricksHL7v2 Interoperability With SmolderDatabricksMedia Mix Modeling (MMM)DatabricksMedicare Risk AdjustmentDatabricksMerchant ClassificationDatabricksModern Investment PlatformDatabricksMulti-Touch AttributionDatabricksOptimized Order PickingDatabricksOverall Equipment EffectivenessDatabricksPredictive Maintenance (IoT)DatabricksPrice TransparencynewDatabricksProduct Quality InspectionDatabricksPropensity ScoringnewDatabricksR&D Optimization with Knowledge GraphsnewDatabricksReal-Time Bidding OptimizationDatabricksReal-Time Financial Fraud PreventionDatabricksReal-Time Point-of-Sale AnalyticsnewDatabricksReal-world EvidenceDatabricksRecommendation EngineDatabricksRegulatory ReportingDatabricksReputation RiskDatabricksRetention ManagementDatabricksRisk ManagementDatabricksSafety StockDatabricksSales Forecasting & Ad Attribution\ud83d\udd25DatabricksScalable Route GenerationDatabricksSocial Determinants of HealthDatabricksSubscriber Churn PredictionDatabricksSupply Chain Distribution OptimizationDatabricksSurvival Analysis & Lifetime ValueDatabricksThreat Detection with DNSDatabricksVideo Quality of ExperienceFAQHow much do Solution Accelerators cost?Solution Accelerators are available to any Databricks customer free of charge.Do I need to be a Databricks customer to use a Solution Accelerator?You can implement Solution Accelerators with a free Databricks trial or with your existing Databricks account.What can I expect from a Solution Accelerator?Solution Accelerators are designed to help you save hours of discovery, design, development and testing. Our goal is to jump-start your data and AI use cases by providing the right resources (notebooks, proven patterns and best practices). You can expect to go from idea to proof of concept (PoC) in as little as two weeks.See how actual customers use DatabricksExplore Customer StoriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/threat-detection","text":"Threat Detection at Scale With DNS Data and AI | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorThreat Detection at Scale With DNS Data and AIPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedDetect cybercriminals using DNS data, threat intelligence feeds and MLLeverage the Databricks Solution Accelerator for DNS analytics to accelerate time to detection and response across petabytes of data. Tap into DNS traffic logs, enrich streaming threat intelligence, and apply advanced analytics to detect DNS abnormalities and prevent malicious attacks.Enrich petabytes of DNS data for analyticsUncover unknown threat patternsScale security operations efficientlyDownload notebookResourcesCase studyLearn moreWebinarLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/11\/13\/how-to-evaluate-data-pipelines-for-cost-to-performance.html","text":"How Databricks Customer METEONOMIQS Evaluates Data Pipeline Cost to Performance - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorHow to Evaluate Data Pipelines for Cost to Performanceby Hector LeanoNovember 13, 2020 in Company BlogShare this postLearn best practices for designing and evaluating cost-to-performance benchmarks from Germany\u2019s #1 weather portal.While we certainly conduct several benchmarks, we know the best benchmark is your queries running on your data. But what are you benchmarking against in your evaluation? The answer seems obvious - cost and integration with your cloud architecture roadmap.\nWe are finding, however, that many enterprises are only measuring the costs of individual services within a workflow, rather than the entire cost of the workflow. When comparing different architectures, running a complete workflow will demonstrate the total resources consumed (data engine + compute + ancillary support functions).\nWithout knowing the duration, job failure rate of each architecture, and manual effort required to support a job, comparing list prices of the individual components in two architectures will be misleading at best.wetter.com case studywetter.com is the DACH region\u2019s #1 B2C weather portal with up to 20 million monthly unique users along with full cross-media production. To leverage and monetize its data, wetter.com created a new business unit called METEONOMIQS. With METEONOMIQS, the company could now generate new revenue-streams out of their data by developing and selling data-products to business customers. METEONOMIQS provides weather and geo-based data science services to decode the interrelation between weather, consumer behaviour and many other factors used by clients in retail, FMCG, e-commerce, tourism, food and advertising.\nMETEONOMIQS\u2019 challenge\nMETEONOMIQS had chosen Amazon EMR for processing their data from raw ingestion through to cleansed and aggregated to serve downstream API users. Originally EMR had been the obvious choice as a best-in-class cloud-based Spark engine that fit into their AWS stack.\nHowever, this architecture soon hit its limits. The data pipeline required substantial manual effort to update rows and clean tables, required high DevOps effort to maintain, and limited the potential to use ML due to prolonged development cycles. The poor notebook experience and risk of errors when handing over ML models from DS to DE made it harder to support\u00a0 multiple models at a time.\nThe greatest risk to the business however was the inability to implement an automated GDPR-compliant workflow by, for example, easily deleting individual customers. Instead METEONOMIQS had to manually clean the data, leading to days of downtime. With GDPR penalties reaching up to 4% of the parent company\u2019s global revenue, this presented a large risk for parent company ProSiebenSat.1.\nBuilding the testMETEONOMIQS turned to Databricks to see if there was a better way to architect their data ingest, processing, and management on Amazon S3. Working with Databricks, they set up a test to see how running this pipeline on Databricks compared in terms of:\nVector analyzedCapabilities requiredSetupAbility to set up IAM-access roles by usersAbility to integrate into their existing AWS Glue data catalogue as a metastorePipeline migrationAbility to migrate code from existing pipeline directly to Databricks without major re-engineering. Note: they did not tackle code optimization in this testGDPR complianceAbility to build a table with (test) customer\/app-ids which could be removed to fulfill the GDPR requirements (right to be forgotten).Ability to set up automated deletion job removing the IDs from all intermediate and results-tables and validate the outcomeClean up \/ UpdateAbility to reconstruct an example of a previously updated \/ cleaned-up procedure.Build a clean-up procedure based on above example and do an update on the affected recordsEase of useEase of building visualisations within the databricks-notebooks by using the built-in functionalities and external plotting libraries (like matplotlib).Ability to work on multiple projects\/streams by attaching two notebooks to a clusterML model managementSelect an existing model from the current environment and migrate the code for the training-procedure to DatabricksConduct training-run(s) and use MLFlow tracking server to track all parameters, metrics and artifactsOPTIONAL: Store the artifacts in the currently used proprietary formatRegister (best) model in the MLflow Model Registry, set it into \u201cproduction\u201d state and demonstrate the approval processDemonstrate the handover from data domain (model building) to systems of engagement domain (model production) via MLflow Model RegistryTotal costUse the generated data from the PoC and additional information (further pipelines\/size of the data\/number of users\/ \u2026) to project infrastructure costs, inclusive of Databricks, compute, and storage.Benchmark resultsVector analyzedEMR-based architectureDatabricks-based architectureSetup\u2714\u2714Pipeline migration\u2014\u2714GDPR compliance\u2718 GDPR deletes in hours\/days with downtime\n\u2714 GDPR deletes in minutes without downtime\nClean up \/ Update\u2718 Requires days of downtime\n\u2714 Data corrections\/enhancements without downtime\nEase of use\u2718\u2714ML model management\u2718\u2714 Improved collaboration between Data Scientists and Data Engineers \/ Dev Team\nTotal cost\n80% of EMR costs were from dedicated dev and analytics clusters leading to unpredictable compute costs.\n DataOps required substantial developer resources to maintain.\n\nThrough cluster sharing, METEONOMIQS could use cloud resources much more efficiently\n But more importantly, they can now do new use cases like automated GDPR compliance and scale their ML in ways not possible before.\nFor METEONOMIQS the main gains to the Databricks architecture were:\nAdding use cases (e.g., automated data corrections and enhancements) that hadn\u2019t been deployed on EMR due to the high level of development costsMassively decreasing the amount of manual maintenance required for the pipelineSimplifying and automating GDPR compliance of the pipeline so that it could now be done in minutes without downtime compared to hours\/days with downtime previouslyAdditionally, the team had high AWS resource consumption in the EMR architecture since shared environments were not possible on EMR. As a result team members had to use dedicated clusters. Databricks\u2019 shared environment for all developers plus the ability to work on shared projects (i.e., notebooks), resulted in a more efficient use of human and infrastructure resources.\nHandover of ML models from data scientists to the data engineering team was complicated and led the ML code to diverge. With MLflow the team now has a comfortable way to hand over models and track changes over time.\nFurther, as Databricks notebooks are much easier to use, METEONOMIQS could enable access to the data lake to a broader audience like, for example, the mobile app team.\nAs one of their next steps, METEONOMIQS will look to optimize their code for further infrastructure savings and performance gains as well as look at other pipelines to transition to Databricks architecture.\nTakeawaysThe keys to the team\u2019s successful benchmark relied on\nKnowing what they were measuring for: Often clients will only compare list prices of individual services (e.g., compare the cost of one Spark engine versus another) when evaluating different architectures. What we try to advise clients is not to look at individual services but rather the total job cost (data engine + compute + team productivity) against the business value delivered. In this case, wetter.com\u2019s data engineering team aligned their test with the overall business goal - ensuring their data pipelines could support business and regulatory requirements while decreasing infrastructure and developer overhead.Choosing critical workloads: Instead of trying to migrate all pipelines at once, the team\u00a0 narrowed the scope to their most pressing business case. Through this project they were able to validate that Databricks could handle data engineering, machine learning, and even basic business analytics at scale, on budget, and in a timely manner.Delivering value quickly: Critical for this team was to move from discussions to PoCs to production as quickly as possible to start driving cost savings. Discussions stretching months or longer was not an option nor a good use of their team\u2019s time. Working with Databricks, they were able to stand up the first benchmark PoCs in less than three weeks.Ready to run your own evaluation?If you are looking to run your own tests to compare costs and performance of different cloud data pipelines, drop us a line at [email\u00a0protected]. We can provide a custom assessment based on your complete job flow and help qualify you for any available promotions. Included in the assessment are:\nTech validation: understand data sources, downstream data use, and resources currently required to run pipeline jobBusiness value analysis: identify the company\u2019s strategic priorities, to understand how the technical use case (e.g., ETL) drives business use cases (e.g., personalization, supply chain efficiency, quality of experience). This ensures our SAs are designing a solution that fits not just today\u2019s needs but the ongoing evolution of your business.Below is an outline of our general approach based on best practices for designing and evaluating your benchmark test for data pipelines.\nDesigning the testGiven data pipelines within the same enterprise can vary widely depending on the data\u2019s sources and end uses - and large enterprises can have thousands of data pipelines spanning supply chain, marketing, product, and operations - how do you test an architecture to ensure it can work across a range of scenarios, end-user personas, and use cases? More importantly, how can you do it within a limited time? What you want is to be able to go from test, to validation, to scaling across as many pipelines as possible as quickly as possible to reduce costs as well as the support burden on your data engineers.\nOne approach we have seen is to select pipelines that are architecturally representative of most of an enterprise\u2019s pipelines. While this is a good consideration, we find selecting pipelines based primarily on architectural considerations does not necessarily lead to the biggest overall impact. For example, your most common data pipeline architecture might be for smaller pipelines that aren\u2019t necessarily the ones driving your infrastructure costs or requiring the most troubleshooting support from your data engineers.\nInstead, we recommend clients limit the scope of their benchmark tests to 3-5 data pipelines based on just two considerations:\nTest first on business critical data workloads: Often the first reflex is to start with less important workloads and then move up the stack as the architecture proves itself. However, we recommend running the test on strategic, business critical pipelines first because it is better to know earlier rather than later if an architecture can deliver on the necessary business SLAs. Once you prove you can deliver on the important jobs, then it becomes easier to move less critical pipelines over to a new architecture. But the reverse (moving from less critical to more critical) will require validating twice - first on the initial test and then once again for important workloads.Select pipelines based on the major stressors affecting performance: What\u2019s causing long lead times, job delays, or job failures? When selecting test pipelines, make sure you know what the stressors are to your current architecture, and select representative pipelines generating long delays, high fail rates, and\/or require constant support from your data engineering teams. For example, if you\u2019re a manufacturer trying to get a real-time view of your supply chain, from parts vendors to assembly to shipping, but your IoT pipelines take hours to process large volumes of small files in batches, that is an ideal test candidate.Evaluating the resultsOnce you have selected the data pipelines to test, the key metrics to evaluate are:\nTotal cost to run a job: What are the total resources required to run a job? This means looking not just at the data engine costs for ingest and processing, but also total compute and support function costs (like data validation) to complete the data query. In addition, what is your pipeline\u2019s failure rate? Frequent job failures mean reprocessing the data several times, significantly increasing infrastructure costs.Amount of time to run a job: How long does it take to run a job once you add cluster spin up and data processing along with the amount of time it takes to identify and remediate any job failures? The longer this period, the higher the infrastructure costs but also, the longer it will take for your data to drive real business value\/insights. Enterprises rely on data to make important business decisions and rigid pipelines with long lead times prevent businesses from iterating quickly.Productivity: How often are your jobs failing and how long does it take your data engineers to go through the logs to find the root cause, troubleshoot, and resolve? This loss of productivity is a real cost in terms of increased headcount plus the opportunity cost of having your data engineers focused on basic data reliability issues instead of solving higher level business problems. Even if your jobs run correctly, are your downstream users working with the most up to date information? Are they forced to deduplicate and clean data before use in reports, analytics, and data science? Particularly with streaming data where you can have out-of-order files, how can you ensure you have consistent data across users?Extensibility: Will adding new use cases or data sources require full re-engineering of your data pipelines, or do you have a schema that can evolve with your data needs?Additionally, as enterprises look to create a more future proof architecture, they should look to:\nImplementation complexity: How big of a migration will this be? How complex is the re-engineering required? How much and for how long will it take data engineering resources to stand up a new data pipeline? How quickly can your architecture conform to security requirements? When UK-based food box company Guosto rebuilt their ETL pipelines to Delta Lake on Databricks, they noted, \u201cthe whole implementation, from the first contact with Databricks to have the job running in production took about two months \u2014 which was surprisingly fast given the size of Gousto tech and the governance processes in place.\u201dPortability: As more enterprises look to multi-cloud, how portable is their architecture across clouds? Is data being saved in proprietary formats resulting in vendor lock in (i.e., will it require substantial costs to switch in the future)?Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/glossary\/tensorflow-guide","text":"Everything You Wanted To Know About TensorFlowPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWTensorFlowAll>TensorFlowTry Databricks for freeGet StartedIn November of 2015, Google released its open-source framework for machine learning and named it TensorFlow. It supports deep-learning, neural networks, and general numerical computations on CPUs, GPUs, and clusters of GPUs. One of the biggest advantages of TensorFlow is its open-source community of developers, data scientists, and data engineers who contribute to its repository. The current version of TensorFlow can be found on GitHub along with release notes. TensorFlow is by far the most popular AI engine being used today. What is TensorFlow?TensorFlow is an open-source library for numerical computation, large-scale machine learning, deep learning, and other statistical and predictive analytics workloads. This type of technology makes it faster and easier for developers to implement machine learning models, as it assists the process of acquiring data, serving predictions at scale, and refining future results.Okay, so exactly what does TensorFlow do? It can train and run deep neural networks for things like handwritten digit classification, image recognition, word embeddings, and natural language processing (NLP). The code contained in its software libraries can be added to any application to help it learn these tasks.TensorFlow applications can run on either conventional CPUs (central processing units) or GPUs (higher-performance graphics processing units). Because TensorFlow was developed by Google, it also operates on the company\u2019s own tensor processing units (TPUs), which are specifically designed to speed up TensorFlow jobs.You might also be wondering: what language is TensorFlow written in? Although it uses Python as a front-end API for building applications with the framework, it actually has wrappers in several languages including C++ and Java. This means you can train and deploy your machine learning model quickly, regardless of the language or platform you use.Click here for more FAQs about TensorFlow model development.TensorFlow historyGoogle first released TensorFlow in 2015 under the Apache 2.0 license. Its predecessor was a closed-source Google framework called DistBelief, which provided a testbed for deep learning implementation.Google's first TPUs were detailed publicly in 2016, and used internally in conjunction with TensorFlow to power some of the company\u2019s applications and online services. This included Google\u2019s RankBrain search algorithm and the Street View mapping technology.In early 2017, Google TensorFlow reached Release 1.0.0 status. A year later, Google made the second generation of TPUs available to Google Cloud Platform users for training and running their own machine learning models.Google released the most recent version, TensorFlow 2.0, in October 2019. Google had taken user feedback into account in order to make various improvements to the framework and make it easier to work with \u2014 for instance, it now uses the relatively simple Keras API for model training.Who created TensorFlow?As you now know, Google developed TensorFlow, and continues to own and maintain the framework. It was created by the Google Brain team of researchers, who carry out fundamental research in order to advance key areas of machine intelligence and promote a better theoretical understanding of deep learning.The Google Brain team designed TensorFlow to be able to work independently from Google\u2019s own computing infrastructure, but it gains many advantages from being backed by a commercial giant. As well as funding the project\u2019s rapid development, over the years Google has also improved TensorFlow to ensure that it is easy to deploy and use.Google chose to make TensorFlow an open source framework with the aim of accelerating the development of AI. As a community-based project, all users can help to improve the technology \u2014 and everyone shares the benefits.How does TensorFlow work?TensorFlow combines various machine learning and deep learning (or neural networking) models and algorithms, and makes them useful by way of a common interface.It enables developers to create dataflow graphs with computational nodes representing mathematical operations. Each connection between nodes represents multidimensional vectors or matrices, creating what are known as tensors.While Python provides the front-end API for TensorFlow, the actual math operations are not performed in Python. Instead, high-performance C++ binaries perform these operations behind the scenes. Python directs traffic between the pieces and hooks them together via high-level programming abstractions.TensorFlow applications can be run on almost any target that\u2019s convenient, including iOS and Android devices, local machines, or a cluster in the cloud \u2014 as well as CPUs or GPUs (or Google\u2019s custom TPUs if you\u2019re using Google Cloud).TensorFlow includes sets of both high-level and low-level APIs. Google recommends the high-level APIs for simplifying data pipeline development and application programming, but the low-level APIs (called TensorFlow Core) are useful for debugging applications and experimentation.What is TensorFlow used for? What can you do with TensorFlow?TensorFlow is designed to streamline the process of developing and executing advanced analytics applications for users such as data scientists, statisticians, and predictive modelers.Businesses of varying types and sizes widely use the framework to automate processes and develop new systems, and it\u2019s particularly useful for very large-scale parallel processing applications such as neural networks. It\u2019s also been used in experiments and tests for self-driving vehicles.As you\u2019d expect, TensorFlow\u2019s parent company Google also uses it for in-house operations, such as improving the information retrieval capabilities of its search engine, and powering applications for automatic email response generation, image classification, and optical character recognition.One of the advantages of TensorFlow is that it provides abstraction, which means developers can focus on the overall logic of the application while the framework takes care of the fine details. It\u2019s also convenient for developers who need to debug and gain introspection into TensorFlow apps.The TensorBoard visualization suite has an interactive, web-based dashboard that lets you inspect and profile the way graphs run. There\u2019s also an eager execution mode that allows you to evaluate and modify each graph operation separately and transparently, rather than creating the entire graph as a single opaque object and evaluating it all at once.Databricks Runtime for Machine Learning includes TensorFlow and TensorBoard, so you can use these libraries without installing any packages.Now let\u2019s take a look at how to use TensorFlow.How to install TensorFlowFull instructions and tutorials are available on tensorflow.org, but here are the basics.System requirements:Python 3.7+pip 19.0 or later (requires manylinux2010 support, and TensorFlow 2 requires a newer version of pip)Ubuntu 16.04 or later (64-bit)macOS 10.12.6 (Sierra) or later (64-bit) (no GPU support)Windows 7 or later (64-bit)Hardware requirements:Starting with TensorFlow 1.6, binaries use AVX instructions which may not run on older CPUs.GPU support requires a CUDA\u00ae-enabled card (Ubuntu and Windows)#1. Install the Python development environment on your systemCheck if your Python environment is already configured:python3 - -versionpip3 - -versionIf these packages are already installed, skip to the next step.Otherwise, install Python, the pip package manager, and venv.If not in a virtual environment, use python3 -m pip for the commands below. This ensures that you upgrade and use the Python pip instead of the system pip.#2. Create a virtual environment (recommended)Python virtual environments are used to isolate package installation from the system.#3. Install the TensorFlow pip packageChoose one of the following TensorFlow packages to install from PyPI:tensorflow \u2014Latest stable release with CPU and GPU support (Ubuntu and Windows)tf-nightly \u2014Preview build (unstable). Ubuntu and Windows include GPU supporttensorflow==1.15 \u2014The final version of TensorFlow 1.x.Verify the installation. If a tensor is returned, you've installed TensorFlow successfully.Note: A few installation mechanisms require the URL of the TensorFlow Python package. The value you specify depends on your Python version.How to update TensorFlowThe pip package manager offers a simple method to upgrade TensorFlow, regardless of the environment.Prerequisites:Python 3.6-3.9 installed and configured (check the Python version before starting).TensorFlow 2 installed.The pip package manager version 19.0 or greater (check the pip version and upgrade if necessary).Access to the command line\/terminal or notebook environment.To upgrade TensorFlow to a newer version:#1. Open the terminal (CTRL+ALT+T).#2. Check the currently installed TensorFlow version:pip3 show tensorflowThe command shows information about the package, including the version.#3. Upgrade TensorFlow to a newer version with:pip3 install - -upgrade tensorflow==<version>Make sure you select a version compatible with your Python release, otherwise the version will not install. For the notebook environment, use the following command, and restart the kernel after completion:!pip install - -upgrade tensorflow==<version>This automatically removes the old version along with the dependencies and installs the newer upgrade.#4. Check the upgraded version by running:pip3 show tensorflowWhat Is TensorFlow Lite?In 2017, Google introduced a new version of TensorFlow called TensorFlow Lite. TensorFlow Lite is optimized for use on embedded and mobile devices. It\u2019s an open-source, product-ready, cross-platform deep learning framework that converts a pre-trained TensorFlow model to a special format that can be optimized for speed or storage.To ensure you\u2019re using the right version for any given scenario, you need to know when to use TensorFlow and when to use TensorFlow Lite. For example, if you need to deploy a high-performance deep learning model in an area without a good network connection, you\u2019d use TensorFlow Lite to reduce the file size.If you\u2019re developing a model for edge devices, it needs to be lightweight so that it uses minimal space and increases download speed on lower-bandwidth networks. To achieve this, you need optimization to reduce the size of the model or improve the latency\u2014which TensorFlow Lite does via quantization and weight pruning.The resulting models are lightweight enough to be deployed for a low-latency inference on edge devices such as Android or iOS cell phones, or Linux-based embedded devices like Raspberry Pis or Microcontrollers. TensorFlow Lite also uses several hardware accelerators for speed, accuracy, and optimizing power consumption, which are important for running inferences at the edge.What is a dense layer in TensorFlow?Dense layers are used in the creation of both shallow and deep neural networks. Artificial neural networks are brain-like architectures made up of a system of neurons, and they\u2019re able to learn through examples instead of being programmed with specific rules.In deep learning, multiple layers are used to extract higher-level features from the raw input; when the network is composed of several layers, it\u2019s called a stacked neural network. Each of these layers is made of nodes, which combine input from the data with a set of coefficients called weights that either amplify or dampen the input.For its 2.0 release, TensorFlow has adopted a deep learning API called Keras, which runs on top of TensorFlow and provides a number of pre-built layers for different neural network architectures and purposes. A dense layer is one of these \u2014 it has a deep connection, meaning that each neuron receives input from all the neurons of its previous layer.Dense layers are typically used for changing dimensions, rotation, scaling, and translation of the vectors it generates. They have the ability to learn features from all the combined features of the previous layer.What's the difference between TensorFlow and Python?TensorFlow is an open-source machine learning framework, and Python is a popular computer programming language. It\u2019s one of the languages used in TensorFlow. Python is the recommended language for TensorFlow, although it also uses C++ and JavaScript.Python was developed to help programmers write clear, logical code for both small and large projects. It\u2019s often used to build websites and software, automate tasks, and carry out data analysis. This makes it relatively simple for beginners to learn TensorFlow.A useful question to ask is: what version of Python does TensorFlow support? Certain TensorFlow releases are only compatible with specific versions of Python, and 2.0 requires Python 3.7 to 3.10. Make sure you check the requirements before installing TensorFlow.What is PyTorch and TensorFlow?TensorFlow is not the only machine learning framework in existence. There are a number of other choices, such as PyTorch, which have similarities and cover many of the same needs. So, what is the actual difference between TensorFlow and PyTorch?PyTorch and TensorFlow are just two of the frameworks developed by tech companies for the Python deep learning environment, helping human-like computers to solve real-world problems. The key difference between PyTorch and TensorFlow is the way they execute code. PyTorch is more tightly integrated with the Python language.As we\u2019ve seen, TensorFlow has robust visualization capabilities, production-ready deployment options, and support for mobile platforms. PyTorch isn\u2019t as established but is still popular for its simplicity and ease of use, as well as dynamic computational graphs and efficient memory usage.As for the question of which is better, TensorFlow or Pytorch \u00ad\u2014 it really depends on what you want to achieve. If your aim is to build AI-related products, TensorFlow will be a good fit for you, whereas PyTorch is more suited to research-oriented developers. PyTorch is a good fit for getting projects up and running in short order, but TensorFlow has more robust capabilities for larger projects and more complex workflows.Companies Using TensorFlowAccording to the TensorFlow website, a number of other big-name companies use the framework as well as Google. These include Airbnb, Coca-Cola, eBay, Intel, Qualcomm, SAP, Twitter, Uber, Snapchat developer Snap Inc., and sports consulting company STATS LLC.Top five TensorFlow alternatives\u00a01. DataRobot\u00a0DataRobot is a cloud-based machine learning framework designed to help businesses extend their data science capabilities by deploying machine learning models and creating advanced AI applications.The framework enables you to use and optimize the most valuable open-source modeling techniques from the likes of R, Python, Spark, H2O, VW, and XGBoost. By automating predictive analytics, DataRobot helps data scientists and analysts produce more accurate predictive models.There\u2019s a growing library of the best features, algorithms, and parameter values for building each model\u2014and with automated ensembling, users can easily find and combine multiple algorithms and pre-built prototypes for feature extraction and data preparation (with no need for trial-and-error guesswork).2. PyTorchDeveloped by the team at Facebook and open sourced on GitHub.com in 2017, PyTorch is one of the newer deep learning frameworks. As we mentioned earlier, it has several similarities with TensorFlow, including hardware-accelerated components and a highly interactive development model for design-as-you-go.PyTorch also optimizes performance by taking advantage of native support for asynchronous execution from Python. Benefits include built-in dynamic graphs and a stronger community than that of TensorFlow.However, PyTorch doesn't provide a framework to deploy trained models directly online, and an API server is needed for production. It also requires a third party \u2014 Visdom \u2014 for visualization, and the features of this are rather limited.3. KerasKeras is a high-level open-source neural network library designed to be user-friendly, modular, and easy to extend. It\u2019s written in Python and supports multiple back-end neural network computation engines \u2014 although its primary (and default) back end is TensorFlow, and its primary supporter is Google.We already mentioned the TensorFlow Keras high-level API, and Keras also runs on top of Theano. It has a number of standalone modules that you can combine, including neural layers, cost functions, optimizers, initialization schemes, activation functions, and regularization schemes.Keras provides support for a wide range of production deployment options, and strong support for multiple GPUs and distributed training. However, community support is minimal, and the library is typically used for small datasets.4. MXNetApache MXNet is an open-source deep learning software framework, which is used to define, train and deploy deep neural networks on a wide array of devices. It has the honor of being adopted by Amazon as the premier deep learning framework on AWS.It can scale almost linearly across multiple GPUs and multiple machines, allowing for fast model training, and supports a flexible programming model that enables users to mix symbolic and imperative programming for maximum efficiency and productivity.MXNet also supports multiple programming language APIs, including Python, C++, Scala, R, JavaScript, Julia, Perl, and Go (although its native APIs aren\u2019t as task-agreeable as TensorFlow\u2019s).5. CNTKCNTK, also known as the Microsoft Cognitive Toolkit, is a unified deep-learning toolkit that uses a graph structure to describe data flow as a series of computational steps (just like TensorFlow, although it isn\u2019t as easy to learn or deploy).It focuses largely on creating deep learning neural networks and can handle these tasks rapidly. CNTK allows users to easily realize and combine popular model types such as feed-forward DNNs, convolutional nets (CNNs), and recurrent networks (RNNs\/LSTMs).CNTK has a broad set of APIs (Python, C++, C#, Java) and can be included as a library in your Python, C#, or C++ programs\u2014or used as a standalone machine-learning tool through its own model description language (BrainScript). It supports 64-bit Linux or 64-bit Windows operating systems.Note: the 2.7 version was the last main release of CNTK, and there are no plans for new feature development.Should I use TensorFlow?TensorFlow has plenty of advantages. The open source machine learning framework provides excellent architectural support, which allows for the easy deployment of computational frameworks across a variety of platforms. It benefits from Google\u2019s reputation, and several big names have adopted TensorFlow to carry out artificial intelligence tasks.On the flipside, some details of TensorFlow\u2019s implementation make it difficult to obtain totally deterministic model training results for some training jobs \u2014 but the team is considering more controls to affect determinism in a workflow.Getting started is simple, especially with TensorFlow by Databricks, an out-of-the-box integration via Databricks Runtime for Machine Learning. You can get clusters up and running in seconds and benefit from a range of low-level and high-level APIs.Additional ResourcesTry TensorFlow on Databricks todayBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/solutions\/data-pipelines","text":"Data Engineering | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWData EngineeringMillionen Produktions-Workloads werden t\u00e4glich auf Databricks ausgef\u00fchrtErste SchritteDemo ansehen\nWEBINAR \u2022 Goodbye, Data Warehouse. Hello, Lakehouse.\nAttend on May 18 and get a $100 credit toward a Databricks certification course\nRegister nowNehmen Sie Batch- und Streaming-Daten auf einfache Weise in die\u00a0Databricks Lakehouse-Plattform auf und transformieren Sie sie. Orchestrieren Sie zuverl\u00e4ssige Produktionsabl\u00e4ufe, w\u00e4hrend Databricks Ihre Infrastruktur automatisch in gro\u00dfem Ma\u00dfstab verwaltet. Steigern Sie die Produktivit\u00e4t Ihrer Teams mit integrierten Datenqualit\u00e4tstests und Support f\u00fcr Best Practices f\u00fcr die Softwareentwicklung.Batch und Streaming zusammenf\u00fchrenBeseitigen Sie die Trennung von Datenbest\u00e4nden und f\u00fchren Sie sie auf einer Plattform mit einer einzigen und einheitlichen API zusammen, um Batch- und Streaming-Daten in gro\u00dfem Ma\u00dfstab zu erfassen, zu transformieren und schrittweise zu verarbeiten.Auf die Wertsch\u00f6pfung aus Daten konzentrierenDatabricks verwaltet automatisch Ihre Infrastruktur und die operativen Komponenten Ihrer Produktionsabl\u00e4ufe, sodass Sie sich auf die Wertsch\u00f6pfung und nicht auf die Tools konzentrieren k\u00f6nnen.Die Tools Ihrer Wahl verbindenEine offene Lakehouse-Plattform zum Verbinden und Verwenden Ihrer bevorzugten Data Engineering-Tools f\u00fcr Datenaufnahme, ETL\/ELT und Orchestrierung.Auf der Lakehouse-Plattform entwickeltDie Lakehouse-Plattform bietet die beste Grundlage f\u00fcr die Entwicklung und die gemeinsame Nutzung vertrauensw\u00fcrdiger Datenbest\u00e4nde, die zentral verwaltet werden, zuverl\u00e4ssig und blitzschnell sind.\u201eF\u00fcr uns wird Databricks zum Allzweck-Tool f\u00fcr unsere gesamte ETL-Arbeit. Je mehr wir mit der Lakehouse-Plattform arbeiten, desto einfacher ist sie sowohl f\u00fcr Benutzer als auch f\u00fcr Plattformadministratoren.\u201c\u2013 Hillevi Crognale, Engineering Manager, YipitDataWie funktioniert es?Vereinfachte DatenaufnahmeAutomatisierte ETL-VerarbeitungZuverl\u00e4ssige Workflow-OrchestrierungDurchg\u00e4ngige Beobachtbarkeit und \u00dcberwachungDatenverarbeitungs-Engine der n\u00e4chsten GenerationGrundlage von Governance, Zuverl\u00e4ssigkeit und LeistungVereinfachte DatenaufnahmeNehmen Sie Daten in Ihre Lakehouse-Plattform auf und betreiben Sie Ihre Analytics-, KI- und Streaming-Anwendungen von einem Ort aus.\u00a0Auto Loader\u00a0verarbeitet Dateien, die im Cloud-Speicher landen, inkrementell und automatisch in geplanten oder kontinuierlichen Jobs, ohne dass Statusinformationen verwaltet werden m\u00fcssten. Neue Dateien werden effizient \u00fcberwacht, ohne sie in einem Verzeichnis auflisten zu m\u00fcssen, wobei das System bis in den Milliardenbereich skaliert. Au\u00dferdem kann Auto Loader das Schema automatisch aus den Quelldaten ableiten und im Laufe der Zeit an aufkommende \u00c4nderungen anpassen. Der Befehl\u00a0COPY INTO\u00a0erleichtert Analysten die Batch-Dateiaufnahme in\u00a0Delta Lake\u00a0\u00fcber SQL.\u201eWir konnten eine Produktivit\u00e4tssteigerung von 40\u00a0% beim Data Engineering verzeichnen \u2013 die Zeit, die f\u00fcr die Entwicklung neuer Ideen ben\u00f6tigt wird, wurde von Tagen auf Minuten reduziert und die Verf\u00fcgbarkeit und Genauigkeit unserer Daten erh\u00f6ht.\u201c\u2013 Shaun Pearce, Chief Technology Officer,\u00a0GoustoMehr InformationenAutomatisierte ETL-VerarbeitungNach der Erfassung m\u00fcssen Rohdaten transformiert werden, um sie f\u00fcr Analytics und KI aufzubereiten. Databricks bietet mit\u00a0Delta-Live-Tables\u00a0(DLT) leistungsstarke ETL-Funktionen f\u00fcr Data Engineers, Data Scientists und Analysten. DLT ist das erste Framework, das in der Lage ist, mithilfe eines einfachen deklarativen Ansatzes ETL- und ML-Pipelines f\u00fcr Batch- oder\u00a0Streaming-Daten zu erstellen und gleichzeitig betriebliche Komplexit\u00e4ten wie Infrastrukturmanagement, Aufgabenorchestrierung, Fehlerbehandlung und Wiederherstellung sowie Leistungsoptimierung zu automatisieren. Mit DLT k\u00f6nnen Engineers ihre Daten auch als Code behandeln und Best Practices f\u00fcr die Softwareentwicklung wie Tests, \u00dcberwachung und Dokumentation anwenden, um zuverl\u00e4ssige Pipelines auch in gro\u00dfer Zahl bereitzustellen.Mehr InformationenZuverl\u00e4ssige Workflow-OrchestrierungDatabricks\u00a0Workflows\u00a0ist der vollst\u00e4ndig verwaltete Orchestrierungsservice f\u00fcr alle Ihre Daten, Analytics und KI und nativ in Ihrer\u00a0Lakehouse-Plattform vorhanden. Orchestrieren Sie verschiedene Workloads f\u00fcr den gesamten Lebenszyklus, einschlie\u00dflich\u00a0Delta-Live-Tables\u00a0und\u00a0Jobs f\u00fcr SQL,\u00a0Spark, Notebooks, dbt, ML-Modelle und mehr. Die tiefgreifende Integration in die zugrunde liegende Lakehouse-Plattform stellt sicher, dass Sie zuverl\u00e4ssige Produktions-Workloads in jeder Cloud erstellen und ausf\u00fchren und gleichzeitig eine umfassende und zentralisierte, f\u00fcr Endbenutzer jedoch niederschwellige \u00dcberwachung bieten.\u201eUnsere Mission ist es, die Art und Weise zu ver\u00e4ndern, wie wir den Planeten mit Energie versorgen. Unsere Kunden im Energiesektor ben\u00f6tigen Daten, Beratungsdienste und Forschung, um diese Transformation zu erreichen. Databricks Workflows gibt uns die Geschwindigkeit und Flexibilit\u00e4t, um die Erkenntnisse zu liefern, die unsere Kunden ben\u00f6tigen.\u201c\u2014 Yanyan Wu, Vice President of Data,\u00a0Wood MackenzieMehr InformationenDurchg\u00e4ngige Beobachtbarkeit und \u00dcberwachungDie Lakehouse-Plattform bietet Ihnen Transparenz \u00fcber den gesamten Daten- und KI-Lebenszyklus, sodass Data Engineers und Betriebsteams den Zustand ihrer Produktionsabl\u00e4ufe in Echtzeit sehen, die Datenqualit\u00e4t verwalten und historische Trends verstehen k\u00f6nnen. In Databricks\u00a0Workflows\u00a0k\u00f6nnen Sie auf Datenflussdiagramme und Dashboards zugreifen, die den Zustand und die Leistung Ihrer Produktionsauftr\u00e4ge und\u00a0Delta Live Tables-Pipelines\u00a0verfolgen. Ereignisprotokolle werden auch als\u00a0Delta Lake Tables\u00a0angezeigt, sodass Sie Leistungs-, Datenqualit\u00e4ts- und Zuverl\u00e4ssigkeits-Metrics aus jedem Blickwinkel \u00fcberwachen und visualisieren k\u00f6nnen.Datenverarbeitungs-Engine der n\u00e4chsten GenerationDatabricks Data Engineering basiert auf\u00a0Photon. Photon ist die mit Apache Spark-APIs kompatible Next-Generation-Engine, die ein\u00a0rekordverd\u00e4chtiges\u00a0Preis-Leistungs-Verh\u00e4ltnis bietet und gleichzeitig automatisch auf Tausende von Knoten skalierbar ist.\u00a0Spark Structured Streaming\u00a0implementiert eine zentrale und einheitliche API f\u00fcr die Batch- und Stream-Verarbeitung, sodass\u00a0Streaming im Lakehouse\u00a0ganz einfach eingef\u00fchrt werden kann, ohne Code \u00e4ndern oder neue Kompetenzen erwerben zu m\u00fcssen.Mehr InformationenModernste Data-Governance, Zuverl\u00e4ssigkeit und LeistungData Engineering auf Databricks bedeutet, dass Sie von den grundlegenden Komponenten der\u00a0Lakehouse-Plattform\u00a0\u2013 Unity Catalog und Delta Lake \u2013 profitieren. Ihre Rohdaten sind f\u00fcr\u00a0Delta Lake optimiert, ein Open-Source-Speicherformat, das durch ACID-Transaktionen zuverl\u00e4ssig ist und skalierbare Metadatenbearbeitung mit blitzschneller Leistung bietet. In Kombination mit\u00a0Unity Catalog\u00a0erhalten Sie eine detaillierte Governance f\u00fcr alle Ihre Daten- und KI-Assets. So wird die Art und Weise, wie Sie Governance durchsetzen, mit einem einheitlichen Modell vereinfacht, um Daten \u00fcber Clouds hinweg zu entdecken, darauf zuzugreifen und sie zu teilen. Unity Catalog bietet auch native Unterst\u00fctzung f\u00fcr\u00a0Delta Sharing, das branchenweit erste offene Protokoll f\u00fcr den einfachen und sicheren Datenaustausch mit anderen Unternehmen.Zu Databricks migrierenSind die Datensilos, die langsame Leistung und die hohen Kosten f\u00fcr Altsysteme wie Hadoop und Enterprise Data Warehouses m\u00fcde? Holen Sie sich eine einzige moderne Plattform f\u00fcr alle Ihre Daten-, Analytics- und KI-Anwendungsf\u00e4lle.Zu Databricks migrierenIntegrationenBieten Sie Ihren Datenteams maximale Flexibilit\u00e4t \u2013 nutzen Sie\u00a0Partner Connect\u00a0und ein \u00d6kosystem aus\u00a0Technologiepartnern,\u00a0um nahtlos beliebte Data Engineering-Tools zu integrieren. Sie k\u00f6nnen beispielsweise gesch\u00e4ftskritische Daten mit Fivetran aufnehmen, sie mit dbt transformieren und Ihre Pipelines mit Apache Airflow orchestrieren.Datenaufnahme und ETL+ jeder sonstige Apache Spark\u2122-kompatible ClientKundenberichteMehr entdeckenDelta LakeWorkflowsDelta Live TablesDelta-Freigabe\u00c4hnliche Inhalte\nAlle Ressourcen, die Sie brauchen. Alle an einem Ort.\nIn der Ressourcenbibliothek finden Sie E-Books und Videos zu den Vorteilen von Data Engineering in Databricks.\nRessourcen erkundenE-Books\u201eErrichten eines Data Lakehouse\u201c von Bill Inmon, dem Vater des Data WarehouseDaten, Analysen und KI-GovernanceGrundlagen des DatenmanagementsDas gro\u00dfe Buch des Data EngineeringDie neue Delta-Sharing-L\u00f6sung erkundenMigrieren von einem Data Warehouse zu einem Data Lakehouse f\u00fcr DummiesVeranstaltungenDatentransformation \u2013 mit Delta Live Tables kein ProblemProblemlose Datenerfassung Webinar-ReiheDATA+AI SUMMIT 2022Ihr Data Warehouse modernisierenBlogsBekanntgabe der allgemeinen Verf\u00fcgbarkeit von Databricks Delta Live Tables (DLT)Einf\u00fchrung in die Databricks-Abl\u00e4ufeEin \u00dcberblick \u00fcber alle neuen strukturierten Streaming-Funktionen, die 2021 f\u00fcr Databricks und Apache Spark entwickelt wurden10 leistungsstarke Funktionen zur Vereinfachung des halbstrukturierten Datenmanagements im Databricks LakehouseM\u00f6chten Sie loslegen?Kostenlos testenMitglied der Community werdenAWSAzureGCPProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/blog\/2020\/09\/15\/building-a-modern-risk-management-platform-in-financial-services.html","text":"How to Build a Modern Financial Services Risk Management Platform - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorBuilding a Modern Risk Management Platform in Financial Servicesby Antoine Amend and Dael WilliamsonSeptember 15, 2020 in Company BlogShare this postThis blog was collaboratively written with Databricks partner Avanade. A special thanks to Dael Williamson, Avanade CTO, for his contributions.Financial Institutions today are still struggling to keep up with the emerging risks and threats facing their business. Managing risk, especially within the banking sector, has increased in complexity over the past several years.\nFirst, new frameworks (such as FRTB) are being introduced that potentially require tremendous computing power and an ability to analyze years of historical data. Second, regulators are demanding more transparency and explainability from the banks they oversee. Finally, the introduction of new technologies and business models means that the need for sound risk governance is at an all-time high. However, the ability for the banking industry to effectively meet these demands has not been an easy undertaking.\nAgile approach to risk managementTraditional banks relying on on-premises infrastructure can no longer effectively manage risk. Banks must abandon the computational inefficiencies of legacy technologies and build an agile Modern Risk Management practice capable of rapidly responding to market and economic volatility using data and advanced analytics.\nOur work with clients shows that as new threats, such as the last decade\u2019s financial crisis, emerge, historical data and aggregated risk models lose their predictive values quickly. Luckily, modernization is made possible today based on open-source technologies powered by cloud-native big data infrastructure that bring an agile and forward-looking approach to financial risk analysis and management.\nTraditional datasets limit transparency and reliabilityRisk analysts must augment traditional data with alternative datasets to explore new ways of identifying and quantifying the risk factors facing their business, both at scale and in real time. Risk management teams must be able to efficiently scale their simulations from tens of thousands up to millions by leveraging both the flexibility of cloud compute and the robustness of open-source computing frameworks like Apache SparkTM.\nThey must accelerate model development lifecycle by bringing together both the transparency of their experiment and the reliability in their data, bridging the gap between science and engineering and enabling banks to have a more robust approach to risk management.\nData organization is critical to understanding and mitigating riskHow data is organized and collected is critical to creating highly reliable, flexible and accurate data models. This is particularly important when it comes to creating financial risk models for areas such as wealth management and investment banking.\nIn the financial world, risk management is the process of identification, analysis and acceptance or mitigation of uncertainty in investment decisions.\nWhen data is organized and designed to flow within an independent pipeline, separate from massive dependencies and sequential tools, the time to run financial risk models is significantly reduced. Data is more flexible, easier to slice and dice, so institutions can apply their risk portfolio at a global and regional level as well as firmwide.\nPlagued by the limitations of on-premises infrastructure and legacy technologies, banks particularly have not had the tools until recently to effectively build a modern risk management practice. A modern risk management framework enables intraday views, aggregations on demand and an ability to future proof\/scale risk assessment and management.\nReplace historical returns with highly accurate predictive modelsFinancial risk modeling should include multiple data sources to create more predictive financial and credit risk models. A modern risk and portfolio management practice should not be solely based on historical returns but also must embrace the variety of information available today.\nFor example, a white paper from Atkins et al describes how financial news can be used to predict stock market volatility better than close price. As indicated in the white paper, the use of alternative data can dramatically augment the intelligence for risk analysts to have a more descriptive lens of modern economy, enabling them to better understand and react to exogenous shocks in real time.\nA modern risk management model in the cloudAvanade and Databricks have demonstrated how Apache Spark, Delta Lake and MLflow can be used in the real world to organize and rapidly deploy data into a value-at-risk (VAR) data model. This enables financial institutions to modernize their risk management practices into the cloud and adopt a unified approach to data analytics with Databricks.Using the flexibility and scale of cloud compute and the level of interactivity in an organization\u2019s data, clients can better understand the risks facing their business and quickly develop accurate financial market risk calculations. With Avanade and Databricks, businesses can identify how much risk can be decreased and then accurately pinpoint where and how they can quickly apply risk measures to reduce their exposure.\nJoin us at the Modern Data Engineering with Azure Databricks Virtual Event on October 8th to hear Avanade present on how Avanade and Databricks can help you manage risk through our Financial Services Risk Management model. Sign up here today.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/explore\/de-data-warehousing\/rise-of-the-data-lakehouse#page=1?itm_data=dataengineering-link-pf-riselakehousebook","text":"\n\n\n\n\n\n\n\nRise Of The Data Lakehouse by Bill Inmon\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThumbnails\n\n\nDocument Outline\n\n\nAttachments\n\n\nLayers\n\n\n\n\n\n\n\nCurrent Outline Item\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\nHighlight All\n\nMatch Case\n\n\n\nMatch\nDiacritics\n\nWhole Words\n\n\n\n\n\n\n\n\n\nColor\n\n\n\nSize\n\n\n\n\n\n\n\nColor\n\n\n\nThickness\n\n\n\nOpacity\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\nGo to First Page\n\n\nGo to Last Page\n\n\n\nRotate Clockwise\n\n\nRotate Counterclockwise\n\n\n\n\nText Selection Tool\n\n\nHand Tool\n\n\n\n\n\nPage Scrolling\n\n\nVertical Scrolling\n\n\nHorizontal Scrolling\n\n\nWrapped Scrolling\n\n\n\n\n\nNo Spreads\n\n\nOdd Spreads\n\n\nEven Spreads\n\n\n\n\nDocument Properties\u2026\n\n\n\n\n\n\n\n\nToggle Sidebar\n\n\n\nFind\n\n\n\nPrevious\n\n\n\nNext\n\n\n\n\n\n\n\nPresentation Mode\n\n\nOpen\n\n\nPrint\n\n\nDownload\n\n\nCurrent View\n\n\n\n\nFreeText Annotation\n\n\nInk Annotation\n\n\n\n\nTools\n\n\n\n\n\nZoom Out\n\n\n\nZoom In\n\n\n\n\n\nAutomatic Zoom\nActual Size\n\nPage Fit\nPage Width\n\n\n50%\n\n75%\n\n100%\n\n125%\n\n150%\n\n200%\n\n300%\n\n400%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMore Information\n\n\nLess Information\n\n\n\n\nClose\n\n\n\n\n\n\n\n\n\nEnter the password to open this PDF\nfile:\n\n\n\n\n\nCancel\nOK\n\n\n\n\nFile name:\n-\n\n\nFile size:\n-\n\n\n\nTitle:\n-\n\n\nAuthor:\n-\n\n\nSubject:\n-\n\n\nKeywords:\n-\n\n\nCreation Date:\n-\n\n\nModification Date:\n-\n\n\nCreator:\n-\n\n\n\nPDF Producer:\n-\n\n\nPDF Version:\n-\n\n\nPage Count:\n-\n\n\nPage Size:\n-\n\n\n\nFast Web View:\n-\n\n\nClose\n\n\n\n\nPreparing document for printing\u2026\n\n\n\n0%\n\n\nCancel\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/anil-puliyeril\/#","text":"Anil Puliyeril - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnil PuliyerilSenior Architect at HabuBack to speakersAnil Puliyeril, Senior Architect at Habu, has 10+ years of experience building innovative, highly scalable and best in class software systems using open source technologies. He is a specialist in Microservices, Cloud Services, and a self-proclaimed API-enthusiast. \nBefore Habu, Anil was a Principle Software Engineer at Salesforce where he was part of the Data Management Platform (DMP) Engineering Team that provided cloud-based data management services to organizations across the world. Prior to that, Anil held numerous engineering roles at Saba where he led the design and development of an api management framework and data integration platform. \nAnil has a Master of Science, Computer Software Engineering degree from the Birla Institute of Technology and Science, Pilani and a Bachelor of Engineering, Computer Science from the University of Mumbai.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/xuefu-wang","text":"Xuefu Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingXuefu WangSr. Data Scientist at The Trade DeskBack to speakersXuefu Wang is a Sr. Data Scientist at The Trade Desk, the world's largest demand-side platform for accessing premium advertisement inventories across multiple channels. He has a PhD in statistics and previously worked in data science at JP Morgan ChaseLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/unify-bi-and-ai-on-a-single-platform?itm_data=gcp-promo-gcplaunch","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/fr\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"Page partenaire\u00a0: partenaires Conseil et SI | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWProgramme Partenaire C&SILe Programme Partenaire C&SI (conseil et int\u00e9gration de syst\u00e8mes) de Databricks est ax\u00e9 sur la valeur et optimise notre collaboration pour produire d'excellents r\u00e9sultats.Inscrivez-vous maintenantRejoignez un \u00e9cosyst\u00e8me mondial de fournisseurs de donn\u00e9es et de services d\u2019IA\u00a0: ensemble, nous aidons nos clients communs \u00e0 devenir des entreprises ax\u00e9es sur les donn\u00e9es. En tant que partenaire, vous jouez un r\u00f4le strat\u00e9gique\u00a0:Impact commercial\n\u00c9changez avec nos \u00e9quipes de terrain pour vendre la vision du lakehouse et \u00e9largir l'empreinte de Databricks.Valeur client\nFormez votre \u00e9quipe sur la plateforme pour d\u00e9velopper ses capacit\u00e9s et ses comp\u00e9tences.innovation\nD\u00e9montrez votre expertise en d\u00e9veloppant des solutions reproductibles pour r\u00e9pondre aux cas d'usage qui ont le plus d'impact pour vos clients.Acc\u00e9dez \u00e0 des avantages en mati\u00e8re d'engagement et d'activation pour d\u00e9velopper votre pratique et consolider votre partenariat\u00a0:Formation technique DatabricksAcc\u00e8s \u00e0 la plateforme Lakehouse de DatabricksAssistance technique et commercialeFrais d'enregistrement et de recommandation d\u2019opportunit\u00e9Fonds d'investissement clientsActivation et ressources de mise sur le march\u00e9Pr\u00eat \u00e0 vous lancer\u00a0?Inscrivez-vous maintenantTrouver un partenaireProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/solutions\/migration","text":"Migrer vers Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWMigrer vers DatabricksModernisez votre plateforme de donn\u00e9es en adoptant le lakehouse de Databricks\nEssayer gratuitement DatabricksContacter DatabricksR\u00e9duisez les co\u00fbts, innovez plus rapidement et simplifiez votre plateforme de donn\u00e9es en migrant les donn\u00e9es de votre data warehouse ou de votre data lake d'entreprise vers le lakehouse Databricks. Vous pouvez d\u00e9sormais ex\u00e9cuter toutes vos charges de donn\u00e9es, d'analytique et d'IA sur une plateforme unifi\u00e9e moderne qui s'appuie sur des normes ouvertes et sur une approche de gouvernance commune pour plus de s\u00e9curit\u00e9.Pourquoi migrer vers Databricks\u00a0?Simplifiez votre plateforme de donn\u00e9esCentralisez vos cas d'usage de donn\u00e9es, d'analytique et d'IA sur une plateforme moderne unique. Unifier la gouvernance et l'exp\u00e9rience utilisateur pour toutes les \u00e9quipes de donn\u00e9es et sur l'ensemble de vos clouds.\nMontez en charge \u00e0 bas co\u00fbtArr\u00eatez de g\u00e9rer des serveurs. \u00c9voluez en fonction de vos besoins avec le serverless. Faites passer l'entreposage de donn\u00e9es \u00e0 l'\u00e9chelle sup\u00e9rieure avec un rapport performance \/ prix jusqu'\u00e0 12\u00a0fois meilleur.\nAcc\u00e9l\u00e9rez l'innovationCr\u00e9ez rapidement des capacit\u00e9s d'IA, de ML et d'analytique en temps r\u00e9el gr\u00e2ce \u00e0 des outils collaboratifs en libre-service. Appuyez-vous sur des technologies open source telles que MLflow et Apache Spark\u2122.\nMigration depuis Hadoop\nEn savoir plusMigration depuis un data warehouse\nEn savoir plusMigrez en toute confianceNous avons aid\u00e9 des centaines de clients \u00e0 migrer leurs donn\u00e9es depuis des plateformes traditionnelles. Notre processus de migration complet et \u00e9chelonn\u00e9 offre un mod\u00e8le pr\u00e9visible qui permet de comprendre les co\u00fbts, pendant et apr\u00e8s la migration. Quant \u00e0 notre approche \u00ab\u0000\u00a0lakehouse-first\u00a0\u00bb, qui permet de migrer toutes les charges de travail, elle garantit la prise en charge des cas d'usage actuels comme des nouveaux. Le r\u00e9sultat\u00a0? Des risques r\u00e9duits, une rentabilisation plus rapide et un meilleur ROI.Les cinq phases de la migration des donn\u00e9esPhase\u00a01\u00a0:\nD\u00e9couverte\nUtilisez des profileurs pour automatiser la d\u00e9couverte. Obtenez des insights sur les charges de travail des plateformes traditionelles et estimez les co\u00fbts de consommation de la plateforme Databricks.\nPhase\u00a02\u00a0:\n\u00c9valuation\nUtilisez des analyseurs pour \u00e9valuer la complexit\u00e9 du code avec finesse et estimer les co\u00fbts du projet de migration.\nPhase\u00a03\u00a0:\nStrat\u00e9gie\nAvec les conseils d'experts Databricks, finalisez le mapping de vos technologies et cr\u00e9ez des parcours optimaux pour la migration depuis chaque plateforme source.\nPhase\u00a04\u00a0:\nProjet pilote en production\nR\u00e9alisez un pilote pour tester vos cas d'usage et utilisez des convertisseurs de code pour rendre votre code existant compatible avec Databricks. \u00c9laborez un plan de migration et une feuille de route de migration.\nPhase\u00a05\u00a0:\nEx\u00e9cution\nR\u00e9p\u00e9tez l'op\u00e9ration pour toutes les charges. Obtenez de l'aide pour l'ex\u00e9cution de la migration et b\u00e9n\u00e9ficiez de l'appui de partenaires certifi\u00e9s ou des Services professionnels Databricks.\nClients ayant r\u00e9ussi leur migration vers DatabricksT\u00e9moignage de clientPersonnaliser les soins pharmaceutiques pour am\u00e9liorer les r\u00e9sultats des patients\nEn savoir plusBlog clientsAbandon complet des solutions on-premice, r\u00e9duction des co\u00fbts et acc\u00e9l\u00e9ration de la r\u00e9ussite\nEn savoir plusT\u00e9moignage de clientLa migration vers le cloud s'impose dans une nouvelle \u00e8re de la vente au d\u00e9tail data-driven\nEn savoir plusSolutions BrickbuilderAppuyez-vous sur les solutions Brickbuilder, propos\u00e9es par des partenaires de premier plan sp\u00e9cialis\u00e9s dans le conseil et con\u00e7ues pour migrer vers le lakehouse Databricks.Migration des donn\u00e9es vers le cloud par AccentureR\u00e9duisez l'incertitude et optimisez la valeur\nD\u00e9marrerMigration des syst\u00e8mes h\u00e9rit\u00e9s par AvanadeD\u00e9placez vos donn\u00e9es pour lib\u00e9rer toute leur valeur\nD\u00e9marrerMigrer vers le cloud et Databricks par CapgeminiRationaliser la migration des donn\u00e9es vers la plateforme lakehouse Databricks\nD\u00e9marrerMigrer vers Databricks par Celebal TechnologiesUne migration plus rapide et moins ch\u00e8re des syst\u00e8mes sur site\nD\u00e9marrerSolution de migration LeapLogic par ImpetusTransformation automatique des charges de travail ETL, data warehouse, analytique et Hadoop dans Databricks\nD\u00e9marrerAssistant de migration des donn\u00e9es Hadoop\/EDW par InfosysTransf\u00e9rez vos donn\u00e9es vers Databricks en toute confiance\nD\u00e9marrerMigration de Snowflake vers Databricks par LovelyticsPour un processus de migration rapide et fiable\nD\u00e9marrerAcc\u00e9l\u00e9rateur de migration SAS par Tensile\u00a0AIUne solution de migration d\u00e9velopp\u00e9e par Tensile\u00a0AI et bas\u00e9e sur la plateforme Lakehouse de Databricks.D\u00e9marrerSuite de Data intelligence de WiproMigrez vers Databricks en toute confiance\nD\u00e9marrerAdopter une strat\u00e9gie de data lakehouse, le choix de la sagesseUne approche de data lakehouse peut vous aider \u00e0 d\u00e9passer les limitations courantes des data warehouses et des data lakesT\u00c9L\u00c9CHARGER MAINTENANTRessourcesEbooksMigrer d'Hadoop vers un data lakehouse en quelques motsLa migration d'un data warehouse vers un data lakehouse en quelques mots\u00c9v\u00e9nementsGuide \u00e9tape par \u00e9tape de la migration HadoopModernisez votre data warehouseBlogsCinq \u00e9tapes cl\u00e9s pour r\u00e9ussir la migration de Hadoop vers l'architecture Lakehouse7\u00a0raisons de migrer d'un Hadoop cloud vers la plateforme lakehouse DatabricksD\u00e9marrerChanger de plateforme ne doit pas \u00eatre un casse-t\u00eate. Contactez-nous d\u00e8s aujourd'hui et nous verrons comment vous pourriez proc\u00e9der.Essayer gratuitement DatabricksContacter DatabricksProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/fr\/legal","text":"Master Cloud Services Agreement | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the \u201cMCSA\u201d) is entered into as of the Effective Date between Databricks, Inc. (\u201cDatabricks\u201d or \u201cwe\u201d) and\u00a0Customer\u00a0(as defined below) and governs Customer\u2019s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the \u201cPlatform Services\u201d), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case \u201cCustomer,\u201d \u201cyou,\u201d or \u201cyour\u201d will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (\u201cSupport Services\u201c), (c) training services (\u201cTraining Services\u201c), or (d) advisory services (\u201cAdvisory Services,\u201d and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the \u201cDatabricks Services\u201d). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks.\u00a0Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.\u00a0\n\u201cAcceptable Use Policy\u201d means the acceptable use policy governing the Platform Services located at\u00a0databricks.com\/legal\/aup.\u201cAffiliate\u201d of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.\u201cAgreement\u201d means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.\u201cAuthorized User\u201d means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.\u201cBeta Service\u201d means any feature of the\u00a0 Databricks Services ( that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.\"Cloud Environment\u201d means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.\u201cCloud Service Provider\u201d means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.\u201cCustomer Content\u201d means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.\u201cCustomer Data\u201d means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services.\u00a0\u201cCustomer Instructional Input\u201d means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.\u201cCustomer Results\u201d means any output Customer or its Authorized Users generate from their use of the Platform Services.\"Databricks Global Code of Conduct\u201d means the Databricks Global Code of Conduct located at\u00a0\u00a0databricks.com\/global-code-of-conduct.\u201cDatabricks Powered Service\u201d means any third-party software or service powered by Databricks, including those at\u00a0https:\/\/www.databricks.com\/legal\/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party.\u00a0 This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.\u201cDocumentation\u201d means the documentation related to the Platform Services located at\u00a0databricks.com\/documentation.\u201cDPA\u201d\u00a0means the\u00a0 Data Processing Addendum located at\u00a0databricks.com\/legal\/dpa.\u201cEffective Date\u201d means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.\u201cFees\u201d means all amounts payable for Databricks Services.\u201cHIPAA\u201d means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.\u201cIntellectual Property Rights\u201d means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.\u201cOrder\u201d means an order form (\u201cOrder Form\u201d), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.\u201cPCI-DSS\u201d means the Payment Card Industry Data Security Standard.\u201cPHI\u201d means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.\u201cSecurity Addendum\u201d means the Platform Security Addendum located at\u00a0databricks.com\/legal\/security-addendum.\u201cSchedule\u201d means any of the schedules referenced herein or otherwise set forth in an Order.\u201cShared Data\u201d means\u00a0 (i)\u00a0Customer Content that you electto share with third parties or\u00a0 (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.\u201cSupport Policy\u201d means the available Support Services plans located at\u00a0databricks.com\/support.\u201cSystem\u201d means any application, computing or storage device, or network.\u201cUsage Data\u201d\u00a0means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.\u201cWorkspace\u201d means a Platform Services environment.Confidentiality.Confidential Information.\u00a0\u201cConfidential Information\u201d\u00a0means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks\u2019 Confidential Information, Customer Content is Customer\u2019s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party\u2019s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and\/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and\/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party\u2019s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.\nOwnership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content.\u00a0As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback.\u00a0You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (\u201cFeedback\u201d). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an \u201cas-is\u201d basis with no warranties of any kind.Use of the Platform Services.\nAccess.\u00a0Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities.\u00a0Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources.\u00a0Security Measures. Databricks shall implement reasonable\u00a0administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (\u201cSecurity Measures\u201d); and shall, without limiting the foregoing, maintain certification to ISO\/IEC 27001:2013 or equivalent\/greater standards during the term of this Agreement.\u00a0Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts.\u00a0While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities.\u00a0General Responsibilities.\u00a0\u00a0You acknowledge and agree that you are responsible for:\nensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content;\u00a0configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data;\u00a0using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User\u2019s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented.\u00a0Use\u00a0Limits.\u00a0You will not, and will not permit your Authorized Users to:\nviolate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party\u2019s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5\u00a0 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities.\u00a0Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content.\u00a0\u00a0Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain.\u00a0You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the \u201cPHI Permitted Workspaces\u201d) identified on such Order; and (b) you have entered into a Business Associate Agreement (\u201cBAA\u201d) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (\u201cCardholder Data\u201d) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the \u201cPCI Permitted Workspaces\u201d). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use.\u00a0\u00a0Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may use to create a custom container file (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:\ninclude in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks\u2019 Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection.\u00a0Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.\nSuspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace.\u00a0Monthly Pay-As-You-Go (PAYG)\u00a0Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer\u2019s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks\u2019 Systems, upon thirty (30) days\u2019 prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party\u2019s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so.\u00a0 In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS\u2019 SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS\u2019 REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS\u2019 SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS\u2019 ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.\u00a0\nIndemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a \u201cClaim Against Customer\u201d)alleging that the Databricks Services as provided to Customer by Databricks or Customer\u2019s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party\u2019s Intellectual Property Rights (an \u201cIP Claim\u201d), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at\u00a0github.com\/apache\/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User\u2019s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks\u2019 obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against\u00a0 Databricks by a third party (a \u201cClaim Against Databricks\u201d) (a) arising from or related to Customer\u2019s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and \/ or\u00a0 materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (\u201cCustomer Materials\u201d) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party\u2019s Intellectual Property Rights, and \/ or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy.\u00a0SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party\u2019s (each, an \u201cIndemnitor\u201d) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an \u201dIndemnitee\u201d) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor\u2019s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee\u2019s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee\u2019s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor\u2019s prior written consent.Limitation of Liability.\nEXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS\u2019 INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER\u2019S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE \u201cGENERAL CAP\u201d). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER\u2019S AND ITS AFFILIATES\u2019 PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS\u2019 AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS\u2019 BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS\u2019 GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE\u00a0LIMITED TO TWO (2) TIMES THE\u00a0TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (\u201cSUPERCAP\u201d).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE,\u00a0DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement.\u00a0The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days\u2019 prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days\u2019 prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks\u2019 material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival.\u00a0All provisions of the Agreement that by their nature should survive termination will so survive.Payment.\u00a0Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally.\u00a0Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks\u2019 provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer\u2019s particular use of the services.By Customer Generally.\u00a0You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy.\u00a0Export Controls; Trade Sanctions.\u00a0The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and\/or any other relevant restrictions in Customer\u2019s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and \/ or Affiliate accessing the Databricks Services)\u00a0 is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s).\u00a0Business Practices; Code of Conduct.\u00a0Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks\u2019 Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.\nGoverning Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer\u2019s principal place of business (\u201cDomicile\u201d), as follows:\nCustomer\u2019s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial.\u00a0 In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks\u2019 obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at\u00a0databricks.com\/legal\/mcsa\u00a0shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer\u2019s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party\u2019s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks\u2019 use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services (\"Case Study\"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party\u2019s rights and obligations under the Agreement (\u201cAssignment\u201d) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld.\u00a0 Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party\u2019s (\u201cImpacted Party\u201d) reasonable control, including without limitation the following force majeure events (\u201cForce Majeure Event(s)\u201c): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party\u2019s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party\u2019s reasonable control.Last Updated December 1, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cTOS Request\u201d in the subject).MCSA_OnlineStandard_ENG_v.3.0_20221201ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/frank-munz\/#","text":"Frank Munz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFrank MunzPrincipal Technical Marketing Engineer at DatabricksBack to speakersDr. Frank Munz works as a Principal Technical Marketing Engineer at Databricks after kickstarting DevRel EMEA. Previously, Frank built up technical evangelism for Amazon Web Services in Germany, Austria and Switzerland. Frank\u2019s focus is on Cloud strategies, Machine Learning, cloud-native\/containers, big & fast & non-relational data and High-Performance Computing.\nWith over 22 years of professional experience in distributed systems, Java Enterprise, microservices, SOA, and cloud computing, Frank has published 17 scientific articles in computer science and brain research as well as three computer science textbooks with some of them used by lecturers of US universities.\nHe trained keynote speakers for events with up to 3.500 attendees from many verticals including clinical research, pharmacy and genomics. Frank still presents regularly at conferences all over the world such as Devoxx, Java One, JConf, Voxxed Days, Code One, and KubeCon. \nHis prolific global and cross-industry experience in IT was awarded the Technologist of the Year Award for Cloud Computing and nominated as an independently working Oracle ACE Director. 2017 he was nominated as one of the first Developer Champions worldwide.\nFrank holds a Ph.D. with summa cum laude (1,0) in computer science from the Technische Universit\u00e4t M\u00fcnchen where he spent 4 years in supercomputing and distributed systems. He developed distributed functional algorithms for human brain research, cardiology and oncology. \nFrank sold his first computer program (a kind of mini e-business suite) with 16 years. After having jobs as a furniture mover in Paris he was hired as a data scientist at the German Cancer Research Center with the team of Prof. zur Hausen. The study Frank worked on won the Nobel prize in medicine for linking a human virus (HPV) to the development of cancer. The vaccine in use today saves over 30k people in the US from developing cancer.\nJust recently Frank unlocked his goal to present at major conferences on every continent except Antarctica (because it is so cold there). He enjoys writing about himself in the third person.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sachin-balgonda-patil\/#","text":"Sachin Balgonda Patil - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSachin Balgonda PatilSolutions Architect at DatabricksBack to speakersSachin is a Solutions Architect at Databricks and is based out of London, UK. He has spent around 20 years Architecting, Designing and Implementing complex production grade applications for various customers across the globe. In his prior role, he has implemented streaming applications for the financial services and has deep interest in real time streaming workloads. Before joining Databricks, he worked for a global system integration company.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rong-ma","text":"Rong Ma - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRong MaSoftware Engineer at intelBack to speakersRong Ma is a software engineer from Intel data analytics team. She has two years\u2019 experience in bigdata and cloud system optimization, focusing on computation, storage, network software stack performance analysis and optimization. She participated in the development works including Spark-Sql, Spark-Shuffle optimization, cache implementation, etc.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/technology-partner-program","text":"Databricks-Technologiepartnerprogramm \u2013 DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWTechnologiepartnerprogrammSprechen Sie Tausende von Databricks-Kunden an, die nur darauf warten, Ihr Produkt zu nutzenJetzt bewerbenDatabricks l\u00e4sst sich in die besten Daten- und KI-Produkte auf dem Markt integrieren und f\u00f6rdert sie. Wir bieten unseren Partnern technischen Support und Unterst\u00fctzung bei der Vermarktung, die sie ben\u00f6tigen, um neue Kunden zu gewinnen und ihr Gesch\u00e4ft zu befeuern.Vorteile f\u00fcr TechnologiepartnerVerkaufsanreizeIncentives f\u00fcr Databricks-Vertreter, um den Verkauf Ihres Produkts zu unterst\u00fctzenZugang zu KundenSofort neue Kunden gewinnen \u2013 mit Databricks Partner ConnectMehr InformationenMarketingunterst\u00fctzungNutzen Sie Marketinginvestitionen, um Ihre Reichweite zu erh\u00f6henInanspruchnahme von Produkt- und F&E-TeamsErhalten Sie Zugang zu Produkt-, Technik- und Supportmitarbeitern von DatabricksKostenlose Sandbox-UmgebungEntwickeln und Testen in einer kostenfreien Sandbox-UmgebungGemeinsame MarketingprogrammeGemeinsamen Marketingprogrammen mit Databricks beitretenBereit zur Kontaktaufnahme?Jetzt bewerbenPartner findenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/morgan-hsu\/#","text":"Morgan Hsu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMorgan HsuDirector, Data and ML Engineering at FanDuelBack to speakersMorgan manages the Insights and ML platform teams at FanDuel. His teams provide ML infrastructure and services used to support use cases including responsible gaming, fraud detection, and marketing optimization.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/bin-mu","text":"Bin Mu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBin MuVice President and Head of Data & Analytics at AdobeBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/data-partner-program","text":"Datenpartner-Programm | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWPartnerprogramm f\u00fcr DatenanbieterMit Databricks Zugang zu einem umfassenden und offenen \u00d6kosystem von Datenkonsumenten erhaltenJetzt bewerbenDatabricks hilft unseren Partnerdatenanbietern, Datenbest\u00e4nde \u00fcber eine zentrale Plattform in einem umfassenden und offenen \u00d6kosystem mit Datenkonsumenten zu monetarisieren. 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{"source":"https:\/\/www.databricks.com\/p\/webinar\/delta-lake-the-foundation-of-your-lakehouse","text":"Delta Lake: The Foundation of Your Lakehouse | DatabricksVirtual Event + Live Q&ADelta Lake: The Foundation of Your LakehouseBring reliability, performance and security to your data lakeAvailable on-demandAs an open format storage layer, Delta Lake delivers reliability, security and performance to data lakes. Customers have seen 48x faster data processing, leading to 50% faster time to insight, after implementing Delta Lake.Watch a live demo and learn how Delta Lake:Solves the challenges of traditional data lakes \u2014 giving you better data reliability, support for advanced analytics and lower total cost of ownershipProvides the perfect foundation for a cost-effective, highly scalable lakehouse architectureOffers auditing and governance features to streamline GDPR complianceHas dramatically simplified data engineering for our customersSpeakersHimanshu RajaProduct ManagementDATABRICKSSam SteinyProduct MarketingDATABRICKSBrenner HeintzProduct MarketingDATABRICKSBarbara EckmanSoftware ArchitectCOMCASTTranscript\nSam Steiny: Hi, and welcome to the Databricks event, Delta Lake, the foundation of your lakehouse. My name is Sam Steiny and I work in product marketing at Databricks, focusing specifically on data engineering and on Delta Lake. I'm excited to be here today. I get to be the MC for today's event, and I will be guiding you through today's sessions. More and more, we've seen the term lakehouse referenced in news at events in tech blogs, and thought leadership. And beyond our work at Databricks, organizations across industries have really increasingly turned to this idea of a lakehouse as the future for unified analytics, data science and machine learning.Sam Steiny: In today's event, we'll see an overview of Delta Lake, which is the secure data storage and management layer for your data lake that really forms the foundation of a lakehouse. We'll see a demo of Delta Lake in action, and we'll actually hear how Comcast has leveraged Delta Lake to bring reliability, performance, and security to their data. We'll finish today's event with a live Q and A. So, come prepared with your questions and we'll do our best to answer as many as possible. So, before we start just some quick housekeeping, today's session is being recorded. So, it'll be available on demand to anyone who has registered.Sam Steiny: And then also, if you have any questions throughout the event, please feel free to add them to the Q and A box. We'll do our best to actually answer them in real time there. But we'll also answer the leftover questions as well as any additional ones in the live Q and A at the end of the session. So, now before we get to our speakers, I wanted to share a quick overview of Delta Lake in a video we recently launched. This'll give you a high level understanding of what Delta Lake is, before Himanshu who is the Delta Lake product manager, will go into more detail about Delta Lake and how it forms the foundation of a lakehouse.Speaker 3: Businesses today have the ability to collect more data than ever before. And that data contains valuable insights into your business and your customers, if you can unlock it. As most organizations have discovered, it's no simple task to turn data into insights. Today's data comes in a variety of formats, video, audio, and text. Data lakes have become the defacto solution because they can store these different formats at a low cost and don't lock businesses into a particular vendor like a data warehouse does. But traditional data lakes have challenges, as data lakes accumulate data in different format, maintaining reliable data is challenging and can often lead to inaccurate query results.Speaker 3: The growing data volume also impacts performance, slowing down analysis and decision-making, and with few auditing and governance features data lakes are very hard to properly secure and govern. With all of these challenges, as much as 73% of company data goes unused for analytics and decision-making and value in it is never realized. Delta Lake solves these challenges. Delta Lake is a data storage and management layer for your data lake that enables you to scale insights throughout your organization with a reliable single source of truth for all data workloads, both batch and streaming, increase productivity by optimizing for speed at scale with performance features like advanced indexing and schema enforcement.Speaker 3: Operate with flexibility in an open source environment stored in Apache parquet format and reduce risk by quickly and accurately updating data in your data lake for compliance and maintain better data governance through audit logging. By unlocking your data with Delta Lake, you can do things like dramatically simplified data engineering by performing ETL processes directly on the data lake. Make new real-time data instantly available for data analysis, data science and machine learning, gain confidence in your ability to reliably meet compliance standards like GDPR and CCPA.Speaker 3: Delta Lake on Databricks brings reliability, performance and security to your data all in an open format, making it the perfect foundation for a cost-effective highly scalable lakehouse architecture. Delta Lake, the open, reliable, performant and secure foundation of your lakehouse.Sam Steiny: Great. So, with that high level view, now you have an understanding of Delta Lake and I'm going to now pass it over to Himanshu Raja, who's the product manager for Delta Lake at Databricks. He's going to do a deeper dive into Delta Lake and explain how it really enables a lakehouse for our customers. Over to you, Himanshu.Himanshu Raja: Thank you, Sam. I'm super excited to be here and talk to you about Delta Lake and why it is the right foundation for lakehouse. In today's session, I will cover the challenges of building data analytics stack while lakehouse is the only future proof solution. What is Delta Lake? And why it is the best foundation for your lakehouse? Brenner, will then jump into the most exciting part of the session and do a demo. After the session, you will have enough context, links to the supporting material to get started and build your first data lake.Himanshu Raja: Every company is feeling the pull to become a data company, because when large amounts of data are applied to even simple models, the improvements on use cases is exponential. And here at Databricks, our entire focus is on helping customers apply data to their toughest problems. I'll dig examples of two such customers, Comcast and Nationwide. Comcast is a great example of a media company that has successfully adopted data and machine learning to create new experiences for their viewers that help improve satisfaction and retention.Himanshu Raja: They have built a voice-activated remote control that allows you to speak into the remote, ask it a question, and it will provide some really relevant results, leveraging things like natural language processing and deep learning. And they've built all of this on top of Databricks platform. Nationwide is one of the largest insurance providers in the U.S. nationwide saw that the explosive growth in data availability and increasing market competition was challenging them to provide better pricing to their customers. With hundreds of millions of insurance records to analyze for downstream ML nationwide realized that their legacy batch analysis process was slow and inaccurate, providing limited insights to predict the frequency and severity of the claims.Himanshu Raja: With Databricks, they have been able to employ deep learning models at scale to provide, more accurate pricing predictions resulting in more revenue from claims. Because of this potential, it's not surprising that, 83% of CEOs say AI is a strategic priority. According to a report published by MIT Sloan management review, or that Gartner predicts AI will generate almost trillion dollars in business value in only a couple of years. But it is very hard to get right. Gartner says 85% of the big data projects will fail. Venture Beat published a report that said 87% of data science projects never make it into production. So, while some companies are having success most still struggle.Himanshu Raja: So, the story starts with data warehouses, which it is hard to believe. Will soon celebrate its 40th birthday. Data warehouses came around in the 80s and were purpose-built for BI and reporting. Overtime they have become essential and today every enterprise on the planet has many of them. However, they weren't built for modern data use cases. They have no support for data like video or audio or text. Datasets that are crucial for modern use cases. It had to be very structured data queriable only with SQL. As a result, there is no viable support for data science or machine learning. In addition, there is no support for real-time streaming. They are great for batch processing, but either do not support streaming or can be cost prohibitive.Himanshu Raja: And because they are closed and proprietary systems, they force you to lock your data in, so you cannot easily move data around. So, today the result of all of that is that most organizations will first store all of their data in data lakes and block stores, and then move subsets of it into the data warehouse. So, then the thinking was that potentially data lakes could be the answer to all our problems. Data lakes came around about 10 years ago and they were great because they could indeed handle all your data. And they were there for good for data science and machine learning use cases. And data lakes serves as a great starting point for a lot of enterprises.Himanshu Raja: However, they aren't able to support that data warehousing or BI use cases. Data lakes are actually more complex to set up than a data warehouse. Our warehouse has a lot of familiar support semantics like asset transactions. With the data lakes, you are just dealing with files. So, those abstractions are not provided, you really have to build them yourself. And they're very complex to set up. And even after you do all of that, the performance is not great. You're just dealing with files, the end. In most cases, customers end up with a lot of small files and even the simplest queries will require you to list all those files. That takes time.Himanshu Raja: And then lastly, when it comes to reliability, they are not that great either. We actually have lot more data in that data lakes, then the warehouse, but is the data reliable? Can I actually guarantee that the schema is going to stay the same? How easy it is for an analyst to merge a bunch of different schemas together. As a result of all of these problems, data lakes have sort of turned into these unreliable data swamps where you have all the data, but it's very difficult to make any sense of it. So, understandably in the absence of a better alternative, what we are seeing with most organizations is a strategy of coexistence.Himanshu Raja: So, this is what a data swamp look like. There are tons of different tools to power each architecture required by a business unit or the organization. It's a whole slew of different open source tools that you have to connect. In the data warehousing stack, on the left side, you are often dealing with proprietary data formats. And if you want to enable advanced use cases, you have to move the data across to other stacks. It ends up being expensive and resource intensive to manage. And what does it result into? Because the systems are siloed, the teams become siloed too. Communication slows down, hindering innovation and speed.Himanshu Raja: Different teams often end up with different versions of the truth. The result is multiple copies of data, no consistent security governance model, closed systems and disconnected, less productive data teams. So, how do we get the best of both worlds? We want some things from the data warehouse, we want some things from the data lakes. We want the performance and reliability of the data warehouses, and we want the flexibility and the scalability of the data lakes. This is what we called the lakehouse paradigm. And the idea here is that the data is in the data lake, but now we are going to add some components so that we can now do all the BI and reporting from the warehouse and all the data science and machine learning from data lakes and also support streaming analytics. So, let's build a lakehouse. What are the things we need to build a lakehouse?Himanshu Raja: We said that we want all our data to be in an really scalable storage layer. And we want a unified platform where we can do multiple use cases. We can achieve multiple use cases. So, we need some kind of transactional layer on top of that data storage layer. So, what do you really need is something like asset compliance, so that when you write data, it either fully succeeds or fully fails and things are consistent. The structure transaction layer is what is data lake. And then the other requirement we talked about was performance. So, to support the different type of use cases, we needed to be really fast. We have lot of data that we want to work with. So, there is the data engine, which is a high-performance query engine that Databricks has created in order to support different types of use cases, whether it is SQL, data science, ETL, BI reporting, streaming, all that stuff on top of the engine to make it really, really fast.Himanshu Raja: So, let's do a deep dive on what is data lake. Data lake is an open, reliable, performant and secure data storage and management layer for your data lakes that enable you to create a true single source of truth. Since it's built upon a budget spot, you are able to build high-performance data pipelines to clean your data from raw injection to business level aggregates. And given the open format, it allows you to avoid unnecessary replication and proprietary lock-in. Ultimately, data lake provides that reliability, performance, and security you need to solve your downstream data use cases. Next, I'm going to talk about each of those benefits of data lake. The first and foremost benefit that you get with data lake is high-quality reliable data in your analytics stack.Himanshu Raja: Let me just talk about three key things here. The first is asset transaction. The second is schema enforcement and schema evolution. And then third is unified batch and streaming. So, on asset transactions, Delta employs an all or nothing asset transaction approach to guarantee that any operation you do on your data lake either fully succeeds or gets aborted so that it can be rerun. On schema enforcement Delta Lake uses schema validation on right, which means that all new rights to our table are checked for compatibility with the target table schema at right time. If the schema is not compatible, Delta Lake cancels the transaction altogether, and no data is written and raises an exception to let the user know about the mismatch.Himanshu Raja: We have very recently introduced capabilities to also do schema evolution, where we can evolve the schema on the fly as the data is coming in especially in the cases where the data is semi structured or unstructured. And you may not know what the data types are, or even in a lot of cases, what the columns that are coming in are. The third thing I would like to talk about is unified batch and streaming. Delta is able to handle both batch and streaming data, including the ability to concurrently, write batch and streaming to the same data table. Delta Lake directly integrates with spark structured streaming for low-latency updates.Himanshu Raja: Not only does this result in a simpler system architecture by not requiring you to build a Lambda architecture anymore. It also results in a shorter time from data ingest to query results. The second key advantage of Delta Lake is performance, lightning, fast performance. There are two aspects to performance in data analytic stack. One is how the data is stored, and then the other is performance during query, during run time. So, let's talk about how their data is stored and how does Delta optimizes the data storage format excel. Delta comes with out-of-box capabilities to store the data optimally for querying. Capabilities such as the ordering where the data is automatically structured along multiple dimensions for fast query performance is one. Delta also has data skipping, where Delta maintains the file statistics so that the data subsets relevant to the queries are used instead of the entire tables.Himanshu Raja: We don't have to go and read all the files. Files can be skipped based on the statistics. And then auto-optimize, optimize is a set of features that automatically compacts small files into fewer larger files so that the query performance is great out of the box. It's paying a small pause during writes to offset and give really great benefit for the tables during the requering. So, that's the part about how the data is stored. Now, let's talk about the Delta engine, which comes into play when you actually query that data. Data engine has three key components to provide super fast performance, photon, the query optimizer and caching. Photon is a native vectorized engine, fully compatible with Apache spark, build to accelerate all structured and semi-structured workloads by more than 20X compared to spark 2.4.Himanshu Raja: Second key component of Delta engine is query optimizer. The query optimizer extends the sparks cost-based optimizer and adaptive query execution with the advanced statistics to provide up to 18 X faster query performance for data warehousing workloads than Spark 3.0. And then the third key component of Delta engine is caching. Delta engine automatically caches IO data, and transcodes it into a more CPU efficient fallback to take advantage of NBMESSTs providing up to 5X faster performance for table scans than Spark 3.O. it also includes a second cache for query results to instantly provide results for any subsequent raps. This improves performance for repeated queries like dashboards, where the underlying tables are not changing frequently.Himanshu Raja: So, let me talk about the third main benefit of Delta Lake, which is to provide security and compliance at scale. Delta Lake reduces risk by enabling you to quickly and accurately update data in your data lake, to comply with regulations like GDPR and maintain better data governance through audit logging. Let me talk about two specific features, time-travel and stable and role-based access controls. With time-travel Delta automatically versions the big data that you store in your data lake and enables you to access any historical version of that data. This temporal data management simplifies your data pipeline by making it easy to audit, rollback data in case of accidentally bad writes or deletes and reproduce experiments and reports.Himanshu Raja: Your organization can finally standardize on a clean centralized version, big data repository in your own cloud storage for your analytics. The second feature I would love to talk about is that table and role based access controls. The data lake, you can programmatically grant and revoke access to your data based on specific workspace or role to ensure that your users can only access the data that you want them to. The Databrick's is extensive ecosystem of partners. Customers can enable a variety of security and governance functionality based on their individual needs.Himanshu Raja: Lastly, but one of the most important benefits of Delta Lake is that, it's open and agile. Delta Lake is an open format that works with other open source technologies, avoiding vendor lock-in and opening up an entire community and ecosystem of tools. All the data in Delta Lake is stored in an open Apache parquet format, allowing data to be read by any compatible reader. Developers can use their Delta Lake with their existing data pipelines with minimum changes, as it is fully compatible with spark. The most commonly used big data processing engine. Delta Lake also supports SQL DML, out-of-box to enable customers to migrate SQL workloads to Delta simply and easily.Himanshu Raja: So, let's talk about how we have seen customers leverage Delta Lake for a number of use cases, primarily among them is improving data pipelines, doing ETL at scale, unifying batch, and streaming with direct integration with Apache spark structured streaming to run both batch and streaming workloads in sort of doing the Lambda architecture, doing BI on your data Lake with our Delta engine, super fast, ready performance. You don't need to choose between a data lake and a data warehouse. As we talked about with the lakehouse, you can do BI directly on your data lake and then meeting regulatory needs with standards like GDPR by keeping a record of historical data changes. And who are these users?Himanshu Raja: The data lake is being used by some of the largest Fortune 100 companies in the world. We have customers like Comcast, Wirecomm, Conde Nast, McAfee, Edmonds. In fact, here Databricks all the data analytics is done using data lake. So, I would love to just deep dive in and would like to talk about the Starbucks use case to just give you an idea as to how our customers have used data lake in their ecosystem. Starbucks today does demand forecasting and personalizes the experiences of their customers on their app. And their architectures are actually struggling to handle petabytes of data adjusted for downstream ML and analytics, and they needed a scalable platform to support multiple use cases across the organization.Himanshu Raja: And with Azure Databricks and Delta Lake, their data engineers are able to build pipelines that support batch and real-time workloads on the same platform. They have enabled their data science teams to blend various data sets, to create new models that improve the customer experiences. And most importantly, data processing performance has improved dramatically allowing them to deploy environments and deliver insights in minutes. So, let me wrap up by summarizing what data lake can do for you, why it is the right foundation for your lakehouse. As we discovered that with Delta Lake, you can improve analytics and data science and machine learning throughout your organization by enabling teams to collaborate and ensure that they are working on reliable data to improve speed with which they make decisions.Himanshu Raja: You can simplify data engineering, reduce infrastructure and maintenance costs with best price performance, and you can enable a multi-cloud secure infrastructure platform with data lake. So, how do you get started on data lake? It's actually really easy, if you have a Databricks deployment already on Azure or AWS, and now GCP if you deploy a cluster with DBR, which is the Databricks right time release version 8.0 or higher, you actually do not need to do anything. Delta is now the default format for all creative tables and the data frame APIs. But we also have plenty of sources for you to try out the product and learn.Himanshu Raja: It's actually a lot of fun to deploy your first data lake and just build a really cool dashboard using a notebooks. If you have not tried Databricks before you can sign up for a free trial account and then you can follow our getting started guide. And Brenner, will do a demo very shortly to just showcase the capabilities that we talked about. So, with that over to you, Sam.Sam Steiny: Awesome. Thank you, Himanshu. That was great. Now, in the past the stage over to Brenner Heintz and Brenner is going to take us through a demo that really brings Delta Lake to life. Now, that you've heard what it is and how powerful it can be, let's see it in action. So, over to you, Brenner.Brenner Heintz: My name is Brenner Heintz. I am a technical PMM at Databricks, and today I'm going to show you how Delta Lake provides the perfect foundation for your lakehouse architecture. We're going to do a demo, and I'm going to show you how it works from a practitioner's perspective. Before we do so, I want to highlight the Delta Lake cheat sheet. I've worked on this with several of my colleagues, and the idea here is be able to provide a resource for practitioners like yourself, to be able to quickly and easily get up to speed with Delta Lake and be able to be productive with it very, very quickly. We've provided most, if not all of the commands in this notebook, it's part of the cheat sheet. So, I highly encourage you to download this notebook and you can click directly on this image, it'll take you directly to the cheat sheet, provide a one pager for Delta Lake with Python and a one pager for Delta Lake with Spark SQL.Brenner Heintz: So, first in order to use Delta Lake, you need to be able to convert your data to Delta Lake format. And the way that we're able to do that is instead of saying parquet as part of your create table or your Spark data frame writer command, all you have to do is place that with the word Delta, to be able to start using Delta Lake right away. So, here's a look at what that looks like. With Python, we can use Spark to read in our data in parquet format. You could also read in your data in CSV or other formats for example. Spark is very flexible in that way. And then we simply write it out in Delta format by indicating Delta here.Brenner Heintz: And we're going to save our data in the loans Delta table. We can do the same thing with SQL. We can use a create table command using Delta to then save our table in Delta format. And finally, the convert to Delta command makes it really easy to convert our data to Delta Lake format in place. So, now that we have shown you how to convert your data to Delta like format, let's take a look at a Delta Lake table and what that looks like. So, I've run the cell already. We have 14,705 batch records in our loans Delta table. Today, we're working with some data from the lending club, and you can see the columns that are currently part of our table here.Brenner Heintz: So, I went ahead and kicked off a couple of right streams to our table. And the idea here was to show you that Delta Lake tables are able to handle batch and streaming data, and they're able to integrate those straight out of the box without any additional configuration or anything else that's needed. You don't need to build a Lambda architecture, for example, to integrate both batch in real-time data. Delta Lake tables can easily manage both at once. So, as you can see, we're writing about 500 records per second, into our existing Delta Lake table. And we're doing so with two different writers, just to show you that you can concurrently both read and write from Delta Lake tables consistently with asset transactions, ensuring that you never deal with a pipeline breakage that corrupts the state of your table, for example.Brenner Heintz: Everything in Delta Lake is a transaction. And so this allows us to create isolation between different readers and writers. And that's really powerful, it saves us a lot of headache and a lot of time undoing mistakes that we may have made if we didn't have acid transactions. So, as I promised as well, those two streaming writes have been coupled. I've also created two streaming reads to show you what's happening in the table in near real time. So, we had those initial 14,705 batch records here. But since then we have about 124,000 streaming records that have entered our table since that time.Brenner Heintz: This is essentially the same chart, but showing you what's happening over each 10-second-window, each of these bars represents a 10-second-window, over which as you can see, since our streams began, we have about 5,000 records per stream that are written to our table at any time. So, all of this is just to say that Delta Lake is a very powerful tool that allows you to easily integrate batch and streaming data straight out of the box. It's very easy to use, and you can get started right away. To put the cherry on top, we added a batch query just for good measure, and we plotted it using Databricks built-in visualization tools, which are very easy and allow you to visualize things very quickly.Brenner Heintz: So, now, that we've showed you how easy it is to integrate batch and streaming data with Delta Lake, let's talk about data quality. You need tools like schema enforcement and schema evolution in order to enforce the quality in your tables. And the reason for that is that what you don't want are upstream data sources, adding additional columns, removing columns, or otherwise changing your schema without you knowing about it. Because what that can cause is a pipeline breakage that then affects all of your downstream data tables. So, to avoid that, we can use schema enforcement first and foremost. So, here I've created this new data, data frame that contains a new column, the credit score column, which is not present in our current table.Brenner Heintz: So, because Delta Lake offers schema enforcement when we run this command, we get an exception because the schema mismatch has been detected by Delta Lake. And that's a good thing. We don't want our data to successfully write to our Delta Lake table because it doesn't match what we expect. However, as long as we're aware and we want to intentionally migrate our schema, we can do so by adding a single command to our write command, we include the merge schema option. And now, that extra column is successfully written to our table, and we're also able to evolve our schema. So, now, when we try and select the records that were in our table, in our new data table, you can see that those records were in fact successfully written to the table and that new credit score column is now present in the schema of our table as well.Brenner Heintz: So, these tools give you, they're very powerful and they allow you to enforce your data quality the way that you need to in order to transition your data from raw unstructured data to high quality structured data, that's ready for downstream apps and users overtime. So, now, that we've talked about schema enforcement and scheme evolution, I want to move on to Delta Lake time travel. Time travel is a really powerful feature of Delta Lake. And because everything in Delta Lake as a transaction, and we're tracking all of the transactions that are made to our Delta Lake tables over time in the transaction log, that allows us to go back in time and recreate the state of our Delta Lake table at any point in time.Brenner Heintz: First, let's look at what that looks like. So, at any point, we can access the transaction log by running this describe history command. And as you can see, each of these versions of our table represent some sort of transaction, some sort of change that was made to our tables. So, our most recent change was that we upended those brand new records with a new column to our Delta Lake table. So, you can see that transaction here, before that we had some streaming updates. All of those rights that were occurring to our table were added as transactions. And basically this allows you to then go back and use the version number or timestamp, and then query historical versions of your Delta Lake tables at any point. That's really powerful because you can even do creative things like compare your current version of a table to a previous version to see what has changed since then, and do other sorts of things along those lines.Brenner Heintz: So, let's go ahead and do that. Let's look, we'll use time travel to view the original version of our table, which was version zero. And this should include just those 14,705 records that we started with because at that point version zero of our table, we hadn't streamed any new records into our table at all. And as you can see, the original version, those 14,705 records are the only records that are present in version as of zero. And there is no credit score column either, because of course, back in version zero, we had not yet evolved Delta Lake table schema.Brenner Heintz: So, compare that 14,705 records to the current number of records in our table, which is over 326,000. Finally, another thing you can do with Delta Lake time-travel is restore a previous version of your tables at any given point in time. So, this is really powerful, if you accidentally delete a column you didn't mean to, or delete some records you didn't mean to, you can always go back and use the restore command to then have the current version of your table restored exactly the way that your data was at that given timestamp or version number. So, as you can see, when we run this command to restore our table to its original state version as of zero, we have been able to do so successfully. Now, when we query it, we only get those 14,705 records as part of the table.Brenner Heintz: Next, one of the features that I think developers, data engineers and other data practitioners are really looking for when they're building their lakehouse is the ability to run simple DML command with just one or two lines of code, be able to do operations like deletes, updates, merges, inserts, et cetera. On a traditional data lake, those simply aren't possible. With Delta Lake, you can run those commands and they simply work and they do so transactionally. And they're very, very simple. So, managing change data becomes much, much easier when you have these simple commands at your disposal.Brenner Heintz: So, let's take a look, we'll choose user ID 4420 as our test case here, we'll use sort of modify their data specifically to show you what Delta Lake can do. As you can see, they are currently present in our table, but if we run this delete command and we specify that specific user, when we run the command and then we select all from our table, we now have no results. The delete has occurred successfully. Next, when we look at the described history command, the transaction log, so you can see the delete that we just carried out is now present in our table. And you can also see the restore that we did to jump back to the original version of our table version zero is also present. We can also do things like insert records directly back into our table if we want to do so.Brenner Heintz: Here, we're going to use time-travel to look at version as of zero, the original version of our table before this user was deleted and then insert that user's data back in. So, now when we run the select all command, the user is again, present in our table. The insert into command works great. Next, there's the update command. Updates are really useful, if you have row level changes that you need to make. Here, we're going to change this users funded amount to 22,000. Actually let's make it 25,000, it looks like it was already 22,000 before.Brenner Heintz: So, we'll update that number and then when we query our table, now, in fact, the user's funded amount has been updated successfully. Finally, in Delta Lake you have the ability to do really, really powerful merges. You can have a table full of change data that for example represents inserts and updates to your Delta Lake table. And with Delta Lake, you can do upsert. In just one single step you can... for each row in your data frame that you want to write to your Delta Lake table, if that row is already present in your table, you can simply update the values that are in that row. Whereas if that row is not present in your table, you can insert it.Brenner Heintz: So, that's what's known as an upsert and those are completely possible and they're very, very easy in Delta Lake. They make managing your Delta Lake very, very simple. So, first we create a quick data frame with just two records in it, we want to add user 4420's data back into our table. And then we also created a user whose user ID rather is one under 1 million. So, it's 999,999. And this user is not currently present in our table. We want to insert them. So, this is what our little data frame looks like. And as you can see, we have these as an update or an insert. And when we run our merge into command, Delta Lake is able to identify the rows that already exist, like user 4420, and those that don't already exist. And when they don't exist, we simply insert them.Brenner Heintz: So, as you can see, these updates, and inserts occurred successfully and Delta Lake has no problem with upserts. Finally, the last thing I want to point out are some specific performance enhancements that are offered as part of Delta Lake. But also as part of Databricks, Delta Lake only. We have a couple of commands that are Databricks, Delta Lake only at the moment. First there's the vacuum command. The vacuum command takes a look at the files that are currently a part of your table, and it removes any files that aren't currently part of your table that have been around for a retention period that you specify. So, this allows you to clean up the old versions of your table that are older than a specific retention period, and sort of save on cloud costs that way.Brenner Heintz: Another thing you can do on Databricks Delta Lake is you can cache the results of specific commands in memory. So, if you have a specific table that your downstream analysts tend to always group by a specific dimension, you can cache that SQL command, and it will always appear much quicker than it, and that way it's able to avoid doing a full read of your data, for example. You also had the ability to use the Z order optimized command, which is really powerful. Z order optimize essentially looks at the layout of your data tables and it figures out the perfect way to locate your data in different files. It essentially lays out your files in an optimized fashion, and that allows you to save on cloud storage costs because the way that it lays them out is typically much more compact than would be when you start. And it also then optimizes those tables for a read and write throughput.Brenner Heintz: So, it's very powerful. It speeds up the results of your queries and saves you on storage and compute costs ultimately. So, that's the demo. I hope you've enjoyed this demo. Again, take a look at the Delta Lake cheat sheet that we will post as part of the description or in the chat that is part of the presentation below. So, thanks so much. I hope you've enjoyed this demonstration. Check out Delta Lake and join us on GitHub, Slack, or as part of our mailing list. Thanks so much.Sam Steiny: Awesome. Thanks, Brenner. That was really, really great. I'm so excited now to be joined by Barbara Eckman. Barbara is a senior principal software architect at Comcast, and she's going to be sharing her experience with Delta Lake and how working with Databricks has really made an impact on her day-to-day and on the Comcast business. So, thanks so much for being here, Barbara. We're super excited to have you.Barbara Eckman: Hi, everybody. Really glad to be here. Hope you're all doing well. I'm here to talk about hybrid cloud access control in a self-service computer environment here at Comcast. I want to just real briefly mentioned that Comcast takes very seriously its commitment to our customers to protect their data. I'm part of the Comcast, what we call data experience big data group. And big data in this case means not only public cloud, but also on-prem data. So, we have a heterogeneous data set, which offers some challenges and challenges are fun, right? Our vision is that data is treated as an enterprise asset. This is not a new idea, but it's an important one.Barbara Eckman: And our mission is to power Comcast enterprise through self-service platforms, data discovery lineage, stewardship governance, engineering services, all those important things that enable people to really use the data in important ways. And we know as many do that powerful business insights, the most powerful insights come from models that integrate data, that span silos. Insights for improving the customer experience as well as business value. So, what this means for the business there are some examples. Basically, this is based on the tons of telemetry data that we capture from sensors and Comcast's network. We capture things like latency, traffic, signal to noise ratio, downstream and upstream, error rates and other things that I don't even know what they mean.Barbara Eckman: But this enables us to do things that improve customer experience like plan the network topology to help if there's a region that has a ton of traffic, we might change the policy to support that. Minimizing truck rolls, truck rolls are what we call it when the Comcast guy cable guy comes or cable female comes to your house. And in this COVID times, we really would like to minimize that even more. And if we can analyze the data ahead of time, we can perhaps make any adjustments or suggest adjustments that the user can make to minimize the need for people to come to their house.Barbara Eckman: We can monitor, predict problems and remedy them often before the user even knows because of this data and this involves both the telemetry data and integrating it with other kinds of data across the enterprise. And then optimizing network performance for region or for the whole household. So, now this is really important stuff and it really helps the customers. And we're working to make this even more prevalent. So, what makes your life hard? This is a professional statement. If you want to talk about personally, what makes your life hard? We can do that later, but what makes your life harder as a data professional?Barbara Eckman: People usually say, \"I need to find the data. So if I'm going to be integrating data across silos, I need to find it. I know where it is in myself silo, but maybe.\" And the way we do that is a metadata search and discovery, which we do through Elasticsearch. Then once I find the data that might be of interest to me, I need to understand what it means. So, what someone calls an account ID might not be the same account ID that you are used to calling an account ID, billing IDs, or back office account IDs need to know what it means in order to be able to join it, to make sense as opposed to Franklin data, monster data that isn't really appropriately joined. We need to know who produced it, that it come from a set-top box. Did it come from a third party who touched it while it was journeying through Comcast, through Tenet, through Kafka or Kinesis and someone aggregated it and then maybe somebody else enriched it with other data.Barbara Eckman: And then it landed in a data lake. The user of the data in the data lake wants to know where the data came from, and who added what piece. And you could see this as both the publisher looks at the data in the data lake and says, \"This looks screwy, what's wrong with this? Who messed up my data?\" He could also say, or they could say, \"Wow, this is enriched really great. I want to thank that person.\" And also someone who's just using the data wants to know who to ask questions. What did you enrich this with? Where did that data come from, that kind of thing? So, and all that really is helpful when you're doing this integration. That's data governance and lineage, which we do in Apache Atlas.Barbara Eckman: That's our metadata and lineage repository. Then once you found data and understood it, you have to be able to access it. And we do that through at Apache Ranger and its extension that's provided by Privacera. Once you have access to it, you need to be able to integrate it and analyze it across the enterprise. So, finally, now we get to the good stuff to be able to actually get our hands on the data. And we do that with self-service compute using Databricks. And Databricks is a really powerful tool for that. And finally we find that we do really need asset compliance for important operations. And we do that with Delta Lake. So, I can talk about this in more detail, as this top goes on or in the question session.Barbara Eckman: I'm an architect. So, I have to have bus and line diagrams. So, this is a high-level view of our hybrid cloud solution. So, income passed on our data centers, we have a Hadoop data lake that involves Hadoop Ranger and Apache Atlas working together. We are, as many companies are kind of phasing that out, but not immediately, it takes a while. We have a Terra data, enterprise data warehouse. Similarly, we are thinking to move that and not necessarily to the cloud entirely, but maybe to another on-prem source, like the object store. We use MinIO and basically that gives us the mix this object so it look like S3. So, when the spark jobs that we like to use on S3 also can run on our on pre data store.Barbara Eckman: And that's a big plus of course. And for that, we have a Ranger data service that helps with access control there. Up in the cloud, we use AWS though Azure also has a big footprint in Comcast. And Databricks compute is kind of the center here. We use it to access Kinesis. Redshift is only, we're just starting with that. We use Delta Lake and S3 object store and we have a Ranger plugin that the Databricks folks worked carefully with Privacera to create so that our self-service Databricks environment can have all the nit script and the configurations that it needs to run the access control that Privacera provides.Barbara Eckman: We also use Presto and for our federated query capability, it also has a Ranger plugin and all the tags that are applied to metadata on which policies are built, or are housed in Apache Atlas and Ranger and Atlas synced together. And that's how Ranger knows what policies to apply to what data. And in the question session, if you want to dig deeper into any of this, I'd be very happy to do it. So, this is very exciting to me, we're just rolling this out and it's so elegant and I didn't create it so I can say that. So, Ranger analysis together provide a declarative policy based access control. And as I said, Privacera extends Ranger, which originally only worked in Hadoop to AWS through plugins and proxies. And one of the key ones that we use, of course, is Databricks on all three of these environments. And basically what I like about this is we really have one ranger to rule them all and Atlas is his little buddy, because he provides or she, provides the tags that really power our access control.Barbara Eckman: So, here's again a diagram. And we have a portal that we built for our self service applications and the user tags, the metadata with tags, like this is PII, this is a video domain, that kind of stuff. That goes into Atlas, the tags and the metadata associations are synced with Ranger, the policies based on that. So, who gets the CPI? Who gets to see video domain data? Those are synced and cashed in the range of plugins. And then when a user calls an application, whether it's a cloud application in Databricks, or even an on-prem application, the application asks Ranger, \"Does this user have the access to do what they're asking to do on this data?\" If the answer is yes, and it's very fast, because these are plugins. If the answer is yes, they get access.Barbara Eckman: If no, then they get an error message and we can also do masking and show the data, if someone has access to many columns, but not all columns, I would say a glue table we can mask out the ones that they don't have access to and still give them what data they are allowed to see. Recently we've really needed acid compliance. So, traditionally big data lakes are write once, read many. We have things streaming in from set top boxes in the cable world, those aren't transactional, that's not transactional data. That's what we're used to, but now increasingly we are finding that we need to delete specific records from our parquet files or whatever. We can do this in Spark, but it is a terribly performant. It certainly it can be done, but it turns out Delta Lake does it much better.Barbara Eckman: The deletes are much more performant and you get to view snapshots of past data lake states, which is really pretty awesome. So, we're really moving toward, I love this word, a lakehouse being able to do, write once, read many and acid all in one place. And that is largely thanks to data lakes. So, this is me. Please reach out to me an email if you wish. And I'll be happy to answer questions in the live session if you have any. So, thank you very much for listening.Sam Steiny: Thank you for joining this event, Barbara. That was so awesome. It's great to hear the Comcast story. So, with that, let's get to some questions. We're going to move over to live Q&A. So, please add your questions to that Q&A.Watch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. 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{"source":"https:\/\/www.databricks.com\/customers\/yipitdata","text":"Yipit \u2013 DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYYipitData transforms financial market information overload into insight60%Lower database costs$2.5Million annual savings90%Reduction in data processing time INDUSTRY: Financial services SOLUTION: Data-driven ESG,risk management,transaction enrichment PLATFORM USE CASE: Delta Lake,data science,machine learning,ETL CLOUD: AWS\u201cWith Databricks, we\u2019re innovating faster than ever before across our data engineering and analyst functions, and paying less in database expenses every year.\u201d\n\u2014 Steve Pulec, CTO at YipitDataYipitData provides data-driven research to empower investors by combining alternative data sources with web data for comprehensive coverage. By leveraging Databricks, YipitData\u2019s data team has been able to reduce data processing time by up to 90 percent, increasing their analysts\u2019 ability to deliver impactful, reliable insights to their clients. Additionally, by moving to Databricks on AWS, YipitData has reduced database expenses by almost 60%.Unlocking hidden insights in alternative dataMaking sound investment choices requires information. The more actionable information you have, the odds of financial services institutions (FSIs) obtaining a better understanding of their customers, markets, and businesses increases significantly. YipitData is in the business of providing data-driven insights to the world\u2019s largest hedge funds and corporations to help them gain a real competitive edge and provide better service to their customers. Specifically, they leverage alternative data sources and web scrapes to help banking institutions and asset managers alike make better decisions by revealing valuable information about consumer behavior (e.g. utility payment history, transaction information) and extends across a variety of use cases including trade analyses, credit risk, and\u00a0ESG\u00a0risk.\u201cAlternative data is a critical key to the success of our financial services customers,\u201d explained Anup Segu, Senior Software Engineer at YipitData. \u201cHowever, most organizations don\u2019t have the means to leverage alternative data to the greatest extent possible. That\u2019s where we come in to help.\u201dThe challenge the YipitData team faced however was not only the sheer volume and variety of alternative data (each month they make billions of requests collecting data from hundreds of websites), but they were also limited by siloed teams and the inability to scale their data processing and analytics. Running queries and scaling their previous data warehouse proved challenging and time-consuming.\u201cWe were constantly running into performance bottlenecks,\u201d explained Segu. \u201cVery large queries could take up to six hours which slowed our ability to answer questions.\u201dCollaboration across teams was also an issue as they struggled to share learnings and code. \u201cWe struggled with siloes of tribal knowledge, which hampered our ability to scale and operate with speed,\u201d explained Bill Mensch, data analyst at YipitData.Democratizing data analytics across the organizationWith Databricks, the team at YipitData is now able to manage the entire data analytics workflow from data ingestion to downstream analytics. Integrated cluster management with features like autoscaling has greatly simplified infrastructure management while lowering operational costs. \u201cSince we can manage compute and storage independently, Databricks has allowed us to optimize our cluster management and AWS spend,\u201d explained Segu.Databricks has empowered its 40+ data analysts to evolve their roles into hybrid data engineers and analysts \u2014 enabling them to independently create data ingestion systems, manage ETL workflows, and produce meaningful financial research for their clients.Databricks has given our analysts flexibility so that they can be in control,\u201d explained Steve Pulec, CTO at YipitData. \u201cAs a result, data engineering doesn\u2019t even need to be involved and can focus on higher valued tasks.\u201dNow they can rapidly construct and deploy robust ETL workflows within the Databricks notebooks, and leverage their programming language of choice (Python or SQL) to explore, visualize, and analyze their data.Behind the story: The Data Team EffectMeet the great data team that\u2019s behind YipitDataMeet the teamFaster processing and simplified operations help to lower costsThe biggest gains from using Databricks has been the sheer processing power at scale, improved cost efficiencies of a cloud platform, and the democratization of data. With scalable cloud infrastructure at their fingertips, they\u2019ve been able to accelerate their data pipelines by up to 90% on average. And in some cases, some very large queries that used to take up to 6 hours can now be completed in roughly 7 seconds.\u201cDatabricks allows us to effortlessly trade scale for speed, which was not possible before,\u201d said Andrew Gross, Staff Engineer from YipitData. \u201cNow we are able to answer more questions with the same resources.\u201dNot only are they processing more data faster, but they are also doing so more efficiently which has helped drive business forward. \u201cCOVID has created tons of questions in the market, and we have gone into overdrive in terms of analyzing data to uncover answers,\u201d said Pulec. \u201cAll of that additional work has had a huge impact on our top line and has really helped our business to be able to answer those questions for investors in a timely manner. It probably would not have been possible in the old world.\u201dAlthough the scale of analyses and reporting to customers has increased by 4-5x, Pulec estimates that overall operational spending has decreased significantly. \u201cDatabricks has reduced our operations costs by almost 60%,\u201d said Pulec. And overall, with the help of Databricks and some\u00a0savvy cost-cutting techniques, they were able to cut their annual AWS bill by 50% or $2.5 million.Databricks serving as the foundation for their data analytics workflow, YipitData is looking to expand the adoption of Databricks across the company \u2014 promoting greater transparency and cross-team collaboration. Looking ahead, YipitData is well-positioned to take full advantage of the explosion of alternative data and unlocking new insights for FSIs and corporations to make smarter business decisions.Related ContentBlogYipitData Example Highlights Benefits of Databricks integration with AWS GlueSessionTechnical Talk at Spark + AI Summit 2020Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr\/company\/careers","text":"Databricks \ucc44\uc6a9 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Databricks \ucc44\uc6a9Databricks\ub294 \uc138\uc0c1\uc758 \uac00\uc7a5 \uc5b4\ub824\uc6b4 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\ub3c4\ub85d \ub370\uc774\ud130 \ud300\uc744 \ub3d5\ub294 \uac83\uc744 \uc0ac\uba85\uc73c\ub85c \uc0bc\uc2b5\ub2c8\ub2e4. \uc5ec\ub7ec\ubd84\ub3c4 \ud568\uaed8 \ud558\uc2dc\uaca0\uc2b5\ub2c8\uae4c?\uacf5\uc11d \ubcf4\uae30 OverviewCultureBenefitsDiversityStudents & new grads\ucee4\ub9ac\uc5b4\ub97c \ud55c\uce35 \ub354 \ubc1c\uc804\uc2dc\ucf1c, \ud55c \ucc28\uc6d0 \ub354 \ubc1c\uc804\ub41c \ubbf8\ub798\ub85c \ub098\uc544\uac00\uc138\uc694.Databricks\ub294 \ub370\uc774\ud130\uc640 AI \ud601\uba85\uc744 \uc120\ub3c4\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. 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Databricks\uc758 \uc9c1\uc6d0\uc744 \uc77c\uceeb\ub294 '\ube0c\ub9ad\uc2a4\ud130'\ub294 \ub611\ub611\ud558\uace0, \ud638\uae30\uc2ec \ub9ce\uace0, \uae30\ubbfc\ud558\uac8c \uc0ac\uace0\ud558\ub294 \ud2b9\ubcc4\ud55c \uc778\uc7ac\uac00 \ubaa8\uc5ec \uc788\uc2b5\ub2c8\ub2e4. \ube0c\ub9ad\uc2a4\ud130\uc5d0\uac8c Databricks\uc758 \uc7a5\uc810\uc744 \ubb3b\ub294\ub2e4\uba74, \uc544\ub9c8 \ub300\ubd80\ubd84\uc774 \uae30\uc5c5 \ubb38\ud654\ub77c\uace0 \ub2f5\ud560 \uac83\uc785\ub2c8\ub2e4.\uae30\uc5c5 \ubb38\ud654 \uc6d0\uce59 \ubcf4\uae30\uc790\uc2e0\uc758 \ud300 \ucc3e\uae30\uad00\ub9ac\uc0ac\uc5c5 \uac1c\ubc1c\uace0\uac1d \uc131\uacf5\uacf5\ud559\ud544\ub4dc \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc7ac\ubb34IT\ubc95\uc801 \uace0\uc9c0\ub9c8\ucf00\ud305\uc6b4\uc601\uc778\uc0ac \ubc0f HR\uc81c\ud488\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ucc44\uc6a9\uc601\uc5c5\ubcf4\uc548\uc778\ud134\uc2ed \ubc0f \uc870\uae30 \ucee4\ub9ac\uc5b4\ud61c\ud0dd, \ud2b9\uc804 \ubc0f \ud558\uc774\ube0c\ub9ac\ub4dc \uc791\uc5c5\uc77c\uc5d0\uc11c \ucd5c\uace0\uc758 \uc131\uacfc\ub97c \ub0b4\ub824\uba74 \uc9c1\uc6d0\uc758 \uac74\uac15\uacfc \ud589\ubcf5\uc774 \ud575\uc2ec\uc785\ub2c8\ub2e4. \uadf8\ub798\uc11c Databricks\uc5d0\uc11c\ub294 \uc720\uc5f0\ud55c \uadfc\ubb34 \uc81c\ub3c4\ub97c \ud3ec\ud568\ud558\uc5ec \uc88b\uc740 \ud61c\ud0dd\uacfc \ud2b9\uc804\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774 \ubaa8\ub4e0 \uac83\uc740 \uc9c1\uc6d0\uacfc \ud300\uc5d0\uac8c \uac00\uc7a5 \uc88b\uc740 \uac83\uc744 \ub4dc\ub9ac\uae30 \uc704\ud55c \ub178\ub825\uc785\ub2c8\ub2e4.\ud61c\ud0dd \uc0b4\ud3b4\ubcf4\uae30\ub2e4\uc591\uc131, \ud3c9\ub4f1 \ubc0f \ud3ec\uc6a9\uc131Databricks\ub294 \ubc30\uacbd, \uad00\uc810, \uae30\uc220\uc758 \ub2e4\uc591\uc131\uc774 \uc131\uacf5\uc744 \uc774\ub04c\uc5b4\ub0b8\ub2e4\uace0 \uc0dd\uac01\ud569\ub2c8\ub2e4. \uadf8\ub798\uc11c Databricks\ub294 \ud3ec\uc6a9\uc801\uc774\uace0 \uc9c0\uc6d0\uc744 \uc544\ub07c\uc9c0 \uc54a\ub294 \ud658\uacbd\uc744 \uc870\uc131\ud558\uace0\uc790 \ub178\ub825\ud569\ub2c8\ub2e4. Databricks\uc5d0\uc11c \uc5b4\ub5bb\uac8c \uc784\uae08 \uaca9\ucc28\ub97c \ud574\uc18c\ud558\uace0, \ucc44\uc6a9\uc5d0\uc11c \ubb34\uc758\uc2dd\uc801\uc778 \ud3b8\uacac\uc744 \uc81c\uac70\ud558\ub294 \ub4f1\uc758 \ub178\ub825\uc744 \uae30\uc6b8\uc774\ub294\uc9c0 \uc54c\uc544\ubcf4\uc138\uc694.\ud3ec\uc6a9 \ud65c\ub3d9 \ubcf4\uae30\uc9c0\uc5edDatabricks\ub294 \uce98\ub9ac\ud3ec\ub2c8\uc544\uc8fc \uc0cc\ud504\ub780\uc2dc\uc2a4\ucf54\uc5d0 \ubcf8\uc0ac\ub97c \ub450\uace0 \uc788\uc73c\uba70, \uc774\uc81c 12\uac1c \uad6d\uac00\uc5d0 20\uac1c \uc774\uc0c1\uc758 \uc9c0\uc0ac\ub97c \uc124\uce58\ud588\uc2b5\ub2c8\ub2e4. \uc804 \uc138\uacc4\uc801\uc73c\ub85c 4,500\uba85 \uc774\uc0c1\uc758 \uc9c1\uc6d0\uc744 \ub450\uace0 \uc788\uace0 \uc57c\uc2ec \ucc2c \uc131\uc7a5 \uc804\ub7b5\uc744 \uc138\uc6cc \ucd94\uc9c4\ud558\uace0 \uc788\uae30\uc5d0 Databricks\ub294 \uac00\uc7a5 \ube60\ub974\uac8c \uc131\uc7a5\ud558\ub294 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \uc18c\ud504\ud2b8\uc6e8\uc5b4 \ud074\ub77c\uc6b0\ub4dc \uae30\uc5c5\uc73c\ub85c \uc6b0\ub69d \uc130\uc2b5\ub2c8\ub2e4.\uc804 \uc138\uacc4 \uc9c0\uc0ac \ub458\ub7ec\ubcf4\uae30\ubbf8\uc8fc \uc9c0\uc5ed\uc0cc\ud504\ub780\uc2dc\uc2a4\ucf54\uc2dc\uc560\ud2c0\uc6cc\uc2f1\ud134 DC\ub274\uc695\ub354 \ubcf4\uae30\uc720\ub7fd\ub7f0\ub358\uc554\uc2a4\ud14c\ub974\ub2f4\ubca0\ub97c\ub9b0\ubb8c\ud5e8\ub354 \ubcf4\uae30\uc544\uc2dc\uc544 \ud0dc\ud3c9\uc591\ub3c4\ucfc4\uc2f1\uac00\ud3ec\ub974\uc11c\uc6b8\ud56d\uc800\uc6b0\ub354 \ubcf4\uae30\ud559\uc0dd \ubc0f \ub300\uc878 \uc2e0\uc785\uc744 \uc704\ud55c \uae30\ud68cDatabricks\uc5d0\uc11c\ub294 \uc790\uc0ac\uc758 \ucc28\uc138\ub300 \ub9ac\ub354\ub97c \ud0a4\uc6cc\ub0b4\uace0\uc790 \ucd5c\uc120\uc744 \ub2e4\ud569\ub2c8\ub2e4. \uadf8\ub798\uc11c \uc778\ud134\uacfc \uc0c8\ub85c\uc6b4 \ub300\uc878 \uc2e0\uc785 \uc9c1\uc6d0\uc774 \ud50c\ub7ab\ud3fc \uac1c\ubc1c\uc5d0 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud558\ub3c4\ub85d \ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.Databricks\uc758 University Program\uc740 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ud574\ucee4\ud1a4, \uc778\ud134 \uc62c\ub9bc\ud53d\uc5d0\uc11c\ubd80\ud130 \ubcf4\ub4dc \uac8c\uc784\uc73c\ub85c \ubc24\uc744 \uc9c0\uc0c8\uc6b0\ub358 \ub098\ub0a0\ub4e4, \ud574\ud53c \uc544\uc6cc\ub85c \ubcf4\ub0b8 \uc2dc\uac04\uc5d0 \uc774\ub974\uae30\uae4c\uc9c0 \uc5ec\ub7ec\ubd84\uc758 \uacbd\ud5d8\uc744 \ucd5c\ub300\ud55c \ud65c\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \uc124\uacc4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.\uc778\ud134\uc2ed \ubc0f \ucc44\uc6a9 \uae30\ud68c \uc0b4\ud3b4\ubcf4\uae30 \uac74\uac15 \ubcf4\ud5d8 \ubcf4\uc7a5 \uc815\ubcf4(\ubbf8\uad6d\ub9cc \ud574\ub2f9)\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\u0000\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/uri-may","text":"Uri May - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingUri May HuntersBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/liping-huang\/#","text":"Liping Huang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLiping HuangSenior Solutions Architect at DatabricksBack to speakersDatabricks Senior Solutions Architect, ex-Microsoft, specializing in Big Data Analytics, Enterprise Data Warehouse, and Business Intelligence, passionate about solving real world problems using data and technology.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.\u63a1\u7528\u60c5\u5831Databricks \u306e\u30df\u30c3\u30b7\u30e7\u30f3\u306f\u3001\u30c7\u30fc\u30bf\u6d3b\u7528\u3092\u901a\u3058\u3066\u96e3\u984c\u89e3\u6c7a\u306b\u6311\u3080\u7d44\u7e54\u306e\u652f\u63f4\u306b\u53d6\u308a\u7d44\u3080\u3053\u3068\u3067\u3059\u3002\u53c2\u52a0\u3057\u307e\u305b\u3093\u304b\uff1f\u63a1\u7528\u60c5\u5831\u3092\u898b\u308b OverviewCultureBenefitsDiversityStudents & new grads\u5c06\u6765\u306e\u305f\u3081\u306e\u30ad\u30e3\u30ea\u30a2\u30a2\u30c3\u30d7Databricks \u306f\u3001\u30c7\u30fc\u30bf\u3068 AI 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u901a\u77e5|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/akira-ajisaka\/#","text":"Akira Ajisaka - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAkira AjisakaSenior Software Development Engineer at Amazon Web ServicesBack to speakersAkira Ajisaka is a Senior Software Development Engineer on the AWS Glue team at Amazon Web Services. He likes open source software and distributed systems. He is an Apache Hadoop committer and PMC member.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/avinash-sooriyarachchi\/#","text":"Avinash Sooriyarachchi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAvinash SooriyarachchiSenior Solutions Architect at DatabricksBack to speakersAvinash Sooriyarachchi is a Solutions Architect at Databricks. His current work involves working with large Retail and Consumer Packaged Goods organizations across the United States and enabling them to build Machine Learning based systems. His specific interests include streaming machine learning systems and building applications leveraging foundation models. Avi holds a Master\u2019s degree in Mechanical Engineering and Applied Mechanics from the University of Pennsylvania.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rafael-barcelos\/#","text":"Rafael Barcelos - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRafael BarcelosSoftware Architect at Microsoft CorporationBack to speakers15+ years of experience as Full Stack Software Engineer working in several areas from user facing features, to backend services and platform features to support other engineers' goals.\nSince 2017, working as Architect driving the vision for a Data Mesh based platform that is being built by 100+ engineers distributed across the globe to support Data engineering and Data Science efforts on Office 365.\nEnjoy to mentor junior\/senior engineers in their technical careers and to work in fast paced teams focused on delivering solutions for hard problems, especially large-scale related ones.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/product\/data-streaming","text":"\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\uac04\ub2e8\ud55c \uc2e4\uc2dc\uac04 \ubd84\uc11d, ML \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 \ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \ub300\ud3ed \ub2e8\uc21c\ud654\ud558\uc5ec \uc2e4\uc2dc\uac04 \ubd84\uc11d, \uba38\uc2e0 \ub7ec\ub2dd, \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \ud558\ub098\uc758 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \uc81c\uacf5\ud569\ub2c8\ub2e4.\ub370\uc774\ud130 \ud300\uc774 \uc774\ubbf8 \uc54c\uace0 \uc788\ub294 \uc5b8\uc5b4\uc640 \ub3c4\uad6c\ub85c \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \uc6cc\ud06c\ub85c\ub4dc\ub97c \uad6c\ucd95\ud560 \uc218 \uc788\ub3c4\ub85d \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \uc2e4\uc2dc\uac04 \ub370\uc774\ud130 \uc6cc\ud06c\ub85c\ub4dc \uad6c\ucd95 \ubc0f \uad00\ub9ac\uc640 \uad00\ub828\ub41c \ud504\ub85c\ub355\uc158 \uce21\uba74\uc744 \uc790\ub3d9\ud654\ud568\uc73c\ub85c\uc368 \uac1c\u0000\u0000\ubc1c \ubc0f \uc6b4\uc601\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4. \uc2a4\ud2b8\ub9ac\ubc0d \ubc0f \ubc30\uce58 \ub370\uc774\ud130\uc5d0 \ub2e8\uc77c \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130 \uc0ac\uc77c\ub85c\ub97c \uc81c\uac70\ud569\ub2c8\ub2e4.\uc2a4\ud2b8\ub9ac\ubc0d \ud30c\uc774\ud504\ub77c\uc778 \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \ub354\uc6b1 \ube60\ub974\uac8c \uad6c\ucd95SQL\uacfc Python\uc5d0\uc11c \ud1b5\ud569 \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d API\ub85c \uc774\ubbf8 \uc54c\uace0 \uc788\ub294 \uc5b8\uc5b4\uc640 \ub3c4\uad6c\ub97c \uc0ac\uc6a9\ud558\uc138\uc694. \uc804\uccb4 \uc870\uc9c1\uc5d0 \uc2e4\uc2dc\uac04 \ubd84\uc11d, ML \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\uc790\ub3d9\ud654\ub41c \ud234\ub9c1\uc73c\ub85c \uc6b4\uc601 \ub2e8\uc21c\ud654\ud504\ub85c\ub355\uc158\uc5d0\uc11c \uc2e4\uc2dc\uac04 \ud30c\uc774\ud504\ub77c\uc778 \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc190\uc27d\uac8c \ubc30\ud3ec\u0000\u0000\ud558\uace0 \uad00\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc790\ub3d9\ud654\ub41c \ud234\ub9c1\uc740 \uc791\uc5c5 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158, \ub0b4\uace0\uc7a5\uc131\/\ubcf5\uad6c, \uc790\ub3d9 \uccb4\ud06c\ud3ec\uc778\ud305, \uc131\ub2a5 \ucd5c\uc801\ud654, \uc790\ub3d9 \ud655\uc7a5\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4.\ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ubaa8\ub4e0 \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \uac70\ubc84\ub10c\uc2a4 \ud1b5\ud569Unity Catalog\ub294 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0 \ubaa8\ub4e0 \uc2a4\ud2b8\ub9ac\ubc0d \ubc0f \ubc30\uce58 \ub370\uc774\ud130\uc5d0 \ub300\ud55c \ud558\ub098\uc758 \uc77c\uad00\uc801 \uac70\ubc84\ub10c\uc2a4 \ubaa8\ub378\uc744 \uc81c\uacf5\ud558\uba70, \uc2e4\uc2dc\uac04 \ub370\uc774\ud130\ub97c \ubc1c\uacac, \uc561\uc138\uc2a4 \ubc0f \uacf5\uc720\ud558\ub294 \ubc29\ubc95\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4.\uc5b4\ub5bb\uac8c \uc791\ub3d9\ud558\ub098\uc694?\uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \ubcc0\ud658\uc2e4\uc2dc\uac04 \ubd84\uc11d, ML \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc790\ub3d9\ud654\ub41c \uc6b4\uc601 \ud234\ub9c1\ucc28\uc138\ub300 \uc2a4\ud2b8\ub9bc \ucc98\ub9ac \uc5d4\uc9c4\ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4 \ubc0f \uc2a4\ud1a0\ub9ac\uc9c0\uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \ubcc0\ud658Delta Live Tables\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc5d0 \ub300\ud55c \ub370\uc774\ud130 \uc785\ub825 \ubc0f ETL\uc744 \ub2e8\uc21c\ud654\ud569\ub2c8\ub2e4. \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\uc5d0 \ub300\ud55c \uac04\ub2e8\ud55c \uc120\uc5b8\uc801 \uc811\uadfc\ubc95\uc744 \ud65c\uc6a9\ud558\uc5ec SQL \ubc0f Python \ub4f1\uacfc \uac19\uc774 \uc774\ubbf8 \uc54c\uace0 \uc788\ub294 \uc5b8\uc5b4\uc640 \ub3c4\uad6c\ub97c \ud300\uc5d0 \uc9c0\uc6d0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc81c\uc5b4\uac00 \uac00\ub2a5\ud55c \uc790\ub3d9 \uc0c8\ub85c \uace0\uce68 \uc124\uc815\uc73c\ub85c \ud55c \uacf3\uc5d0\uc11c \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9ac\ubc0d \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uc5ec \uc2e4\ud589\ud558\uba74, \uc2dc\uac04\uc744 \uc808\uc57d\ud558\uace0 \uc6b4\uc601 \ubcf5\uc7a1\uc131\uc744 \ub0ae\ucd9c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130\ub97c \uc804\uc1a1\ud560 \uc7a5\uc18c\uac00 \uc5b4\ub514\ub4e0, Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0 \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uba74 \uc6d0\uc2dc \ub370\uc774\ud130\ub97c \uc815\ub9ac\ud558\ub294 \ub370 \uc2dc\uac04\uc744 \ub0ad\ube44\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4.\"\uc608\uc804\uc5d0\ub294 \ubd88\uac00\ub2a5\ud588\ub358 \uc140\ud504 \uc11c\ube44\uc2a4 \ubc29\uc2dd\uc73c\ub85c \ud50c\ub7ab\ud3fc\uc744 \uc0ac\uc6a9\ud558\ub294 \uc0ac\uc5c5\ubd80\uac00 \uc810\uc810 \ub298\uc5b4\ub0ac\uc2b5\ub2c8\ub2e4. Databricks\uac00 Columbia\uc5d0 \uc77c\uc73c\ud0a8 \uae0d\uc815\uc801 \uc601\ud5a5\uc740 \uc785\uc774 \ub2f3\ub3c4\ub85d \ub9d0\ud574\ub3c4 \ubaa8\uc790\ub78d\ub2c8\ub2e4.\"\u2014 Columbia Sportswear \uc120\uc784 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \ub370\uc774\ud130 \uad00\ub9ac\uc790 Lara Minor\uc790\uc138\ud788\uc2e4\uc2dc\uac04 \ubd84\uc11d, ML \ubc0f \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\uba74 \ubd84\uc11d \ubc0f AI\uc758 \uc815\ud655\ub3c4\uc640 \uc2e4\ucc9c \uac00\ub2a5\uc131\uc744 \uc989\uc2dc \uac1c\uc120\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ube44\uc988\ub2c8\uc2a4\ub294 \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc758 \ub2e4\uc6b4\uc2a4\ud2b8\ub9bc \ud6a8\uacfc\ub85c \uc2e4\uc2dc\uac04 \uc778\uc0ac\uc774\ud2b8\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. SQL \ubd84\uc11d, BI \ubcf4\uace0, ML \ubaa8\ub378 \ud6c8\ub828 \ub610\ub294 \uc2e4\uc2dc\uac04 \uc6b4\uc601 \uc560\ud50c\ub9ac\ucf00\uc774\uc158 \uad6c\ucd95\uc744 \uc218\ud589\ud558\ub294 \uacbd\uc6b0\uc5d0\ub3c4 \ube44\uc988\ub2c8\uc2a4\uc5d0 \uac00\uc7a5 \uc2e0\uc120\ud55c \ub370\uc774\ud130\ub97c \uc81c\uacf5\ud568\uc73c\ub85c\uc368 \uc2e4\uc2dc\uac04 \uc778\uc0ac\uc774\ud2b8, \ub354\uc6b1 \uc815\ud655\ud55c \uc608\uce21, \ub354\uc6b1 \ube60\ub978 \uc758\uc0ac\uacb0\uc815\uc744 \uc5bb\uc5b4 \uacbd\uc7c1\uc5d0 \uc55e\uc124 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u201c\uc800\ud76c\ub294 \ud56d\uc0c1 \uc5b8\uc81c\ub098 \uac00\uc7a5 \uc815\ud655\ud55c \ucd5c\uc2e0 \ub370\uc774\ud130\ub97c \ube44\uc988\ub2c8\uc2a4 \ud30c\ud2b8\ub108\uc5d0\uac8c \uc81c\uacf5\ud574\uc57c \ud569\ub2c8\ub2e4. \uadf8\ub807\uc9c0 \u0000\uc54a\uc73c\uba74 \uc778\uc0ac\uc774\ud2b8\uc5d0 \ub300\ud55c \uc2e0\ub8b0\ub97c \uc783\uc744 \ud14c\ub2c8\uae4c\uc694. . . Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ub355\ubd84\uc5d0 \uc774\uc804\uc5d0\ub294 \ubd88\uac00\ub2a5\ud588\ub358 \uc77c\uc774 \uc9c0\uae08\uc740 \ub9e4\uc6b0 \uc190\uc26c\uc6cc\uc84c\uc2b5\ub2c8\ub2e4.\u201d\u2014 Guillermo Rold\u00e1n, \uc544\ud0a4\ud14d\ucc98 \ucc45\uc784\uc790, LaLiga Tech\uc790\uc138\ud788\uc790\ub3d9\ud654\ub41c \uc6b4\uc601 \ud234\ub9c1\uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778\uc744 \uad6c\ucd95\ud558\uace0 \ubc30\ud3ec\ud558\ub294 \ub3d9\uc548 Databricks\ub294 \ud504\ub85c\ub355\uc158\uc5d0 \ud544\uc694\ud55c \ub2e4\uc218\uc758 \ubcf5\uc7a1\ud55c \uc6b4\uc601 \uc791\uc5c5\uc744 \uc790\ub3d9\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc5ec\uae30\uc5d0\ub294 \uae30\ubcf8 \uc778\ud504\ub77c\uc758 \uc790\ub3d9 \ud655\uc7a5, \ud30c\uc774\ud504\ub77c\uc778 \uc885\uc18d\uc131\uc758 \uc624\ucf00\uc2a4\ud2b8\ub808\uc774\uc158, \uc624\ub958 \ucc98\ub9ac\uc640 \ubcf5\uad6c, \uc131\ub2a5 \ucd5c\uc801\ud654 \ub4f1\uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4.Enhanced Autoscaling\ub294 \uac01\uac01\uc758 \uace0\uc720\ud55c \uc6cc\ud06c\ub85c\ub4dc\uc5d0 \ucef4\ud4e8\ud305 \ub9ac\uc18c\uc2a4\ub97c \uc790\ub3d9\uc73c\ub85c \ud560\ub2f9\ud568\uc73c\ub85c\uc368 \ud074\ub7ec\uc2a4\ud130 \ud65c\uc6a9\uc744 \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4. \uc774\ub4e4 \uae30\ub2a5\uc744 \uc790\ub3d9 \ub370\uc774\ud130 \ud488\uc9c8 \ud14c\uc2a4\ud2b8 \ubc0f \uc608\uc678 \uad00\ub9ac\uc640 \ud568\uaed8 \uc0ac\uc6a9\ud558\uba74 \uc6b4\uc601 \ud234\ub9c1\uc744 \uad6c\ucd95 \ubc0f \uad00\ub9ac\ud558\ub294 \ub370 \uc0ac\uc6a9\ud558\ub294 \uc2dc\uac04\uc744 \uc904\uc774\uace0 \ub370\uc774\ud130\uc5d0\uc11c \uac00\uce58\ub97c \ucc3d\ucd9c\ud558\ub294 \ub370 \uc9d1\uc911\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc790\uc138\ud788\ucc28\uc138\ub300 \uc2a4\ud2b8\ub9bc \ucc98\ub9ac \uc5d4\uc9c4Spark Structured Streaming\uc740 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ub370\uc774\ud130 \uc2a4\ud2b8\ub9bc\uc744 \uc9c0\uc6d0\ud558\ub294 \ud575\uc2ec \uae30\uc220\uc774\uba70, \ubc30\uce58 \ubc0f \uc2a4\ud2b8\ub9bc \ucc98\ub9ac\ub97c \uc704\ud55c \ud1b5\ud569 API\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc740 99.95%\uc758 \uac00\ub3d9 \uc2dc\uac04\uc774 \uac80\uc99d\ub41c \uad00\ub9ac\ud615 \uc11c\ube44\uc2a4\ub85c Apache Spark \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc2e4\ud589\ud558\uae30\uc5d0 \ucd5c\uc801\uc758 \uc7a5\uc18c\uc785\ub2c8\ub2e4. Spark \uc6cc\ud06c\ub85c\ub4dc\ub294 Apache Spark API\uc640 \ud638\ud658\ub418\ub294 \ucc28\uc138\ub300 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc5d4\uc9c4\uc778 Photon\uc73c\ub85c \uac00\uc18d\ud654\ub418\uba70, \uc218\ucc9c \uac1c\uc758 \ub178\ub4dc\ub85c \uc790\ub3d9 \ud655\uc7a5\ub418\uace0 \ucd5c\uace0\uc758 \ube44\uc6a9\ub2f9 \uc131\ub2a5\ube44\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc790\uc138\ud788\ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4 \ubc0f \uc2a4\ud1a0\ub9ac\uc9c0Databricks\uc5d0\uc11c \ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \uc0ac\uc6a9\ud558\uba74 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc758 \uae30\ubcf8 \uad6c\uc131 \uc694\uc18c(Unity Catalog \ubc0f Delta Lake)\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uac8c \ub429\ub2c8\ub2e4. \uc6d0\uc2dc \ub370\uc774\ud130\ub294 \uc2a4\ud2b8\ub9ac\ubc0d \ubc0f \ubc30\uce58 \ub370\uc774\ud130\ub97c \uc5fc\ub450\uc5d0 \ub450\uace0 \uc124\uacc4\ud55c \uc720\uc77c\ud55c \uc624\ud508 \uc18c\uc2a4 \uc2a4\ud1a0\ub9ac\uc9c0 \ud504\ub808\uc784\uc6cc\ud06c, Delta Lake\ub85c \ucd5c\uc801\ud654\ub429\ub2c8\ub2e4.Unity Catalog\ub294 \ud558\ub098\uc758 \uc77c\uad00\uc801\uc778 \ubaa8\ub378\ub85c \ubaa8\ub4e0 \ub370\uc774\ud130 \ubc0f AI \uc790\uc0b0\uc5d0 \ub300\ud55c \uc138\ubd84\ud654\ub41c \ud1b5\ud569 \uac70\ubc84\ub10c\uc2a4\ub97c \uc81c\uacf5\ud568\uc73c\ub85c\uc368, \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ub370\uc774\ud130 \ubc1c\uacac, \uc561\uc138\uc2a4, \uacf5\uc720\ub97c \uc9c0\uc6d0\ud569\ub2c8\ub2e4. \ub610\ud55c, Unity Catalog\ub294 \ub2e4\ub978 \uc870\uc9c1\uacfc \uac04\ub2e8\ud558\uace0 \uc548\uc804\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\ub294 \uc5c5\uacc4 \ucd5c\ucd08\uc758 \uc624\ud508 \ud504\ub85c\ud1a0\ucf5c\uc778 Delta Sharing\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\ud1b5\ud569\ub370\uc774\ud130 \ud300\uc5d0 \ucd5c\ub300\uc758 \uc720\uc5f0\uc131\uc744 \uc81c\uacf5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Partner Connect  \ubc0f \uae30\uc220 \ud30c\ud2b8\ub108 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc744 \ud65c\uc6a9\ud558\uc5ec \uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ud558\ub294 \ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d \ub3c4\uad6c\uc640 \ub9e4\ub044\ub7fd\uac8c \ud1b5\ud569\ud574 \ubcf4\uc138\uc694.\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\uace0\uac1d \uc0ac\ub840\u201c\uc800\ud76c\ub294 \uace0\uc18d \ub370\uc774\ud130 \ucc98\ub9ac\uc5d0 Databricks\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \ub9e4\uc7a5\uc774\ub098 \uc628\ub77c\uc778\uc5d0\uc11c \ud658\uc790\uc758 \uc694\uad6c \uc0ac\ud56d\uc5d0 \ub300\uc751\ud560 \uc218 \uc788\ub294 \uc18d\ub3c4\ub85c \ud601\uc2e0\ud558\ub294 \ub370 \uc815\ub9d0\ub85c \ud070 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4. \ud604\uc7ac \uc2ed\uc5ec \uac1c\uc758 \uc774\ub2c8\uc154\ud2f0\ube0c\ub97c \ucd94\uc9c4\ud558\uace0 \uc788\uc73c\uba70, \ubaa8\ub4e0 \uc774\ub2c8\uc154\ud2f0\ube0c\ub294 Databricks\uc758 \ub370\uc774\ud130\ub97c \ud1b5\ud574 \uc11c\ube44\uc2a4\ub429\ub2c8\ub2e4.\u201d\u2014 Sashi Venkatesan, \uc81c\ud488 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uc774\uc0ac, Walgreens\u201c\uc774\uc81c \uc2e4\uc2dc\uac04 \ud0d0\uc9c0\ub97c \ud1b5\ud574 \uc0ac\uae30\ubc94\uc744 \ub2a5\uac00\ud558\uace0 \ud3b8\ubc95\uc744 \uc4f0\ub294 \uc0ac\uae30\ubc94, \ubd88\ubc95\uc801 \uce68\uc785, \uc790\ub3d9 \ub179\uc74c \uc804\ud654 \ubc0f \uc790\ub3d9 \ud14d\uc2a4\ud2b8, \uc2e0\uc6d0 \uc815\ubcf4 \ub3c4\ub09c \ub4f1\uc758 \uc601\uc5ed\uc5d0\uc11c \uc0ac\uae30\ubc94\ubcf4\ub2e4 \uc55e\uc11c \ub098\uac08 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\u201d\u2014 Kate Hopkins, AT&T \ubd80\uc0ac\uc7a5\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uae30Delta Live \ud14c\uc774\ube14Databricks \uc6cc\ud06c\ud50c\ub85cUnity CatalogDelta LakeSpark Structured Streaming\uad00\ub828 \ucf58\ud150\uce20eBooks \ubc0f \ub370\ubaa8\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0 Bill Inmon\uc774 \uad6c\ucd95\ud55c \ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI \uac70\ubc84\ub10c\uc2a4Databricks Lakehouse \ud50c\ub7ab\ud3fc\uc5d0 \ub300\ud55c \ub370\uc774\ud130 \ud300 \uac00\uc774\ub4dcDelta Live Tables \uc2a4\ud2b8\ub9ac\ubc0d \ub370\ubaa8\uc774\ubca4\ud2b8Delta Live Tables\ub97c \uc0ac\uc6a9\ud55c \ub370\uc774\ud130 \ubcc0\ud658 \ucc98\ub9ac\uac04\ud3b8\ud55c \ub370\uc774\ud130 \uc218\uc9d1 \uc6e8\ube44\ub098 \uc2dc\ub9ac\uc988DATA + AI SUMMIT 2022Data +AI \uc6d4\ub4dc \ud22c\uc5b4 2022\ube14\ub85c\uadf8Delta Live Tables \ubc0f Apache Kafka\ub97c \uc0ac\uc6a9\ud55c \ub0ae\uc740 \uc9c0\uc5f0 \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \ud30c\uc774\ud504\ub77c\uc778Delta Lake\uc5d0 \ub300\ud55c \uc2a4\ud2b8\ub9ac\ubc0d \ub370\uc774\ud130 \uc218\uc9d1\uc744 \ub2e8\uc21c\ud654\uc2e4\uc2dc\uac04 \uc778\uc0ac\uc774\ud2b8: \uace0\uac1d\uc774 Databrick\uc744 \ud1b5\ud55c \ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\uc744 \uc88b\uc544\ud558\ub294 3\uac00\uc9c0 \uc8fc\uc694 \uc774\uc720Project Lightspeed: Apache Spark\ub97c \uc0ac\uc6a9\ud55c \ub354\uc6b1 \ube60\ub974\uace0 \ub2e8\uc21c\ud55c \uc2a4\ud2b8\ub9bc \ucc98\ub9ac2021\ub144\uc5d0 Databricks \ubc0f Apache Spark\ub97c \uc704\ud574 \uac1c\ubc1c\ub41c \ubaa8\ub4e0 \uc0c8\ub85c\uc6b4 Structured Streaming \uae30\ub2a5\uc5d0 \ub300\ud55c \uac1c\uc694 \u2014 The Databricks Blog\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\ubb34\ub8cc \uc2dc\ud5d8\ud310\uc0ac\uc6a9\ud574 \ubcf4\uae30\ucee4\ubba4\ub2c8\ud2f0 \uac00\uc785\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/fr\/p\/whitepaper\/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025","text":"La vision des CIO pour 2025\u00a0: combler le foss\u00e9 entre BI et IA \u2013 DatabricksRapportLa vision des CIO pour 2025Combler le foss\u00e9 entre BI et IAUne \u00e9tude mondiale men\u00e9e aupr\u00e8s des CIO sur l'adoption de l'IA ax\u00e9e sur la valeur commercialeD\u00e9couvrez comment les plus grandes entreprises et organisations rel\u00e8vent leurs d\u00e9fis de donn\u00e9es les plus ardus afin de ma\u00eetriser l'IA. Dans le nouveau rapport de recherche du MIT Technology Review, vous d\u00e9couvrirez les perspectives de plus de 600\u00a0CIO issus de 18\u00a0pays et 14\u00a0industries.Comment les CIO hi\u00e9rarchisent-ils l'adoption de l'IA\u00a0? Comment investissent-ils dans l\u2019am\u00e9lioration de leur strat\u00e9gie de donn\u00e9es\u00a0?Profitez des \u00e9clairages de dirigeants de Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global, Marks & Spencer et d'autres grandes entreprises.D\u00e9couvrez les principales conclusions des t\u00e9moignages des CIO\u00a0:72\u00a0% affirment que les donn\u00e9es repr\u00e9sentent le plus grand d\u00e9fi pour l'IA, et 68\u00a0% pensent qu'il est crucial d'unifier leur plateforme de donn\u00e9es pour l'analytique et l'IA.Les r\u00e9pondants sont d\u00e9j\u00e0 94\u00a0% \u00e0 utiliser l'IA dans les fonctions m\u00e9tier, et plus de la moiti\u00e9 pensent qu'elle sera largement r\u00e9pandue en 2025.Le multi-cloud est essentiel pour 72\u00a0% des personnes interrog\u00e9es, qui sont nombreuses \u00e0 recourir aux standards ouverts pour conserver une flexibilit\u00e9 strat\u00e9giqueObtenir le rapportProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ellie-hajarian\/#","text":"Ellie Hajarian - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEllie HajarianSnr IT Manager at TD BankBack to speakersDriven Information Technologist with a strategic mindset in delivering superior solutions. A passionate problem solver who thrives in challenging, fast-paced IT organizations for over 20 years demonstrating solid knowledge in delivery excellence, risk management and emerging technologies. \nAn advocate for diversity and inclusion, leading the 'Women In Leadership' Committee and a member of 'Girls in STEM' committee at my current workplace.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sreekanth-ratakonda\/#","text":"Sreekanth Ratakonda - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSreekanth RatakondaPrincipal Solutions Architect at LabcorpBack to speakersSreekanth Ratakonda is a principal solutions architect at Labcorp, where he is responsible for building robust Data and Analytics platform and Data products. He has over 15 years of experience in solving complex business challenges in various functional domains utilizing several technologies and frameworks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/company\/partners\/consulting-and-si","text":"Databricks \ucee8\uc124\ud305 \ud30c\ud2b8\ub108 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 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\ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDatabricks \ucee8\uc124\ud305 \ud30c\ud2b8\ub108\uc804 \uc138\uacc4 Databricks \ud30c\ud2b8\ub108\uc640 \uc5f0\uacb0\ud558\uace0 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \uad6c\ucd95, \ubc30\ud3ec\ud558\uac70\ub098 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ub9c8\uc774\uadf8\ub808\uc774\uc158\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \ubc1b\uc73c\uc138\uc694.Databricks \ucee8\uc124\ud305 \ud30c\ud2b8\ub108\ub294 \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1, \ud611\uc5c5\ud615 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4, \uc804\uccb4 \uc218\uba85 \uc8fc\uae30 \uba38\uc2e0 \ub7ec\ub2dd\uacfc \ube44\uc988\ub2c8\uc2a4 \ubd84\uc11d \uc774\ub2c8\uc154\ud2f0\ube0c\ub97c \uad6c\ud604, \ud655\uc7a5\ud558\ub3c4\ub85d \ub3d5\ub294 \ub370 \uc720\ub9ac\ud55c \ub3c5\ubcf4\uc801\uc778 \uc5ed\ub7c9\uc744 \uac00\uc9c4 \uc804\ubb38\uac00\uc785\ub2c8\ub2e4.\n\uae30\uc220, \uc0b0\uc5c5 \ubc0f \uc0ac\uc6a9 \uc0ac\ub840\uc5d0 \ub300\ud55c \uc804\ubb38 \uc9c0\uc2dd\uc744 \ud65c\uc6a9\ud558\uc5ec \uace0\uac1d\uc774 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc\uc744 \ucd5c\ub300\ub85c \ud65c\uc6a9\ud560 \uc218 \uc788\ub3c4\ub85d \ub3d5\uc2b5\ub2c8\ub2e4. \ube44\uc988\ub2c8\uc2a4\uc5d0 \uac00\uc7a5 \uc54c\ub9de\uc740 \ub370\uc774\ud130 \ubcc0\ud658 \uc804\ub7b5 \uc124\uacc4, \ub370\uc774\ud130 \ud604\ub300\ud654 \ubc0f \ub9c8\uc774\uadf8\ub808\uc774\uc158, \ub370\uc774\ud130 \uad00\ub9ac \ubc0f \uac70\ubc84\ub10c\uc2a4 \ub4f1\uc758 \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.Loading...\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/officehours?utm_source=databricks&utm_medium=Website&utm_campaign=7013f000000LkdAAAS&utm_content=learn-page","text":"Databricks Office Hours | DatabricksWebinarDatabricks Office HoursProviding answers to your questionsDatabricks customer-exclusive Office Hours connect you directly with experts through a LIVE Q&A where you can ask all your Databricks questions.Register for one of our upcoming events with the form on the right, and join us to:Learn the best strategies to apply Databricks to your use caseTroubleshoot your technical questionsMaster tips and tricks to maximize your usage of our platformQuestions are answered on a rolling basis, so come and go as you please, or stay for the whole event to hear what questions other users have.Who can attend\nThis event is exclusive to Databricks customers seeking platform-related support. For account-related questions, please contact your Databricks representative.Register nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/satish-garla\/#","text":"Satish Garla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSatish GarlaSr Solutions Architect at DatabricksBack to speakersSatish has a distinguished background in cloud modernization, data management, data science and financial risk management. He started his career implementing enterprise risk solutions using SAS. Satish leveraged open source tools and dotData technology to implement automated Feature Engineering and AutoML. Currently Satish works as a Sr Solutions Architect at Databricks helping enterprises with cloud and Lakehouse adoption using open source technologies such as Apache Spark, Delta and MLFlow.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/startups","text":"Databricks for Startups | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBuild your startup on DatabricksThe most powerful platform for data and AIBuild on the Databricks Lakehouse to address all your data, analytics and AI on one platform. Accelerate speed to product while Databricks manages your data infrastructure. Prepare your product for growth with cost-efficient scalability and performance. Maintain flexibility with open source and multicloud options.Databricks for Startups helps you get up and running quickly. Build data-driven applications on the lakehouse \u2014 the data platform that scales to all your data needs, from zero to IPO and beyond.Free credits\nGet easy access to the Databricks Lakehouse Platform with up to $21K in free creditsExpert advice\nReceive advice from experts and the community to help build your productGo to market\nReach more customers with access to Databricks marketing, events and customersBuilt on DatabricksReady to build?If you\u2019re a startup building data-driven applications and have raised VC funding, we want to hear from you.\nApply nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/rekha-bachwani","text":"Rekha Bachwani - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRekha BachwaniEngineering Director, ML Engineering at The Walt Disney CompanyBack to speakersRekha Bachwani is an Engineering Director at Disney Streaming. She leads the ML Engineering team that drives the strategy for ML infrastructure, platform and applications for the services and engineering organization. She has a PhD in Computer Science from Rutgers University, and worked at Netflix and Intel Labs prior to joining Disney.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/company\/partners\/cloud-partners","text":"Databricks Cloud Service Provider Partner | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPartner cloud di DatabricksDatabricks Lakehouse gira su tutti i cloud pubblici, integrandosi strettamente con i servizi di sicurezza, calcolo, storage, analisi e AI offerti in maniera nativa dai provider cloud. Le aziende possono cos\u00ec contare sull'agilit\u00e0 necessaria per sfruttare il proprio fornitore di servizi cloud come e quando vogliono.Azure Databricks \u00e8 un servizio sviluppato congiuntamente da Databricks e Microsoft. Per cominciare basta un clic nel portale Azure per integrare il sistema in maniera nativa con i servizi di sicurezza e gestione dei dati di Azure.Maggiori informazioniDatabricks su AWS consente di conservare e gestire tutti i dati S3 su una semplice piattaforma lakehouse aperta che unisce il meglio di data warehouse e data lake per unificare tutti i carichi di lavoro di analisi e AI.Maggiori informazioniDatabricks su Google Cloud porta la piattaforma lakehouse aperta sul cloud aperto, per unificare data engineering, data science e analisi, con una stretta integrazione con Google Cloud Storage, BigQuery e la piattaforma AI di Google Cloud.Maggiori informazioniRegioni cloud\u25cfAzure\u00a0\u00a0\u25cfAWS\u00a0\u00a0\u25cfGoogle\u00a0\u25cfAlibabaProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/kasey-uhlenhuth\/#","text":"Kasey Uhlenhuth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKasey UhlenhuthStaff Product Manager at DatabricksBack to speakersKasey Uhlenhuth is a product manager on the machine learning platform team at Databricks. Before Databricks, she worked on the Visual Studio and C# team at Microsoft building developer productivity tools. Kasey holds an MBA from the Stanford Graduate School of Business and a BA in Computer Science from Harvard University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/macgregor-winegard","text":"MacGregor Winegard - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMacGregor WinegardAssociate Data Engineer at KPMGBack to speakersMacGregor Winegard works alongside clients to develop cloud applications that extract, load and transform data for business use cases. He has experience utilizing Databricks in fields such as ESG reporting, IoT data collection, and energy data processing. MacGregor holds a Bachelor of Science from St. John Fisher University in Mathematics and Economics. As a student, MacGregor pursued research in several areas, including image processing, baseball statistics, and planar discrete dynamical systems. MacGregor currently is an associate Data Engineer at KPMG, and Databricks certified Data Engineer Associate.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/matthew-karasick\/#","text":"Matthew Karasick - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew KarasickChief Product Officer at HabuBack to speakersMatt is passionate about finding ways to use data to achieve the wins that data-powered technology can create between companies and consumers.\nHe has spent his career helping companies do more with data. He has held product leadership positions at DoubleClick, Trilogy, Acerno, Akamai, and most recently at Indeed. After working closely together with Matt Kilmartin at Akamai, Matt (Karasick) worked with the Krux team as a consultant, where he helped create Krux for Marketers.\nMatt believes that, when done correctly and with sustainable mutual value as the measuring stick, interests between consumers and companies are always aligned.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/marcel-kramer\/#","text":"Marcel Kramer - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarcel KramerHead of Data Engineering at ABN AMRO Bank N.VBack to speakersAccountable for ~50 DevOps teams with 500+ IT engineers delivering all bank wide data capabilities (DQ monitoring, data distribution, data privacy and security, data governance, advanced analytics, process mining and MLE platforms). Broad tech stack ranging from traditional to latest cutting edge technologies. Defined together with CDO rigorous data strategy, to make ABN AMRO a data driven company. Actively involved with AA ventures in data technology investments.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/discover\/data-brew","text":"Data Brew by DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData Brew: Let\u2019s talk dataWelcome to Data Brew by Databricks with Denny and Brooke!\n\u00a0\nIn this series, we explore various topics in the data and AI community and interview experts in data engineering and data science. So join us with your morning brew in hand and get ready to dive deep into data and AI.\nSee episodesMeet the hostsWatch or listen on your favorite platformAbout the hosts\u00a0Brooke WenigDirector of the Machine Learning PracticeDATABRICKSBrooke Wenig is a Director of the Machine Learning Practice at Databricks. She leads a team of data scientists who develop large-scale machine learning pipelines for customers, as well as teach courses on distributed machine learning best practices. Previously, she was a Principal Data Science Consultant at Databricks. She received an M.S. in Computer Science from UCLA with a focus on distributed machine learning. She speaks Mandarin Chinese fluently and enjoys cycling.\n\u00a0\n\nDenny LeeDeveloper AdvocateDATABRICKSDenny Lee is a Developer Advocate at Databricks. He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premises and cloud environments. He has a Master\u2019s of Biomedical Informatics from Oregon Health and Sciences University and has architected and implemented powerful data solutions for enterprise healthcare customers. His current technical focuses include distributed systems, Apache Spark, deep learning, machine learning and genomics.\n\u00a0\n\nBrooke and Denny are two of the co-authors of\u00a0Learning Spark, 2nd edition.Contact the Data Brew team on Twitter:\u00a0@databrew_db\u00a0or on\u00a0LinkedInProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/david-tempelman\/#","text":"David Tempelman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid TempelmanResident Solutions Architect at DatabricksBack to speakersDavid is a Resident Solutions Architect at Databricks and helps customers to get most value out of their data. He has several years of experience in the Big Data and Machine Learning domain across different industries including manufacturing, retail & finance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/solutions\/accelerators","text":"Acceleratori Databricks - Generare valore per dati e AI pi\u00f9 velocemente - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWSoluzioni per settori specificiOttieni con dati e AI i risultati pi\u00f9 rilevanti... pi\u00f9 velocementeComincia la prova gratuitaAcceleratori DatabricksRisparmia molte ore nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo con gli Acceleratori Databricks. Le nostre guide specifiche \u2014 notebook con funzionalit\u00e0 complete e best practice \u2014 velocizzano l'ottenimento di risultati per i casi d'uso pi\u00f9 comuni e di maggior impatto. Dall'idea al progetto concettuale (Proof of Concept) in sole due settimane.\n\u00a0\nComincia a usare gli Acceleratori con la prova gratuita di Databricks o il tuo account attivo.\n\u00a0\nComincia la prova gratuita oggi stessoScorri l'elenco degli AcceleratorisearchHide filtersIndustrySortDatabricksRimozione automatica di dati sanitari protetti (PHI)featurednewDatabricksPrevisione granulare della domandafeatured\ud83d\udd25DatabricksIndividuazione di comportamenti tossici nei videogiochifeaturedDatabricksDisponibilit\u00e0 a scaffalefeaturedDatabricksAbbinamento di elementi alla rinfusaDatabricksAggiustamento del rischio MedicareDatabricksAnalisi del punto vendita in tempo realenewDatabricksAnalisi delle prestazioni ESG\ud83d\udd25DatabricksAnalisi di sopravvivenza e valore lungo il ciclo di vitaDatabricksAnalisi geospaziale per individuare le frodiDatabricksAnalisi immagini digitali di patologieDatabricksAntiriciclaggioDatabricksAstrazione di dati del mondo reale per oncologiaDatabricksAttribuzione multitouchDatabricksClassificazione dei commerciantiDatabricksCostruzione della coorte con i grafici della conoscenzaSplunkCyber Analytics (connettore Splunk)DatabricksDeterminanti sociali della saluteDatabricksEfficacia totale dell'impianto (OEE)DatabricksEvidenze nel mondo realeDatabricksFondamenti di computer visionDatabricksGemelli digitaliDatabricksGenerazione scalabile di percorsiDatabricksGestione del rischioDatabricksGestione della ritenzione (fidelizzazione)DatabricksIndividuare reazioni avverse ai farmacinewDatabricksInteroperabilit\u00e0 FHIR con dbigniteDatabricksInteroperabilit\u00e0 HL7v2 con SmolderDatabricksManutenzione Predittiva (IoT)DatabricksMotore di raccomandazioneDatabricksOttimizzazione delle offerte in tempo realeDatabricksPiattaforma di investimenti modernaDatabricksPicking ottimizzato degli ordiniDatabricksPrevenzione delle frodi finanziarie in tempo realeDatabricksPrevisioni di disdette degli abbonatiDatabricksPrevisioni di vendita e attribuzione delle inserzioni pubblicitarie\ud83d\udd25DatabricksPunteggio di propensionenewDatabricksQualit\u00e0 di esperienza videoDatabricksR&D Ottimizzazione con i grafi della conoscenzanewDatabricksReporting normativoDatabricksRilevamento di minacce con DNSDatabricksRischio reputazionaleDatabricksRisoluzione dell'entit\u00e0 clienteDatabricksScorte di SicurezzaDatabricksSegmentazione clientiDatabricksStudi di associazione genomicaDatabricksTrasparenza dei prezzinewDatabricksValore lungo il ciclo di vita del cliente\ud83d\udd25Domande frequentiQuanto costano gli Acceleratori Databricks?Gli Acceleratori Databricks vengono messi a disposizione di tutti i clienti di Databricks gratuitamente.Devo essere cliente di Databricks per utilizzare un Acceleratore?Gli Acceleratori possono essere implementati attivando una prova gratuita di Databricks o utilizzando un account attivo.Che cosa posso fare con un Acceleratore?Gli Acceleratori Databricks sono pensati per far risparmiare ore nelle attivit\u00e0 di scoperta, progettazione, sviluppo e collaudo. Il nostro obiettivo \u00e8 approntare in tempi rapidissimi casi d'uso di dati e AI fornendo le giuste risorse (notebook, pattern consolidati e best practice). Dall'idea al progetto concettuale (Proof of Concept) in sole due settimane.Scopri come clienti reali usano DatabricksLeggi le storie dei clientiProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/jp\/dataaisummit\/?itm_data=menu-learn-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/jp\/learn\/labs","text":"Databricks Labs Projects | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI\/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources \u2192Documentation \u2192Blog \u2192TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark\u2122. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources \u2192Documentation \u2192Webinar \u2192MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark\u2122\ufe0f. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources \u2192Documentation \u2192Blog \u2192Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources \u2192Learn more \u2192SmolderSmolder provides an Apache Spark\u2122 SQL data source for loading EHR data from\u00a0HL7v2\u00a0message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources \u2192Learn more \u2192GeoscanApache Spark ML Estimator for density-based spatial clustering based on\u00a0Hexagonal Hierarchical Spatial Indices.Github Sources \u2192Learn more \u2192MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more:\u00a0AWS\u00a0|\u00a0AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated\/synthetic data sets for test, POCs, and other usesGithub Sources \u2192Learn more \u2192DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources \u2192Learn more \u2192DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources \u2192Learn more \u2192Please note that all projects in the\u00a0https:\/\/github.com\/databrickslabs\u00a0account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/it","text":"L'azienda dell'architettura Data Lakehouse e AI - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWLa migliore data warehouse \u00e8 un lakehouseUnifica tutti i dati, le analisi e l'AI su un'unica piattaformaComincia gratisMaggiori informazioniRiduci i costi e accelera l'innovazione sulla piattaforma lakehouseMaggiori informazioniUnificataUn'unica piattaforma per tutti i tuoi dati, gestita in modo omogeneo e disponibile per tutte le attivit\u00e0 di analisi e AIApertaBasata su standard aperti e integrata con tutti i cloud per operare direttamente all'interno del tuo moderno stack di datiScalabileScalabilit\u00e0 efficiente per ogni carico di lavoro, dalle semplici pipeline di dati ai modelli linguistici di grandi dimensioni (LLM)Organizzazioni data-driven che hanno scelto il lakehouse\nVedi tutti i clienti\nIl lakehouse unifica i team di gestione dei datiGestione e ingegneria dei datiSnellire l'acquisizione e la gestione dei datiGrazie a processi ETL automatizzati e affidabili, alla condivisione aperta e sicura dei dati e a prestazioni velocissime, Delta Lake trasforma il data lake nella destinazione finale di tutti i dati strutturati, semi-strutturati e non strutturati.Maggiori informazioni Guarda la demoData warehouseRicavare nuove informazioni dai dati pi\u00f9 completiPotendo accedere immediatamente ai dati pi\u00f9 aggiornati e completi e potendo contare sulla potenza di Databricks SQL (che offre un rapporto prezzo\/prestazioni fino a 12 volte migliore rispetto ai tradizionali data warehouse in cloud), analisti e data scientist possono ottenere nuove informazioni approfondite e dettagliate.Maggiori informazioni Guarda la demoData science e machine learningAccelerare il ML lungo tutto il ciclo di vitaIl lakehouse rappresenta le fondamenta di Databricks Machine Learning, una soluzione collaborativa nativa per la gestione dei dati, che abbraccia tutto il ciclo di vita del machine learning, dalla definizione delle funzionalit\u00e0 alla produzione. Insieme a pipeline di dati con qualit\u00e0 e prestazioni elevate, il lakehouse accelera il machine learning e la produttivit\u00e0 dei team.Maggiori informazioni Guarda la demoGovernance e condivisione dei datiUnifica la governance e la condivisione di dati, analisi e AIDatabricks mette a disposizione un modello comune di sicurezza e governance per tutte le risorse di dati, analisi e AI presenti nel lakehouse su qualsiasi cloud. Si possono cos\u00ec reperire e condividere dati su molteplici piattaforme, cloud o regioni geografiche, senza duplicazioni o vincoli, oltre a distribuire prodotti di dati attraverso un marketplace aperto.Maggiori informazioni Guarda la demoIl data warehouse \u00e8 ormai superato. Scopri perch\u00e9 il lakehouse \u00e8 diventato la nuova architettura per dati e AI.Scopri il Lakehouse\u00c8 disponibile il catalogo delle sessioniVieni a San Francisco per scoprire l'ecosistema lakehouse e i progressi delle tecnologie open-sourceScopri le sessioniScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivo.Richiedi il report600 CIO. 14 settori industriali. 18 Paesi.Questo nuovo studio conferma che la strategia di gestione dei dati \u00e8 fondamentale per il successo dell'AI. Scopri il punto di vista di altri CIO.Richiedi il reportLettura preziosa per tecnici di Machine Learning e data scientist che cercano strumenti migliori per le MLOpsRichiedi l'eBookPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/kr\/product\/delta-sharing","text":"Delta Sharing | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\u0000\u0000\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 \uc5b4\ub5bb\uac8c \ubd80\ud569\ud558\ub294\uc9c0 \uc774\ud574\ud558\ub824\uba74 \ucc38\uc11d\ud558\uc2ed\uc2dc\uc624.\n\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\uc194\ub8e8\uc158\uc0b0\uc5c5\ubcc4 \uc194\ub8e8\uc158\uae08\uc735 \uc11c\ube44\uc2a4\uc758\ub8cc \uc11c\ube44\uc2a4 \ubc0f \uc0dd\uba85 \uacf5\ud559\uc81c\uc870\ucee4\ubba4\ub2c8\ucf00\uc774\uc158, \ubbf8\ub514\uc5b4 \ubc0f \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8\uacf5\uacf5 \ubd80\ubb38\ub9ac\ud14c\uc77c\ubaa8\ub4e0 \uc0b0\uc5c5 \ubcf4\uae30\uc0ac\uc6a9 \uc0ac\ub840\ubcc4 \uc194\ub8e8\uc158\uc194\ub8e8\uc158 \uc561\uc140\ub7ec\ub808\uc774\ud130\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ub514\uc9c0\ud138 \ub124\uc774\ud2f0\ube0c \ube44\uc988\ub2c8\uc2a4\ub370\uc774\ud130 \ud50c\ub7ab\ud3fc \ub9c8\uc774\uadf8\ub808\uc774\uc1585\uc6d4 9\uc77c | \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\u00a0\n\uc81c\uc870\uc5c5\uc744 \uc704\ud55c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc0b4\ud3b4\ubcf4\uae30\n\ucf54\ub2dd\uc774 \uc218\ub3d9 \uac80\uc0ac\ub97c \ucd5c\uc18c\ud654\ud558\uace0 \uc6b4\uc1a1 \ube44\uc6a9\uc744 \uc808\uac10\ud558\uba70 \uace0\uac1d \ub9cc\uc871\ub3c4\ub97c \ub192\uc774\ub294 \uc911\uc694\ud55c \uacb0\uc815\uc744 \ub0b4\ub9ac\ub294 \ubc29\ubc95\uc744 \ub4e4\uc5b4\ubcf4\uc2ed\uc2dc\uc624.\uc9c0\uae08 \ub4f1\ub85d\ud558\uc138\uc694\ud559\uc2b5\uad00\ub828 \ubb38\uc11c\uad50\uc721 \ubc0f \uc778\uc99d\ub370\ubaa8\ub9ac\uc18c\uc2a4\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0University Alliance\uc774\ubca4\ud2b8Data + AI Summit\ube14\ub85c\uadf8LabsBeacons2023\ub144 6\uc6d4 26\uc77c~29\uc77c\n\uc9c1\uc811 \ucc38\uc11d\ud558\uac70\ub098 \ud0a4\ub178\ud2b8 \ub77c\uc774\ube0c\uc2a4\ud2b8\ub9bc\uc744 \uc2dc\uccad\ud558\uc138\uc694.\uc9c0\uae08 \ub4f1\ub85d\ud558\uae30\uace0\uac1d\ud30c\ud2b8\ub108\ud074\ub77c\uc6b0\ub4dc \ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOWDelta Sharing\ub370\uc774\ud130 \uc790\uc0b0\uc744 \uc548\uc804\ud558\uac8c \uacf5\uc720\ud558\uae30 \uc704\ud55c \uac1c\ubc29\uc801 \ud45c\uc900\uc2dc\uc791\ud558\uae30\ub370\ubaa8 \ubcf4\uae30Databricks Delta Sharing\uc740 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc5d0\uc11c \ubaa8\ub4e0 \ucef4\ud4e8\ud305 \ud50c\ub7ab\ud3fc\uc73c\ub85c \uc548\uc804\ud558\uac8c \ub77c\uc774\ube0c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\ub294 \uc624\ud508 \uc194\ub8e8\uc158\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.\uc8fc\uc694 \uc7a5\uc810\uac1c\ubc29\uc801\uc774 \ud50c\ub7ab\ud3fc \uac04 \uacf5\uc720\uacf5\uae09\uc5c5\uccb4 \uc885\uc18d \ud6a8\uacfc\ub97c \ud53c\ud558\uace0, Delta Lake\uc640 Apache Parquet \ud615\uc2dd\uc73c\ub85c \ubaa8\ub4e0 \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\uc5d0 \uae30\uc874 \ub370\uc774\ud130\ub97c \uac04\ud3b8\ud558\uac8c \uacf5\uc720\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ubcf5\uc81c \uc5c6\uc774 \ub77c\uc774\ube0c \ub370\uc774\ud130 \uacf5\uc720\ub77c\uc774\ube0c \ub370\uc774\ud130\ub97c \ubcf5\uc81c\ud558\uac70\ub098 \ub2e4\ub978 \uc2dc\uc2a4\ud15c\uc5d0 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\ud074\ub9b0\ub8f8\ub370\uc774\ud130\ub97c \uc548\uc804\ud558\uac8c \ubcf4\ud638\ud558\uba74\uc11c\ub3c4 \uc548\uc804\ud55c \ud638\uc2a4\ud305 \ud658\uacbd\uc744 \ud1b5\ud574 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \uace0\uac1d \ubc0f \ud30c\ud2b8\ub108\uc640 \ud611\uc5c5\ud558\u0000\uc138\uc694.\uc791\ub3d9 \ubc29\uc2ddDatabricks \ud50c\ub7ab\ud3fc\uacfc \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569Unity Catalog\uc640 \uae30\ubcf8\uc801\uc73c\ub85c \ud1b5\ud569\ub418\uae30 \ub54c\ubb38\uc5d0 \uc804\uc0ac\uc801\uc73c\ub85c \uacf5\uc720 \ub370\uc774\ud130\ub97c \uc911\uc559\uc5d0\uc11c \uad00\ub9ac\ud558\uace0 \uac10\uc0ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub807\uac8c \ud558\uba74 \uacf5\uae09\uc790, \ud611\ub825\uc5c5\uccb4\uc640 \uc2e0\ub8b0\ub97c \ubc14\ud0d5\uc73c\ub85c \ub370\uc774\ud130 \uc790\uc0b0\uc744 \uacf5\uc720\ud560 \uc218 \uc788\uc5b4 \ube44\uc988\ub2c8\uc2a4 \uc870\uc728\uc5d0 \ub3c4\uc6c0\uc774 \ub418\uace0, \ub3d9\uc2dc\uc5d0 \ubcf4\uc548\uacfc \uaddc\uc815 \uc900\uc218 \uc694\uad6c \uc0ac\ud56d\uc5d0\ub3c4 \ubd80\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uacf5\uc720\ub97c \uac04\ud3b8\ud558\uac8c \uad00\ub9ac\uc644\uc804\ud55c CLI \ubc0f Terraform \uc9c0\uc6d0\uc740 \ubb3c\ub860\uc774\uace0, \uac04\ub2e8\ud558\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 UI, SQL \uba85\ub839 \ub610\ub294 REST API\ub97c \ud65c\uc6a9\ud558\uc5ec \uacf5\uae09\uc790, \uc218\uc2e0\uc790 \ubc0f \uacf5\uc720 \uc0dd\uc131 \ubc0f \uad00\ub9ac\uc624\ud508 \ub9c8\ucf13\ud50c\ub808\uc774\uc2a4\ub97c \ud1b5\ud574 \ub370\uc774\ud130 \uc81c\ud488\uc744 \ubc1c\uacac\ud558\uace0 \uc561\uc138\uc2a4Databricks \ud50c\ub7ab\ud3fc\uc774 \uc544\ub2c8\ub354\ub77c\ub3c4 \uc5b4\ub514\uc11c\ub098 \ub370\uc774\ud130 \uc138\ud2b8, \uba38\uc2e0 \ub7ec\ub2dd \ubaa8\ub378, \ub300\uc2dc\ubcf4\ub4dc, \ub178\ud2b8\ubd81 \ub4f1\uc758 \ub370\uc774\ud130 \uc81c\ud488\uc744 \uac04\ud3b8\ud558\uac8c \ubc1c\uacac, \ud3c9\uac00\ud558\uace0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4\ub97c \uc548\uc804\ud558\uac8c \ubcf4\ud638\ud558\ub294 \ub370\uc774\ud130 \ud074\ub9b0\ub8f8\uac1c\uc778 \uc815\ubcf4\uac00 \uc548\uc804\ud558\uac8c \ubcf4\ud638\ub418\ub294 \ud658\uacbd\uc5d0\uc11c \uc5b4\ub5a4 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c\ub098 \uace0\uac1d \ubc0f \ud30c\ud2b8\ub108\uc640 \ud611\uc5c5 \ub370\uc774\ud130 \ubcf5\uc81c \uc5c6\uc774 \uc790\uc2e0\uc758 \ub370\uc774\ud130 \ub808\uc774\ud06c\uc5d0\uc11c \uc548\uc804\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud569\ub2c8\ub2e4. \ud611\uc5c5 \ub300\uc0c1\uc774 \uc120\ud638\ud558\ub294 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ub9cc\ub098\uc11c SQL, R, Scala, Java, Python \ub4f1\uc744 \ube44\ub86f\ud55c \ubaa8\ub4e0 \uc5b8\uc5b4\ub85c \ubcf5\uc7a1\ud55c \uc5f0\uc0b0\uacfc \uc6cc\ud06c\ub85c\ub4dc\ub97c \uc720\uc5f0\ud558\uac8c \uc2e4\ud589\ud558\uc138\uc694. \uc0ac\uc804 \uc815\uc758\ub41c \ud15c\ud50c\ub9bf, \ub178\ud2b8\ubd81, \ub300\uc2dc\ubcf4\ub4dc\ub97c \uc0ac\uc6a9\ud55c \uacf5\ud1b5\uc801\uc778 \uc0ac\uc6a9 \uc0ac\ub840\ub97c \ud1b5\ud574 \ud611\uc5c5 \ub300\uc0c1\uc744 \uc548\ub0b4\ud558\uace0 \ub354\uc6b1 \ube60\ub974\uac8c \uc778\uc0ac\uc774\ud2b8\ub97c \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\uc0ac\uc6a9 \uc0ac\ub840\uae30\uc5c5 \ub0b4 \uacf5\uc720 \uacc4\ud1b5Deltah Sharing\uc73c\ub85c \ub370\uc774\ud130 \uba54\uc2dc\ub97c \uad6c\ucd95\ud558\uba74 \ub370\uc774\ud130\ub97c \ubcf5\uc0ac\ud558\uac70\ub098 \ubcf5\uc81c\ud558\uc9c0 \uc54a\uace0 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\ub098 \ub9ac\uc804\uc5d0\uc11c \uac01 \uc0ac\uc5c5\ubd80\uc640 \uc790\ud68c\uc0ac\uc5d0 \uc548\uc804\ud558\uac8c \ub370\uc774\ud130\ub97c \uacf5\uc720\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.B2B \uacf5\uc720\ub370\uc774\ud130 \uc218\uc775\ud654\uace0\uac1d\u201cDelta Sharing \ub355\ubd84\uc5d0 \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \ub370\uc774\ud130 \uc804\uc1a1 \ud504\ub85c\uc138\uc2a4\ub97c \uac04\uc18c\ud654\ud560 \uc218 \uc788\uc5c8\uc2b5\ub2c8\ub2e4. \uc6b0\ub9ac \uace0\uac1d\ub4e4\ub3c4 \uc790\uc2e0\uc758 \ucef4\ud4e8\ud305 \ud658\uacbd\uc5d0\uc11c \ud1b5\ud569 \uc791\uc5c5\uc744 \uac70\uc758 \ud558\uc9c0 \uc54a\uac70\ub098 \uc804\ud600 \ud558\uc9c0 \uc54a\uace0 \uac13 \ud050\ub808\uc774\uc158\ud55c \ub370\uc774\ud130\ub97c \uc77d\uc744 \uc218 \uc788\uace0, \uc800\ud76c\ub3c4 \uace0\uc720\ud55c \uace0\ud488\uc9c8 \ub370\uc774\ud130 \uc81c\ud488\uc73c\ub85c \uad6c\uc131\ub41c \uce74\ud0c8\ub85c\uadf8\ub97c \uc9c0\uc18d\uc801\uc73c\ub85c \ud655\uc7a5\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\u201d\u2014 William Dague, Alternative Data \ucc45\uc784\uc790\u201c\uc800\ud76c\ub294 \ub370\uc774\ud130 \uae30\uc5c5\uc774\uae30 \ub54c\ubb38\uc5d0 \uace0\uac1d\uc5d0\uac8c \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc81c\uacf5\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. Delta Sharing\uc744 \uc81c\uacf5\ud558\ub294 Databricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fc \ub355\ubd84\uc5d0 \uc774 \ud504\ub85c\uc138\uc2a4\uac00 \uac04\uc18c\ud654\ub418\u0000\uc5b4, \ud074\ub77c\uc6b0\ub4dc\ub098 \ud50c\ub7ab\ud3fc\uc5d0\uc11c \ud6e8\uc52c \uad11\ubc94\uc704\ud55c \uc0ac\uc6a9\uc790 \uae30\ubc18\uc5d0 \uc548\uc804\ud558\uac8c \ub2ff\uc744 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\u201d\u2014 Felix Cheung, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ubd80\uc0ac\uc7a5\u201cPumpjack Dataworks\ub294 Databricks\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 Delta Sharing\uc758 \uac15\ub825\ud55c \uae30\ub2a5\uc744 \ud65c\uc6a9\ud558\uace0 \ub098\uc11c \uc628\ubcf4\ub529 \uacbd\ud5d8\uc5d0 \uac78\ub9ac\ub294 \uc2dc\uac04\uc744 \ub2e8\ucd95\ub418\uc5c8\uace0, \ub370\uc774\ud130\ub97c \ub0b4\ubcf4\ub0b4\uace0 \uac00\uc838\uc640 \ub9ac\ubaa8\ub378\ub9c1\ud560 \ud544\uc694\uc131\uc774 \uc0ac\ub77c\uc838 \uace0\uac1d\uc5d0\uac8c \uc989\uac01\uc801\uc73c\ub85c \uac00\uce58\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uc800\ud76c \uace0\uac1d\uacfc \ud30c\ud2b8\ub108\ub294 \ub354\uc6b1 \ube60\ub974\uac8c \uacb0\uacfc\ub97c \uc5bb\uc5c8\uace0, \uc601\uc5c5 \uae30\ud68c\uac00 \ucee4\uc84c\uc2b5\ub2c8\ub2e4.\u201d\u2014 Corey Zwart, \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \ucc45\uc784\uc790\u201cDelta Sharing\uc744 \uc0ac\uc6a9\ud558\uace0 \ub098\uc11c \uc6b0\ub9ac \uace0\uac1d\uc740 \ud050\ub808\uc774\uc158\ub41c \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uac70\uc758 \uc989\uc2dc \uc561\uc138\uc2a4\ud558\uace0, \uc6d0\ud558\ub294 \ubd84\uc11d \ub3c4\uad6c\uc640 \ud1b5\ud569\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4. \uace0\uac1d\uacfc\uc758 \ub300\ud654\ub294 \uac00\uce58\uac00 \ub0ae\uc740 \uae30\uc220\uc801\uc778 \ubc18\ubcf5\uc801 \uc218\uc9d1\uc5d0 \ub300\ud55c \ub0b4\uc6a9\uc5d0\uc11c \uac00\uce58\uac00 \ub192\uc740 \ubd84\uc11d\uc801 \ub17c\uc758\ub85c \ubc14\ub00c\uc5c8\uace0, \uc774\ub97c \ud1b5\ud574 \uc131\uacf5\uc801\uc778 \uace0\uac1d \uacbd\ud5d8\uc744 \uc774\ub04c\uc5b4\ub0c8\uc2b5\ub2c8\ub2e4. \uace0\uac1d \uad00\uacc4\uac00 \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c, Delta Sharing\uc744 \ud1b5\ud574 \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc6d0\ud65c\ud558\uac8c \uc81c\uacf5\ud558\uace0 \uae30\uc874 \ub370\uc774\ud130 \uc138\ud2b8\ub294 \uac31\uc2e0\ud558\uc600\uace0, \uc774\ub97c \ud1b5\ud574 \uace0\uac1d\ub3c4 \uc5c5\uacc4\uc758 \uc8fc\uc694 \ud2b8\ub80c\ub4dc\ub97c \uc0b4\ud544 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.\u201d\u2014 Anup Segu, \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1 \uae30\uc220 \ucc45\uc784\uc790\uac1c\ubc29\ud615 \uc5d0\ucf54\uc2dc\uc2a4\ud15c\uc0ac\uc6a9\ud558\uae30 \uac04\ud3b8\ud55c SQL, Python, BI \ub3c4\uad6c\uc5d0\uc11c \uacf5\uae09\uc5c5\uccb4\uac00 \uc9c1\uc811 \uc81c\uacf5\ud558\ub294 \ucd5c\uc2e0 \uacf5\uac1c \ubc84\uc804\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\ub9ac\uc18c\uc2a4\ud0a4\ub178\ud2b8 \ubc0f \uc6e8\ube44\ub098[\ud0a4\ub178\ud2b8]Data + AI Summit 2022\uc5d0\uc11c \ubc1c\ud45c\ub41c \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4 \ubc0f \uacf5\uc720[\uc628\ub514\ub9e8\ub4dc \uc6e8\ube44\ub098]Delta Sharing\uc744 \uc0ac\uc6a9\ud55c \ube44\uc988\ub2c8\uc2a4 \uac00\uce58 \ucc3d\ucd9c \uac00\uc18d\ud654\ube14\ub85c\uadf8\ub378\ud0c0 \uacf5\uc720\uc758 \uc77c\ubc18 \uacf5\uae09 \ubc1c\ud45cDelta Sharing \uc18c\uac1c: \uc548\uc804\ud55c \ub370\uc774\ud130 \uacf5\uc720\ub97c \uc704\ud55c \uac1c\ubc29\uc801 \ud504\ub85c\ud1a0\ucf5cDelta Sharing\uc744 \uc0ac\uc6a9\ud55c \ubca0\uc2a4\ud2b8 \ub370\uc774\ud130 \uacf5\uc720 \uc0ac\uc6a9 \uc0ac\ub840 3\uac00\uc9c0\uc194\ub8e8\uc158 \uc2dc\ud2b8 \ubc0f eBook[eBook] \uc0c8\ub85c\uc6b4 Delta Sharing \uc194\ub8e8\uc158 \uc54c\uc544\u0000\ubcf4\uae30Delta Sharing: \uc548\uc804\ud55c \ub370\uc774\ud130 \uacf5\uc720\ub97c \uc704\ud55c \uac1c\ubc29\uc801 \ud45c\uc900\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc758 \ubd80\uc0c1 by \ube4c \uc778\ubaac, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4\uc758 \uc544\ubc84\uc9c0Databricks\ub97c \uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \u0000\uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sridhar-devarapalli","text":"Sridhar Devarapalli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSridhar DevarapalliSenior Director, Product Management at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/alain-briancon","text":"Alain Briancon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlain BrianconVP Data Science Profiles by Kantar at Kantar GroupBack to speakersAlain is Vice President of Data Science at Kantar Profiles decision. Alain is a serial entrepreneur and inventor with 77 patents. Over the last ten years, through various startups, Alain has applied data science to IoT, predicting appliance failures, political campaigns, food and diet management, customer engagement, upsell\/cross-sells, and now surveys. Alain graduated from the Massachusetts Institute of Technology with a Ph.D. in Electrical Engineering and Computer Science. Outside work, he enjoys writing movie scripts, collecting fountain pens, and enjoying family and dogs.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/scott-starbird\/#","text":"Scott Starbird - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott StarbirdGeneral Counsel, Public Affairs and Strategic Partnerships at DatabricksBack to speakersScott Starbird heads the Public Affairs function at Databricks, and has held various leadership positions within Databricks\u2019 Legal Department since early 2016. Scott is a member of the Board of Directors of BSA | The Software Alliance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/privacypolicy","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/christina-taylor-0","text":"Christina Taylor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChristina TaylorData Engineer at ToptalBack to speakersChristina is passionate about modern data platforms, mutil-cloud architecture, scalable data pipelines, as well as the latest and greatest in the open source community. An intensely curious lifelong learner and effective team leader, she builds data lakes with medallion structure that support advanced analytics, data science models, and customer facing applications. She also has a keen interest in interdisciplinary areas such as Cloud FinOps, DevOps and MLOps.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/kr\/company\/awards-and-recognition","text":"\uc218\uc0c1 \uc2e4\uc801 | DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uac00 \ucd5c\uc2e0 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0 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100\ub300 \uae30\uc5c5AI 50\ub300 \uae30\uc5c5\ubbf8\uad6d \ucd5c\uace0\uc758 \uc2a4\ud0c0\ud2b8\uc5c5 \uae30\uc5c5\uae30\uc220 \ubd84\uc57c\uc5d0\uc11c \uc77c\ud558\uae30 \uc88b\uc740 \ucd5c\uace0\uc758 \uc9c1\uc7a5\ubca0\uc774 \uc5d0\ub9ac\uc5b4\uc5d0\uc11c \uc77c\ud558\uae30 \uc88b\uc740 \ucd5c\uace0\uc758 \uc9c1\uc7a5\ubc00\ub808\ub2c8\uc5bc\uc744 \uc704\ud55c \ucd5c\uace0\uc758 \ub300\uae30\uc5c5CNBC\uac00 \uc120\uc815\ud55c 50\ub300 \ud601\uc2e0 \uae30\uc5c52022\ub144 \uc77c\ud558\uae30 \uc88b\uc740 \ucd5c\uace0\uc758 \uc9c1\uc7a5\ub354 \uc790\uc138\ud788 \uc54c\uc544\ubcfc \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?\uadc0\uc0ac\uc758 \ube44\uc988\ub2c8\uc2a4 \ubaa9\ud45c\ub97c \uc790\uc138\ud788 \uc54c\uc544\ubcf4\uace0 \uc11c\ube44\uc2a4 \ud300\uc5d0\uc11c \uadc0\uc0ac\uc758 \uc131\uacf5\uc744 \ub3c4\uc6b8 \ubc29\ubc95\uc744 \ud568\uaed8 \uc54c\uc544\ubcf4\uace0\uc790 \ud569\ub2c8\ub2e4.Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc 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\ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/p\/ebook\/data-lakehouse-is-your-next-data-warehouse","text":"Why the Data Lakehouse Is Your Next Data Warehouse | DatabrickseBookWhy the Data Lakehouse Is Your Next Data WarehouseUnder the hood of Databricks SQLMost organizations routinely operate their business with complex cloud data architectures that silo applications, users and data. As a result, there isn\u2019t a single source of truth of data for analytics, and most analysis is performed with stale data. To solve these challenges, the lakehouse is quickly emerging as the new standard for data architecture, with the promise to unify data, AI and analytic workloads in one place.In this eBook, you will discover the inner workings of the Databricks Lakehouse Platform. Learn why the data lakehouse is your next cloud data warehouse, how Databricks SQL works under the hood, and how it allows you to operate a multicloud lakehouse architecture that delivers world-class performance and data lake economics with up to 12x better price\/performance than legacy cloud data warehouses.Specifically, you\u2019ll learn:How to ingest, store and govern business-critical data at scale to build a curated data lakeHow to get started in seconds with instant, elastic SQL compute to process all query types with best-in-class performanceHow to quickly find and share new insights with a built-in SQL editor, visualizations and dashboards, or your favorite BI toolsThe differences between a data lake vs. data warehouseGet Your CopyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/pricing","text":"Databricks pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWExtended Time SQL Price Promotion - Save 40%+ Take advantage of our 15-month promotion on Serverless SQL and the brand new SQL ProLearn moreDatabricks pricingOne simple platform to unify all your data, analytics and AI workloads \u2014 across all your preferred cloudsStart free trialHow does Databricks pricing work?Pay as you goDatabricks offers you a pay-as-you-go approach with no up-front costs. Only pay for the products you use at per second granularity.SAVE MORE WITHCommitted-use discountsDatabricks helps you lower your costs with discounts when you commit to certain levels of usage. The larger your usage commitment, the greater your discount compared to pay as you go, and you can use commitments flexibly across multiple clouds. Contact us for details.Explore productsWorkflows & StreamingJobsStarting at $0.07 \/ DBURun data engineering pipelines to build data lakes and manage data at scaleLearn moreWorkflows & Streaming Delta Live TablesStarting at $0.20 \/ DBUEasily build high-quality streaming or batch ETL pipelines using Python or SQL with the DLT edition that is best for your workloadLearn moreData WarehousingDatabricks SQLStarting at $0.22 \/ DBURun SQL queries for BI reporting, analytics and visualization to get timely insights from data lakes. Available in both Classic and Serverless (managed) Compute.Learn moreData Science & Machine LearningAll Purpose Compute for Interactive WorkloadsStarting at $0.40 \/ DBURun interactive data science and machine learning workloads. Also good for data engineering, BI and data analyticsLearn moreData Science & Machine LearningServerless Real-Time InferenceStarting at $0.07 \/ DBUMake live predictions in your apps and websites.\nLearn moreDatabricks Platform & Add-OnsDatabricks Platform & Add-OnsCross-platform capabilities that provide the right level of management, governance and security to run everything from basic to enterprise-critical workloadsLearn moreTry Databricks for freeGet started for freeSchedule a demoFAQWhat does the free trial include?The 14-day free trial gives you:A collaborative environment for data teams to build solutions togetherInteractive notebooks to use Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn and morePlease note that you will still be charged by your cloud provider for resources, like compute instances, used within your account during the free trialWhat happens after the free trial?At the end of the trial, you are automatically subscribed to the plan that you have been on during the free trial. You can cancel your subscription at any time.Is pricing based on usage or storage volume?Databricks pricing is based on your compute usage. Storage, networking and related costs will vary depending on the services you choose and your cloud service provider.What is a DBU?A Databricks Unit (DBU) is a normalized unit of processing power on the Databricks Lakehouse Platform used for measurement and pricing purposes. The number of DBUs a workload consumes is driven by processing metrics, which may include the compute resources used and the amount of data processed. Is pricing the same in every region?Databricks prices and Cloud Infrastructure prices may vary based on geographic region and cloud service provider. For details, please see the Databricks pricing pages for individual productsIs Databricks as cost effective as other cloud services or open source solutions?Databricks products are priced to provide compelling Total Cost of Ownership (TCO) to customers for their workloads. When estimating your savings with Databricks, it is important to consider key aspects of alternative solutions, including job completion rate, duration and the manual effort and resources required to support a job. To help you accurately estimate your savings, we recommend comparing side-by-side results as part of a proof of concept deployment. For example, see the speedup achieved by this customer and the results of this customer benchmark. Contact us to get started.What is Databricks Community Edition?Databricks Community Edition is a free, limited functionality platform designed for anyone who wants to learn Spark. Sign up here.How will I be billed?By default, you will be billed monthly based on per second usage on your credit card. Contact us for more billing options, such as billing by invoice or an annual plan.Do you provide technical support?We do offer technical support. You can also check the technical documentation. Contact us to learn more.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/mitch-ertle\/#","text":"Mitch Ertle - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMitch ErtlePartner Solutions Engineer at Sigma ComputingBack to speakersMitch Ertle is an experienced data practitioner with over a decade of experience in Data Analytics. Prior to joining Sigma, Mitch spent three years leading data teams on Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers\/open-positions?department=professional%20services","text":"Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ben-wilson","text":"Ben Wilson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBen WilsonPrincipal Specialist Solutions Architect at DatabricksBack to speakersBen works on the team supporting MLflow and other notable Open Source ML products at Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/legal\/service-specific-terms","text":"Service Specific Terms | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesService Specific TermsThe following Service Specific Terms apply to the specific Databricks Services indicated below. In the event of a conflict or inconsistency between the terms of these Service Specific Terms and the terms of the Databricks Master Cloud Services Agreement or other agreement with us governing your use of the Databricks Services (the \u201cAgreement\u201d) the terms and conditions of these Service Specific Terms apply except as noted in Section 1.4 below. Capitalized terms used herein but not defined herein shall have the meanings set forth in the Agreement (or if not therein defined, shall refer to the term in such Agreement that is closest in meaning to such term).You may sign up to receive updates of these Service Specific Terms here.Universal Terms (applicable to all Databricks Services).Your use of the Platform Services must at all times comply with the Acceptable Use Policy.You must comply with the current Documentation as posted by us and updated by us from time to time on https:\/\/www.databricks.com\/documentation (or such other website as we provide).If you process the personal data of Authorized End Users or other identifiable individuals in your use of a Databricks Service, you are responsible for providing legally adequate privacy notices and obtaining necessary consents for the processing of such data. You represent to us that you have provided all necessary privacy notices and obtained all necessary consents. You are responsible for processing such data in accordance with applicable law.Your use of any Databricks Service described below is subject to these Service Specific Terms notwithstanding anything to the contrary in an Agreement, provided that if your Agreement already contains terms that specifically cover the indicated features below (such terms, \u201cOverriding Terms\u201d) (e.g., you entered into the Databricks Master Cloud Services Agreement at https:\/\/www.databricks.com\/legal\/mcsa from 28 March 2022 onwards), the terms in your Agreement will apply and the terms for that specific feature will be considered superseded by your Agreement; if your Agreement limits the applicability of these Service Specific Terms, you are not authorized to enable or access a Databricks Service covered by these Service Specific Terms unless such feature is covered by Overriding Terms.You may perform benchmarks or comparative tests or evaluations (each, a \u201cBenchmark\u201d) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Databricks may update these terms from time to time. Updates of these terms shall be deemed effective: (a) for new products and services, upon posting of the updated terms here; and (b) for updates to these terms that were previously posted (i) for Monthly PAYG Service customers (i.e., customers who are not on committed usage contracts), 30 days after such update is made to these Service Specific Terms and notified as described herein or (ii) for all other customers, upon renewal of the applicable Order Form. Databricks will provide notice to anyone who has subscribed to receive an update to these terms as indicated in the introduction above and may additionally provide notice to administrative users of the Platform Services.Definitions (applicable to all Platform Services).\u201cCloud Environment\u201d of a party means the cloud or other compute or storage infrastructure controlled by such party and utilized under the Agreement.\u201cCompute Plane\u201d means the portion of the applicable Cloud Environment where compute resources of the Platform Services are deployed during use of the Platform Services for the primary processing of Customer Data. In the case of Serverless Compute, the Compute Plane is within the Databricks Cloud Environment (the \u201cDatabricks Compute Plane\u201d). In all other cases, the Compute Plane is within the Customer Cloud Environment (the \u201cCustomer Compute Plane\u201d), and in such cases the processing activity results in fees being charged directly to Customer by the Cloud Service Provider. For the avoidance of doubt, none of the terms \u201cCompute Plane\u201d, \u201cCustomer Compute Plane\u201d or \u201cDatabricks Compute Plane\u201d include Customer\u2019s cloud storage. In certain Databricks agreements and Documentation, the Compute Plane may be interchangeably referred to as the \u201cData Plane\u201d.\u201cDatabricks Control Plane\u201d means the elements of the Platform Services residing within the Databricks Cloud Environment, other than the Databricks Compute Plane, including without limitation the user interface of the Platform Services.\"Serverless Compute\u201d means a Platform Service where the Compute Plane is located in Databricks\u2019 Cloud Environment rather than in Customer\u2019s Cloud Environment.Platform Services - General.Deployment and Responsibilities.\nGenerally. Customer acknowledges that the Platform Services are implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content. Without limiting the foregoing, Customer acknowledges and agrees that (1) in order to utilize the current Platform Services other than Serverless Compute, Customer must have an account with the Cloud Service Provider; (2) Databricks does not host the Customer Cloud Environment into which certain parts of the Platform Services may be deployed or the Systems in which your Customer Data may be stored (e.g., an AWS S3 bucket); (3) while certain Customer Data may in some cases be present within the Databricks Cloud Environment of the Platform Services (e.g., within the Customer Results), Databricks\u2019 current Platform Services are not designed to archive or permanently retain Customer Data (e.g., they are intended to provide an environment to facilitate Customer\u2019s processing of Customer Data by permitting Customer to execute Customer Instructional Input and view Customer Results); and (4) Databricks\u2019 current Platform Services do not provide backup services or disaster recovery to enable recovery of Customer Data. Accordingly, and without limiting the foregoing, Databricks is not responsible for any loss, destruction, alteration, or corruption of Customer Content, except to the extent caused by the gross negligence or willful misconduct of Databricks.Your Responsibilities. You acknowledge and agree that you are responsible for (1) protecting the security of all your credentials used to access the Platform Services (with Databricks also responsible for taking adequate steps to protect Customer credentials to the extent such credentials are within the control of Databricks); (2) securing the Customer Cloud Environment and any Customer System (with such steps to include without limitation the regular rotation of access keys and other industry standard steps to preclude unauthorized access); (3) backing up Customer Instructional Input (e.g., via Github or other third party System); (4) backing up and securing Customer Data under Customer\u2019s control within the Customer Cloud Environment or other Customer controlled System (e.g., by turning on versioning and encryption within AWS S3); (5) any security or other issues resulting from any Customer Instructional Input; and (6) managing and paying the charges associated with your usage of the Customer Cloud Environment (e.g., compute and storage fees); and Customer expressly assumes the risks associated with the foregoing responsibilities set forth in this Section.Databricks Responsibilities. Databricks acknowledges and agrees that, as between the parties and except to the extent caused by the action or intentional or negligent inaction of you or your Authorized Users, including without limitation any customizations or configurations of the Platform Services by you or anything specified to be your responsibility above, Databricks is primarily responsible for: (1) the operation (excluding to the extent such operation is directed by the Customer Instructional Input) of the Databricks Cloud Environment (including the user interface of the Platform Services, the Databricks Compute Plane with respect to Serverless Compute, and the portion of the Platform Services within the Databricks Control Plane in which the Customer Instructional Input and Customer Results are held until deleted by you) and, with respect to Platform Services other than Serverless Compute, the Databricks software that operates the computing resources in the Customer Compute Plane; and (2) implementing reasonable technical and organizational measures designed in accordance with ISO\/IEC 27001:2013 or equivalent\/greater standard to protect the security of the foregoing. Additionally, while it is your responsibility to back up Customer Instructional Input, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts where reasonably possible.Platform Services other than Serverless Compute. With respect to your use and Databricks\u2019 provisioning of Platform Services other than Serverless Compute, including without limitation All Purpose Compute, Jobs Compute (including Jobs Light Compute) and SQL Compute using Classic SQL Endpoints, the Compute Plane is deployed within the Customer Cloud Environment. Notwithstanding the foregoing, Databricks may in the future add additional Platform Services that may be subject instead to other Service Specific Terms by indicating in the Databricks release notes at the time of release that such Platform Services are subject to additional Service Specific Terms.\nServerless Compute (part of the Platform Services; in Public Preview on Databricks on AWS as of the date of these Service Specific Terms). Databricks Serverless Compute, including without limitation Serverless SQL Endpoints, operates by Databricks deploying the Compute Plane into the Databricks Cloud Environment instead of the Customer Cloud Environment. Accordingly, your use of and\/or our provision of Databricks Serverless Compute may conflict with or be inconsistent with certain terms you have previously agreed to with Databricks in an Agreement (including without limitation, the terms relating to your deployment or the respective responsibilities of the parties in the terms of service and\/or data processing addendum governing the Platform Services, as well as any security schedule or other terms), particularly as such terms may relate to our security obligations or our rights and responsibilities regarding data processing.Unless expressly permitted in an Order Form, Customer may not use Databricks Serverless Compute to process Cardholder Data or PHI.Downloadable Services.\nDatabricks may make available to you certain Databricks Services as software from time to time in a downloadable manner (\u201cDownloadable Services\u201c). Unless expressly stated otherwise at the time of download or as otherwise agreed by Databricks, Downloadable Services may only be used as a part of the Databricks Services. You are granted a non-exclusive, royalty-free right and license to use and copy during the term of the Agreement the Downloadable Services solely as necessary to enable your use of the Databricks Services.Beta Services.\u201cBeta Service\u201d means any Databricks Service (or feature of a Databricks Service) that is clearly designated as \u201cbeta\u201d, \u201cexperimental\u201d, \u201cpreview\u201d or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use.If you elect to receive any Beta Services offered by Databricks, you agree that, in addition to adhering to all other restrictions generally applicable to your use of the Platform Services under the Agreement and any requirements set forth by Databricks in writing regarding the particular Beta Services, you will not use such Beta Services for production workloads or for any mission critical work, and that you will not use sensitive data (e.g., PHI or Cardholder Data) in conjunction with such Beta Services unless explicitly permitted in an Order Form. For the avoidance of doubt, information pertaining to the Beta Services constitutes Databricks Confidential Information.BETA SERVICES ARE PROVIDED \u201cAS-IS\u201d AND WITHOUT WARRANTY OF ANY KIND. CUSTOMER BEARS THE RISK OF USING THE BETA SERVICES. DATABRICKS AND ITS SUPPLIERS GIVE NO EXPRESS OR IMPLIED WARRANTIES, GUARANTEES OR CONDITIONS RELATED TO THE BETA SERVICES. TO THE EXTENT PERMITTED UNDER YOUR LOCAL LAWS, DATABRICKS AND ITS SUPPLIERS EXCLUDE THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT.Databricks Container Services (part of the Platform Services).As part of the Databricks Container Services, Databricks may provide a sample stub container file (a \u201cSample Container\u201d) that you may (but are not required to) use to create a custom container file to use with Databricks Container Services (a \u201cModified Sample Container\u201d). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container by inserting your own code into the Sample Container to create a Modified Sample Container. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to the creation of the Modified Sample Container.You may not:\nupload to the Platform Services or otherwise make available for use with Databricks Services a container file (including a Modified Sample Container) (together, a \u201cCustom Container\u201d) or other code that contains any viruses, worms, time bombs, Trojan horses and other harmful or malicious code, files, scripts, agents or programs designed to impede the use of the Databricks Services or any other systems, whether or not connected to the Databricks Services;include in a Custom Container any code for which you do not have the necessary right or license or that contains any code that could subject Databricks Services (including the Databricks Container Services) to any term that seeks to require Databricks to make any Databricks Services code available in source code form or which may impose any other obligation or restriction with respect to Databricks\u2019 intellectual property rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services.Delta Sharing (part of the Platform Services; in Preview on Databricks on AWS as of the date of these Service Specific Terms).Delta Sharing allows a Databricks Authorized User to share data outside of the Authorized User\u2019s Customer organization. Accordingly, Customer\u2019s use of and\/or Databricks\u2019 provision of Delta Sharing may conflict with or be inconsistent with certain terms you have previously agreed to with Databricks in an Agreement (including, without limitation, terms relating to your deployment or the respective responsibilities of the parties in the terms of service and\/or data processing addendum governing the Platform Services, as well as any security schedule or other terms), particularly as such terms may relate to our security obligations or our rights and responsibilities regarding data processing.Additional Terms Relating to your Deployment.\nAdditional Definitions. The following additional terms apply to any use of Delta Sharing (as defined below).\n\"Data Recipient\" means a person who receives Customer Data from a Data Provider through Delta Sharing. A Data Recipient may be another Databricks customer or may be a third party entity that is not a Databricks customer (\u201cNon-Customer Recipient\u201d).\"Data Share\" means an individual set of Shared Data.\"Data Provider\" means a person who initiates the share of the Customer Data from the Platform Services.\"Delta Sharing\" means the portion of the Databricks Platform Services that enable a Data Provider to share Customer Data with a Data Recipient, as further described in the Documentation.\"Shared Data\" means Customer Data (either Customer\u2019s Customer Data or the Customer Data of another Databricks customer) that is shared via Delta Sharing.Generally. The Platform Services include functionality that lets Customer, at its option and in its sole discretion, provide Data Recipients outside of its Databricks workspace(s) with read-only access to Shared Data or receive Shared Data from other Data Providers.When Customer is the Data Provider. Customer may, at its option and in its sole discretion and subject to the rest of the Agreement, use Delta Sharing to grant one or more Data Recipients read-only access to some or all of its Customer Data via one or more Data Shares. Customer:\nis solely responsible for ensuring that it is entitled to share any Shared Data with any Recipient and that any such Data Share is in compliance with all applicable laws.acknowledges and agrees that (i) Data Recipients will have ongoing access to the Shared Data with the permissions set by Customer until the applicable Data Share is disabled; (ii) nothing in Delta Sharing prevents a Data Recipient from making a permanent copy of the Shared Data; (iii) Databricks has no control over, and will have no liability for, the acts or omissions of any Data Recipient with respect to the Shared Data; and (iv) Customer remains responsible for all Customer Data in accordance with the Agreement, irrespective of whether Customer or Data Recipient is in control of such data.as between Databricks and Customer, acknowledges and agrees that it is responsible for any fees (including fees charged by a Cloud Service Provider) associated with the access to and use of any Shared Data by a Data Recipient.represents that it has the right to share with Databricks any personal data associated with any Data Recipients that it shares with Databricks.acknowledges and agrees that it is fully responsible for any actions or inactions of a Data Recipient with respect to the Shared Data and will, subject to the conditions of indemnification set forth in the Agreement, but notwithstanding any liability cap or disclaimer or exclusion of damages therein (or otherwise agreed between the parties), defend all Databricks Indemnitees from and against any claims, demands, suits or proceedings made by a third party including without limitation a Data Recipient, and will indemnify each Databricks Indemnitee from and against any damages, attorneys\u2019 fees and costs finally awarded against a Databricks Indemnitee, arising from or related to any Shared Data provided to any Data Recipient through the Delta Sharing. \u201cDatabricks Indemnitees\u201d, if no equivalent term is defined in the Agreement, shall mean Databricks and its Affiliates and its and each of their officers, employees, directors, and agents.When Customer is the Data Recipient. By accessing a Data Provider\u2019s Shared Data as a Data Recipient, Customer represents that it has been authorized to access the Data Share(s) provided to it by the Data Provider and acknowledges that (1) Databricks has no liability for such Shared Data or Customer\u2019s use of such Shared Data, and (2) Databricks may collect information about Customer\u2019s use of and access to the Shared Data (including identifying Customer and any individual who accesses the Shared Data using the credential file in connection with such information) and may share it with the applicable Data Provider.Restrictions on Shared Data; Suspension. Unless set forth in an Order Form, Customer may not include any PHI (as defined by the Health Insurance Portability and Accountability Act) or Cardholder Data (as defined by PCI-DSS) in any Shared Data. Customer acknowledges and agrees that Databricks may, but is not required to, disable a given Data Share or Customer\u2019s use of the Delta Sharing or access to a Data Share if Databricks reasonably suspects or becomes aware of a claim that a Data Share may violate applicable law or may harm Databricks, Customer, Recipient or other third party.Last Updated March 28, 2022. For earlier versions, please send a request to [email\u00a0protected] (with \u201cService Specific Terms Request\u201d in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/cdn-cgi\/l\/email-protection#5b2b29322d3a38221b3f3a2f3a39293238302875383436","text":"\n\n\n\n  \n\nEmail Protection | Cloudflare\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPlease enable cookies.\n\n\nEmail Protection\nYou are unable to access this email address databricks.com\n\n\n\n\nThe website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.\nIf you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare.\n\n\n\n\n\n\nHow does Cloudflare protect email addresses on website from spammers?\nCan I sign up for Cloudflare?\n\n\n\n\n\n\n\n\n\nCloudflare Ray ID: 7c5c3e734f2082ec\n\u2022\n\n      Your IP:\n      Click to reveal\n2601:147:4700:3180:15eb:de93:22f5:f511\n\u2022\n\nPerformance & security by Cloudflare\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/br\/university","text":"Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark\u2122Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you\u2019re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now\u201cHaving access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.\u201d\u2014 Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don\u2019t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you\u2019re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners\nProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cody-ferguson","text":"Cody Ferguson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCody FergusonData & AI Management Branch Chief at Chief Digital and Artificial Intelligence Office - AdvanaBack to speakersCody is a proven leader in the data and analytics domain with experience in managing large technical teams on implementation of features that increase the ability for DoD to better utilize data to manage business and gain better insights for informed decision-making. Cody currently serves as the Data Operations Director for Advana, DoD's enterprise data and analytics platform within the Office of the Chief Digital and Artificial Intelligence Officer (OCDAO). In this role, he is responsible for large-scale data acquisition efforts through federation and integration of over 300 data sources, automation of data ingestion and governance processes to decrease overall time-to-insight for DoD analysts and data scientists, and scalable solutions for data architecture and management of all data assets on the Advana platform. Cody has 8 years of DoD experience which include assisting in the creation of executive analytics to enhance and inform senior leader decision-making in coordination with the Immediate Office of the Deputy Secretary of Defense, and leading the creation of budget analytics metrics that allow the Department to effectively utilize resources and align requirements to financial execution and outcomes. Prior to working in OSD, Cody was a Financial Management Trainee in the OPM Pathways program and a Financial Analyst, where he spent 5 years working in various positions within the Department of the Navy. Cody obtained a M.S. in Forensic Accounting from American University and received a B.S. in Business Administration from High Point UniversityLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/partner-solutions?itm_data=menu-item-brickbuildersoverview","text":"Partner Solutions - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner SolutionsPartner-developed industry and migration solutions for the lakehouseWe have partnered with leading consulting partners to build innovative solutions for industry and migration use cases. Databricks Brickbuilder Solutions are expertly designed by our partners to help you cut costs and increase value from your data. Backed by their years of industry experience \u2014 and built for the Databricks Lakehouse Platform \u2014 you can be confident that you get solutions that are tailored for your business.Search available partnerssearchPublic SectorCloud Data Migration by Accenture - DatabricksLearn moreRetail and Consumer GoodsUnified View of Demand by AccentureLearn moreAdvertising and Marketing TechnologyCPG Control Tower by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent Healthcare on Azure Databricks by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent ManufacturingLearn moreAdvertising and Marketing TechnologyLegacy System Migration by AvanadeLearn moreAdvertising and Marketing TechnologyRisk Management by AvanadeLearn moreTechnology and SoftwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksLearn moreTechnology and SoftwareMigrate to Cloud and Databricks by Capgemini and DatabricksLearn moreTechnology and SoftwareCapgemini Revenue Growth ManagementLearn moreTechnology and SoftwareMigrate to Databricks by Celebal Technologies and DatabricksLearn moreTechnology and SoftwareCognizant Video Quality of ExperienceLearn moreAdvertising and Marketing TechnologyPersona 360 by DataSentics and DatabricksLearn moreAdvertising and Marketing TechnologySAP Migration Accelerator by DataSentics - DatabricksLearn moreAdvertising and Marketing TechnologyPrecisionView\u2122 by DeloitteLearn moreAdvertising and Marketing TechnologyTrellis by DeloitteLearn moreAdvertising and Marketing TechnologySmart Migration to Databricks by EPAMLearn moreAdvertising and Marketing TechnologyLeapLogic Migration Solution by ImpetusLearn moreLoad MoreReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/session_na20\/geospatial-analytics-at-scale-analyzing-human-movement-patterns-during-a-pandemic","text":"AboutPressCopyrightContact usCreatorsAdvertiseDevelopersTermsPrivacyPolicy & SafetyHow YouTube worksTest new featuresNFL Sunday Ticket\u00a9 2023 Google LLCDatabricks - YouTube"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=DataLakehouse-FooterCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/toxicity-detection-for-gaming","text":"Detect Toxic Gamer Behavior in Real Time | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorToxicity Detection for GamingPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedFoster healthier gaming communities with real-time detection of toxic languageThis Solution Accelerator walks you through the steps required to detect toxic comments in real time to improve the user experience and foster healthier gaming communities. Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.Enable real-time detection of toxic comments within in-game chatEasily integrate into existing community moderation processesSeamlessly add new sources of gamer data (e.g., streams, files or voice data)Download notebookResourcesCase studyLearn moreExplainer videoWatch nowBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/br\/documentation","text":"\n\n\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDatabricks documentation | Databricks on AWS\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSupport\nFeedback\nTry Databricks\n\n\n\n\n\n\n\n\n\nHelp Center\nDocumentation\nKnowledge Base\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n        Amazon Web Services\n    \n\n        Microsoft Azure\n    \n\n        Google Cloud Platform\n    \n\n\n\n\n\n\n\n\n\n\n\nDatabricks on AWS\nGet started\n\nGet started\nWhat is Databricks?\nTutorials and best practices\nRelease notes\n\nLoad & manage data\n\nLoad data\nExplore data\nPrepare data\nShare data (Delta sharing)\nData Marketplace\n\nWork with data\n\nData engineering\nMachine learning\nData warehousing\nDelta Lake\nDeveloper tools\nTechnology partners\n\nAdministration\n\nAccount and workspace administration\nSecurity and compliance\nData governance\nLakehouse architecture\n\nReference & resources\n\nReference\nResources\nWhat\u2019s coming?\nDocumentation archive\n\n\n\n\n    Updated May 10, 2023\n  \n\n\nSend us feedback\n\n\n\n\n\n\n\n\n\n\nDocumentation \nDatabricks documentation\n\n\n\n\n\n\n\nDatabricks documentation \nDatabricks documentation provides how-to guidance and reference information for data analysts, data scientists, and data engineers working in the Databricks Data Science & Engineering, Databricks Machine Learning, and Databricks SQL environments. The Databricks Lakehouse Platform enables data teams to collaborate.\n\n\n\n\n\n\n\n\n\n\n\nTry Databricks \n\nGet a free trial & set up\nQuery data from a notebook\nBuild a basic ETL pipeline\nBuild a simple Lakehouse analytics pipeline\nFree training\n\n\n\nWhat do you want to do? \n\nData science & engineering\nMachine learning\nSQL queries & visualizations\n\n\n\nManage Databricks \n\nAccount & workspace administration\nSecurity & compliance\nData governance\n\n\n\nReference Guides \n\nAPI reference\nSQL language reference\nError messages\n\n\n\n\nResources \n\nRelease notes\nOther resources\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n          \u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation.\n      \n\nSend us feedback\n        \n     | Privacy Policy | Terms of Use\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"}
{"source":"https:\/\/www.databricks.com\/jp\/company\/contact","text":"\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fc\u30a6\u30a7\u30d3\u30ca\u30fc 5 \u6708 18 \u65e5\u5348\u524d 8 \u6642 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{"source":"https:\/\/www.databricks.com\/\/legal\/databricks-subprocessors","text":"Databricks Subprocessors | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks SubprocessorsDatabricks engages certain subprocessors in connection with providing the Platform Services or Support Services. A subprocessor is a Databricks affiliate (\u201cDatabricks Affiliate'') or a third-party engaged by Databricks, Inc. or a Databricks Affiliate to process personal data on behalf of Databricks\u2019 customers. Capitalized terms used herein have the same meaning as defined in the Master Cloud Services Agreement or other written agreement you have with Databricks (\u201cAgreement\u201d).Subscribe to be notified when we add new Subprocessors.Third-party SubprocessorsEntity NamePurposeEntity CountryAmazon Web Services, Inc.Cloud Service ProviderUnited StatesAmazon Data Services Ireland LtdCloud Service ProviderIrelandGoogle LLCCloud Service ProviderUnited StatesMicrosoft CorporationCloud Service ProviderUnited StatesIntercom R&D Unlimited CompanyProvide a platform for Databricks to send messages to our customers.IrelandOktaGenerate OAuth tokens (if customer does not choose to provide their own) to connect with customer-selected third parties.United StatesTwilio Inc.Provide customer communications, including in-product messaging and email.United StatesAtlassian Pty Ltd.Customer support and ticket handling.AustraliaMicrosoft CorporationCustomer support (in Microsoft Teams).United Statessalesforce.com, inc.Customer support ticketing.United StatesSlack Technologies, Inc.Customer support.United StatesSupportLogic, Inc.Monitor quality of service in responding to support tickets.United StatesDatabricks AffiliatesThe following entities are members of the Databricks Group. Accordingly, they may function as Subprocessors to provide the Databricks Services.Entity NameEntity CountryDatabricks Federal LLCUnited StatesDatabricks B.V.The NetherlandsDatabricks U.K. LimitedUnited KingdomDatabricks Australia Pty LtdAustraliaDatabricks SARLFranceDatabricks GmBHGermanyDatabricks Asiapac Unified Analytics Pte. Ltd.SingaporeDatabricks Japan K.K.JapanDatabricks India Private LimitedIndiaDatabricks Canada ULCCanadaDatabricks Italy S.r.l.ItalyDatabricks Sweden ABSwedenDatabricks Switzerland GmbHSwitzerlandDatabricks Spain S.L.SpainDatabricks Korea LLCSouth KoreaDatabricks New Zealand LimitedNew ZealandDatabricks Costa Rica SRLCosta Rica\u00a0Last Modified: March 31, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/product\/feature-store?itm_data=product-link-featureStore","text":"Databricks Feature Store | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWFeature StoreThe first feature store co-designed with a data platform and MLOps frameworkTry for freeSchedule a demoProvide data teams with the ability to create new features, explore and reuse existing ones, publish features to low-latency online stores, build training data sets and retrieve feature values for batch inference.Features as reusable assetsFeature Registry provides a searchable record of all features, their associated definition, source data, and their consumers, eliminating considerable rework across teams. Data scientists, analysts and ML engineers can search for features based on the consumed raw data and either use features directly or fork existing features.Consistent features for training and servingFeature Provider serves the features in two modes. Batch mode provides features at high throughput for training ML models or batch inference. Online mode provides features at low latency for serving ML models or for the consumption of the same features in BI applications. Features used in model training are automatically tracked with the model and, during model inference, the model itself retrieves them directly from the feature store.Secure features with built-in governanceFeature store integrations provide the full lineage of the data used to compute features. Features have associated ACLs to ensure the right level of security. Integration with MLflow ensures that the features are stored alongside the ML models, eliminating drift between training and serving time.ResourcesVirtual EventLearn moreDocumentationDatabricks Feature Store DocumentationReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/databricks-ventures","text":"Databricks Ventures | DatabricksSkip to main content\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0Delta Lake\u30c7\u30fc\u30bf\u30ac\u30d0\u30ca\u30f3\u30b9\u30c7\u30fc\u30bf\u30a8\u30f3\u30b8\u30cb\u30a2\u30ea\u30f3\u30b0\u30c7\u30fc\u30bf\u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u30c7\u30fc\u30bf\u30a6\u30a7\u30a2\u30cf\u30a6\u30b9\u30c7\u30fc\u30bf\u5171\u6709\u6a5f\u68b0\u5b66\u7fd2\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u6599\u91d1Marketplace\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\uff06\u30c8\u30e9\u30b9\u30c8\u30bb\u30f3\u30bf\u30fcWEBINAR May 18 \/ 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack.\n\u3054\u767b\u9332\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u306e\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u91d1\u878d\u30b5\u30fc\u30d3\u30b9\u533b\u7642\u30fb\u30e9\u30a4\u30d5\u30b5\u30a4\u30a8\u30f3\u30b9\u88fd\u9020\u901a\u4fe1\u3001\u30e1\u30c7\u30a3\u30a2\u30fb\u30a8\u30f3\u30bf\u30fc\u30c6\u30a4\u30e1\u30f3\u30c8\u516c\u5171\u6a5f\u95a2\u5c0f\u58f2\u30fb\u6d88\u8cbb\u8ca1\u5168\u3066\u306e\u696d\u754c\u3092\u898b\u308b\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u5225\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30a2\u30af\u30bb\u30e9\u30ec\u30fc\u30bf\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30c7\u30b8\u30bf\u30eb\u30cd\u30a4\u30c6\u30a3\u30d6\u30d3\u30b8\u30cd\u30b9\u30c7\u30fc\u30bf\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u79fb\u884c\u30d0\u30a4\u30aa\u533b\u85ac\u54c1\u4f01\u696d\u306e\u7d4c\u55b6\u9663\u3092\u5bfe\u8c61\u306b\u884c\u3063\u305f\u65b0\u305f\u306a\u8abf\u67fb\u306b\u3088\u308a\u3001\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u30a8\u30d3\u30c7\u30f3\u30b9\uff08RWE\uff09\u306e\u6d3b\u7528\u306b\u3088\u308b\u6210\u679c\u304c\u660e\u3089\u304b\u306b\u306a\u308a\u307e\u3057\u305f\u3002\n\u30a2\u30f3\u30b1\u30fc\u30c8\u306e\u7d50\u679c\u3092\u898b\u308b\u5b66\u7fd2\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30c7\u30e2\u95a2\u9023\u30ea\u30bd\u30fc\u30b9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5927\u5b66\u3068\u306e\u9023\u643a\u30a4\u30d9\u30f3\u30c8DATA+AI \u30b5\u30df\u30c3\u30c8\u30d6\u30ed\u30b0\u30e9\u30dcBeaconsJoin Generation AI in San Francisco June 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessions\u5c0e\u5165\u4e8b\u4f8b\u30d1\u30fc\u30c8\u30ca\u30fc\u30af\u30e9\u30a6\u30c9\u30d1\u30fc\u30c8\u30ca\u30fcAWSAzureGoogle CloudPartner Connect\u6280\u8853\u30fb\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u6280\u8853\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0\u30c7\u30fc\u30bf\u30d1\u30fc\u30c8\u30ca\u30fc\u30d7\u30ed\u30b0\u30e9\u30e0Built on Databricks Partner ProgramSI \u30b3\u30f3\u30b5\u30eb\u30c6\u30a3\u30f3\u30b0\u30d1\u30fc\u30c8\u30ca\u30fcC&SI \u30d1\u30fc\u30c8\u30ca\u30fc\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3Databricks \u8a8d\u5b9a\u306e\u30d1\u30fc\u30c8\u30ca\u30fc\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3092\u3054\u5229\u7528\u3044\u305f\u3060\u3051\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u4f1a\u793e\u60c5\u5831\u63a1\u7528\u60c5\u5831\u7d4c\u55b6\u9663\u53d6\u7de0\u5f79\u4f1aDatabricks \u30d6\u30ed\u30b0\u30cb\u30e5\u30fc\u30b9\u30eb\u30fc\u30e0Databricks Ventures\u53d7\u8cde\u6b74\u3068\u696d\u754c\u8a55\u4fa1\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305bDatabricks \u306f\u3001\u30ac\u30fc\u30c8\u30ca\u30fc\u306e\u30de\u30b8\u30c3\u30af\u30fb\u30af\u30a2\u30c9\u30e9\u30f3\u30c8\u3067 2 \u5e74\u9023\u7d9a\u3067\u30ea\u30fc\u30c0\u30fc\u306b\u4f4d\u7f6e\u4ed8\u3051\u3089\u308c\u3066\u3044\u307e\u3059\u3002\u30ec\u30dd\u30fc\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9Databricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u3092\u898b\u308b\u3054\u76f8\u8ac7\u30fb\u304a\u554f\u3044\u5408\u308f\u305b\u30ed\u30b0\u30a4\u30f3JUNE 26-29\u3054\u767b\u9332Databricks Ventures\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306e\u672a\u6765\u3078\u306e\u6295\u8cc7\nDatabricks Ventures \uff08\u30c7\u30fc\u30bf\u30d6\u30ea\u30c3\u30af\u30b9\u30fb\u30d9\u30f3\u30c1\u30e3\u30fc\u30ba\uff09\u306f\u3001\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306e\u672a\u6765\u306b\u3064\u3044\u3066 Databricks \u3068\u5171\u901a\u306e\u30d3\u30b8\u30e7\u30f3\u3092\u6301\u3064\u9769\u65b0\u7684\u306a\u4f01\u696d\u306b\u6295\u8cc7\u3092\u884c\u3063\u3066\u3044\u307e\u3059\u3002\u305d\u306e\u7b2c\u4e00\u5f3e\u3067\u3042\u308b\u300c\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30d5\u30a1\u30f3\u30c9\u300d\u3067\u306f\u3001\u5275\u696d\u671f\u304b\u3089\u6210\u9577\u671f\u306e\u4f01\u696d\u306e\u3046\u3061\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u306e\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u666e\u53ca\u30fb\u767a\u5c55\u306b\u53d6\u308a\u7d44\u3080\u4f01\u696d\u3084\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u57fa\u76e4\u306b\u30c7\u30fc\u30bf\u3068 AI \u306e\u6b21\u4e16\u4ee3\u3092\u5275\u9020\u3059\u308b\u4f01\u696d\u306b\u91cd\u70b9\u3092\u7f6e\u3044\u3066\u3044\u307e\u3059\u3002\u6295\u8cc7\u5148\u4f01\u696d\u306e\u30e1\u30ea\u30c3\u30c8Databricks \u88fd\u54c1\u30ed\u30fc\u30c9\u30de\u30c3\u30d7\u3078\u306e\u7279\u5225\u30a2\u30af\u30bb\u30b9\u3068\u3001Databricks \u306b\u3088\u308b\u9ad8\u5ea6\u306a\u6280\u8853\u7d71\u5408\u306e\u30b5\u30dd\u30fc\u30c8Databricks \u306e\u30e1\u30f3\u30bf\u30fc\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u3088\u308b\u30ac\u30a4\u30c0\u30f3\u30b9\u3068\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u306e\u5171\u6709Databricks \u306e Go-to-Market \u30d7\u30ed\u30b0\u30e9\u30e0\u3078\u306e\u53c2\u52a0\u306b\u3088\u308b\u9867\u5ba2\u30ea\u30fc\u30c1\u306e\u62e1\u5927Lakehouse Fund investment focus\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u57fa\u76e4\u3068\u3059\u308b\u30c7\u30fc\u30bf\u3001\u5206\u6790\u3001AI \u306e\u672a\u6765\u306b\u3064\u3044\u3066\u3001Databricks \u3068\u5171\u901a\u306e\u30d3\u30b8\u30e7\u30f3\u3092\u6301\u3064\u4f01\u696d\u306b\u6295\u8cc7\u5275\u696d\u671f\u304b\u3089\u6210\u9577\u671f\u306e\u4f01\u696d\u3092\u5bfe\u8c61\u306b\u3001\u30ea\u30fc\u30c9\u30a4\u30f3\u30d9\u30b9\u30bf\u30fc\u3068\u9023\u643a\u3057\u3066\u6295\u8cc7Databricks \u306e\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u3092\u306f\u3058\u3081\u3068\u3059\u308b\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u304a\u3088\u3073\u30aa\u30fc\u30d7\u30f3\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306e\u69cb\u7bc9\u306b\u30b3\u30df\u30c3\u30c8Our PortfolioAlation is the leader in enterprise data intelligence solutions. It helps organizations transform raw data into actionable insights with its data intelligence platform that empowers users to find, understand, govern and use data collaboratively.\n\u8a73\u3057\u304f\u898b\u308bArcion is a cloud-native, distributed CDC-based data replication platform that makes building real-time data pipelines simple. Arcion helps enterprises eliminate brittle pipelines and data silos.\n\u8a73\u3057\u304f\u898b\u308bdbt is a data transformation framework. Users can work directly within their data lakehouse or warehouse to quickly produce trusted data sets for reporting, ML modeling and operational workflows.\n\u8a73\u3057\u304f\u898b\u308bHex is a platform for collaborative analytics and data science. Users can connect to data, analyze in a collaborative SQL and Python-powered notebook, and share work as interactive data apps that anyone can use.\u8a73\u3057\u304f\u898b\u308bThe Hunters SOC platform empowers security teams to automatically identify and respond to incidents that matter, helping teams mitigate real threats faster and more reliably than SIEMs.\u8a73\u3057\u304f\u898b\u308bThe Immuta Data Security Platform enables organizations to unlock value from their cloud data by protecting it and providing secure access. The platform provides sensitive data discovery, security and access control, and data activity monitoring.\u8a73\u3057\u304f\u898b\u308bLabelbox is building a collaborative training data platform that makes it easy to create and manage labeled data, enabling rapid deployment of AI applications.\u8a73\u3057\u304f\u898b\u308bMatillion is the data productivity cloud that gets data business-ready, faster \u2014 with enterprise-scale load, transform, sync and orchestration \u2014 for insights, analytics, data science, machine learning and AI.\u8a73\u3057\u304f\u898b\u308bPerplexity advances the way people discover and share information using AI-powered search \u2014 providing instant answers and information on any topic, with up-to-date sources to help people discover, research and learn faster.\u8a73\u3057\u304f\u898b\u308bRevelate\u2019s data fulfillment platform provides a suite of capabilities for data sharing and data commercialization for customers to fully realize the value of their data.\u8a73\u3057\u304f\u898b\u308bTecton, the machine learning feature platform company, enables data teams to build, centralize, share, and serve production-ready ML features for offline training and online inference, at scale.\u8a73\u3057\u304f\u898b\u308bFAQDatabricks Ventures \u3068\u63d0\u643a\u3059\u308b\u30e1\u30ea\u30c3\u30c8\u306f\uff1f\n\u6295\u8cc7\u306e\u898f\u6a21\u3084\u6bb5\u968e\u306b\u5fdc\u3058\u3066\u3001Databricks \u306e\u88fd\u54c1\u30ed\u30fc\u30c9\u30de\u30c3\u30d7\u3078\u306e\u7279\u5225\u30a2\u30af\u30bb\u30b9\u8a31\u53ef\u3001\u6280\u8853\u7d71\u5408\u306e\u30b5\u30dd\u30fc\u30c8\u3001\u5e02\u5834\u53c2\u5165\u306e\u30b5\u30dd\u30fc\u30c8\u3001Databricks \u30e1\u30f3\u30bf\u30fc\u306b\u3088\u308b\u30ac\u30a4\u30c9\u3068\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\u306e\u7d39\u4ecb\u304c\u53d7\u3051\u3089\u308c\u308b\u307b\u304b\u3001Databricks \u304c\u958b\u50ac\u3059\u308b Data+AI \u30b5\u30df\u30c3\u30c8\u30b7\u30ea\u30fc\u30ba\u306a\u3069\u306e\u30b0\u30ed\u30fc\u30d0\u30eb\u306a Go-to-Market \u30d7\u30ed\u30b0\u30e9\u30e0\u3078\u306e\u53c2\u52a0\u304c\u53ef\u80fd\u3067\u3059\u3002Databricks Ventures \u306e\u6295\u8cc7\u57fa\u6e96\u306f\uff1f\n\u30c7\u30fc\u30bf\u3068 AI \u306e\u672a\u6765\u306b\u3064\u3044\u3066 Databricks \u3068\u5171\u901a\u306e\u30d3\u30b8\u30e7\u30f3\u3092\u6301\u3061\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30a8\u30b3\u30b7\u30b9\u30c6\u30e0\u306e\u666e\u53ca\u3068\u767a\u5c55\u3084\u3001\u30ec\u30a4\u30af\u30cf\u30a6\u30b9\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u306b\u57fa\u3065\u3044\u305f\u6b21\u4e16\u4ee3\u306e\u30c7\u30fc\u30bf\u30fbAI 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\u306f\u3001\u6295\u8cc7\u3092\u30ea\u30fc\u30c9\u3059\u308b\u6a5f\u95a2\u6295\u8cc7\u5bb6\u3068\u5171\u306b\u6295\u8cc7\u3092\u884c\u3046\u3053\u3068\u3092\u65b9\u91dd\u306b\u3057\u3066\u3044\u307e\u3059\u3002Databricks Ventures \u306e\u6295\u8cc7\u898f\u6a21\u306f\uff1f\nDatabricks Ventures \u306f\u3001\u30d9\u30f3\u30c1\u30e3\u30fc\u30ad\u30e3\u30d4\u30bf\u30eb\u304c\u30ea\u30fc\u30c9\u3059\u308b\u30e9\u30a6\u30f3\u30c9\u306b\u53c2\u52a0\u3057\u3066\u30de\u30a4\u30ce\u30ea\u30c6\u30a3\u6295\u8cc7\u3092\u884c\u3044\u307e\u3059\u3002\u6295\u8cc7\u898f\u6a21\u306f\u4f01\u696d\u306e\u6210\u9577\u6bb5\u968e\u3084\u8cc7\u91d1\u8abf\u9054\u30e9\u30a6\u30f3\u30c9\u306e\u898f\u6a21\u306b\u3088\u3063\u3066\u7570\u306a\u308a\u307e\u3059\u3002Databricks \u306f\u7d4c\u55b6\u306b\u53c2\u52a0\u3057\u307e\u3059\u304b\uff1f\u3044\u3044\u3048\u3001Databricks \u304c\u6295\u8cc7\u5148\u4f01\u696d\u306b\u53d6\u7de0\u5f79\u3092\u9001\u308b\u3053\u3068\u306f\u3042\u308a\u307e\u305b\u3093\u3002Databricks \u3067\u30b9\u30bf\u30fc\u30c8\u30a2\u30c3\u30d7\u3092\u69cb\u7bc9\u3059\u308bDatabricks for Startups \u306f\u3001Databricks \u3067\u5229\u7528\u3067\u304d\u308b\u7121\u6599\u306e\u30af\u30ec\u30b8\u30c3\u30c8\u3001\u5c02\u9580\u5bb6\u306e\u30a2\u30c9\u30d0\u30a4\u30b9\u3001Go To Market \u6226\u7565\u306e\u30b5\u30dd\u30fc\u30c8\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002\u8a73\u3057\u304f\u898b\u308b\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u88fd\u54c1\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u6599\u91d1\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30c6\u30af\u30ce\u30ed\u30b8\u30fcDatabricks \u7121\u6599\u30c8\u30e9\u30a4\u30a2\u30eb\u30c7\u30e2\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5b66\u7fd2\u30fb\u30b5\u30dd\u30fc\u30c8\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u7528\u8a9e\u96c6\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30fb\u8a8d\u5b9a\u30d8\u30eb\u30d7\u30bb\u30f3\u30bf\u30fc\u6cd5\u52d9\u30aa\u30f3\u30e9\u30a4\u30f3\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u696d\u7a2e\u5225\u30d7\u30ed\u30d5\u30a7\u30c3\u30b7\u30e7\u30ca\u30eb\u30b5\u30fc\u30d3\u30b9\u4f1a\u793e\u60c5\u5831\u4f1a\u793e\u6982\u8981\u63a1\u7528\u60c5\u5831\u30c0\u30a4\u30d0\u30fc\u30b7\u30c6\u30a3\uff06\u30a4\u30f3\u30af\u30eb\u30fc\u30b8\u30e7\u30f3Databricks 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All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|\u5229\u7528\u898f\u7d04|\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u8a2d\u5b9a|\u30ab\u30ea\u30d5\u30a9\u30eb\u30cb\u30a2\u5dde\u306e\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u6a29\u5229"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/elliot-shmukler","text":"Elliot Shmukler - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingElliot ShmuklerCo-Founder & CEO at AnomaloBack to speakersElliot Shmukler is the co-founder and CEO at Anomalo, where he and the team are building software to help data teams detect and root cause issues in their data before anyone else notices. Before starting Anomalo, Elliot has long championed using data to make decisions and build products as a senior Silicon Valley executive at companies like Instacart, Wealthfront, LinkedIn, and eBay. Elliot is a recognized Silicon Valley expert in data-driven product management and consumer growth strategies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/fr\/resources","text":"Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/prateek-chawla","text":"Prateek Chawla - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPrateek ChawlaFounding Engineer at Monte CarloBack to speakersPrateek Chawla is a founding engineer and technical lead at Monte Carlo, where he drives the technical strategy for their data observability platform. Previously, he served as a technical lead at Barracuda, working on email fraud prevention technologies. He graduated Summa Cum Laude with a B.S. in Computer Science and Engineering from the University of California, Santa Cruz. In his free time, Prateek enjoys watching Broadway shows, flying airplanes, reading, and exploring new places.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/denny-lee\/#","text":"Denny Lee - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDenny LeeSr. Staff Developer Advocate at DatabricksBack to speakersDenny is a Databricks Developer Advocate. A hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale data platforms, and predictive analytics systems. He also has a Masters of Biomedical Informatics from Oregon Health and Sciences University and has implemented powerful data solutions for enterprise Healthcare customers. His current technical focuses include Distributed Systems, Apache Spark, Deep Learning, Machine Learning, and Genomics.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/blog\/2022\/01\/14\/top-three-data-sharing-use-cases-with-delta-sharing.html","text":"Top Three Data Sharing Use Cases With Delta Sharing - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorTop Three Data Sharing Use Cases With Delta Sharingby Jay Bhankharia, Itai Weiss, Matei Zaharia and Sachin ThakurJanuary 14, 2022 in Platform BlogShare this postUpdate:\u00a0Delta Sharing is now generally available on AWS and Azure.\u00a0Data sharing has become an essential component to drive business value as companies of all sizes look to securely exchange data with their customers, suppliers and partners. According to a recent Gartner survey, organizations that promote data sharing will outperform their peers on most business value metrics.There are various challenges with the existing data sharing solutions that limit the data sharing within or across organizations and fail to realize the true value of data. Over the last 30 years, data sharing solutions have come in two forms: homegrown solutions or third-party commercial solutions. With homegrown solutions, data sharing has been built on legacy technologies such as SFTP and REST APIs, which have become difficult to manage, maintain or scale with new data requirements. Alternatively, commercial data sharing solutions only allow you to share data with others leveraging the same platform, which limits the data sharing and can be costly.These challenges have led us, at Databricks, to rethink the future of data sharing as open. During the Data + AI Summit 2021, we announced Delta Sharing, the world\u2019s first open protocol for secure and scalable real-time data sharing. Our vision behind Delta Sharing is to build a data-sharing solution that simplifies secure live data sharing across organizations, independent of the platform on which the data resides or is consumed. With Delta Sharing, organizations can easily share existing large-scale datasets based on the Apache Parquet and Delta Lake formats without moving data and empower data teams with the flexibility to query, visualize and enrich shared data with their tools of choice.Delta Sharing ecosystemSince the private preview launch, we have seen tremendous engagement from customers across industries to collaborate and develop a data-sharing solution fit for purpose and open to all. Customers have already shared petabytes of data using Delta Sharing. The Delta Sharing partner ecosystem has also grown since the announcement with both commercial and open-source clients having built-in Delta Sharing connectors such as PowerBI, Pandas, and Apache Spark\u2122 with many others to be released soon.Through our customer conversations, we have identified three common use cases: data commercialization, data sharing with external partners and customers, and line of business data sharing. In this blog post, we explore each one of the top use cases and share some of the insights we are hearing from our customers.Use case 1: Data commercializationCustomer example: A financial data provider was interested in reducing operational inefficiencies with their legacy data delivery channels and making it easier for the end customers to seamlessly access large new datasets.ChallengesThe data provider recently launched new textual datasets that were large in size, with terabytes of data being produced regularly. Providing quick and easy access to these large datasets has been a persistent challenge for the data provider as the datasets were difficult to ingest in bulk for the data recipients. With the current solution, the provider had to replicate data to external SFTP servers, which had many potential points of failure and increased latency.On the recipient side, ingesting and managing this data was not easy due to its size and scale. Data recipients had to set up infrastructure for ingestion, which further required approvals from IT and database administrators, resulting in delays that could take weeks if not longer to complete before the end consumer could start using the data.How Delta Sharing helpsWith Delta Sharing, the data provider can now share large datasets in a seamless manner and overcome the scalability issues with the SFTP servers. These large terabyte sized textual datasets which had to be extracted in batches to SFTP can now be accessed in real time through Delta Sharing. The provider now can simply grant and manage access to the data recipients instead of replicating the data, thereby reducing complexity and latency. With the improved scalability, the data provider is seeing a significant increase in customer adoption as the data consumers have access to live data instead of having to pull the datasets on a regular basis.Use case 2: Data sharing with external partners\/customersCustomer example: A large retailer needed to easily share product data (e.g., cereal SKU sales) with partners without being on the same data sharing or cloud computing platform as them. The retailer wanted to create partitioned datasets based on SKUs for partners to easily access the relevant data in real time.ChallengesThe retailer was utilizing homegrown SFTP and APIs to share data with partners, which had become unmanageable. This solution required a considerable amount of development resources to maintain and operate. The retailer looked at other data sharing solutions, but these solutions required their partners to be on the same platform, which is not feasible for all parties due to cost considerations and operational overhead of replicating data across different regions.How Delta Sharing helpsDelta Sharing was an exciting proposition for the retailer to manage and share data efficiently across cloud platforms without the need to replicate the data across regions. The retailer found it easy to manage, create and audit data shares for their 100+ partners through Delta Sharing. For each partner, the retailer can easily create partitions and share the data securely without the need to be on the same data platform. In addition to making the management of the shares easy, Delta Sharing also minimizes the cost, as the data provider only incurs data egress cost from the underlying cloud provider and does not have to pay for any compute charges for data sharing.Use case 3: Internal data sharing with line of businessCustomer example: A manufacturer wants data scientists across its 15+ divisions and subsidiaries to have access to permissioned data to build predictive models. The manufacturer wants to do this with strong governance, controls, and auditing capabilities because of data sensitivity.ChallengesThe manufacturer has many data lake deployments, making it difficult for teams across the organization to access the data securely and efficiently. Managing all this data across the organization is done in a bespoke manner with no strong controls over entitlements and governance. Additionally, many of these datasets are petabytes in size causing concern in the ability to scalably share this data. Management was hesitant about sharing data without the proper data access controls and governance. As a result, the manufacturer was missing unique opportunities to unlock value and allow more unique insights for the data science teams.How Delta Sharing helpsWith Delta Sharing, the manufacturer now has the ability to govern and share data across distinct internal entities without having to move data. Delta Sharing lets the manufacturer grant, track, and audit access to shared data from a single point of enforcement. Without having to move these large datasets, the manufacturer doesn\u2019t have to worry about managing different services to replicate the data. Delta Sharing enabled the manufacturer to securely share data much quicker than they expected, allowing for immediate benefits as the end-users could begin working with unique datasets that were previously siloed. The manufacturer is also excited to utilize the built-in Delta Sharing connector with PowerBI, which is their tool of choice for data visualization.Getting started with Delta SharingDelta Sharing makes it simple to share data with other organizations regardless of which data platforms they use. We are thrilled to share the first solution that provides an open and secure solution without proprietary lock-in that helps data teams easily share data, manage privacy, security and compliance across organizations.To try Delta Sharing on Databricks, reach out to your Databricks account executive or sign up to get an early access. For many of our customers, governance is top of mind when sharing data. Delta Sharing is natively integrated with Unity Catalog, which enables customers to add fine-grained governance and security controls, making it easy and safe to share data internally or externally. Once you have enabled Unity Catalog in your databricks account, try out the quick start notebooks below to get started with Delta Sharing on Databricks:Creating a share and granting access to a data recipientConnecting to a share and accessing the data\u00a0To try the open source Delta Sharing release, follow the instructions at delta.io\/sharing.Interested in participating in the Delta Sharing open source project?We\u2019d love to get your feedback on the Delta Sharing project and ideas or contributions for new features. Get involved with the Delta Sharing community by following the instructions here.Try Databricks for freeGet StartedSee all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=NavBar-TryDatabricks-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/jp\/legal\/privacynotice#dbadditionalinformation","text":"Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (\u0000\u0000\u201cDatabricks\u201d, \u201cwe\u201d, \u201cour\u201d, and \u201cus\u201d) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the \u201cSites\u201d), our data processing platform products and services (the \u201cPlatform Services\u201d) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, \u201cDatabricks Services\u201d). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, \u201cCustomers\u201d) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (\u201cAuthorized Users\u201d). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities.\u00a0We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes.\u00a0Information we collect automatically\u00a0We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information).\u00a0For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications.\u00a0The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our\u00a0Cookie Notice.\u00a0When you use our Platform Services, we automatically collect information about how you are using the Platform Services (\u201cUsage Data\u201d). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services.\u00a0We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you.\u00a0Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers;\u00a0to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking\u00a0here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https:\/\/sift.com\/service-privacy;with third party business partners, such as resellers, distributors, and\/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside.\u00a0Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission\u2019s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected.\u00a0Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311\/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking\u00a0here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information.\u00a0If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email\u00a0protected]. We will respond to requests that we receive in accordance with applicable laws. Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email\u00a0protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (\u201cCCPA\u201d) requires us to provide you with additional information regarding your rights with respect to your \u201cpersonal information. This information is described in our Supplemental Privacy Notice to California Residents.\u00a0\u00a0Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and\/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States.\u00a0We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place.\u00a0You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under \u201cYour Choices and Rights\u201d.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and\/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account.\u00a0How to Contact UsPlease contact us at\u00a0[email\u00a0protected]\u00a0if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization\u2019s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/stephen-shelton\/#","text":"Stephen Shelton - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStephen SheltonVice President, Business Intelligence at Pluto TVBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
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{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/ajali-sen","text":"Ajali Sen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAjali SenSenior Manager at AccentureBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/special-events?itm_data=hp-hamburger-specialevents-dais23","text":"Special Events - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpecial EventsYour pass will give you free access to a host of special events across four days in San Francisco. Attend parties and get-togethers, networking opportunities, meetups and specialist panels, such as the Women in Data discussion.MeetupsWomen in Data + AIPartiesMeetupsJoin like-minded professionals at our Data + AI Summit meetups to discuss the latest news, innovations and trends across the data, analytics and AI ecosystem.\nCome to a meetup!Eat, socialize and network with fellow data prosLearn new tips and tricks for your favorite technologiesSee what new features are in the pipelineWomen in Data and AIAttend our popular Women in Data and AI panel discussion and explore the array of activities and opportunities for women in data to connect. Join us for a special luncheon, a meetup at our after-party and much, much more throughout Summit.\nAs an attendee, you can: Hear from women who are making an impact and revolutionizing the world of data, analytics and AI \u2014 during a lunch and learn sessionJoin us at a dedicated meetup and offsite party for Data + AI Summit womenNetwork throughout the event with inspirational women who work in data, analytics and AIPartiesEnjoy exclusive parties \u2014 celebrate the world of data, analytics and AI with your fellow data professionals throughout four days in San Francisco.\nJoin us for a variety of social gatherings including an offsite party featuring live entertainment and more fun activities! Details coming soon.\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/what-is-parquet","text":"What is Apache Parquet?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWParquetAll>ParquetTry Databricks for freeGet StartedWhat is Parquet?Apache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. Apache Parquet is designed to be a common interchange format for both batch and interactive workloads. It is similar to other columnar-storage file formats available in Hadoop, namely RCFile and ORC.Characteristics of ParquetFree and open source file format.Language agnostic.Column-based format - files are organized by column, rather than by row, which saves storage space and speeds up analytics queries.Used for analytics (OLAP) use cases, typically in conjunction with traditional OLTP databases.Highly efficient data compression and decompression.Supports complex data types and advanced nested data structures.Benefits of ParquetGood for storing big data of any kind (structured data tables, images, videos, documents).Saves on cloud storage space by using highly efficient column-wise compression, and flexible encoding schemes for columns with different data types.Increased data throughput and performance using techniques like data skipping, whereby queries that fetch specific column values need not read the entire row of data.Apache Parquet is implemented using the record-shredding and assembly algorithm, which accommodates the complex data structures that can be used to store the data. Parquet is optimized to work with complex data in bulk and features different ways for efficient data compression and encoding types. This approach is best especially for those queries that need to read certain columns from a large table. Parquet can only read the needed columns therefore greatly minimizing the IO.Advantages of Storing Data in a Columnar Format:Columnar storage like Apache Parquet is designed to bring efficiency compared to row-based files like CSV. When querying, columnar storage you can skip over the non-relevant data very quickly. As a result, aggregation queries are less time-consuming compared to row-oriented databases. This way of storage has translated into hardware savings and minimized latency for accessing data.Apache Parquet is built from the ground up. Hence it is able to support advanced nested data structures. The layout of Parquet data files is optimized for queries that process large volumes of data, in the gigabyte range for each individual file.Parquet is built to support flexible compression options and efficient encoding schemes. As the data type for each column is quite similar, the compression of each column is straightforward (which makes queries even faster). Data can be compressed by using one of the several codecs available; as a result, different data files can be compressed differently.Apache Parquet works best with interactive and serverless technologies like AWS Athena, Amazon Redshift Spectrum, Google BigQuery and Google Dataproc.Difference Between Parquet and CSVCSV is a simple and common format that is used by many tools such as Excel, Google Sheets, and numerous others. Even though the CSV files are the default format for data processing pipelines it has some disadvantages:Amazon Athena and Spectrum will charge based on the amount of data scanned per query.Google and Amazon will charge you according to the amount of data stored on GS\/S3.Google Dataproc charges are time-based.Parquet has helped its users reduce storage requirements by at least one-third on large datasets, in addition, it greatly improved scan and deserialization time, hence the overall costs. The following table compares the savings as well as the speedup obtained by converting data into Parquet from CSV.DatasetSize on Amazon S3Query Run TimeData ScannedCostData stored as CSV files1 TB236 seconds1.15 TB$5.75Data stored in Apache Parquet Format130 GB6.78 seconds2.51 GB$0.01Savings87% less when using Parquet34x faster99% less data scanned99.7% savingsParquet and Delta LakeThe open source Delta Lake project builds upon and extends the Parquet format, adding additional functionality like ACID transactions on cloud object storage, time travel, schema evolution, and simple DML commands (CREATE\/UPDATE\/INSERT\/DELETE\/MERGE). Delta Lake implements many of these important features through the use of an ordered transaction log that makes data warehousing functionality possible on cloud object storage. Learn more in the Databricks blog post Diving into Delta Lake: Unpacking the Transaction Log.Additional ResourcesACID, Time Travel and more for Parquet - Tech Talk SeriesOptimizing Delta\/Parquet Data Lakes for Apache SparkSpark + Parquet In DepthParquet Files DocumentationDelta Lake Product PageBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/derek-sugden","text":"Derek Sugden - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDerek SugdenAd Measurement Lead \u2013 Measurement & Attribution at EffectvBack to speakersDerek Sugden is an accomplished professional who serves as the Ad Measurement Lead on the Measurement and Attribution Team at Effectv. With a background in Ichthyology, Derek made a transition to the media and entertainment industry over 5 years ago. He brings a unique perspective and a wealth of knowledge to his role, utilizing his expertise to advance attribution capabilities and measure the effectiveness of cross-screen advertising campaigns.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-lai\/#","text":"Justin Lai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin LaiDistinguished Data Architect at BlackBerryBack to speakersJustin is Software Architect at BlackBerry for over 12 years and have experience working in many areas ranging from low level network stack on BlackBerry Devices, Android application development, to Cloud Data engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/harsh-mishra","text":"Harsh Mishra - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarsh MishraLead Enterprise Architect at Australian Rail Track CorporationBack to speakersHarsh Mishra, as a Lead Enterprise Architect of Systems and Integration, plays an integral role in facilitating the design and implementation of the Strengthening the Core work packages for the ARTC Digital Strategy and building integrated technology roadmaps to drive the successful foundation of the ARTC Digital Strategy.\nHe comes from a strong digital transformation background where he has successfully transformed multiple Australian company's digital and data footprints.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/careers","text":"Careers at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAttention: Databricks applicantsDue to reports of phishing, all Databricks applicants should apply on our official Careers page (good news \u2014 you are here). All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Careers at DatabricksWe\u2019re on a mission to help data teams solve the world\u2019s toughest problems. Will you join us?See open jobs OverviewCultureBenefitsDiversityStudents & new gradsUplevel your career. Level up the future.Databricks is leading the data and AI revolution. We created a category called the lakehouse. And now, thousands of companies are using it to solve problems like climate change, fraud, customer churn and so much more. If you\u2019re looking for an opportunity that could truly define your career, this is it.Why lakehouse is the futureWhy Databricks?We\u2019re growing fast and attracting the best talent in the world. Bricksters \u2014 as we call ourselves \u2014 are a special mix of smart, curious, quick thinkers. If you ask a Brickster what they love about working here, you\u2019ll likely hear about our culture.See our culture principlesFind your teamAdministrationBusiness DevelopmentCustomer SuccessEngineeringField EngineeringFinanceITLegalMarketingOperationsPeople & HRProductProfessional ServicesRecruitingSalesSecurityInternships & Early CareerBenefits, perks and hybrid workTo do your best work, your health and well-being are key. That\u2019s why we offer great benefits and perks \u2014 including flexible ways of working. It all depends on what works best for you and your team.Check out our benefitsDiversity, Equity and InclusionWe believe different backgrounds, perspectives and skills fuel our success. That\u2019s why we work hard at cultivating an inclusive and supportive environment. Find out how we\u2019re closing the pay gap, removing unconscious bias from recruitment and more.See inclusion in actionLocationsHeadquartered in San Francisco, California, we now have over 20 offices in 12 countries. With 4,500+ Bricksters worldwide and an ambitious growth strategy, we\u2019re one of the fastest growing enterprise software cloud companies.Check out our offices around the worldAmericas\n\u00a0San FranciscoSeattleWashington, D.C.New York CitySee moreEurope\n\u00a0LondonAmsterdamBerlinMunichSee moreAsia-Pacific\n\u00a0TokyoSingaporeSeoulHangzhouSee moreOpportunities for students and new graduatesWe\u2019re committed to developing our next generation of Databricks leaders. That\u2019s why we\u2019re intentional about having our interns and new college grads play an integral role in developing our platform.Our University Program is designed to help you make the most of your experience \u2014 from engineering hackathons and Intern Olympics to board game nights and happy hours.Explore internships and opportunities Health plan transparency in coverage (U.S. only)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/customer-segmentation","text":"Solution Accelerator - How to build: Customer segmentation for personalization | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorHow to build: Customer segmentation for personalizationSegment your customers for better targeting\nCreate advanced customer segments to drive better purchasing predictions based on behaviors. Using sales data, campaigns and promotions systems, this solution helps derive a number of features that capture the behavior of various households. Build useful customer clusters to target with different promos and offers.\nRead the full write-up\nDownload notebooksBenefits and business valueKnow which customers to targetIdentify target customer groups and what to offer themPersonalize at scaleScale fine-grain-level segmentations rapidly to quickly personalize customer experiencesCollaborate and shareSegmentation data is used by product, marketing and other teams, and the Databricks Lakehouse Platform is built for flexible collaborationReference ArchitectureDeliver AI innovation faster with Solution Accelerators for popular industry use cases.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/amanda-milberg\/#","text":"Amanda Milberg - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmanda MilbergSenior Partner Sales Engineer at DataikuBack to speakersAmanda is a Senior Partner Sales Engineer with a strong interest in NLP and AI \/ Machine Learning business solutions. Amanda has a proven track record of assisting large institutions in business transformation efforts in the advanced analytics space and an innate ability to explain deep technical concepts to a broad audience.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/glossary\/unified-data-warehouse","text":"Unified Data WarehousePlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUnified Data WarehouseAll>Unified Data WarehouseWhat is a Unified Data Warehouse?A unified database also known as an enterprise data warehouse holds all the business information of an organization and makes it accessible all across the company. Most companies today, have their data managed in isolated silos while different teams of the same organization use various data management tools for various types of data such as data quality, data integration, data governance, metadata and master data management, B2B data exchange, database administration and architecture,etc. The adoption of enterprise DWs in large companies has become a best practice for storing integrated and centralized data extracted from various disparate operational sources. In this way, complicated queries can be executed without conflicting with the transactional operations of the operational systems.The typical architecture of a DW consists of different components where data is passed from one component to the next after some critical operation is performed on the data. The structure of a unified data warehouse consists of a subset of the components contained in the Data warehouse architecture, namely: the data sources, the core DW, the data marts, the Extraction, Transformation and Loading (ETL) processes and the metadata repositories. The most important benefit of unified data warehousing comes from the fact that all the data is based on one central premise: as a result, there is no need to analyze the data separately in order to convert it into actionable information which can facilitate an improved decision-making process.Advantages Offered by a Unified Data Warehouses:Data warehouses offer added support for data, in that they are designed to track, manage, and analyze information, providing a great environment that is designed for decision support, analytics reporting, and data mining.A unified data warehouse works hand-in-hand with other analytics programs to promote company growth.All the company\u2019s data is constantly available for analyzing and planning purposesUsers can store vast amounts of data with a large variety of parameters. That data can be drawn from multiple, usually unrelated sources.A unified data warehouse has the ability to refine data, eliminating redundant information, while increasing overall data quality.Keeps data manipulation to a minimum and integrity at its highest level.Provides improved and up-to-date informationAdditional ResourcesUnified Cloud Data Analytics PlatformModern Cloud Data Platform for DummiesNew Microsoft Azure Data Warehouse Service and Azure Databricks Combine Analytics, BI, and Data ScienceBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/paul-wellman\/#","text":"Paul Wellman - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul WellmanVP, Executive Product Owner, Data-as-a-Service at TD BankBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/solutions\/accelerators\/customer-lifetime-value","text":"Calculate Customer Lifetime Value | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorAnalyze Customer Lifetime ValuePre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAccurately identify your high-value and longtime customersAnalyzing customer lifetime value is critical to improving marketing decision-making, campaign ROI and customer retention. Learn how to identify your most valuable customers with our Customer Lifetime Value Solution Accelerator. In this accelerator, you will ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases.Understand your customers to appropriately engage with themEnhance customer acquisition strategiesImprove retention to drive growth from existing customersDownload notebookResourcesBlogLearn moreBlogLearn moreeBooks & VideosLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries.\u00a0See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/justin-breese\/#","text":"Justin Breese - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin BreeseSr. Product Manager at DatabricksBack to speakersJustin is a Product Manager at Databricks and works on areas like query processing and SQL. \nHe has a ton of interests: soccer, hiking, brewing beer, roasting coffee, and older cars. \nJustin lives in Topanga, CA with his wife and a baby boy (due in July).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/de\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"Partnerseite: Consulting- und SI-Partner | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai \/ 8 Uhr PT\nAuf Wiedersehen, Data Warehouse. Hallo, Lakehouse.\nNehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.\nMelden Sie sich jetzt anL\u00f6sungenL\u00f6sungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und Unterhaltung\u00d6ffentlicher SektorEinzelhandelAlle Branchen anzeigenL\u00f6sungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT\n\u00a0\nEntdecken Sie das Lakehouse f\u00fcr die Fertigung\nErfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erh\u00f6hen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.\u201329. Juni 2023\nNehmen Sie pers\u00f6nlich teil oder schalten Sie f\u00fcr den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammL\u00f6sungen von PartnernVernetzen Sie sich mit validierten Partnerl\u00f6sungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWC&SI-PartnerprogrammDas Databricks Consulting and SI (C&SI)-Partnerprogramm ist wertorientiert und erm\u00f6glicht es uns, besser zusammenzuarbeiten, um enorme Erfolge zu erzielen.Jetzt bewerbenWerden Sie Teil eines globalen \u00d6kosystems von Daten- und KI-Serviceanbietern, die unsere gemeinsamen Kunden in datengesteuerte Unternehmen verwandeln. Als Partner spielen Sie eine wichtige Rolle bei der F\u00f6rderung folgender Punkte:Auswirkungen auf den Vertrieb\nBinden Sie unsere Au\u00dfendienstteams ein, um Kunden die Vision des Lakehouse zu vermitteln und die Pr\u00e4senz von Databricks zu erweitern.Kundenwert\nSchulen Sie Ihr Team auf der Plattform, um die Kapazit\u00e4t und F\u00e4higkeit Ihres Gesch\u00e4ftsbereichs aufzubauen.Innovation\nBringen Sie Ihr Fachwissen ein, indem Sie wiederholbare L\u00f6sungen f\u00fcr wichtige Anwendungsf\u00e4lle von Kunden entwickeln.Nutzen Sie die Vorteile von Einbindung und Bef\u00e4higung, damit Sie Ihren Gesch\u00e4ftsbereich ausbauen und eine erfolgreiche Partnerschaft aufbauen k\u00f6nnen:Technische Schulungen von DatabricksZugriff auf die Databricks Lakehouse-PlattformTechnischer Support und Vertriebsunterst\u00fctzungRegistrierung von Gesch\u00e4ftsgelegenheiten und Geb\u00fchren f\u00fcr EmpfehlungenInvestmentfonds f\u00fcr KundenMarkteintrittsbef\u00e4higung und RessourcenM\u00f6chten Sie loslegen?Jetzt bewerbenPartner findenProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityL\u00f6sungenBy IndustriesProfessionelle ServicesL\u00f6sungenBy IndustriesProfessionelle ServicesUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktUnternehmen\u00dcber unsKarriere bei DatabricksDiversit\u00e4t und InklusionUnternehmensblogKontaktWeitere Informationen unter\n\u201eKarriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte"}
{"source":"https:\/\/www.databricks.com\/fr\/professional-services","text":"Services professionnels de Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donn\u00e9esData EngineeringStreaming de donn\u00e9esEntreposage des donn\u00e9esPartage de donn\u00e9esMachine LearningData ScienceTarifsMarketplaceOpen source techCentre s\u00e9curit\u00e9 et confianceWEBINAIRE mai 18 \/ 8 AM PT\nAu revoir, entrep\u00f4t de donn\u00e9es. Bonjour, Lakehouse.\nAssistez pour comprendre comment un data lakehouse s\u2019int\u00e8gre dans votre pile de donn\u00e9es moderne.\nInscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSant\u00e9 et sciences du vivantProduction industrielleCommunications, m\u00e9dias et divertissementSecteur publicVente au d\u00e9tailD\u00e9couvrez tous les secteurs d'activit\u00e9Solutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de donn\u00e9es9 mai | 8h PT\n\u00a0\nD\u00e9couvrez le Lakehouse pour la fabrication\nD\u00e9couvrez comment Corning prend des d\u00e9cisions critiques qui minimisent les inspections manuelles, r\u00e9duisent les co\u00fbts d\u2019exp\u00e9dition et augmentent la satisfaction des clients.Inscrivez-vous d\u00e8s aujourd\u2019huiApprendreDocumentationFORMATION ET CERTIFICATIOND\u00e9mosRessourcesCommunaut\u00e9 en ligneUniversity Alliance\u00c9v\u00e9nementsSommet Data + IABlogLabosBeacons26-29 juin 2023\nAssistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donn\u00e9esProgramme partenaires technologiquesProgramme Partenaire de donn\u00e9esBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics \u00e0 des solutions partenaires valid\u00e9es.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre \u00e9quipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterD\u00e9couvrez pourquoi Gartner a d\u00e9sign\u00e9 Databricks comme leader pour la deuxi\u00e8me ann\u00e9e cons\u00e9cutiveObtenir le rapportEssayer DatabricksRegarder les d\u00e9mosNous contacterLoginJUNE 26-29REGISTER NOWServices professionnels de DatabricksContactez-nous pour en savoir plusAssurez le succ\u00e8s rapide de vos projets gr\u00e2ce \u00e0 une expertise de rang mondial en data engineering, en data science et en gestion de projet. Les services professionnels de Databricks vous accompagnent tout au long de votre parcours ax\u00e9 sur les donn\u00e9es et l'IA\u00a0:AvantagesAcc\u00e9l\u00e9ration de votre parcours donn\u00e9es et IA\nNos offres et services d'experts vous accompagnent dans votre parcours donn\u00e9es et IA en vue d'une acc\u00e9l\u00e9ration optimale et sur-mesure. Nous intervenons de l'int\u00e9gration initiale de votre workspace \u00e0 la mise en place de pratiques DataOps\net d'un centre d'excellence \u00e0\nl'\u00e9chelle de l'entreprise.\n\u00c9liminez les risques de votre projet\nVous souhaitez migrer d'anciennes charges de travail vers Databricks, d\u00e9velopper de nouveaux produits de donn\u00e9es ou des projets de pipeline donn\u00e9es et IA et machine learning\u00a0? Nous serions ravis de vous accompagner et de vous conseiller afin de minimiser les risques et de maximiser la valeur \u00e0 chaque \u00e9tape de votre parcours.\nMettre en service \u00e0 grande \u00e9chelle\nLa cr\u00e9ation d'un POC de pipeline de donn\u00e9es ou d'un d\u00e9veloppement de mod\u00e8le \u00e0 n\u0153ud unique est relativement facile \u00e0 g\u00e9rer. Le d\u00e9fi r\u00e9side dans l'adoption et la mise \u00e0 l'\u00e9chelle r\u00e9ussies des pratiques donn\u00e9es et IA dans toute l'entreprise. Nous serions ravis de vous aider \u00e0 atteindre cet objectif ambitieux gr\u00e2ce \u00e0 notre expertise et nos offres normatives.\nOffres en coursAssurer le succ\u00e8s rapide des projets gr\u00e2ce \u00e0 une expertise de rang mondial en data engineering, en data science et en gestion de projetLancement rapideAcc\u00e9l\u00e9rez le planning de vos projets en vous familiarisant avec la plateforme Databricks et ses principales fonctionnalit\u00e9s qui appliquent les bonnes pratiques.Migration HadoopNotre approche normative maximise la valeur de vos investissements existants dans les donn\u00e9es et les pipelines, tout en assurant une migration sereine.D\u00e9veloppement de LakehouseAcc\u00e9l\u00e9rez la mise en \u0153uvre d'une plateforme simplifi\u00e9e pour l'analytique de donn\u00e9es, la data science et le ML, en \u00e9tablissant les bases de votre vision du lakehouse.Machine learningRenforcez vos initiatives de ML d'entreprise et leur adoption gr\u00e2ce \u00e0 notre m\u00e9thodologie prescriptive.Acc\u00e9l\u00e9rateur de services partag\u00e9sAcc\u00e9l\u00e9rez votre mod\u00e8le op\u00e9rationnel \u00e0 l'\u00e9chelle de l'entreprise pour favoriser l'excellence donn\u00e9es et IA gr\u00e2ce \u00e0 notre m\u00e9thodologie normative.Services sur mesureContactez-nous pour obtenir un cahier des charges sur-mesure r\u00e9pondant \u00e0 vos besoins particuliers.Nos experts en services professionnels sont parvenus \u00e0 r\u00e9aliser des projets de cycle de vie complet afin de r\u00e9pondre \u00e0 des exigences complexes, tr\u00e8s sp\u00e9cifiques et cibl\u00e9es.Architectes de solutions r\u00e9sidents | data scientistsDes ressources tr\u00e8s exp\u00e9riment\u00e9es et techniques, avec de solides comp\u00e9tences en leadership et en conseil. Pour garantir votre r\u00e9ussite, nous exploitons notre vaste \u00e9cosyst\u00e8me de partenaires et si n\u00e9cessaire, nous assurons les prestations en commun avec eux.Experts Databricks et Spark10\u00a0ans d'exp\u00e9rience\nSolide exp\u00e9rience en Big Data\nComp\u00e9tences de terrain en mati\u00e8re de mise en \u0153uvre\nPlanification et ex\u00e9cution de projetsAssister dans la conception et l'architecture\nAider \u00e0 adapter le projet aux capacit\u00e9s de la plateforme\nContribuer au calendrier des projets et aux besoins en ressources\nMise en \u0153uvre et planification de la productionConcevoir des solutions \u00e9volutives\nAssister dans le d\u00e9veloppement de prototypes\nR\u00e9pondre aux exigences d'int\u00e9gration DevOps\nAssister dans la mise en \u0153uvre d'un COE (centre d'excellence)D\u00e9velopper des normes et cadres communs\n\u00catre disponible en tant que ressource pour plusieurs \u00e9quipes\nFaciliter les interactions avec d'autres \u00e9quipes Databricks\nRessourcesAper\u00e7u du programme de cr\u00e9dit SuccessFormulaire de demande d\u2019\u00e9changeLa Databricks AcademyLe facteur humain est d\u00e9terminant pour la r\u00e9ussite des clients. Gr\u00e2ce aux formations et aux certifications propos\u00e9es par la Databricks Academy, vous apprendrez \u00e0 ma\u00eetriser l\u2019analytique de donn\u00e9es avec l\u2019\u00e9quipe qui a lanc\u00e9 le projet de recherche Spark \u00e0 l'universit\u00e9 de Californie \u00e0 Berkeley. Progressez plus rapidement avec la Databricks Academy.Gagnez en comp\u00e9tences d\u00e8s maintenantPr\u00eat \u00e0 vous lancer\u00a0?Nous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksD\u00e9moLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunaut\u00e9 en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterEntrepriseNous conna\u00eetreOffres d'emploi chez DatabricksDiversit\u00e9 et inclusionBlog de l'entrepriseNous contacterD\u0000\u00e9couvrez les offres d'emploi\nchez Databrickspays\/r\u00e9gionsEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Avis de confidentialit\u00e9|Conditions d'utilisation|Vos choix de confidentialit\u00e9|Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/madalina-tanasie\/#","text":"Madalina Tanasie - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMadalina TanasieChief Technology Officer at CollibraBack to speakersAs Collibra\u2019s Chief Technology Officer, Madalina oversees Software Engineering, Architecture, Production Engineering, Test Engineering and Security. With over 18 years of software engineering leadership experience, her expertise includes service oriented architecture, cloud-native distributed systems and product operations with a focus on engineering practices, scale and operational excellence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/adriana-ispas\/#","text":"Adriana Ispas - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAdriana IspasStaff Product Manager at DatabricksBack to speakersAdriana Ispas is a staff product manager at Databricks working on the Databricks Runtime and Databricks SQL. She holds a Ph.D. in Computer Science from ETH Zurich.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/try-databricks?itm_data=DataLakehouse-HeroCTA-Trial","text":"Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations\u00a0and RBAC.12x better price\/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1\/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/de\/dataaisummit\/?itm_data=menu-learn-dais23","text":"Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.\nRegister NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you\u2019re an engineering wizard, ML pro, SQL expert \u2014 or you want to learn how to build, train and deploy LLMs \u2014 you\u2019ll be in good company.\nSee all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark\u2122 and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes M\u00fchleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI \u2014 and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.\nSessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.\nExplore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark\u2122, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto\/Trino, DuckDB and much more. You\u2019ll also get a first look at new products and features in the Databricks Lakehouse Platform.\nBrowse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.\nLearn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at \u201cbirds of a feather\u201d meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark\u2122, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world\nSee agendaDon\u2019t miss this year\u2019s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/product\/open-source","text":"Open source | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio \/ 8 AM PT\nAddio, Data Warehouse. Ciao, Lakehouse.\nPartecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno.\nRegistrati oraSoluzioniSoluzioni per settoreServizi finanziariSanit\u00e0 e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT\n\u00a0\nScopri la Lakehouse for Manufacturing\nScopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons\u00a0\n26\u201329 giugno 2023\nPartecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perch\u00e9 Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWOpen sourceGli ingegneri di Databricks sono i creatori di alcune delle tecnologie open-source per la gestione dei dati pi\u00f9 utilizzate al mondoUnisciti a un meetupI nostri progetti open-source pi\u00f9 notiApache Spark\u2122Apache Spark \u00e8 un motore unico per eseguire carichi di lavoro per ingegneria dei dati, data science e ML.\nChe cos'\u00e8 Apache Spark?\nSpark e Databricks a confronto\nVisita spark.apache.org\nDelta LakeDelta Lake consente di costruire un'architettura lakehouse su sistemi di storage come AWS S3, ADLS, GCS e HDFS.\nMaggiori informazioni su Delta Lake\nVisita delta.io\nDibattiti tecnici: Primi passi con Delta Lake\nMLFLOWMLflow gestisce il ciclo di vita ML, con sperimentazione, riproducibilit\u00e0, implementazione e un registro centralizzato dei modelli.\nManaged MLflow su Databricks\nVisita mlflow.org\nDibattiti tecnici: Gestire il ciclo di vita del ML\nRedashRedash consente a tutti di utilizzare SQL per esplorare, interrogare, visualizzare e condividere dati da sorgenti di piccola e grande entit\u00e0.\nVisita Redash su GitHub\nDelta SharingDelta Sharing \u00e8 il primo protocollo aperto per la condivisione sicura dei dati, che semplifica la condivisione con altre organizzazioni.\nVisita Delta Sharing\nDatabricks supporta altre tecnologie open-source molto diffusetensorflowDatabricks supporta TensorFlow, una libreria per deep learning e calcolo generico su cluster\nTensorFlow su Databricks\nPyTorch\u2122Facebook, creatore di PyTorch, e Databricks hanno collaborato alle integrazioni\nPyTorch su Databricks\nKeras\u2122API di Deep Learning scritte in Python che girano su TensorFlow. Disponibili in Databricks Runtime per ML.\nKeras su Databricks\nRStudioUna suite open-source di strumenti per data science collaborativa che utilizza R \u200b\nProgrammazione R su Big Data\nscikit-learnPacchetto Python molto utilizzato per machine learning basato su NumPy, SciPy e Matplotlib\u200b\u200b\nScikit-learn su Databricks\nXGBoostLibreria software di regolarizzazione del gradiente per linguaggi come Python, R e C++XGBoost su DatabricksTerraformHashiCorp Terraform \u00e8 uno strumento open-source molto diffuso per creare un'infrastruttura sicura e prevedibile su diversi provider di servizi cloud. Il provider Databricks Terraform consente ai clienti di gestire tutti i loro spazi di lavoro Databricks e il resto dell'infrastruttura con un unico strumento potente e flessibile. L'uso di Terraform porta inoltre i clienti ad adottare best practice con infrastruttura come codice (IaC)Terraform su DatabricksPronto per cominciare?Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversit\u00e0 e inclusioneBlog aziendaleContattiPosizioni aperte\nin DatabricksMondoEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/fr\/try-databricks?itm_data=SiteWide-Footer-Trial","text":"Essayer gratuitement Databricks | DatabricksEssayer gratuitement DatabricksExp\u00e9rimentez pleinement la plateforme Databricks gratuitement pendant 14 jours, sur AWS, Microsoft Azure ou Google Cloud, au choix.Simplification de l'ingestion des donn\u00e9es et automatisation de l\u2019ETLImportez des donn\u00e9es depuis des centaines de sources. Utilisez une approche d\u00e9clarative simple pour cr\u00e9er des pipelines de donn\u00e9es.Collaborez dans votre langage pr\u00e9f\u00e9r\u00e9Codez en Python, R, Scala et SQL. B\u00e9n\u00e9ficiez du RBAC, d\u2019int\u00e9grations avec Git et d\u2019outils comme la r\u00e9daction collaborative et la gestion automatique des versions.Un rapport performance \/ prix jusqu'\u00e0 12 fois sup\u00e9rieur \u00e0 celui des data warehousesD\u00e9couvrez pourquoi plus de 7 000 clients dans le monde s\u2019appuient sur Databricks pour toutes leurs charges de travail de la BI \u00e0 l\u2019IA.Cr\u00e9ez votre compte Databricks1\/2Pr\u00e9nomNomE-mail professionnelEntrepriseIntitul\u00e9 de posteNum\u00e9ro de t\u00e9l\u00e9phone (facultatif)Veuillez s\u00e9lectionnerPaysContinuerAvis de confidentialit\u00e9 (mis \u00e0 jour)Conditions d'utilisationVos choix de confidentialit\u00e9Vos droits de confidentialit\u00e9 en Californie"}
{"source":"https:\/\/www.databricks.com\/trust?itm_data=menu-item-securitytrustcenter","text":"Security and Trust Center - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSecurity & Trust CenterYour data security is our priority\n\u00a0\n\u00a0OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueWe know that data is one of your most valuable assets and always has to be protected \u2014 that\u2019s why security is built into every layer of the Databricks Lakehouse Platform. Our transparency enables you to meet your regulatory needs while taking advantage of our platform.Trusted PlatformTrust comes through transparency. See how we secure the platform through industry-leading practices including penetration testing, vulnerability management and secure software development to protect the Databricks Lakehouse Platform.Learn moreSecurity FeaturesWe provide comprehensive security capabilities to protect your data and workloads, such as encryption, network controls, auditing, identity integration, access controls and data governance.Learn moreComplianceCustomers all over the world and across industries rely on the Databricks Lakehouse Platform. We have the certifications and attestations to meet the unique compliance needs of highly regulated industries.Learn morePrivacyWe value the privacy of your data and understand that it is important to both your organization and your customers. Databricks can help you comply with privacy laws and meet regulatory requirements.Learn morePerform your own self-service security review of Databricks using our due\ndiligence package, which includes documentation and compliance materials.Due Diligence PackageProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/keith-anderson\/#","text":"Keith Anderson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKeith AndersonSolution Principal at Hitachi SolutionsBack to speakersI am a Solution Principal with Hitachi Solutions (Azure & Databricks partner) working with customers on solving data & AI problems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/why-attend\/#","text":"Why Attend - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingWhy AttendExplore everything Data + AI Summit has to offer \u2014 from the latest innovations and technologies to thought-provoking panel discussions to networking opportunities where you can connect with other data professionals in your industry.Register nowSession informationWith 10 amazing tracks and over 20 technologies to learn about, get the right experience for your level.\n\u00a0\nData Lakehouse ArchitectureThe decisions you make about your core data architecture will affect the reliability, performance and utility of your data analytics, data science and machine learning. Increasingly, many organizations are adopting the data lakehouse to improve their data platform. Has the ability to more easily combine structured, unstructured and real-time data workloads created new opportunities for data teams? Has ACID reliability on data lakes simplified how data is used? In this track, get answers to these questions and find out how to adopt a data lakehouse, migrate from data lakes and data warehouses, and integrate lakehouses with other data platforms.\nTechnologies\/topic ideas: lakehouse architecture, Delta Lake, Photon, platform security and privacy, serverless, cost management, data warehouse, data lake, Apache Iceberg, Data Mesh\nData GovernanceData governance, security and compliance are critical \u2014 they help guarantee that all data, BI and ML assets are maintained and managed securely across the enterprise and you\u2019re compliant with regulatory frameworks. In this track, learn best practices, frameworks, processes, roles, policies and standards for data governance of structured and unstructured data across clouds.\nTechnologies\/topic ideas: data governance, multicloud, Unity Catalog, security, compliance, privacy\nData SharingWhen enterprises can easily exchange data with their customers, partners, suppliers and internal lines of business, they can better collaborate, innovate and unlock value from that data. In this track, discover best practices for sharing data across data platforms and clouds, ways to avoid replication and lock-in, and how to distribute data products through marketplaces.\nTechnologies\/topic ideas: sharing and collaboration, Delta Sharing, data cleanliness, data cleanrooms, data marketplaces\nData Engineering If you want to optimize data processing and reduce costs, this session is for you. You\u2019ll learn how to use a combination of systems and processes to ingest, orchestrate and transform raw data for analytics and machine learning. Dive into best practices for data architectures, software engineering, ETL, data management, data quality, DataOps and orchestration.\nTechnologies\/topic ideas: data pipelines, orchestration, CDC, medallion architecture, Delta Live Tables, dbt, Databricks Workflows, ETL\/ELT, DataOps, Parquet, Apache Spark internals\nData Streaming Today\u2019s organization needs to respond in real time as events unfold. In this track, learn how data streaming can help you drive faster decision-making, make more accurate predictions and improve customer experiences. Explore best practices for implementing real-time data pipelines with your favorite tools and languages, find out how to reduce complexity for real-time data workflows and eliminate silos to support all your real-time use cases.\nTechnologies\/topic ideas: Apache Spark Structured Streaming, real-time ingestion, real-time ETL, real-time ML, real-time analytics, real-time applications, Delta Live Tables\nDSML: Production ML\/MLOpsOvercome the challenges of putting ML projects into production and operationalizing them at scale. In this track, you\u2019ll find out how to scale ML in production and apply MLOps best practices across the end-to-end machine learning lifecycle.\u00a0\nTechnologies\/topic areas: MLOps, Feature Stores, organizational ML, MLflow, Model Serving and more\nDSML: ML Use Cases\/TechnologiesMachine learning continues to disrupt industries and accelerate business outcomes across use cases and industries. In this track, discover how to apply ML to solve business challenges, explore technologies and best practices, and learn how to integrate data science with the rest of your organization.\u00a0\nTechnologies\/topic areas: PyTorch, TensorFlow, Keras, XGBoost, fast.ai, scikit-learn, Python and R ecosystems, deep learning, notebooks, LLMs and more\nData Warehouses, BI and Visualization Data analytics is a vital component of business decision-making. In this track, find out how to build analytics pipelines and integrations and learn about tooling and infrastructure for SQL analytics, BI and visualization. \u00a0\nTechnologies\/topic ideas: ANSI SQL, Redash, Databricks SQL, Tableau, Power BI, visualization techniques, Spark SQL and DataFrames, data integration, data warehouse and analytics\nResearchIn this track \u2014 dedicated to academic and advanced industrial research \u2014 explore large-scale data analytics and machine learning systems, the hardware that powers them (GPUs, I\/O storage devices, etc.) and how these systems are applied to use cases like genomics, astronomy, image scanning, disease detection, vaccine research and more.\nData StrategyChoosing a data lakehouse platform is only the first step in implementing your data strategy. Success requires a thoughtful approach to people and processes. In this track, you\u2019ll find out how to align goals, identify the right use cases, organize and enable teams, mitigate risk and operate at scale so you can be even more successful with data, analytics and AI.\nTechnologies\/topic ideas: data management, data governance, strategy, data teams, data mesh, data democratization\u00a0\nContent tailored to your roleData + AI Summit has something for everyone \u2014 explore, learn and connect with us and the data, analytics and AI community.\n\u00a0\n\u00a0\nData EngineerIncrease efficiency, control costs and reduce data risks \u2014 all in a day\u2019s work for today\u2019s data engineer. Broaden your knowledge and expand your skills by learning from industry experts and your peers how to deliver high-quality, reliable data for every use case from BI to AI.\nExplore sessionsData ScientistSuddenly, AI is everywhere and that\u2019s putting pressure on data scientists and ML engineers to quickly deliver results. Learn how lakehouse and tools like MLflow can accelerate productionization of models, increase productivity, reduce risk and increase ROI on new models.\nExplore sessionsData AnalystData analytics has moved beyond the warehouse. Join the global community of data analysts at Data + AI Summit and discover ways to support your stakeholders in making informed and timely decisions, achieve line of business KPIs and reduce rework risks.\nExplore sessionsIT Decision MakerData and AI are now mission critical for every business. Learn how the lakehouse architecture unifies data, analytics and AI on a single platform for better performance, lower TCO and faster innovation.\nExplore sessionsIndustry ExperiencesJoin and learn along with your industry peers in these specialized sessions focused on the unique challenges, use cases, and the data, analytics and AI requirements of your sector.\n\u00a0\nFinancial ServicesLearn how to minimize risk, deliver superior customer experience and accelerate innovation on lakehouse.\nDownload PDF\nGovernment and Public SectorLearn how lakehouse is helping to unlock the full potential of data to deliver mission objectives and better serve citizens.\nDownload PDF\nHealthcare and Life SciencesLearn ways to accelerate research and improve patient outcomes on lakehouse.\nDownload PDF\nManufacturingLearn how the lakehouse helps optimize supply chains, boost product innovation, increase operational efficiencies, predict fulfillment needs and reduce overall costs.\nDownload PDF\nCommunications, Media & EntertainmentLearn ways to accelerate audience and advertiser outcomes \u2014 360\u00b0 view of audience, lower churn, increased ARPU \u2014 with lakehouse.\nDownload PDF\nRetail and Consumer GoodsLearn how lakehouse is helping to harness the full power of data so retailers, suppliers and partners can collaborate across the value chain.\nDownload PDF\nDon\u2019t miss this year\u2019s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/cody-ferguson\/#","text":"Cody Ferguson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCody FergusonData & AI Management Branch Chief at Chief Digital and Artificial Intelligence Office - AdvanaBack to speakersCody is a proven leader in the data and analytics domain with experience in managing large technical teams on implementation of features that increase the ability for DoD to better utilize data to manage business and gain better insights for informed decision-making. Cody currently serves as the Data Operations Director for Advana, DoD's enterprise data and analytics platform within the Office of the Chief Digital and Artificial Intelligence Officer (OCDAO). In this role, he is responsible for large-scale data acquisition efforts through federation and integration of over 300 data sources, automation of data ingestion and governance processes to decrease overall time-to-insight for DoD analysts and data scientists, and scalable solutions for data architecture and management of all data assets on the Advana platform. Cody has 8 years of DoD experience which include assisting in the creation of executive analytics to enhance and inform senior leader decision-making in coordination with the Immediate Office of the Deputy Secretary of Defense, and leading the creation of budget analytics metrics that allow the Department to effectively utilize resources and align requirements to financial execution and outcomes. Prior to working in OSD, Cody was a Financial Management Trainee in the OPM Pathways program and a Financial Analyst, where he spent 5 years working in various positions within the Department of the Navy. Cody obtained a M.S. in Forensic Accounting from American University and received a B.S. in Business Administration from High Point UniversityLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/it\/try-databricks?itm_data=Homepage-HeroCTA-Trial","text":"Prova Databricks gratis | DatabricksProva Databricks gratisProva la piattaforma Databricks completa per 14 giorni su AWS, Microsoft Azure o Google Cloud.Semplifica l\u2019acquisizione dei dati e automatizza i processi ETLAcquisisci i dati da centinaia di sorgenti. Usa un semplice approccio dichiarativo per costruire le pipeline di dati.Collabora nella lingua che preferisciScrivi codice in Python, R, Scala e SQL con co-creazione, gestione automatica delle versioni, integrazioni Git e controllo degli accessi per ruoli (RBAC).Rapporto prezzo\/prestazioni 12 volte migliore rispetto ai data warehouse in cloudScopri perch\u00e9 oltre 7.000 clienti in tutto il mondo si affidano a Databricks per tutti i loro carichi di lavoro, dalla BI all\u2019AI.Crea il tuo account Databricks1\/2NomeCognomeE-mail aziendaleAziendaTitolo professionaleTelefono (Optional)Si prega di selezionareNazioneContinuaInformativa sulla privacy (aggiornata)Condizioni d'usoLe vostre scelte sulla privacyI vostri diritti di privacy in California"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lior-gavish","text":"Lior Gavish - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLior GavishCTO and Co-founder at Monte Carlo DataBack to speakersLior Gavish is CTO and Co-Founder of Monte Carlo, a data reliability company backed by Accel, Redpoint Ventures, GGV, ICONIQ Growth, Salesforce Ventures, and IVP. Prior to Monte Carlo, Lior co-founded cybersecurity startup Sookasa, which was acquired by Barracuda in 2016. At Barracuda, Lior was SVP of Engineering, launching award-winning ML products for fraud prevention. Lior holds an MBA from Stanford and an MSC in Computer Science from Tel-Aviv University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/company\/partners\/consulting-and-si\/candsi-partner-program","text":"Partner page: Consulting and SI partners | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWC&SI Partner ProgramThe Databricks Consulting and SI (C&SI) Partner Program is value-led, allowing us to partner better together to drive big outcomes.Apply nowJoin a global ecosystem of data and AI service providers that are transforming our joint customers into data-driven enterprises. As a partner, you\u2019ll play a critical role in driving:Sales impact\nEngage with our field teams to sell the lakehouse vision and expand the Databricks footprint.Customer value\nTrain your team on the platform to build your practice\u2019s capacity and capability.Innovation\nShowcase your expertise by developing repeatable solutions that tackle high-impact client use cases.Unlock benefits across engagement and enablement so you can grow your practice and build a successful partnership:Databricks Technical TrainingDatabricks Lakehouse Platform AccessTechnical and Sales SupportOpportunity Registration and Referral FeesCustomer Investment FundsGo-to-Market Enablement and ResourcesReady to get started?Apply nowFind a partnerProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/lee-yang","text":"Lee Yang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLee YangSr. Principal SW Engineer at NVIDIABack to speakersLee Yang is a Sr. Principal Software Engineer at NVIDIA, working on integrating deep learning with Apache Spark. Before that, at Yahoo, he created and open-sourced TensorFlowOnSpark, a framework for large-scale, distributed TensorFlow training and inference using Spark.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/product\/marketplace","text":"Databricks Marketplace | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 \/ 8 AM PT\nGoodbye, Data Warehouse. Hello, Lakehouse.\nAttend to understand how a data lakehouse fits within your modern data stack.\nRegister nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.\nSee survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco\nJune 26\u201329\n\u00a0\nLearn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark\u2122, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks MarketplaceOpen marketplace for data, analytics and AIGet startedTo play this video, click here and accept cookiesWhat is Databricks\nMarketplace?\nDatabricks Marketplace is an open marketplace for all your data, analytics and AI, powered by open source Delta Sharing standard. The Databricks Marketplace expands your opportunity to deliver innovation, and advance all your analytics and AI initiatives.\u00a0\nObtain data sets as well as AI and analytics assets \u2014 such as ML models, notebooks, applications and dashboards \u2014 without proprietary platform dependencies, complicated ETL or expensive replication. This open approach allows you to put data to work more quickly in every cloud with your tools of choice.Discover more than just dataUnlock innovation and advance your organization\u2019s AI, ML and analytics initiatives. Access more than just data sets, including ML models, notebooks, applications and solutions.Evaluate data products fasterPrebuilt notebooks and sample data help you quickly evaluate and have much greater confidence that a data product is right for your AI, ML or analytics initiatives.Avoid vendor lock-inSubstantially reduce the time to deliver insights and avoid lock-in with open and seamless sharing and collaboration across clouds, regions or platforms. Directly integrate with your tools of choice and right where you work.Featured data providers on Databricks MarketplaceBecome a data provider on the marketplace\nResourcesEventRegister now for Data + AI Summit 2023RegistereBookA New Approach to Data SharingRead noweBookData, Analytics and AI GovernanceRead nowKeynoteData Governance and Sharing on the Lakehouse at Data + AI Summit 2022 BlogsMarketplace Public Preview AnnouncementDatabricks Marketplace Announcement at Data + AI Summit 2022DocumentationAWSAzureGCPProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/zachary-bannor","text":"Zachary Bannor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingZachary BannorData Engineering Manager at Cond\u00e9 NastBack to speakersDr. Zachary R. Bannor, PharmD, is a data engineering manager at Cond\u00e9 Nast. His team works to de-silo data and to build robust data pipelines to provide valuable datasets to stakeholders across myriad business verticals. He lives in Chicago with his wife, Nicole, and cats, Stuart and Samantha. His interests include cooking, cycling, weight lifting, and playing with his band, Five Step Drop.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/sridhar-devarapalli\/#","text":"Sridhar Devarapalli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSridhar DevarapalliSenior Director, Product Management at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}
{"source":"https:\/\/www.databricks.com\/p\/webinar\/learn-databricks-sql-from-the-experts","text":"Learn Databricks SQL From the Experts | DatabricksOn-DemandLearn Databricks SQL From the ExpertsUplevel your data skillsAvailable on-demandWatch this free training to learn how Databricks SQL allows you to operate a multicloud lakehouse architecture that delivers data warehouse performance at data lake economics \u2014 with up to 12x better price\/performance than traditional cloud data warehouses. Now data analysts and scientists can work with the freshest and most complete data and quickly derive new insights for accurate decision-making.In this webinar, you\u2019ll learn how to:Quickly get up and running with Databricks SQLUse Databricks SQL to profile and explore your dataEasily ingest and transform data in Databricks SQLGo from data to insights faster with Databricks SQL\u2019s built-in visualization and dashboarding toolsLive Q&ASpeakersDoug BatemanMaster InstructorDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers\nat DatabricksWorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the\u00a0Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights"}
{"source":"https:\/\/www.databricks.com\/kr#yourprivacychoices","text":"\ub370\uc774\ud130 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \uc544\ud0a4\ud14d\ucc98 \ubc0f AI \uae30\uc5c5 - DatabricksSkip to main content\ud50c\ub7ab\ud3fcDatabricks \ub808\uc774\ud06c\ud558\uc6b0\uc2a4 \ud50c\ub7ab\ud3fcDelta Lake\ub370\uc774\ud130 \uac70\ubc84\ub10c\uc2a4\ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub9c1\ub370\uc774\ud130 \uc2a4\ud2b8\ub9ac\ubc0d\ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc9d5\ub370\uc774\ud130 \uacf5\uc720\uba38\uc2e0 \ub7ec\ub2dd\ub370\uc774\ud130 \uc0ac\uc774\uc5b8\uc2a4\uac00\uaca9Marketplace\uc624\ud508 \uc18c\uc2a4 \uae30\uc220\ubcf4\uc548 \ubc0f \uc2e0\ub8b0 \uc13c\ud130\uc6e8\ube44\ub098 5\uc6d4 18\uc77c \/ \uc624\uc804 8\uc2dc(\ud0dc\ud3c9\uc591 \ud45c\uc900\uc2dc)\n\uc548\ub155, \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4. \uc548\ub155\ud558\uc138\uc694, \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4.\n\ub370\uc774\ud130 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\ud30c\ud2b8\ub108AWSAzureGoogle CloudPartner Connect\uae30\uc220 \ubc0f \ub370\uc774\ud130 \ud30c\ud2b8\ub108\uae30\uc220 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ub370\uc774\ud130 \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8Built on Databricks Partner Program\ucee8\uc124\ud305 & SI \ud30c\ud2b8\ub108C&SI \ud30c\ud2b8\ub108 \ud504\ub85c\uadf8\ub7a8\ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\ud074\ub9ad \uba87 \ubc88\ub9cc\uc73c\ub85c \uac80\uc99d\ub41c \ud30c\ud2b8\ub108 \uc194\ub8e8\uc158\uacfc \uc5f0\uacb0\ub429\ub2c8\ub2e4.\uc790\uc138\ud788\ud68c\uc0acDatabricks \ucc44\uc6a9Databricks \ud300\uc774\uc0ac\ud68c\ud68c\uc0ac \ube14\ub85c\uadf8\ubcf4\ub3c4 \uc790\ub8ccDatabricks \ubca4\ucc98\uc218\uc0c1 \uc2e4\uc801\ubb38\uc758\ucc98Gartner\uac00 Databricks\ub97c 2\ub144 \uc5f0\uc18d \ub9ac\ub354\ub85c \uc120\uc815\ud55c \uc774\uc720 \uc54c\uc544\ubcf4\uae30\ubcf4\uace0\uc11c \ubc1b\uae30Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8 \ubcf4\uae30\ubb38\uc758\ucc98\ub85c\uadf8\uc778JUNE 26-29REGISTER NOW\ucd5c\uace0\uc758 \ub370\uc774\ud130 \uc6e8\uc5b4\ud558\uc6b0\uc2a4 \ub808\uc774\ud06c\ud558\uc6b0\uc2a4\uc785\ub2c8\ub2e4\ubaa8\ub4e0 \ub370\uc774\ud130, \ubd84\uc11d \ubc0f AI\ub97c\n\ud558\ub098\uc758 \ud50c\ub7ab\ud3fc\uc5d0\ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc790\uc138\ud788\ub808\uc774\ud06c\ud558\uc6b0\u0000\u0000\uc2a4 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ube44\uc6a9 \uc808\uac10 \ubc0f \ud601\uc2e0 \uac00\uc18d\ud654\uc790\uc138\ud788\ud1b5\ud569\ud615\ud558\ub098\uc758 \ud50c\ub7ab\ud3fc\uc73c\ub85c \ub370\uc774\ud130\ub97c \uc77c\uad00\ub418\uac8c \uad00\ub9ac\ud558\uace0 \ubaa8\ub4e0 \ubd84\uc11d\uacfc AI\ub97c \uc9c0\uc6d0\ud569\ub2c8\ub2e4.\uc624\ud508\uac1c\ubc29\ud615 \ud45c\uc900\uc744 \uae30\ubc18\uc73c\ub85c \uad6c\ucd95\ub418\uace0 \ubaa8\ub4e0 \ud074\ub77c\uc6b0\ub4dc\uc640 \ud1b5\ud569\ub418\uc5b4 \ud604\ub300\uc801 \ub370\uc774\ud130 \uc2a4\ud0dd\uc5d0\uc11c \uc6d0\ud65c\ud558\uac8c 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\uc120\uc815\ud55c \uc774\uc720\ub97c \uc54c\uc544\ubcf4\uc138\uc694.\ubcf4\uace0\uc11c \ubc1b\uae30600\uba85\uc758 CIO. 14\uac1c \uc0b0\uc5c5. 18\uac1c \uad6d\uac00.\uc774 \uc0c8\ub85c\uc6b4 \uc870\uc0ac\uc5d0\uc11c \ub370\uc774\ud130 \uc804\ub7b5\uc774 AI\uc758 \uc131\uacf5\uc5d0 \uc911\uc694\ud558\ub2e4\ub294 \uac83\uc744 \uc54c\uc558\uc2b5\ub2c8\ub2e4. \ub354 \ub9ce\uc740 CIO\uc758 \uacac\ud574\ub97c \ud655\uc778\ud558\uc138\uc694.\ubcf4\uace0\uc11c \ubc1b\uae30\ubcf4\ub2e4 \ud6a8\uacfc\uc801\uc778 MLOps \ubc29\ubc95\uc744 \ucc3e\ub294 ML \uc5d4\uc9c0\ub2c8\uc5b4\uc640 \ub370\uc774\ud130 \uc0ac\uc774\uc5b8\ud2f0\uc2a4\ud2b8\uac00 \uc77d\uc5b4\uc57c \ud560 \uc790\ub8cceBook \ub2e4\uc6b4\ub85c\ub4dc\uc2dc\uc791\ud560 \uc900\ube44\uac00 \ub418\uc168\ub098\uc694?Databricks \ubb34\ub8cc\ub85c \uc2dc\uc791\ud558\uae30\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\uc81c\ud488\ud50c\ub7ab\ud3fc \uac1c\uc694\uac00\uaca9\uc624\ud508 \uc18c\uc2a4 \uae30\uc220Databricks \uc774\uc6a9\ud574 \ubcf4\uae30\ub370\ubaa8\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\u0000\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\ud559\uc2b5 \ubc0f \uc9c0\uc6d0\uad00\ub828 \ubb38\uc11c\uc6a9\uc5b4\uc9d1\uad50\uc721 \ubc0f \uc778\uc99d\ud5ec\ud504 \uc13c\ud130\ubc95\uc801 \uace0\uc9c0\uc628\ub77c\uc778 \ucee4\ubba4\ub2c8\ud2f0\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\uc194\ub8e8\uc158\uc0b0\uc5c5 \uae30\uc900\ud504\ub85c\ud398\uc154\ub110 \uc11c\ube44\uc2a4\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98\ud68c\uc0acDatabricks \uc18c\uac1cDatabricks \ucc44\uc6a9\ub2e4\uc591\uc131 \ubc0f \ud3ec\uc6a9\uc131\ud68c\uc0ac \ube14\ub85c\uadf8\ubb38\uc758\ucc98Databricks\n\ucc44\uc6a9 \ud655\uc778\ud558\uae30WorldwideEnglish (United States)Deutsch (Germany)Fran\u00e7ais (France)Italiano (Italy)\u65e5\u672c\u8a9e (Japan)\ud55c\uad6d\uc5b4 (South Korea)Portugu\u00eas (Brazil)Databricks Inc.\n160 Spear Street, 13th Floor\nSan Francisco, CA 94105\n1-866-330-0121\u00a9 Databricks 2023. All rights reserved. Apache, Apache Spark, Spark \ubc0f Spark \ub85c\uace0\ub294\u00a0Apache Software Foundation\uc758 \uc0c1\ud45c\uc785\ub2c8\ub2e4.\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uace0\uc9c0|\uc774\uc6a9\uc57d\uad00|\uadc0\ud558\uc758 \uac1c\uc778 \uc815\ubcf4 \uc120\ud0dd|\uadc0\ud558\uc758 \uce98\ub9ac\ud3ec\ub2c8\uc544 \ud504\ub77c\uc774\ubc84\uc2dc \uad8c\ub9ac"}
{"source":"https:\/\/www.databricks.com\/dataaisummit\/speaker\/faraz-yasrobi\/#","text":"Faraz Yasrobi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFaraz YasrobiSoftware Engineer at GrammarlyBack to speakersFaraz Yasrobi s a software engineer with over 7 years of experience in the data domain. Specializing in data infrastructure, engineering, storage, governance, and security. Faraz is currently a tech lead in Grammarly\u2019s data platform team and has been leading the data democratization project over the past two years.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event."}